Professor of Geophysics
By David Zierler, Director of the Caltech Heritage Project
October 6, 19, and December 6, 2022
DAVID ZIERLER: This is David Zierler, Director of the Caltech Heritage Project. It is Tuesday, October 4, 2022. I am delighted to be here with Professor Zhongwen Zhan. Zhongwen, it's wonderful to be with you. Thank you for having me in your office today.
ZHONGWEN ZHAN: Thank you for coming.
ZIERLER: To start, would you please tell me your title and affiliation here at Caltech?
ZHAN: Yes, I'm a Professor of Geophysics in the Seismo Lab.
ZIERLER: Why is there no professor of seismology at Caltech? Do you have a sense of why? We have the Seismo Lab, there are many seismologists. I understand that seismology is a subset of geophysics, but why the title professor of geophysics?
ZHAN: That's a very good question. I wonder if, in the past, there's been any professor of seismology.
ZIERLER: Maybe Dr. Richter was a professor of seismology.
ZHAN: I think it really comes back to the fact that we're doing geophysics, not seismology. We're using seismology as a tool to study the Earth, and that's geophysics. Seismology is supposed to be the study of vibration. It can mean anything. Seismo means vibration in Greek. I think the idea is that you can understand the tool really well, and in the process, the physics behind the vibration. But you may not use it to study the Earth. We want to think we're studying the Earth using seismology as a tool. I think that's really important.
ZIERLER: Is there anything you do in seismology that's not covered within the larger intellectual umbrella of geophysics?
ZHAN: I think that's starting to happen more and more often. Seismology is still fairly young. Modern seismology started a little bit more than 100 years ago, so the Seismo Lab was really kind of there in the beginning of it. For many years, it has been primarily used to study and the interior of the Earth. Those are the two big topics. But I can see that we're kind of branching out more and more to other domains. Because many things vibrate. [Laugh] Waves propagate through all kinds of mediums. I think our reach is expanding. People starting to use seismology to study acoustic waves in the ocean, you can use seismology to study the shallow layer of the Earth, the soil, hydrology layers of the Earth, which isn't conventional geophysics. People use it to study glaciology, the ice, which is new, too. People are deploying seismic sensors to the moon and to Mars to study planetary science. Of course, we can also call that planetary geophysics. We're definitely expanding beyond just studying the Earth.
ZIERLER: For your research, is it entirely focused terrestrially here on Earth, or is there anything you do that's relevant for Mars, Venus, the moon, exoplanets?
ZHAN: I have been mostly focused on terrestrial geophysics, but I've been thinking about some things we can apply to the moon and Mars. There are going to be some interesting applications there. Even during my PhD, I was involved in some of the discussions on how to use seismology to constrain the thickness of ice on Europa, for example. That kind of thing has always been in our discussions, but we may start something for real soon.
ZIERLER: Hot off the news, you were awarded the James B. Macelwane Medal from the AGU. First, tell me about this award, what its significance is in the field.
ZHAN: It's an award for late-early career people. [Laugh]
ZIERLER: You're not young, but you're not old. [Laugh]
ZHAN: I'm not an early career faculty member anymore, it's considered the later part of my early career. It's for significant contribution to the field of geophysics. Actually, James Macelwane was the first seismologist west of the Mississippi River. [Laugh] One of the pioneers of seismology in North America. He was also chair of the AGU for a while. A very influential seismologist. I'm very honored to get this award. It's given to three to five people across the entire spectrum of the AGU.
ZIERLER: Is the award recognizing a specific paper or project you were involved in, or more a general appreciation of what you've been able to accomplish?
ZHAN: I think it's the general contribution.
ZIERLER: What comes with the award? Will you be giving a talk? Is there a dinner?
ZHAN: I'll go to Chicago for the AGU fall meeting, there's a ceremony and banquet, and there's a talk. There's actually a conflict at the moment. I have a scheduled trip to Antarctica. They're not overlapping, but they're very, very close. And I'm pretty sure to go to Antarctica, you have to prove you've been vaccinated, and also probably some sort of negative test because there's no doctor there to treat anyone or any quarantine facility. I'm very concerned about catching COVID in Chicago, then I only have a week to recover. If I get it and don't recover, I'll be in trouble. [Laugh] Before I knew about the medal, I'd say, "This year, I have to skip the AGU so I can quarantine myself."
ZIERLER: Well, N95s and an outdoor reception maybe is the answer.
ZHAN: In Chicago in the winter? [Laugh] Not so much. That's one of the challenges. But when you're doing research, you're doing something brand new. You're trying to figure out if you're going in the right direction.
ZIERLER: What is the research in Antarctica?
ZHAN: It's using some of the fiber-sensing technology we're using in Southern California. We'll be using it to study the ice there.
ZIERLER: Is Antarctica seismically active?
ZHAN: Not quite. In terms of seismic activity, it's mostly around Antarctica. Within Antarctica, it's mostly stable.
ZIERLER: What do the plate boundaries look like at the bottom of the Earth?
ZHAN: It turns out the plate boundaries sort of cut across Antarctica. There are all these spreading centers around. There generally aren't huge earthquakes, mostly relatively small ones. But the important thing is that we know about the ice. We're losing ice there, which can cause a global sea-level rise. Clearly, that's not a traditional domain of geophysics, but geophysics can contribute to this problem. When you think about how you lose ice, when it's frozen, it moves and deforms very slowly. It's basically solid, but on a long time scale, it can also flow. A more efficient way for it to get into the ocean is for it to slide on the base. Whether it can do that depends on the temperature, whether it's frozen with the rock or there's a layer of water or mud on the bottom.
ZIERLER: In an increasingly warming world, we'll see this more often.
ZHAN: Yes. The problem is, the temperature is not constrained very well. The only way you can measure the bottom temperature precisely is to drill a hole all the way to the bottom and measure the temperature.
ZIERLER: How far down do you have to go?
ZHAN: Where I'm going in Antarctica, it's about 2.8 kilometers or 2 miles.
ZIERLER: For a sense of scale, I know the all-time record is about 10 kilometers drilling, so you're on your way.
ZHAN: Yeah. But there's another way to do this, using seismic reflections from the bottom. If you can imagine, if you've got ice over rock versus ice with a soft layer of mud and rock, the boundary point, the seismic wave will come down, be bounced back, and the signal will be very different if it's frozen or soft.
ZIERLER: How do you make the measurements? Is this geodesy?
ZHAN: We're using seismometers. It basically mirrors vibration, so you have to set up a source to send out the vibration. This is the same thing as when people use ultrasound in the body, but we need something to send out a stronger signal, so we use a small amount of explosives. It's about this long, basically a rod. We get a blank shell, dig a hole three feet deep, bury it, and trigger it. It explodes and sends out a strong seismic wave, which travels all the way down and bounces back. On the surface, you have sensors that record the echoes from the subsurface, and you can study the echo to figure out what's underneath. People have been doing this in the past. It's nothing new. Even on the ice, it's been done for years. In the past, we always had pretty bulky seismometers running on batteries. We'd go there, dig a hole the size of this table, about a person deep, bury it, and next year, you'd come back.
It's very hard, tedious work in a cold environment, and we could only do a sparse set of them. We just didn't have the instruments or time to do enough. But my research in Southern California said, "What if you can turn telecom cables into sensors?" This new technology called distributed acoustic sensing, or DAS, you connect to the end of a cable, then you can turn every meter of that cable into a seismic sensor without adding anything else. What do you do if you don't have a cable already in place? You take a spool of fiber, lower it a couple kilometers underground, connect the instrument, then every meter of that cable becomes a sensor. If you go a kilometer, you have 1,000 sensors right away.
ZIERLER: Are we using these cables elsewhere for similar projects? Or this is a new application?
ZHAN: The cables are the same ones providing us internet. And in Antarctica, it's because there was a conventional seismic station 80 kilometers from the SCAR Station, and they had to transmit the data back, so they deployed a cable there about 20 years ago. Antarctica gets snow every year, so now it's many meters deep, perfectly covered with snow. One end of the cable is at the seismic station, and the other end is in the SCAR station. There are a lot of people there, a nice building with an IT room with power and internet, so we're going to bring this instrument there, plug it in, and that 80-kilometer cable will suddenly become 8,000 sensors.
ZIERLER: How far back does this technology go, or at least the realization that you could use these cables for seismological research?
ZHAN: It started pretty early on, when people had just invented fiber optic cables for telecom purposes. This was in the 1970s. People had already realized that communication was not perfect, that if someone was perturbing the cable, it could disturb the telecom process. And that made people realize that maybe it could be a sensor of some kind. But in the 70s and 80s, there was quite a bit of study on this, and people realized it was actually pretty hard to do. Not until the early 2000s, 2010 or so, did the technology mature enough to make precise enough measurements to use for research purposes. Before that, there were some applications. For example, you can lay cable around an airport.
You won't have much, but you can see if someone is trying to break the fence or trying to intrude somewhere. They use it for intrusion protection. But around 2010, near the end of my PhD, I heard a talk where they started to show earthquakes on the data, and that made me very excited. Even at the time, you got so-called intensity information. You knew how big the signal was, but you didn't know what the phase information looked like. That's still a problem for us because seismology is at the point where we do need to know the phase information. I think around 2015 to 2017 is when the instruments got pretty good, which is when I started to use them for seismic research purposes.
ZIERLER: With this Antarctic trip, are you part of a collaboration, or is it you and a few students?
ZHAN: It's my group.
ZIERLER: What's the funding source for this?
ZHAN: Partially by the Moore Foundation, partially by NSF.
ZIERLER: Best-case scenario, what do you hope to achieve with this research? What are the big questions?
ZHAN: I think there are two questions we want to answer. One, people think there's a lack underneath the South Pole.
ZIERLER: A liquid lake.
ZHAN: A liquid lake, pretty deep, on the order of 10 kilometers or more.
ZIERLER: Fresh water or salt water?
ZHAN: No one really knows. No one's ever drilled to it.
ZIERLER: What would be the theoretical basis for thinking there's a lake?
ZHAN: People actually can observe that the ice kind of fluctuates a little bit, so if there's no cavity down there and everything is on rock, it should not deform. If there's a lake, the water level will change, and it will tend to go up and down a bit.
ZIERLER: This is amazing. I thought we would need to fly to the satellites of Jupiter to study lakes under ice.
ZHAN: No, there are plenty of lakes underneath the Antarctic ice sheet. It's primarily because the surface is extremely cold. Even their summer, highest, is around -20 degrees. In the winter, it's -60 or -80. But the Earth's interior is warm, and there's what we call a geotherm. It's radiating heat outward from the interior. When you have three kilometers of ice on top, and there's a warmth source underneath, it'll warm up the ice from the bottom. If it's warm enough, you may get a lake.
ZIERLER: And the ice insulates the lake, too.
ZHAN: Exactly. On the surface, it's cold and getting colder, and on the bottom, it's getting warm. That's where the lake is. But people know it's warm, and there's a lake, which must mean at that position, it's a near-freezing temperature, zero degrees Celsius, but there's a pressure effect there. The question is, around it, is it also around zero or much colder? If it's much colder than zero, the lake will disappear eventually. It'll be shrinking. But some people say it may be pretty stable, pretty close to zero. And people have different opinions on that because they've only made measurements around the lake. They don't know what's on the sides of the lake. We have the cables exactly on the edge of the lake, which was deployed for a different purpose, but there nonetheless. We hope to see the echoes and determine a temperature, which will tell us whether it's a stable or unstable lake. The second thing is, if we can do this, we'll be able to go to more interesting places.
ZIERLER: I was going to say, the astrobiology community is probably very interested in this.
ZHAN: Of course, that's going to be very exciting. Most of the ice loss is, of course, happening on the edge. It's not uniform everywhere on the edge, and the flow is really fast in some places called ice streams, essentially like rivers. You can use geodesy to measure the movements. They move meters per day, so it's really fast movement. And that's where we really know very little about the base, and we also really need to know about the condition of the base. If we can show that we can use the cable in the South Pole to do this, we can potentially do the same near the edge, where some really big ice streams are channeling a lot of ice to the ocean and measure the base condition there. This is really like a pilot experiment because deploying your own cable in ice is very challenging. We're lucky there's a very long cable in the South Pole. We're going to use this as a demonstration that this can work.
ZIERLER: How long will you be down there?
ZHAN: About a month, but the instrument will stay for an entire year. This is another wonderful thing about this technology. If a conventional sensor is running on a battery, it's not going to last very long. Even with a solar panel, it would only last half a year there. But with this technology, we've got an IT room with power and air conditioning all year long, so we can keep it running for the entire winter. This is going to be the densest and longest array ever in Antarctica. Even if, in the future, we're going to somewhere without a station, and we have to power everything, we still only have to power one end of it. We can deploy a long cable, drill holes through the ice shelf, put a cable down, measure the vibration and temperature everywhere for tens of kilometers, but still only have to worry about this one place, and have it powered and heated.
ZIERLER: Will you be able to analyze this data remotely or wait until the following year to bring it back?
ZHAN: We're bringing back whatever data we get by the time we leave. Then, the other data will be stored on hard drives, and there are IT people there who can swap drives for us every month. They'll ship it back to us. Ships to and from Antarctica are not that frequent, so they'll probably send two copies, one by air, one by ship.
ZIERLER: You mentioned you're at the late-early stage of your career.
ZHAN: I only heard that recently. [Laugh]
ZIERLER: Of course, you were also awarded tenure. You're now a full professor. Congratulations on that as well.
ZHAN: Thank you.
ZIERLER: This is more a question about the culture of Caltech. Particularly because you have a very unique perspective, being a graduate here, assistant professor, all the way to full professor now, can you talk a little bit about the special ways Caltech supports its junior scholars?
ZHAN: I figured I can really be supported very well here for a few different reasons. Of course, being at Caltech, you get access to the best students and post-docs, people who do a lot of the work. That's really amazing. But I think what's unique here is, you really get to interact with people, since it's a small place. Within, say, geophysics or the GPS division, we all know each other very well. There's a lot of interaction that generates many new ideas. Even over the entire campus, it's not that big. I'll give you some examples. Again, this is getting outside of conventional geophysics. In one project, I'm collaborating with one of our early-career oceanographers, Joern Callies. He studies the ocean circulation, mesoscale convection in the ocean, and so on. I was very interested in the work, but I never thought there would be any connection. But we talked a lot with each other, and eventually one of my post-docs and I came up with an idea. Oceanographers are very interested in the warming of the global oceans, and they don't have a very good way of measuring that.
Right now, they just throw buoys in the ocean, and there are about 5,000 of them floating around the Earth, sending off data once in a while. Once they die, they throw new ones in. It's a pretty large-scale experiment. The reason they need so many sensors is, the ocean temperature is very heterogeneous. You could be in a bad spot if you only have one sensor, but with many, you can average. Many years ago, there was a scientist, actually an alumni of the GPS division, Walter Munk, who showed that you can measure the acoustic wave speed in the water to measure the temperature. If the temperature changed, the acoustic wave speed changed, by a very small amount, less than a percent. He set off big explosions in specific places repeatedly, and these acoustic waves are detectable thousands of kilometers away because ocean water is such a high quality channel, the wave just doesn't attenuate. There's actually also a low-velocity channel called the SOFAR channel, where a wave can propagate just forever. But then, the program got shut down because people were concerned the explosions caused harm to ocean mammals, whales, dolphins, and so on. My post-doc and I thought about using repeating earthquakes to do it. There are earthquakes happening in the same location again and again.
ZIERLER: In short order or periodically?
ZHAN: Some of them, periodically, some have only happened a few times, so we don't know if they're periodic. But they're located close enough and rupture on the same patch inside the Earth. It's a pretty mysterious process from an earthquake physics perspective, but we know they're happening. Turns out, we can use that, instead of setting off explosions, to repeatedly send a signal from a particular location to measure the ocean temperature. When we realized that, we asked the oceanographers if it was of interest to them, "What kind of access do you need? What kind of data do you have to verify our observations?" This kind of thing is not necessarily easy to do in other places, given that you need this kind of interaction between different disciplines to really work out this kind of method. I also work with Professor Alireza Marandi on fiber sensing. We want to understand how it actually works and if there are ways to improve that, so there's a connection there. There are also opportunities with other professors, for example, with Zach Ross, who uses machine learning and works with applied mathematicians in the CMS Department. I think these are all great examples where these interactions, both within and without the division, can really bring new insight and new ideas. And some of them are really interesting. I think that's something pretty unique at Caltech.
ZIERLER: Did you have a tenure talk? Was there an opportunity to review what you had accomplished and presented to your would-be executioners?
ZHAN: It's interesting, I always thought it was a standard thing. I even got worried when I didn't get asked to do one. [Laugh] I was like, "Should I give a talk of some kind?" But I didn't. I guess I gave a bunch of talks throughout the years here and there, and people felt like they understood what I was doing pretty well, so I didn't have to give another one.
ZIERLER: How did you receive the news?
ZHAN: I just received an email from our division chair saying, "Come to my office." "I hope it's good news." [Laugh]
ZIERLER: I know you're brand-new into tenure, but I know for assistant professors, the urge is to be very focused and develop an expertise. Do you feel now like you can take a deep breath, and your research agenda can be more expansive or adventurous?
ZHAN: I think the major change I see–first of all, I haven't seen very much of a change so far because I think my research during the tenure track was already very broad. It's been exhausting, but very broad. [Laugh] I worked on many things, and they're connected by some themes. In the beginning, it was the deep Earth and deep earthquakes. Starting from 2017, I really switched to this fiber-sensing direction. But that's the tool. It's the science that matters. I've been using it for earthquake study, volcano study, hydrology, glaciers.
I feel like it's broad enough that I don't need to broaden. If anything, I need to go the other way. [Laugh] But the one really interesting change is, I was not too concerned about risk, I was more concerned about time. I think with tenure, I feel more comfortable to do things that take a lot of time. This Antarctica experiment is a good example of that. I spent a lot of time this past summer preparing the logistics. Once I'm there, I'm going to spend an entire month not doing anything but the experiment. And I'll have to wait for a year for the full dataset to come back. On top of that, this project got delayed for two years because of the pandemic. In total, since we proposed it until now, it's taken more than three years.
By the time the data comes back, it'll be four years, and it'll probably take another year to analyze the 300 terabytes of data we get from it. It takes a lot more time when you're collecting data in a pretty exotic place, but I feel like there's a really exciting science to be done. Now, I feel more comfortable doing that. You also mentioned planetary cases, Europa, other icy worlds. Again, this kind of thing would take a lot more time. It's not the kind of science where you say, "I have an idea. Let's do it." You have a long process leading up to something on that scale. I think with tenure, I feel a little more comfortable saying, "I can spend my time making this happen." But if you're looking at a five- or six-year timeframe before tenure, you wonder, "Where will I be at the end of that, when I need to write papers?" [Laugh]
ZIERLER: Before we get to some of the major things you've worked on so far in your career, I'd like to ask a cultural question. Coming from China, being educated in China, do you feel like there are any unique cultural perspectives you bring to the science that might influence the kinds of things you work on, the kinds of questions you ask? A style of collaboration? Have you ever thought about the role of your culture and heritage in the science that you do?
ZHAN: I've never really thought about it. I guess maybe in the way you collaborate and interact, there's a difference. Of course, in Chinese culture, a big difference is–and this is true in almost every Eastern Asian culture–the respect of more senior people, elderly people. In the US, it's kind of the other way around. The younger people have more of a say, more power, in changing things. I think that's very good, and we benefit a lot from that, generating new ideas. At the same time, because of the Eastern Asian cultural background I have, I think I'm really happy to collaborate with people and get along with people fairly easily. I'm just happy chatting about all different kinds of things. Sometimes nothing comes up, sometimes something interesting happens. I think the way I mentor students, I feel like they also feel pretty comfortable bringing up their ideas to me, even if it's different from what I think or just telling me I'm wrong. I think it helps to generate new ideas that may be different from what I think. I don't know if it's unique with Eastern Asian culture, but I do feel like there's an influence there.
ZIERLER: Do you have opportunities for collaboration, or do you have a sense of what Chinese seismology looks like?
ZHAN: Yeah, I did have a master's degree in China, so I was doing some research there already, and that benefitted me a lot. Sort of what convinced me to come to Caltech was my advisor, who was from Caltech. His advisor was my advisor later. [Laugh] You see, "This is what the top scientists are doing, how they are doing research." That had a pretty early influence on me wanting to come to Caltech to do seismology. But I've kept track of what they're doing, and I would say it's changed a lot in the last 10 years or so, partially because of all the returnees from the US and Europe. Mostly from the US. They're just bringing a culture shift to Chinese academia. They're doing really exciting research and leading in new directions. They've got tons of funding, so they can do expensive experiments, maybe more easily than the US sometimes.
ZIERLER: The Chinese government is supporting basic science in seismology?
ZHAN: Oh, yeah. They're supporting everything in fundamental research. It's quite amazing to see. I think they're doing really well there. I have a lot of friends in China doing great research.
ZIERLER: Unfortunately, there are so many political tensions right now. Has that affected the science from your vantage point?
ZHAN: For sure, yeah.
ZIERLER: In what ways?
ZHAN: Much less interaction. It's also partially the pandemic on top of everything.
ZIERLER: Although, the pandemic and political tensions themselves are connected.
ZHAN: Yes. Before, we had quite a few exchange programs, professors and students visiting. I think it's very healthy. They also attended more international conferences, but it's harder to do that now. In the last few years, because of political issues, we're hosting fewer exchange students. Data is becoming more and more of an issue.
ZIERLER: Less shared.
ZIERLER: That's a problem.
ZHAN: Especially for seismology, it's a big problem.
ZIERLER: It's one planet. We need to see what's happening everywhere.
ZHAN: Seismic waves propagate in every direction. We often need international or global coverage to study a certain process. Without that, it's very challenging. I do hope it gets better. I'm starting to see more people asking if they can visit the US. Some programs seem to be opening up more. I hope it'll change soon.
ZIERLER: At the broadest possible level, where in your research are you more of a theoretician, and where are you more an observationalist or experimentalist?
ZHAN: I'm not a theoretician at all. [Laugh] If you want to go by the narrowest definition, I'm an observational seismologist. But I'm interested in all kinds of observations in seismology.
ZIERLER: What are the theories that are most important for your work, that serve as an intellectual framework or guidepost to know what the data is telling you?
ZHAN: It turns out, the fundamental physical process has two parts. One is the seismic wave itself, how they propagate. The fundamental theory of that has been worked out for a long time.
ZIERLER: Because this is Newtonian physics.
ZHAN: Yeah, exactly. The challenge is mostly that the Earth is complicated. [Laugh] It's simple physics, but the Earth is complicated. The better you can understand the propagation of seismic waves in a complex medium, the better you can extract information from the record you have. You have to account for heterogeneities, you have to account for anisotropy. It's a lossy medium. Propagated waves will be attenuated. There are also small scale things that can scatter waves in different directions. You have all these single- and multi-scattering processes going on. That's kind of the fundamental physics side. And the community has developed a lot of tools to try to deal with, understand, and simulate this process. We use a lot of heavy computation. Seismology is one of the big users of high-performance computing. I think maybe comparable to people doing numerical weather forecasting. That's one part of it. The other side is really kind of the physics of your target science topic. For example, a big part of it is earthquake physics, how rupture happens. A lot of the work we're doing is saying, "An earthquake is rupturing on this fault. We want to understand the mechanics in that process."
It's sort of like a friction sliding unzipping the fault. We want to understand the forces, the stress, how they're evolving in the medium. But it's hard to measure that in situ. earthquakes are happening several kilometers or miles under the surface, and you don't know where it's going to happen. It's very hard to track them. The way we're doing this is to say, "It's a different kind of friction process where the radiated seismic wave has a different behavior." Then, you can use seismic sensors to detect them, and then, knowing what kinds of structure are along the path, try to go back in time and say, "This kind of recording we have means this is happening on the fault plane during the earthquake." That's kind of the way of thinking we have most of the time. As you can imagine, if you want to do that, you also want to know the path pretty well. And if you want to know the path well, you need the earthquake to send out seismic waves. It's a coupled system, the structure and the source. You have to get a bit better on structure, know a bit more about the source, and slowly go forward. That has been basically the process over the last tens of years.
ZIERLER: I want to ask about technology. What technological advances have allowed you to pursue the same questions as Richter, Press, Gutenberg, Benioff? What questions are you asking that are essentially the same questions that founding generation was asking, but with a wealth of technological capability to see things that they couldn't? And what research questions are you asking that simply were not available to them because the technology wasn't there?
ZHAN: That's a great question. Taking the first few directors of the Seismo Lab as an example, Beno Gutenberg basically measured the size of Earth's core with a few seismograms. [Laugh] If I remember right, he worked part-time at a family factory and part-time as a scientist, but he took care of the seismic station there, and he was able to detect earthquakes happening in Japan or other places, detect the waves reflected from the core, all by himself. And he worked out the size of the core, those kinds of things. It's an amazing history. That was the early days, trying to understand the first-order structure of the Earth.
ZIERLER: What does that mean, first-order structure?
ZHAN: In this sense, it's basically the layers of the Earth. There's the crust, the mantle, the core. That was all discovered by seismologists by looking at waves bouncing from the boundaries of the different layers of the Earth. They were very interested in understanding the structure of the Earth, and that's the same question we have today. But we can do much better by, instead of one seismometer detecting a few earthquakes around the globe, or asking someone to mail you film from the sensors, we have a connected global network of sensors. We can look at not only the layer structure, which accounts for 90% of the structures, but another 5 or 10% that tells you the Earth is not a dead planet of layers. It's moving. There are plumes going from the deep Earth, plates diving down and generating earthquakes. Plate tectonics is all in that 5 to 10% of lateral heterogeneities. I'm sure they would've loved to have that kind of data, but at the time, they had a very sparse dataset. Now, there's a lot more data for that. We're continuing doing that, and we can study earthquakes better.
Even in the 1920s, they were very good at detecting and locating large earthquakes. During the first month of my tenure-track position as an assistant professor, a big earthquake happened in Afghanistan in the Kush Mountains. When I studied it, I realized it was an interesting sequence that happened every 50 years. And it's 200 kilometers underneath the surface. It's actually because two plates collide, and one drips down and eventually kind of tears up. It's kind of like a drip of slabs going into the Earth that keeps producing earthquakes. I want to know how far back we can go in the seismic record. At most, I thought I could go to after World War II, which is when we installed global seismic networks. Turns out, I can go to the 1920s because Gutenberg and Richter here actually detected earthquakes by exchanging seismograms and made a very complete catalog for the entire globe. Anything larger than magnitude 7, they had it completely covered. And the locations were only off by a few kilometers.
ZIERLER: That's pretty impressive.
ZHAN: Right. But now, with better data, we can actually see exactly how those earthquakes rupture, how they're tearing the slab off, and we can understand the geodynamics around it much better than before. Those are the kinds of things people have been wondering.
ZIERLER: When you mention the importance of history, is your research completely digital? Is there any role of analog records for the kinds of things you do?
ZHAN: There's one interesting analog record we have, a notebook from Gutenberg. [Laugh] He just hand-drew a table and said, "This earthquake is at this station," based on the seismogram he got. "The P- and S-waves arrived at this time and this time." He did little hand calculations and said, "This is what I think the location is." That eventually led to a catalog, so that's part of it. I know there are a lot of people interested in the old seismograms, too. For example, the study of these Hindu Kush earthquakes goes back for a long time. I did use some of those data, but not a lot. This kind of data is much harder to use. You need a really strong science motivation and say, "That is important question. I have to use that." The absolute majority of our data is digital.
ZIERLER: Is geodesy something you're involved in?
ZHAN: Not really, no.
ZIERLER: Why is that not relevant for the kinds of things you do?
ZHAN: It's measuring the Earth's deformation. Seismology is also Earth's deformation, but on a very different time scale. We're measuring things vibrating on the order of a few Hertz or tens of Hertz to hundreds of seconds. Geodesy has primarily worked on day or longer time scales. But I want to say they're coming closer to us because some of the sensors they have can now go to much shorter time scales. For example, GPS, measuring Earth's deformation. Used to be one sample every day to be accurate enough. Now, sometimes they can do every 10 seconds, sometimes every one second, but the noise is much higher. That really bridges the gap. Maybe I should take it back because in the study of earthquakes, especially the 2019 Ridgecrest earthquake, we did use geodetic data in our imaging of the earthquakes. Not only the vibrations and the seismic waves, but we also looked at the deformation on the surface to image the rupture better. But I'm not a geodesy scientist in the sense that I take their data and use it. I don't work on how to make those measurements. And that's a pretty big field.
I want to get back to your question on the new science we can do because of the technology the pioneers of the field in North America didn't have. Again, I think this is a new theme that's emerging. A lot of the shallow Earth processes are extremely important in the context of climate change, in the context of what resource is used, and so on. Majority of the time, we're only using resources in a very shallow part of the Earth. And the shallow Earth turns out to be extremely heterogeneous. I believe the deep Earth is probably also extremely heterogeneous, but that's an open question. We can't really sample it in any systematic way. But the shallow Earth part, if you want to have a societal impact, you have to account for this heterogeneity. Since you're talking about a water basin a few kilometers in size, and in the past, our sensors, even conventional seismometers, there are tens of kilometers in space between sensors, it limits what we can say about the shallow Earth and near-surface processes.
The last decade, we've seen the development of relatively cheap sensors with a little bit lower sensitivity but much lower power consumption and cost, so we can get many of them. This includes Rob Clayton using seismic nodes. And now, the way I'm using fibers to do the same thing. It all increases the sensor density by orders of magnitude. Now, we can talk about meter scale, tens-of-meters scale. And that's starting to become relevant to these near-surface processes. I think that's something the pioneers would've never thought they could study. They were wondering about thousands-of-kilometers-scale structures. Then, people go into 70s, 80s, 90s, trying to think about tectonic signatures.
"There's a continent. What's the root of the continent? Where's the slab? Where does it go once it's subducted inside the Earth?" Still on the order of hundreds-of-kilometers scale at least. Then, we had good sensors to look at the structure of Southern California with tens-of-kilometers scale where the Earth shaking is going to be the strongest. "How does the history of plate tectonics in the region shape where we are? The topography, the faults, where we're going to have the future earthquakes, and so on." Now, we're at the scale where we can talk about, "Within that basin, where is the water? What is the detailed structure of the fault?" Those kinds of questions. Just like astronomers with their telescopes, each generation brings much higher resolution than before, which allows them to see new things at new sizes.
ZIERLER: Your focus on fiber optics, does that lead you to study particular kinds of earthquakes or particular areas within the Earth's inner structure? Or is this a technology that can be applied wherever your interests happen to be?
ZHAN: We're still in the early stage, but my own vision is that it will be used everywhere. Currently, there are still limitations in the sensitivity such that it's mostly good for relatively high-frequency vibrations. When you go to relatively long-period vibrations to much deeper structures, it doesn't do as well as the conventional sensors. The majority of the contribution now is on relatively shallow-Earth structures. But I can see that this may change very soon as technology improves. It's improved a lot, even just in the last five years. When I first started on this, 8 to 10 kilometers of cable covered 1,000 sensors. Now, I can use 100 kilometers of cables. That's 10 times longer cables with one sensor. It also allows us to use submarine cables. We can put a sensor on land, use the telecom cable, connect to a different continent, start to sense vibrations in the ocean. Some technology can go even further, thousands of kilometers. I really think it's going to have a broad impact in all aspects of seismology. I tend to think of this work as building the next generation of a seismic network. The current generation of seismic networks is doing a lot of wonderful things, but what's next? I think fiber optic cable may become the next generation.
ZIERLER: Is that qualitatively a different seismic network or just a larger seismic network?
ZHAN: Because of the orders of magnitude more sensors in density, it will allow us to ask totally different questions. Fundamentally, they're both measuring vibrations. The scale is just completely different. This gets back to the question you asked about the fundamental physics behind this. If you think about a wave propagating, it's really fast in the Earth. Even the slower waves propagate at a few miles per second. That means if you're measuring a seismic wave at one Hertz per second, it would propagate that one wavelength is a few miles long. If you're interested in waves sent by a very large earthquake, sometimes tens or hundreds of seconds, then the wavelength is hundreds of kilometers. In that sense, if you have an array that's sampled every 100 kilometers, you're pretty good. You're sampling that one wavelength multiple times. You're not aliased. Aliasing is a big problem in every field. That's great. That's why we have made so much progress with our conventional seismic networks. A lot of the big discoveries in this area is coming from the Seismo Lab because we run a world-class network. You may have heard about Hiroo Kanamori's work in calibration.
That was using some of the first networks around the world. But if you're interested in things oscillating at a Hertz, or 10 Hertz, interested in shallow structures, or interested in a particular break in the fault plane during an earthquake, you're talking about a wavelength that is a mile or hundreds of meters. Then, when you have a sensor every 30 kilometers, that's not quite enough. Earth is so complicated that everything will be aliased. With what you see here, you can't make sense of what's happening over there. It's completely aliased. With much denser sensors, with a node on the order of 100 meters between sensors or with fiber 10 meters or 1 meter between sensors, the leap is that suddenly, everything's coherent. I like to think, in a way, you always get the wave propagating. It's as if you're on the ocean and see the wave propagating in different directions. That's a wave field. Previous seismologists were only looking at some points in that and trying to interpolate, based on an understanding of the physics, what's happening in between. With the new generation of sensors, we start to take photos, in some sense. You're watching a movie of how waves are propagating on a fine scale.
ZIERLER: Literally, you can visually see the waves.
ZHAN: Yeah, you can see the wave, you can keep track of it from one to another, you can see how it's changing. Many things you couldn't understand in the past–"What is that phase on this one seismogram?" My advisor, Don Helmberger, the reason he's so good is, he can figure that out by looking at a few seismograms, being able to connect the dots, and say, "I know what that phase is. It's coming from this special structure deep inside the Earth," that no one would have any guess was producing this kind of wave because it's hard.
ZIERLER: Don had wonderful intuition.
ZHAN: I feel like he'd looked at so many seismograms, he could reconstruct what was going on in his head with a sparse dataset. That takes tens of years of experience. That was just what he was very good at doing. But now, it's the next generation of sensors. You can see how the waves propagate. I always tell my group members, "When you are developing your tools, don't think we have 10,000 individual sensors. You're looking at 10,000 pixels of an image. You have to process the data as an image, a movie instead of a bunch of sensors." Because in the past sensors have been relatively sparse, that has always been the challenge. It's hard to think of it as a movie. But now, we finally have the tools to do it.
ZIERLER: This suggests you have a mountain of data. First, how do you separate the signals from the noise?
ZHAN: Petabytes, even within my own group.
ZIERLER: How do you make sense of it?
ZHAN: When I was a student with Don, we looked at every single seismogram we used in our papers.
ZIERLER: Manually, one-by-one.
ZHAN: Manually. We printed them out. This was Don's office. It was bigger, with more windows and a big, long table in the middle. Every one of his students, including me, had to print historical seismograms, one-by-one, with where the earthquake is on the map, with labels on the location of the earthquake stations. And we'd sit here with a pencil and ruler and really look at each one of them to see what was happening. And that's impossible to do now.
ZIERLER: Well, you could, but it's slow, and you would never do it.
ZHAN: One earthquake will give you 10,000 seismograms like that. It's impossible to go through them one-by-one. And that's been a big change for all of us. How do we deal with that? Well, I'm not a computer scientist, so the way I'm dealing with it is purely on the science question. What do I actually have to do? If I have to solve that problem by doing something with the data, I just do it. I don't have a framework for how to organize the data into certain structures.
ZIERLER: It's a brute-force approach?
ZHAN: Not a brute-force approach but to identify what exactly you need for a particular science question. Don't overdo it. I'll wait for some smart computer scientist or someone else to say, "Now, we know all the things about this dataset and what people are using. This will be the optimal solution to downsample the data, compress the data, store it, and share it with people." That's not my expertise.
ZIERLER: Does artificial intelligence or machine learning help you identify those questions?
ZHAN: Oh, yeah, already. I'm happy to use any tool if it helps for a particular science question.
ZIERLER: And you think AI is a tool?
ZHAN: It's absolutely an important tool. It's not saying that you do it by brute force, using the most primitive method. It's to identify the science question and its needs, and identify the right tools for that problem. For example, if you're studying earthquakes, the majority of your signal is actually just the section of data that has the earthquake. And it's pretty sparse in time, so you actually don't have to save all the data for that purpose. But it turns out that what we call noise for earthquake study is just the ambient vibration of the Earth, and that is not noise for other people. When we have cables in cities, the cars generate noise. That's because cars vibrate on the ground and send seismic waves, which actually image the Earth, and that's how we monitor hydrology. It's sort of like, "That's the earthquake part, and this is the noise."
You just throw them away. You have different ways of dealing with that. Our students are very good at finding the most state-of-the-art tools for dealing with different kinds of problems. And they communicate it. And machine learning is a good example. In the past, when we only had a conventional network, we had a staff seismologist down on the second floor whose job it was to pick arrivals from earthquakes. They did this as a day job. It's impossible to do now when you have every earthquake with 10,000 sensors, or more in the future. We use machine learning to learn how to pick the arrivals. They're not yet as good as humans are at it, but when you have this much data, if we can get 80 to 90% of them right, it's good enough for the science. And we're capable of improving this in the future. That's how I deal with it. It's not a very systematic way, saying, "Let's build a data center of this kind, design a new data format," and so on. Rather, we say, "What is the best technology that can help us answer this science question?"
ZIERLER: You mentioned earlier, pre-tenure, your research agenda was quite broad, and maybe you're narrowing it a little bit. Looking back from graduate school to your assistant professorship, what were some of the big questions that connected all of those different areas of research? What was the connecting thread for all of it?
ZHAN: I just like data. [Laugh] I just really like looking at seismic data of all different kinds. If I feel like I look at something and I'm learning something people don't see, I get excited. That means I'm interested in all kinds of science questions. I guess that's another unique aspect, at least in the Seismo Lab and GPS division, that students are all required to have two different projects, and they're encouraged to keep adding more projects as they go. It's not one project with one advisor, and that's your PhD, and that's the only thing you really know about. That's not how we do it in GPS or the Seismo Lab. People are talking, interacting, generating new ideas. The pandemic has almost killed coffee hour, but it's finally coming back, and that's generating a lot of new ideas.
Even during my PhD, I had Don Helmberger as my primary advisor, and we looked at all kinds of interesting projects, but I also had three, four, five projects with other professors like Rob Clayton, Jennifer Jackson, Victor Tsai. I've always been pretty broad and interested in all kinds of things. But I think the common thing, again, being an observational seismologist, is that I'm just excited when I see nice data, and I'm excited to find out what it can tell me that we couldn't see in the past with other data. Maybe it's a new earthquake, a new kind of seismic network, or a unique kind of observation to test some hypothesis. And earthquake-source physics has been one of the primary ones that kind of goes all the way back, from the early part of my PhD until now. Southern California earthquakes, other deep earthquakes around the globe, recently back to Southern California again, but rupture process, earthquake physics. That's been pretty continuous. But there are all these other things happening that come and go. I think the only connecting thread is data. [Laugh] In that aspect, I'm very much like my advisor, Don Helmberger.
ZIERLER: He loved data.
ZHAN: No matter what kind of data it was. As long as you could tell him what it was about, he was excited about it.
ZIERLER: Maybe a different way to frame that question: Caltech is a small place, there are only so many professors here. Every one of them is precious because they have to do big work in a small setting. What intellectual niche do you think you fill within the Seismo Lab? Where is your area of expertise, and how does that fit in overall with what Seismo Lab faculty are doing?
ZHAN: As you said, Caltech is small, so everyone needs to fill an important role. It also means we're all pretty diverse. We all work on many different topics.
ZIERLER: Kind of because you have to.
ZHAN: Yeah. And it's kind of strange, in some other places, you may be worried about stepping on each other's toes with many people in the same place. [Laugh] Here, it's so collaborative, everyone has a different expertise. I'm in observational seismology, Mark is in geodesy, there are people doing geodynamics, doing experiments, like Jennifer Jackson. It's very different, but the science question may involve different aspects, so we naturally collaborate with each other. I think we always kind of constantly look out for new, exciting science opportunities. We feel like we can make a big contribution with that. Because of the interaction, because of the way you can identify such new opportunities, it kind of refreshes our careers all the time.
You're not a person defined just by that technique or that one science question. Most of our professors are not like that, we're pretty broad. We keep discovering new things and moving to new fields. Even fairly senior people are still doing amazing research. I think it's much more dynamic than everyone fitting in a different spot. Everyone is moving and bouncing all the time, and then you find new things you can do together. We mentioned a few things already, related to water, related to ice. I'm sure that will keep coming. Maybe the best way to define it is that it can't be defined. [Laugh] We're always trying to redefine ourselves, what we can do, what the Lab should be doing.
ZIERLER: Because so much of your research is fundamental, is there anything you do, or do you have any motivations, geared really toward sociological or societal benefit? earthquake engineering, earthquake mitigation, earthquake early warning. Do you see any of your areas of research contributing to the kinds of things that help people?
ZHAN: Absolutely. A lot of them will be, I think. It could be done by something else, potentially, but I think it definitely leads in that direction. For example, when we have the new generation of seismic networks, we'll be able to do earthquake early warning much better than before. That's a field of active research in my team, how to estimate earthquake magnitudes and locations much faster and more robustly than before. Even today's best earthquake early warning systems are focused on land because we don't have sensors in the ocean. The fiber sensing is allowing us to turn all this cable in the ocean into sensors. You probably saw the recent LA Times news on this fault that potentially can produce a magnitude-8 or so earthquake. There are many faults offshore of Southern California, and other even bigger faults, in Cascadia, in Japan, all along South America. We just have very little information about this fault.
If we can turn a lot of the cables in the ocean into seismic arrays, it will be basically as dense as on land because of the fibers there. We're going to hopefully change how we warn people about offshore events and tsunamis. I also think, even just away from seismology, there's going to be a lot of potential. Hydrology, I mentioned. I don't want to talk about that anymore, just because we can image and monitor the water. Another fairly unique aspect of my research is, most of the time, the cables are owned by the telecom industry, not by seismology. We don't have the funding to deploy a few thousand kilometers of cable. But telecom is a big industry, so they have the funding to do that. And now, the fiber cable can also be used for sensing purposes. Most of the time, now, they're doing it as a big help to the seismologists, for doing societal good. Philanthropy, in some sense.
But the research has progressed so much that I think we're also seeing a benefit to that industry, meaning that they also are learning things they want to know about their cables. For example, you can tell them about the conditions around the cable now, and you can potentially prevent certain sources of damage to their cables. These kinds of capabilities in the future may mean there's a mutual benefit between these two communities. That may be the fundamental way to actually scale this up. Only when everyone says, "I want to contribute my fiber for this research purpose because it will also benefit me," will things really grow. I think the government may realize earthquake early warning is really important, and the cable owners will realize it will protect and benefit them, too.
As a recent example, certain perturbations along fiber cables can actually produce interruptions, can interrupt telecommunications. When you have a very long cable, it's very hard to know where the trouble is. [Laugh] When the cables utilize fiber sensing, you actually can pinpoint exactly where that's happening. I'm working together with some collaborators on how to mitigate some of the challenges in communication. When I was an undergraduate in China, it was graduate student application season, so I decided to stay as a master's student, so I didn't have to do anything. All my classmates applied to US schools. Then, suddenly, China was completely cut off from the global internet because of an earthquake in Taiwan that triggered a landslide and cut off the cables.
ZIERLER: This hit close to home for you. [Laugh]
ZHAN: Yeah, they were panicking. They were like, "The deadline is tomorrow, and I don't have internet." Of course, they all got extensions. [Laugh] It was a pretty large-scale outage. Maybe the entirety of East Asia. But imagine, with these same cables, we can really understand the kinds of hazardous situations, and utilize the cable much better. Maybe we can do something to reinforce it. Maybe in the future, we can just avoid some of these regions, now that we know the structures better. I think there are quite a lot of opportunities there, too.
ZIERLER: I wonder if you've thought about the issue of extrapolatability. In other words, studying something locally, then being able to universalize that finding so that what you see in the Los Angeles Basin might be relevant for what's happening in Japan or Cascadia. How does that work from your perspective?
ZHAN: We always like to work at the frontier. People have never done this. That's where the exciting research is. What we're doing for Southern California has already been tried in several other places. And people are seeing the benefit of this kind of research, the new things you can see. They're doing it for all kinds of other earthquakes, seismically active regions, big cities, basins. They're doing this in Seattle, Japan, China. There are submarine studies. Again, we're only tapping into a very small fraction of the cables, but it's showing people what kinds of things we can do with these cables. I also see more people joining the effort to make it even better. People are trying it everywhere. Sometimes it's all about identifying what's next. [Laugh]
ZIERLER: You mentioned periodicity, the idea that some earthquakes could be periodic. First, how do you understand the differences between earthquake periodicity and earthquake cyclicity?
ZHAN: Again, I'm an observational seismologist. I like to think about just the data side. When we think something is repeating, we look at the data for one and for the other, and we plug them together. They look exactly the same. It could be just a coincidence. That's totally possible. But there are cases where an earthquake just keeps happening in the same place. When we're talking about a relatively simple system, a fault with one patch that's locked and pushing at a constant rate, in that case, it had a periodic event and cycles. In that case, it's pretty much the same. But again, Earth is complicated. [Laugh] When simple processes can interact with each other, it can give you a very complicated systems. Only in very rare cases or isolated examples do you have these repeating events. In most other cases, when you have earthquakes interacting with each other, they just won't repeat exactly. When we say repeating earthquakes–that's why we're careful in saying it's not cycles, but just repetition. That periodicity may not continue. It could be that there is a period of time it was repeating itself, but something interacts with it and changes its behavior.
You may have heard about this earthquake example, where people saw beautiful periodicity and decided to put all the sensors there, and it never came. [Laugh] I do think we have to be very careful about what we observe and the difference between repeating events and cycles, meaning there's some predictability in the process. It really kind of highlights how complex a system we're dealing with. One recent example–and again, this is using fiber, where we're seeing something we didn't see before–is, there was a magnitude-6 earthquake in Northern California, sort of near the border between California and Nevada, a region without many seismic sensors. The earthquake happened, no one got hurt, no one looked much into it. But we happened to have a fiber seismic array over there with 10,000 sensors. We were able to image where the Earth ruptured, an area about five kilometers in size, which was not a continuous, smooth propagating unzipping of the patch. There were multiple pins on there. Sort of the fault is holding things, but there are also pins inside, sort of holding the blocks together. These are the strong patches we call asperities.
With our data, we can see each one breaking, and that sends out a burst of waves. Of course, the entire Earth was sending a lot of waves out. But those were sending strong bursts of waves, and with our big antenna, we could locate exactly where they were. We could see there were four pins on there, and we could see how they broke in sequence. Then, there was a strong pin holding the rupture, and the earthquake was almost killed by that pin, but at the last moment, that pin also broke. Once that pin broke, it also radiated energy and sent out another earthquake. The earthquake suddenly got three times bigger than if it had stopped. But you can imagine that if the Earth stops in a slightly different patch on the fault, the sequence could've been different, and the earthquake would've been totally different. It would maybe rupture on the same patch. But because of this interaction of pins on the same fault plane, it's not the same thing as before. When you only have data very far away, you say, "These two are the same," but that's ignoring these kinds of complex interactions between different parts of the earthquake.
ZIERLER: Because you do see evidence in particular ways of cyclicity, that leaves open, at least in a consideration way, that maybe, at some point in the future, earthquakes can be predictable. Now, obviously, they're not. But there are two ways of looking at this, as I've come to appreciate. I'm curious how you see it. One, the fact that we can't perceive an earthquake coming now is either a statement of our observational and theoretical limitations, or two, it's a statement of the fundamentally chaotic nature of earthquakes, that the best advances in theory and observation still won't allow us to predict something that fundamentally is unpredictable. Where do you come down on that question?
ZHAN: I try not to take sides on that. [Laugh] Because I do see good reasons for both arguments. There is a fundamental chaotic behavior in earthquakes. Does that mean we cannot understand them in any way? I'm not sure about that. I sometimes compare our work with numerical weather forecasting. It's a complex system there, too. We can do certain things. Doesn't mean we do them extremely well. There are still cases where we're like, "Yeah, they're not much better than us at predicting things." [Laugh]
ZIERLER: But on the things that really help society, we know when the hurricane is going to hit.
ZHAN: Why? Because they have a lot more data than us. The atmosphere is sometimes transparent.
ZIERLER: It's more accessible.
ZHAN: Yeah. You look from above, you see where the hurricane is, you can track where it's moving, you can use radar to track where it's raining, you can measure all kinds of temperature, humidity, pressure. You have everything you need in that system. And it's still a big effort to assimilate all the data into a physical model to predict on some time scales. For seismology and earthquake science, first, much more opaque, and everything's happening on much shorter time scales. It's not like, "It's started, and tomorrow, it's going to rupture." And that's a big challenge. But I do think with more observation tools, we're going to get more and more observation on this. In some sense, it's to get a cloud map of the subsurface, to understand where the stresses are accumulating, where the heterogeneities are, whether they're stationary or moving around. Some of this may be fundamental.
For example, after the earthquake, the stress stayed on a fault, where it looked completely different than before. As it accumulates stress, will it stay completely different or come back to some similarity? If the fault plane is completely homogeneous, maybe every time will be chaotic and depend on how the ruptures randomly happen. But it's also possible that different parts of the fault have different properties. You're shearing the mountains off for hundreds of kilometers. That fault path may have a different rock than the other side. Are these kinds of heterogeneities controlling some of the stress state, controlling where the earthquake is happening and where the fault is just creeping slowly? I don't know the answer to that, but I feel like there is a chance to understand much more about that process.
ZIERLER: For those who declare, "earthquakes are unpredictable," because you're clearly leaving open the possibility, you're simply observing that the system is opaque, and you're also working at the frontier to make it less opaque. Is there a concern for people who tried doing this in the 70s and 80s and said, "Forget about it," where the question of earthquake predictability is not being pursued because some people say it's futile? Or are you not concerned about that? There's a disagreement, and the kinds of questions you're asking are really not relevant to anybody who says, "Don't bother expending efforts on this?"
ZHAN: I think that may be happening. For quite a while, people were very careful with talking about earthquake predictability or forecasting. And by the way, with earthquake forecasting, there are things we can say about where an earthquake will happen over a certain time scale. It's not like we know nothing about where an earthquake is going to happen. My personal take is, if there's no data revolution, I think people looked hard enough. The question is whether there will be a data revolution. A data revolution may not come only from dense arrays. Maybe there's something completely different. I think we have to see if there's a data revolution. It could be that with more data, we also conclude that the problem is fundamentally chaotic, and there's no way to predict it. That may well be the case. But I'm the sort of person who relies on data. I say, "People have tried all this. If the data is not changing, I don't think there's a chance to say one is correct, the other is not. What new data do we need?" That's kind of the question.
ZIERLER: You'll keep looking. Last question for today. What are the kinds of things your students and post-docs are working on right now that suggest where the field might be headed as they look to chart their early careers?
ZHAN: I think the core of the field is still there, conventional geophysics, but I think more and more people are interested in interdisciplinary topics. It's not so much at Caltech, because we're always quite oriented toward fundamental research. But geophysics in general is not. There's a lot of practical application for the oil and gas industry, the energy industry. And of course, that industry's going through some difficult times. I think there's a general kind of branding question that geophysics is not only to benefit the oil and gas industry. We are doing a lot of things that are really important for climate change. Basically, we're the discipline to start at the subsurface. Structures, monitoring the process, looking at those dynamics. That's going to be really important if we're talking about CO2 sequestration. You're talking about the geothermal, about a water resources, about ice problems, the ocean. These are all beneath the surface. And this is what the new people are excited about.
ZIERLER: Seismology is very important generally for sustainability.
ZHAN: Yeah. I think that's the new way of thinking that's emerging very strongly in this field. Of course, there's always going to be a large number of seismologists looking at deep-Earth structure, looking at earthquake rupture. Sometimes you kind of forget about earthquakes if they haven't happened recently. But they will. [Laugh] There will be continuing interest. Sometimes new capabilities kind of [work with] broader aspects of geoscience, like vulcanology, oceanography. I just feel like there are a lot of opportunities. If you think about someone trained traditionally in geophysics, it's not so easy to pick up something brand new. And if they're trained that way in the beginning, they know both, and that's the kind of person I think we need.
ZIERLER: The whole world needs.
ZHAN: Yeah. They're just naturally sitting in that space. I'm definitely encouraged that they're doing this, and that they're doing it all by themselves.
ZIERLER: It's been a wonderful first conversation. Next time, we'll go back and learn about your family in China, how you got interested in earthquakes, and we'll bring the story right up to the present. Thank you.
[End of Recording]
ZIERLER: This is David Zierler, Director of the Caltech Heritage Project. It's Wednesday, October 19, 2022. It's great to be back with Professor Zhongwen Zhan. Zhongwen, thank you so much for having me in your office again.
ZHAN: Thank you for coming.
ZIERLER: Today, what we're going to do is go all the way back and develop your family background in China. In our first conversation, we took a terrific tour of your approach to the research, some of the main questions in the field. Now, I want to learn a little bit about your family. Let's start with your parents and even your grandparents. What region in China are they from?
ZHAN: I come from a province called Anhui in China. Eastern China is relatively flat compared to Tibet or Western China, so there's a lot of population, but there's, like, one mountain area that sticks out in the middle, and that's where I was born. [Laugh] Because it's in kind of a mountain area, transportation is relatively poor. Generally, economically, it's a very underdeveloped region in China. I kind of grew up in the middle of the mountains there. Very close to nature, which is the good part, but very late to see the outside world. [Laugh]
ZIERLER: Where in China is your family from? What ethnicity are they within China?
ZHAN: They're all Han. Pretty much, Eastern China is mostly Han Chinese.
ZIERLER: What was your family's experience during World War II, if you ever heard stories?
ZHAN: It's kind of interesting. The big cities are all in the flatter parts, and whoever lost was hiding in the mountains. Our mountain was sort of the hiding area of the losing party. When the Japanese occupied part of China, their government at the time basically established their leftover kind of government in our little town. [Laugh] Then, the Communist Party tried to grow, and they also took part of this mountain. When they won, they all kind of grew out from this mountain area, which is quite interesting.
ZIERLER: What about the Civil War in 1949?
ZHAN: That's kind of in the second part. Whoever is kind of weaker at the time cannot control the big cities, so they try to establish themselves in this mountain area to hide away from the army's other plans. It was a pretty difficult time. I hear a lot of stories about people starving, trying to run to different places to hide from the Japanese army. And when the Civil War happened, even neighboring towns could support different groups, one for the Kuomintang, one for the Communist Party.
ZIERLER: What were your family's politics? Did they align for one or the other?
ZHAN: They were kind of the most common people who were just trying to survive.
ZIERLER: What were your parents' professions?
ZHAN: Neither of my parents even finished middle school. at the time, you were pretty lucky if you could get into high school, given the economic situations. Both of them dropped out from middle school, and my father became a carpenter, learned as an apprentice of another carpenter for a few years, then picked that up as a profession. My mom has always been a housewife, working just to help my dad in a job.
ZIERLER: And where you grew up, was it an apartment, a house, a farm? What did it look like?
ZHAN: It's a tiny village in the deep mountains. The closest elementary school is, like, a two-hour hike in the mountains. The middle school, you'd have to walk for the entire day to get there. If you think about steep mountain areas, people will try to use any flat space they can find to farm. Everyone is kind of separated in different valleys in the big mountains, and that valley would only feed two or three families. That was my village. The village I grew up in, there were basically three families. [Laugh] It was a tiny area with just the three families, and of course, three families can't have their own school. All the kids in the mountain areas would go to one place. It took about two hours of hiking in a pretty steep place. The year before I went to elementary school, my parents said, "We cannot let our kids suffer this," because they went through it. Then, we moved to a different place. It was nearby, but I had to walk a much shorter distance in the flatter part. But my parents both went through this. They needed to get up around 5 am and carry a torch to climb down the mountain to go to the elementary school. And the elementary school only had 10 or 20 kids in total. There was one teacher, and no matter which grade they were, they were all in one classroom. They'd teach one group for an hour, the next group for an hour, and so on. They went through that, and they finished elementary and part of middle school. The thing is, they needed to work for the family, too. They'd sell eggs and firewood. Even though they'd be going to elementary school, they'd carry those on the way to school so they could sell them, go to school, and bring the money home. It was very hard, and they didn't want me to have to do that. And my father had been doing his carpentry. It wasn't really a shop. He actually had all his tools in two boxes. He would carry them and walk to different villages, asking if people needed something. If they had work for him, he'd stay there for a day or two, make it for them, and then go to the next village. He accumulated a little bit of money by doing that, and they decided we could move away from our area. We moved nearby, a slightly bigger village with more people and a bigger road. The schools were closer.
ZIERLER: Do you think your parents had ambitions for you to do more at least than they were able to do?
ZHAN: Oh, yeah, absolutely. In China, it's kind of a strange thing, even in a really poor place like where my family lived, they put almost the highest priority on education. It's like, there's nothing more important than education. Whatever they could afford, they would do it. Because of that, they moved to this nearby street so I could walk to school.
ZIERLER: Was this the same school that they went to?
ZHAN: No, it was different, a little bit bigger, better teachers. And clearly, that made a huge difference compared to the other schools. Of course, those old schools eventually disappeared. The government realized, "This isn't fair to a lot of people," so they slowly kind of moved people out from the mountains and put them in places where they could build more infrastructure. The last time I went back to China was 2015, and I went back to that village because my grandparents were still living there. They don't want to move. Everyone left, but they refuse to leave. There are only a few people still living there, things are collapsing, no one is maintaining things, so the people all moved out. It's much better now for kids. But I stayed there for three years, then we moved to this village closer to an elementary school.
ZIERLER: What was the name of the town you moved to?
ZHAN: It's just called Little River. [Laugh] It's literally next to a little river. It's Little River Street. The other one was called Date Valley because maybe in that part, there were some dates. That's the name of the little village. The year after we moved, I went to elementary school, so it was very early. Basically, we lived on a road where all the kids who went to school needed to pass by my front door. And my little brother was three years younger than me, so we could not play together. I was watching all these kids pass by my front door in the morning and afternoon looking very happy, and I was like, "What is this?" And of course, in the countryside of China, you don't go to school until you're 7 or 8 because you need to walk pretty far away to get there. I was very bored, and I saw all these kids doing something fun, and I really wanted to go. I went to school very early, 4 and a half years old, I went to their kindergarten. [Laugh]
ZIERLER: Did you stay in that town until middle school, or did you leave?
ZHAN: My family basically lived there until I went to college. They lived there for a fairly long time. There's only one middle school in a much bigger area, which was the only place I could go. There was no other choice. Then, I went to high school, and there were only two or three high schools in the entire so-called county, so there wasn't much choice there either, so I went to the only one I could go to. [Laugh] It was one of the better ones because I scored very high in some of the entrance exams. But there weren't many choices. It's very different from here. Just this past year, we were debating in our family where to send our daughter to elementary school. There are all these choices of public school and private school. so many choices in Pasadena. In our area of China, there was no choice. [Laugh] There was much less discussion about all of this.
ZIERLER: When did you start to get interested in math and science? What were some of your early exposures?
ZHAN: I was always very interested in it. Even before I went to elementary school, my mom always liked to teach me. I think she saw that I had some talent, good memory, good at counting. Even before I was 4 and a half years old, she'd write characters on a paper card from the back of a cigarette box, show me the numbers, and I could remember them pretty quickly, so she was pretty happy. And I was doing pretty well in school. But I think because they were living in the mountains, there was absolutely no after-school program or curriculum. You'd just finish your little homework, and I remember, we had one TV, and there was only one channel, mostly not for kids. All we'd do was go out to play in nature. Go to the river, climb the mountains, play with your dog, those kinds of things. We got pretty close to nature, and I was very curious about what I saw in nature. And in China, at that time, in elementary school, there were only two courses. There was basically, literacy, basic Chinese language, and math. There was no music, drawing, physical education. They didn't have any teachers for that in my area. We were lucky to have math and Chinese teachers. But they didn't have any other programs, so all they could do was keep teaching you Chinese and math. But when I was in middle school, I started to learn geography. And I started to realize that all these questions I had while I was playing in nature had these amazing, simple explanations. I was very amazed by that, and even into high school, I was very intrigued by geography. When you're in the mountain areas, where the sun rises, it's very clear because you have the mountain, trees. Every morning, you get up, "Where's the sun?" It's pretty high already because you're kind of deep in a valley. In the winter, the sun was in a totally different place. I asked my parents why, and they had no idea. [Laugh] But once you go to study geography, you realize, "Oh, the Earth is rotating and tilted at an angle, so in the summer and the winter, the sun appears in different places." I was rather observant, but I had no idea what these things were.
ZIERLER: Did you have access to a library?
ZHAN: No. I think maybe my family had more books than others, partially because we had a lot of old books. A lot of people went at most to high school and then to work, so they didn't want the books anymore. For some reason, we had a lot of their books in our house, and of course, they were way above my reading level. But I liked to flip through them because they were the only books we had, and I'd read some of the simple ones. But there was no library for me to look up the things I wanted answered. Everything I'd ask my parents, their only answer could be, "Ask your teacher." [Laugh] But the teachers, again, didn't know much about these other things. They teach what they teach, and there's not much else in the way of exploration.
ZIERLER: What about a television? Did you have a window to the outside world at all?
ZHAN: Yeah. There was only one channel.
ZIERLER: State television?
ZHAN: Yes, the so-called CCTV1. That's the number-one watched channel in China. Everywhere, you have that. [Laugh] Especially the news part. All channels have to turn to CCTV1 at 7 pm so they can listen to the nationwide news. That was the only channel we had. And there was probably one hour of kids' programming every day. That was all we could watch. I'd watch the news around dinnertime. It's a very different world. [Laugh]
ZIERLER: What about education in the Chinese government? Did you learn about Mao Zedong, Communist ideology, those kinds of things?
ZHAN: Oh, yeah. I think there was very little of that in elementary school. Common things like raising the flag Monday morning, probably similar to the US, we did. I was born in 1987, so I went to school in the 1990s. It wasn't nearly as much as in my parents' time. It was a period of opening up. There was a time when if you were born as a farmer, you were a farmer. If your parents were farmers, you were a farmer. There was no change. My parents' generation was the first, because of the opening up of the country, to have the opportunity to change. They'd go from being a farmer, to a carpenter, to being a small business. Their education included a lot of the political things. I think when they were in middle school, the Cultural Revolution was near the end. I didn't get a lot of that. Maybe more in college because political classes were a requirement. People don't pay a lot of at that moment to them, but they have to take them. I don't feel like there's a lot of emphasis on that in elementary, middle, or high school. All parents have only one thing in mind at that stage, getting to college. And that depends on one test. At the end of high school, there's a single test you take over three days. Each day, you have two exams. Your score determines where you can go. They don't pay much attention to anything else, be it political or extracurricular stuff.
ZIERLER: In high school, did you get exposed to more advanced levels of science?
ZIERLER: Did you have proper biology, chemistry, physics classes?
ZHAN: Yes. And that kind of started in middle school. You start to finally get geography, physics, chemistry, some biology. Then, in high school, you get into deeper math, physics, geography, chemistry, biology. The thing I was most interested in at the time was geography. I was very interested in physics as well. Not too much chemistry and biology.
ZIERLER: Geophysics is perfect for you, then.
ZHAN: Exactly. At the time, chemistry and biology was just memorizing a lot of things. You didn't need to understand the reasoning too much. And I didn't like those at all. The physics was very interesting. Geography, it was so amazing that you could explain all these things. The awkward thing is, in China, when you're getting into high school, to prepare for the exam, there were two setup exams that happen at the same time. One is for people going into a STEM direction. No matter what direction you go, you always need to take Chinese and math, but if you're going in a STEM direction, you have to take physics, chemistry, and biology. If you're not going into STEM, something like history, administration, management, you study history, politics, and geography. You choose in your first year of high school, and you can't change, and you don't study the other courses anymore.
ZIERLER: Your path is set early on.
ZHAN: Yeah. And I knew I had to choose the STEM path, but geography was in the other path.
ZIERLER: Why would geography be in the other one?
ZHAN: I have no idea.
ZIERLER: Like, political boundaries?
ZHAN: Yeah. It's also kind of more related to city planning and those kinds of things. They don't think of it as understanding the physics behind these processes. It's sort of like, "If you want to understand how to build a city, you have to understand how a river flows." I actually didn't get to spend a lot of time on geography, but whenever the class was taught, I was very interested in it. I didn't get to study it deeply, and they didn't even give you homework on that stuff because you weren't taking an exam on it in the future. Maybe that's good. I never lost interest in it because I didn't need to study it for the exam. I felt like physics was great, but I was very interested in geography. You sort of get initial exposure to these things in middle school, the second year, and then you really get deeper into them in high school.
ZIERLER: In the way that you said in elementary school, there wasn't any extra education, like physical education, things like that, by the time you got to high school, did you have more opportunities?
ZHAN: Yeah, you can do more. Even in middle school, you can do more. You do more running, some sports. Table tennis is the most popular thing because it only requires simple facilities. [Laugh] There was no swimming pool, but there was a river nearby, so we'd swim in a river. There's some soccer, basketball. Once you move into higher and higher levels, there are more and more resources more concentrated into a few schools.
ZIERLER: You must've done very well on this test.
ZHAN: Yeah. The test wasn't too hard for me. It started pretty hard. I was never in the top students, though. There were people smarter than me who studied harder than me for the entire time.
ZIERLER: But how many of them became Caltech professors?
ZHAN: [Laugh] That's actually an interesting thing. I feel like trying to be number one is a very popular thing in China.
ZHAN: Yeah, very competitive. I feel like it's a bad measure of what you can do, how much passion you can put into something. To me, finding what you're really passionate about is going to determine the final outcome. Being number one in courses and study isn't quite as important.
ZIERLER: What opportunities did a good score on the test open up for you? What schools were available to you, and what schools might've been out of your range?
ZHAN: For me, it was strange because as I said, I went to school really early because I had nothing to do. I just wanted to go. The teachers initially didn't want me. [Laugh] They said, "You're too young. You can't even control yourself in the classroom." But eventually, I was okay.
ZIERLER: Were the Harvard, Caltech, and Stanford of China available to you as a result of your score on this test?
ZHAN: I didn't get to that point. You take the exam at the end of the third year of high school. but because I was very young, when I was second year in high school, I was 14 years old. There's a special program from one university in China called the University of Science and Technology of China. They have one class. Every year, they find people who are still under 15 and ask them if they want to take this exam a year earlier than everyone else. If you get a high enough score on that, you may be able to get into this special class. The class name is Special Class for the Gifted Young. In the US, when you say, "special class," it's a different meaning. [Laugh] I saw the advertisement for this class, but I had no idea if I could get in.
ZIERLER: Was that attractive to you? Did you want to go to college earlier?
ZHAN: It's well-known. As I said, for Chinese parents, education is a super high priority. In my county, in the entire 50 years after China was established–the program was established in 1978, so by the time I could take the exam, it was around 20 years old. Out of that 20 years, two people got into the class. And they're known by everyone in the country. Everyone knows those two kids. Because every parent pays attention to this kind of thing all the time. I heard about them and this class, and I had no confidence I could get in. As I said, I wasn't particularly near the top of the class, I didn't study very hard at the time for the exams because I knew I had a third year coming. But I knew that if I wanted to succeed in the final exam, it would be great to do a practice exam. And if you applied for this test, you could. It was a real exam, and it was pretty cheap to register to do it. None of my other classmates were allowed to do this practice exam. Only I could do it because I was young enough to register for this class. I said, "I'm just going to try it, not to try to get in, but to practice, so I know what the real exam is like." Then, when all my classmates went for summer vacation, I basically went to audit in the third year of high school to sit in, to see how they're preparing it, to practice with them. From middle school on, I always lived in schools, not with my parents. I started to live by myself in dormitories when I was 10 years old. Ever since then, it was only the vacations, summer and winter breaks, that I went back home.
ZIERLER: Even the weekends, you stayed in the dormitories?
ZHAN: Weekends, I had one day at home. Just went home to get some food. Strangely, in three years of middle school, there's no cafeteria. It's like, "Everyone bring your bucket of food."
ZIERLER: For the week?
ZHAN: Yeah, for the week. It's totally cold, and that's the only thing you get to eat for the entire week. It's not very healthy food for teenagers. [Laugh] When it came to the last year of my high school, I was by myself in my dormitory, sitting in the classroom with the more senior students. There was no pressure. It was great. All my classmates went through huge pressure. As I said, a single exam determined everything. They went through huge pressures the year after, but I had no pressure at all. I did the exam, I went back home, enjoyed my summertime, and once September came, and the school year started, I realized I hadn't done any of my homework for the entire summer. I said, "Today, I'm going to start working hard to finish all my homework." And I received a letter or call that said I was selected to go to the second round of the exam. [Laugh] Now, it was becoming real. I did another round of tests, and it was very different from the first round. The first round was a typical Chinese exam, very strict, very familiar layout of problems. We've done similar problems a hundred times before, been preparing for exactly how to do it for the next nine years. You just need to know how to do it. This other exam, we spent a week there, and none of it was about what we've learned or memorized, a very creative kind of exam. 75 people get to it, and they select 50. I barely got into the 75, and I barely got into the 50.
ZIERLER: But you did.
ZHAN: But I did. I basically only spent two years in high school then went to this program.
ZIERLER: Was that exciting for you, to start college early?
ZHAN: It was very exciting. USTC is one of the top schools. They often call it the Caltech of China.
ZIERLER: Is it small, like not the MIT of China?
ZHAN: Exactly. It only has 30,000 people. [Laugh]
ZIERLER: By Chinese standards, that's tiny.
ZHAN: That's one of their smallest ones. [Laugh] That's still 10 times bigger than Caltech.
ZIERLER: Where is it located?
ZHAN: Anhui, the same province. It was a university in the capitol, Beijing, but during the Cultural Revolution, all universities were kicked out of Beijing, and they went to the poorest of places to help the local development. Most universities were able to get back to the big cities, but the USTC never got back. But I was very happy. It's a very good university, the program was and is very famous. It's so famous that we often think of the program as the university and the university as the program. People don't know about these other 30,000 people, they think the university is for these 50 people every year.
ZIERLER: Did it attract students from all over China?
ZHAN: Yeah, pretty much. It's a pretty even distribution. Proportional to the population, I suppose, so fewer people from western provinces, but in general, it's pretty even.
ZIERLER: Did your parents support you going to college so young?
ZHAN: They were really excited, very proud. As I said, before me, there were two people. [Laugh] They were really happy I got in. We were all very excited. Everybody was very excited. The high school was so proud, they had big banners in the street that said, "We have someone getting into this program."
ZIERLER: Is college in China more like the American system, where there's general study, and then you focus specifically later on? Or is it more like the British system, where you have to declare a focus right away?
ZHAN: You declare your major before you get into school. you have to specify exactly which program you need to get in. And every program in the same university has different scores, a cutoff score. But I was lucky. I think this was one of the luckiest things for me. This particular program for these 50 kids follows the American system. Because you're so young, you have no idea what you're going to do. And you choose later, in the third year.
ZIERLER: You did not go in thinking geophysics?
ZHAN: Not at all. I was thinking about physics. As I said, I went into the STEM branch, and you're not even allowed to take geography in that. I was just eyeing physics. And physics is something USTC is very famous for. Very strong program there. I was definitely looking at physics for the major. But because of the special treatment of this class, no other students in the school at the time are allowed to change major. Maybe by the end of my stay there, they started to relax it a little bit. If you were the top student in your major and wanted to switch, there was an opportunity for you to switch, but it was still limited to a very small number of people. But in this program, you took broad classes and could choose whatever you wanted later. But again, USTC is STEM-focused. It's all about math, physics, computer science, biology, and engineering. There's nothing else. There's one English department called scientific writing. And there's science history, actually. But those are the only two things they do on the non-STEM side of things. In this class, because they have high hopes for these 50 kids, they brought teachers from all over the campus to teach us the best of all departments. We learned the math as if you were a math student and the physics as if you were a physics student. The requirements were very high in the first two years. For example, if you were a physics major in the beginning, you learned a lot of math and physics, but you didn't need to learn as much about computer science. Even math had different levels, one, two, and three, so you didn't need to learn level one, just level two. But in this special program, you had to learn the hardest level of all departments. There was a pretty high bar in the first year. Everyone suffers because of that. [Laugh] But you've got to know what each department is like. You take some introductory class in each one. And there are more research opportunities in each one, too, so it's very much like our SURF program. In the summer, you get to do some research as a volunteer in a lab, and you get to try different things. That was really critical for me in eventually choosing geophysics as my major.
ZIERLER: Growing up, did you experience any earthquakes?
ZHAN: Actually, no. My first earthquake I felt was the Wenchuan earthquake in 2008. At the time, I was already in the second year of my master's degree and had already gotten my offer at Caltech. Actually, I didn't even feel that one. I was walking on the road, and people around me felt it, but I didn't. The first earthquake I actually felt was in California after I joined Caltech.
ZIERLER: How did you come to focus on geophysics from physics? Was it a class, a professor?
ZHAN: Very slowly. I wandered around a lot. I was initially, my first two years, looking at physics. I went to physics labs, did some volunteer work, some simple projects. The particular projects were very boring. A lot of simple programming for some educational modules in the physics classes. I was not very excited about that. I was also talking to people doing more theoretical stuff, but it can be hard to get a grasp on what your research is going to be. Some people just naturally lean toward equations and abstract things. I'm more into things I can see and feel. After trying some of these projects, I happened to be in the Intro to Geoscience class. It talked about everything in geoscience, sort of like our G1 class. And that was great, I really loved it. It reminded me of all the geographic things, but with all the physics, chemistry, and biology integrated. I really liked that. The professor is an environmental scientist. He studies the poop of penguins in Antarctica. He was one of the first Chinese geoscientists to publish a paper in Nature because he studied the chemistry of penguin poop and reconstructed the temperature vibration in Antarctica over a long time. He's a star professor. I was so amazed by the classes, I knew I wanted to do environmental science. I went to talk to him and said, "Is there a research opportunity?" He asked me what I knew how to do. I said, "I'm kind of interested in physics, and I really hate chemistry and biology." [Laugh] And he said his lab is basically chemistry and biology. Because these are kinds of environmental issues. He said, "You're probably not a good fit in my lab." And I think he made the right call, otherwise it may have been a pretty miserable few years for me. I have no idea how to do those kinds of chemistry experiments. Then, I wandered into space science, which is another strong major at that university. But this professor studied plasma, but somehow gave me a project related to ice on Europa. He said, "Take a look at some of these papers, and we'll discuss them."
I still remember it was about big cracks in Europa's ice, and on the sides of the cracks, you get ice mountains because the cracks squeeze back and forth and pump water to the top. And these ice mountains actually bend the ice layer down, and you can measure that bend and estimate how thick the ice is. I thought that was really smart. As a second-year undergraduate student, I said, "Maybe there can be some improvement. Maybe if you have a crack, the temperature in the ice would be different. If it is, the rigid or elastic part of the ice would be not uniform, so their assumptions may not be correct. Maybe I can do something there." And the professor was very excited. "Oh, yeah, that's a great idea." I learned how to do some programming, finite difference modeling of the temperature. Eventually, we got a paper published. That was pretty rare for an undergraduate in China. It was actually in a top journal in China. He was very excited and wanted me to keep working in space science. But I started to feel like the solid Earth side was more interesting. I was kind of unsure exactly what to do getting toward the end of the third year. I had to decide whether to stay as a graduate student or come to the US. USTC is sometimes called the US Training Center. [Laugh] Because more than half of the students come to the US. I wasn't sure what I wanted to do. Space science didn't feel like something I wanted to do with my life. That was the end of 2004. Then, the 2004 Sumatra earthquake happened, magnitude 9.2. It was the biggest earthquake in tens of years and killed something like 270,000 people in Indonesia, India, Sri Lanka, because of a huge tsunami in the Indian Ocean. It was on the news every day. And I wasn't studying that at all. I didn't study geophysics at the time. But our university had just hired a new professor named Sidao Ni. He was a student of Don Helmberger, whose office was here.
ZIERLER: Was this the first you'd thought about Caltech and the Seismo Lab? Had you heard about it at this point?
ZHAN: I'd never heard about it. I had a seismology class, and I knew about the Seismo Lab from the textbooks. [Laugh] It was famous for many things. But I had decided to take seismology as my major. Sidao Ni was a new professor, and he'd just published a Nature paper with an estimate of the size of the earthquake. Because it was the largest earthquake in tens of years, people had kind of forgotten how to estimate the magnitude of the earthquake. Initially, it was said to be magnitude eight-point-something. That would be tens of times smaller than what it actually was. But he figured out a way within a few days. It was actually much bigger than we thought. The paper was published in Nature, and people started to realize it was much bigger. He was just returning as a professor, and he gave a general public lecture for all students about seismology and this earthquake. The classroom was packed with people interested in this. I was totally intrigued by this. I stayed on to discuss with him further about some questions.
ZIERLER: This was the first time you got really excited about something academic?
ZHAN: Yeah. It was amazing that by looking at all these seismograms thousands of kilometers away from the earthquake, you could measure the true size of the event and why it had such a humongous impact. And that was just amazing. It's not seeing it, but listening to the vibrations of the Earth. And it was a great talk, too, because he knew that most students didn't know about seismology. He cited ancient Chinese books that described earthquakes and how they related to modern seismology, and eventually how it was being used in this big earthquake study. It was an amazing talk. I was totally intrigued, and I said, "I want to do an undergraduate thesis on this topic."
ZIERLER: That was it, you were in.
ZHAN: I chatted with him a few times. And he was new. He had inherited a few graduate students from other professors, but I was one of the first undergraduate students to show interest. He immediately took me in. He's also from this special class, actually. [Laugh] He knew this class produced good students, and he immediately took me in.
ZIERLER: Did he tell you about Don Helmberger and the Seismo Lab?
ZHAN: No. We'd chit-chat, and he'd talk about things happening here. Of course, he was trained here, and his style was as such, the way he does research. But really interestingly, I was there to study earthquakes, and he gave me a project just on the noise. On the seismogram, you have the earthquake, and he wanted me to study the noise.
ZIERLER: That's what you give the undergraduate.
ZHAN: Yeah. [Laugh] It's kind of interesting, I think it was really good timing, looking back, because that year, there were one or two papers that basically opened up seismology for the next decade. And he knew that because he just came back from the Seismo Lab, where people discussed the most exciting things. We had never heard about this in China. We had no idea this was happening. He just brought these papers and said, "Look at these papers. They claim they can turn the noise into signal. You don't need to have earthquakes." I said, "Yeah, let's study this. Let's see if what they say is correct. Are things we need to prove better? Are there things we can use it for?" Somehow, luckily, because of this, as an undergraduate the first time in seismology, I was looking at a cutting-edge problem at the time.
ZIERLER: This probably is where your love of data begins.
ZHAN: Yeah, exactly.
ZIERLER: And you knew it was cutting-edge data at the time?
ZIERLER: Looking back, you see how significant it was.
ZHAN: Yeah. That was 2005 when the first paper had just come out. Of course, this thing would grow and grow, and it's still going today. But that was in the very beginning. Only a few groups around the world were realizing this might be important. My advisor had the vision, due to his training here, to say, "This is important. We need to look into this." As an undergraduate, I had no idea the landscape of this huge seismology research area, but I was given it to look into it, and it was really interesting. I was definitely not fighting him, saying, "I want to study earthquakes for sure." But I found this very interesting. That was when my trainings in physics and computer science, which I learned equally well in the beginning, really came into play very nicely. As an undergraduate, I was able to write my entire program to do all this related to data processing, so I could basically catch up on what people were doing other kinds of studies. That was very nice. And I really enjoyed the time with the professor and other group members. Later, I would know this was from Don Helmberger, but we'd just look at data together. We'd print seismograms, try to understand what they were, discuss as a group how to make things more efficient, and so on. I decided I didn't want to go to the US, I wanted to stay as a graduate student with this professor. And he happily took me. There was literally no transition from my undergraduate thesis to my master's research.
ZIERLER: You just stayed.
ZHAN: I just stayed. There was a graduation ceremony, but nothing else changed.
ZIERLER: Was it a terminal master's program? Could you have stayed for the PhD?
ZHAN: I could've. I was kind of undecided exactly what to do in the long term. I wanted to be a scientist, I'd known that for a long time, but I wasn't sure if I wanted to get a PhD there. In China, a master's degree is a little bit different. It's a three-year program. It's not like the US, where you just take classes. You actually need to do research. This is where I owe my advisor, Professor Ni, a lot. In the second year, he said, "I don't have much more to teach you. You should go to Caltech." He helped me with the recommendation letter. I applied to a few US schools, I got into all of them, but I chose Caltech to do my PhD.
ZIERLER: How computational was your education in China? Did you have access to decent computers, good software?
ZHAN: Oh, yeah. This was a top university.
ZIERLER: Well-funded, good resources?
ZHAN: Well-funded, good computers. It was when I first heard about parallel computing, supercomputing. We built a cluster by ourselves. Professor Ni was very interesting. There was one time he said, "I have this big monitor. Who can write this code to solve this particular problem?" When you simulate a seismic wave, you cannot simulate the entire Earth for high-frequency waves. It's too expensive. You need to draw a box. But on the box, you need to make sure the wave goes out and doesn't reflect back because it would be artificial reflection. He said, "Who can figure out how to write the code for this?" Of course, this was a problem our Professor Rob Clayton solved when he was a PhD student. It's a really well-cited paper called Absorbing Boundary Conditions for Acoustic and Elastic Wave Equations. It's part of his thesis. And we didn't know that. We didn't know it was that hard to do. [Laugh] We were just thinking and thinking, but at least we were looking at a simpler problem, not as complicated as what he was doing. But I was just thinking about this all the time. I started dreaming about it. And I figured out the solution. And I wrote it down, I coded it, and it worked. And I was so happy, I showed it to the group, and I got the monitor. [Laugh] There was quite a bit of competition. We'd look at data together, discuss different science questions. And there was quite a bit of coding involved, too. It was a lot of different things, a very good program.
ZIERLER: You said for the master's, there was original research you had to do. What did you want to focus on? What was interesting to you at that point?
ZHAN: I got so into this noise study, I just kept going on that.
ZIERLER: All the way from undergraduate, you stayed on that.
ZHAN: Yeah, even until the second year here at Caltech. I'm still doing some of that these days.
ZIERLER: Is that because, at the end of the day, there are just interesting things to find in what's otherwise rejected as noise?
ZHAN: Yeah. It's really amazing that suddenly, you don't need to know the source. It has always been about the idea that you want to look inside the Earth. Once in a while, the light will be turned on. That's an earthquake. Send waves through it, and you just take an opportunity to look at all those things inside. And suddenly, this totally changed the paradigm, so you don't need that. You just need to look at all these random things propagating around the Earth, and if you have a long enough record and enough sensors, you can get the information out just by doing that. And in the very beginning, there were so many questions. "Why did this work?" [Laugh] Theoretical questions like that. And, "What is the best way to do it to get the max amount of information out of it?" During my master's degree, everyone started to report, "Yeah, we're trying to hear, we're trying to hear." You get all these beautiful surface waves between the sensors. Basically, the idea is, if you have two points, you have in the Earth random vibration. That's essentially generated by noise everywhere on Earth. A lot of it is wind, a lot of it is ocean, and so on. Of course, the noise just looks completely random, but there's a very small fraction of the noise that has been propagated to once sensor and continued to propagate and be detected by the other sensor.
ZIERLER: And that's what you're looking for?
ZHAN: Yes, and that is the only part out of the true noise that has any coherency or relation.
ZIERLER: Which tells you what?
ZHAN: Which tells you the extra leg it traveled between the two sensors. Imagine you have two. There's a source probably to one and to another. They're related. But this one has an extra leg between the two sensors. If you can extract this information, you have measured this extra leg there, thus there was the structure in between. This is as if you turned this sensor, as a source and measured the response as if it propagated from that sensor to the next sensor. That's great. But all these people doing this said, "Look at this beautiful surface wave." Because the seismic wave propagating from one to another, there's a P-wave and an S-wave, propagating deep into the Earth and coming back. There's also the surface waves, like what you see on the ocean surface. It propagates very close to the surface, and it's the biggest wave, so it's the easiest to see. It gives you useful information, but only near the top. The body waves, the P- and S-waves, go down deep, they tell you something deeper, but they're much weaker. My first question when I saw this, I wanted to know whether we could see the body waves, this other phase. I didn't want to do routine information on the surface waves. I did some of those just to learn how it works. I wanted to know if we could get the deeper waves. And if we could not, in most cases, people don't see them, why? Was it because of the way we were processing it, or we really can't see it? Because I had my own code starting from the last year of undergraduate, I just tried many things. I loved to look at data, so I knew where to look for these potential signals. And I was very lucky. I found a few cases where there were super clear body waves coming all the way from 30 kilometers down that reflected to the surface. That was one of the first papers in the entire field to say, "We actually can see body waves."
ZIERLER: Where was this data coming from that you were working with?
ZHAN: Worldwide networks. At the time, there was already this consortium led by US universities called IRIS. All the public data is assembled in this one place. Anyone in the world can download it. I'd just look at different places and find such examples. To a master's student, that was an interesting finding.
ZIERLER: Did you publish this work?
ZHAN: Oh, yeah. But not until a year after I came to Caltech because there were so many interesting things, we just kept adding to it.
ZIERLER: What did that resolve, its significance for the field? What did you add up until that point as a master's student?
ZHAN: Really, to show people that it was possible to do it. We still didn't understand why.
ZIERLER: It was a proof of concept.
ZHAN: Yeah. No one before us showed that you could do it. Most people would say, "You're just going to get surface waves from this problem. Just focus on the surface waves." But our paper was at least one of the first, but probably the first, to say, "In these cases, we see very robust body waves, and we have ways to verify they are body waves, not something else. And we have reasons to explain why in these cases that it makes sense they're stronger here. You may expect this for other places around the world." Of course, I wrote about this in my application to US graduate schools, and I think that played a big part.
ZIERLER: And your advisor could've kept you. It was very generous of him to say, "You'll be best served going to the United States."
ZHAN: Yeah, definitely. It's actually very common that in China, people try to keep students for a very long time. But he was very supportive and said I should go to Caltech.
ZIERLER: How was your English when you were thinking about coming to the United States? Did you have formal English classes?
ZHAN: Oh, yeah. USTC is the US Training Center. [Laugh] Most students take a lot of English classes. And of course, you study it hard for this GRE test that's a requirement at the time. You have to take them. Still, when you come to the US, it's not that easy.
ZIERLER: You're not speaking it every day.
ZHAN: Exactly. But it was okay. All my professors and other professors, even before Professor Ni, said, "You will be fine. Your English is much better than when we arrived in the US." [Laugh]
ZIERLER: Were any of your classes or textbooks in English at USTC?
ZHAN: No. All Mandarin.
ZIERLER: But again, our school has a lot of connections with US universities, including Caltech. Professor Ni was not the first Chinese student Don has had. Don has had, since the 1970s, a continuous stream of Chinese students in his group. And more than half of them have been from USTC. I'd say Don made a tremendous impact on Chinese seismology. His students, in the early days, never went back to China. The difference was too big. They all stayed in the US, many as professors. But then, kind of stating around when my advisor went back to China, there was a steady stream of students going back to China. And later, some of the more senior, established Chinese professors in the US also went back to China, took a joint program, educated students. I think a lot of the seismologists in China have some connections to Don because of all the people he trained who are now seismologists in China. He had a tremendous impact.
ZIERLER: What advice did Professor Ni give about where to apply in the United States? You applied to more than Caltech.
ZHAN: I applied to four places that all had top seismology programs. This is the good thing about applying when you're a graduate student. You're actually doing research and reading papers every day, so you're not going too much on the reputation of the school or the rankings, you actually know who's there.
ZIERLER: Because you've read their work, you know the papers.
ZHAN: Yeah. You discuss with people in your group. Maybe I wasn't working on it, but other people were working on projects related to the projects of these professors. You get a taste of what kind of research style they have, and you apply to the places that line up with yours. At UC San Diego, Peter Shearer was the one I wanted to work with. I ended up being his post-doc. Then, there's Stanford. Then, there's Berkeley, Barbara Romanowicz. I'm sure Professor Ni had a bias that influenced me in the process. [Laugh] Because he was Don's student, I really loved the research style, I was into that research style of looking at data. And he also told us every once in a while that Professor Jeroen Tromp, who was a new professor at the time, how amazing his numerical method was. That was when he was asking us to write down these absorbing boundary conditions for the code. He was teaching us how to do these kinds of things. This was totally the future of seismic wave simulation, the numerical seismology. We got training on both ends. When I applied, I said, "I want to work with Don and Jeroen Tromp. I want to combine this old style of seismology and seismogram reading with the new numerical tools." When I got an offer, it was so exciting. It wasn't an easy decision, but it was very exciting. I got the job offer around the Chinese new year. I was still at home. As I said, I was in the poor countryside. Most other parts of the country had good internet already at the time, 2008. We still only had dial-up. I had to wait for the email to show up on my screen very slowly. But I was very, very excited. It was an amazing opportunity.
ZIERLER: And you didn't know that Jeroen was headed back to Princeton?
ZHAN: That's the interesting part. Then, in summer, around June, when I was graduating, defending, getting ready to go, and I received an email from Jeroen Tromp. He said, "I know you wrote that you wanted to work with me and Don, but I'm going to Princeton. You now have a choice: stay at Caltech, or go with me." And that year, Caltech admitted two students from mainland China. One was me, one was a student from Peking University, another top university was strong geophysics program. He sent that email to both of us. The other student decided to go with him and join Princeton.
ZIERLER: Did you know how closely Jeroen and Mike Gurnis were working, and that sort of closed the gap for you?
ZHAN: No, at the time, I didn't know much about Mike Gurnis at all because I was very focused on seismology. And at that time, at USTC, there was not much of a focus on geodynamics. There was a little bit of lithosphere dynamics. There was one professor, very senior, not too active at the time. But not too much about deep Earth or those state-of-the-art simulations. I didn't have much idea about that at all.
ZIERLER: Even with Jeroen leaving, the prospect of working with Don Helmberger was enough for you?
ZHAN: That was a heavy internal debate. But I felt Don's style was still the one I wanted to learn. I decided to stay.
ZIERLER: This is a perfect place to pick up for next time, when you arrive in Pasadena.
[End of Recording]
ZIERLER: This is David Zierler, Director of the Caltech Heritage Project. It is Tuesday, December 6, 2022. It is great to be back with Professor Zhongwen Zhan. Zhongwen, it's great to be with you again. Thanks for having me in your office.
ZIERLER: Zhongwen, today, we're going to pick up right at that point when you decide to come to Caltech for graduate school. All of the cultural transitions for you, everything from society, and language, and food, and all of those other things you had to manage. Was being the academic grandson of Don Helmberger easy for you? Did that make the transition easier for you in any regard, having that connection with your mentor?
ZHAN: I would say it has been maybe easier than most people for many reasons. One of them is because being Sidao Ni's student, knowing to some level how the research here works, that really helps. Also, as I said last time, I had a master's degree in China, meaning I had two years of experience of actually doing research. That helped a lot, I think. Culture-wise, of course, there's always a big change. But at the same time, I think maybe 10, 20 years before my arrival, there'd been a tradition of a steady flux of students from China. When I arrived at Caltech, there were quite a few other Chinese students here. They were all extremely helpful, which made the transition also much, much easier. I would not say there's a big challenge there. Of course, working indirectly under Don's student mentoring, it's still different from Don himself. [Laugh]
He was, in general, pretty quiet, not giving you a long discussion or details of what he wants to do. He'd sometimes just stare at your result for a long time without saying much. [Laugh] It's sort of like, if you're not used to that, you'd be wondering, "What is he thinking? Am I doing okay, or am I doing something terribly wrong?" [Laugh] But you got used to that. He was really thinking about what those things mean. But I think one very interesting aspect is, because Don had so many Chinese students, even before me, he really seemed to understand that our English was no problem, even when we first arrived. He knew how to communicate.
ZIERLER: And you could just look at the seismograms together.
ZHAN: Yeah, look at the seismograms, but also he knew when to kind of slow down and understand exactly what you mean in very simple words. I think he seemed to have the magic power of understanding even just new Chinese students with no problem. I think I was very lucky in that even just in the first couple months, we were getting some very interesting research results. Because when I arrived in August, September, very quickly, there was an earthquake in Southern California, the 2008 Chino Hills earthquake. It was a 5.4, but one of the bigger ones in the couple years around there. We quickly did some work there. And then, what was surprising, just after those three months, he sent me to a conference to present these results. From China, it was, you work hard for a few years until the end of this thesis–
ZIERLER: Before you're ready for showtime.
ZHAN: –and then it's your showtime to present your conference or something. For him, it was no big deal. "Yeah, you've got something. I think it's interesting. There's a SCEC meeting. You just arrived, but yeah, go with someone and figure out what you want to do at the conference." [Laugh] I attended my first conference a month or two after I arrived, and it was a great experience to know that it's not like you have to get the final thing ready to present. That's kind of the mindset in China, I would say, at least of the time. But here, it's much more–
ZHAN: –informal, yeah. Go show stuff, go discuss with people what those things mean. Research-wise, I think it had been a pretty smooth transition, although there were some good surprises in learning how it works here.
ZIERLER: It would've been before your time, but when Don Helmberger was director of the Seismo Lab, after Hiroo and before Jeroen, do you have a sense from him what his impact was on the Seismo Lab, what he brought to that role?
ZHAN: I don't really know much about that. Don was not the kind of person who always had a grand vision of something and tried to gather people together to move towards some big science goal or something like that. I think he was much more like, "Yeah, you're all doing interesting stuff. That's great." He would encourage you to do whatever you felt excited about, and that was how he mentored students as well. But I don't know how he was when leading the Seismo Lab. But at least in terms of how he was educating students, that had always been the case. He had his own ideas, and he definitely tried to talk to you about what those were and what he thought might be interesting to do.
But if you came back not doing that, he would not poke and push you again on those things. He would just listen to what you had done and say, "Oh, that's really exciting." [Laugh] And a lot of good stuff happened that way. He just knew data and liked to look at data, so when you'd show him something, he'd feel genuinely excited. "Oh, that's really interesting. I didn't know about that." And he'd encourage you to get a little bit deeper into some of the observations and figure out how to understand them. I think many, many of his big discoveries probably came that way instead of a grand vision and a detailed plan, finding the right expertise and moving toward that. It was more about exploring and finding what was interesting.
ZIERLER: What was he working on when you first connected with him in 2008?
ZHAN: As I said last time, I was drawn into seismology because of the 2004 Sumatra earthquake. That earthquake seemed to be the beginning of a few years with a lot of global large earthquakes. I think the community in general just thought it was random chance. It happens that there are a few years with a lot of big earthquakes. But in terms of observational data, suddenly there was a lot of observation on big earthquakes. I had no experiments studying large Earthquakes at that time because I was asked to study noise. And there was a lot of excitement and activity about how to image these large earthquakes. Many of the best tools were developed here under Don's supervision. When I arrived, it was already 2008, but there were still a lot of big earthquakes and a lot of study on them.
You can clearly see there were quite a few people, both in Don's group and in others, especially Mark Simons's and Jean-Philippe's groups. They both had a lot of geodetic tools to image earthquakes. They were really working very closely with each other. And the most exciting part was, at the time, the coffee hour was very different, I feel. It was because with any significant earthquake, not necessarily huge ones, there were always people producing models, background, and pictures on the earthquake. They'd bring it into coffee hour, and we'd discuss what the earthquakes were telling us. I think a lot of Don's focus at the time was also on the big earthquake part of it. I know that in the 1990s or early 2000s, maybe the focus was slightly more on the deep-Earth part of things. But when I arrived, there was a lot more focus on that. There's still a lot of structure study, but more focused on bigger earthquakes. That was an exciting time.
ZIERLER: Because you had already come in with a master's and done original research, did that make you more focused on what you wanted to do at the Seismo Lab for your PhD?
ZHAN: I thought that way when I arrived because I was like, "Yeah, I've done some research. I know what I'm interested in." I think even when I was applying, my research statement was probably different from many others in that I actually had a very detailed list of some questions I wanted to study, with some preliminary observations, even. [Laugh] There was an understanding of ambient noise, body waves, there was a study I did about Earth's core structure. Turned out to be very different. I think that was a very good thing. When I arrived, I thought I knew what I want to do.
ZIERLER: But you want to be open to what's happening here.
ZHAN: Yeah, but then they ask you to talk to all the professors, and I did that, and I realized, "Oh, there are so many other things going on here." And of course, my initial idea was working with Don and Jeroen Tromp, but Tromp left just a few months before I arrived.
ZIERLER: Did you talk with him at all before he left?
ZHAN: No. There was email communication in which he asked me if I wanted to move to Princeton, but I decided not to, and we didn't have further discussion. I thought I would combine Don's expertise on waveforms and waveform monitoring with Jeroen's expertise in H1 tomography, a very mathematical way of doing the inversion. I realized that wasn't going to happen. [Laugh]
ZIERLER: When Jeroen came here to really embrace high-powered computing in geophysics, by the time he left in 2008, was your sense that that project was complete? Or it was he had come here, and he had accomplished what he had set to, and with Mike Gurnis succeeding him, that project continued? Or was there sort of unfinished work that Jeroen could have completed if he'd stayed?
ZHAN: I feel like he did the first prototype, the first complete demonstration of how this H1 method works, using Southern California as an example. In that sense, Caltech would've been a unique place to do that because we are in Southern California, we're around the network with USGS, there's a lot of background understanding of their velocity structures, earthquakes, geology, so it's the perfect place for doing that. I think he chose the right place to run this prototype. And the result is spectacular, to show a brand-new way of thinking about the inversion of the Earth. The Southern California structure really brings a new image of the subsurface. It was really a pretty complete prototype. And of course, even in the years immediately after he left, there was still substantial effort to make it even better.
I would say now, the Southern California community velocity model, which is largely based on the kind of method he developed, while the model exactly follows that effort, it's still very different from the exact model his group was producing, but with the same kind of technology. I definitely would not say it's complete, even for Southern California. It showed a clear path of how to do it, and people continued to work on it. And there are other groups, like at USC, another seismo lab run by Tom Jordan, also made an effort with a slightly different approach to do the same problem and also got a fantastic result. And that was just the beginning. There were many more groups using related methods to other regions, to the entire globe. By no means was it complete, in that sense. [Laugh] But I think I was very impressed by the first real data demonstration of his idea in one big area, Southern California. I think it was the right place to start. And I think at the time, I was really quite eager to understand what exactly was making this model better in some ways, different from what people had done before.
That definitely shaped a lot of my interests in terms of, "Yeah, I'll work with Don and try to make different ways, try to solve the imaging problem to be better. But there's this other way, very different from Don's approach. [Laugh] What is really good about it, and can we learn something from that?" I think that partly kind of got me interested, so when Jeroen was not here, and I looked around the lab and talked to all the geophysics faculty members to figure out what I wanted to do, that may have partially influenced my work with Mark Simons. Because Mark is also very interested in this kind of inverse problem and the mathematics behind it. I never really finished my project with him, but I learned a lot in the inverse problem aspect.
ZIERLER: What about the coffee hour? How important was the coffee hour for you, realizing that it was best to be open to new research ideas?
ZHAN: It's just a really fascinating place. Even in my first year, I went to coffee hour quite a lot, which is, I think, kind of rare, at least these days. People are just busier. Students also feel like there's a lot of pressure to get things done.
ZIERLER: You have the pandemic, remote learning, and all that now.
ZHAN: Exactly. But it just opened your mind to all these different kinds of research problems. Again, as I said, at the time I think earthquakes was a much bigger topic than it is now. I didn't study big earthquakes before, but I feel like all I know about how to do imaging of big earthquakes came from coffee hour. People would just lay out how they actually did it. And it was not like a lecture, it was based on an example. And I didn't understand much every time, but they'd just do it again and again. Every earthquake, they'd come in, show results, and explain what had been done differently either from other people or from what they had done previously in the method. You'd just learn a lot about what they used to study earthquakes, what was challenging, and how they tried to improve it. That aspect was really valuable. You just got to see all these other topics besides earthquakes.
It felt like I learned more there than in a lot of the classes, simply because classes are much more systematic about something, but this was a sampling of everything people felt excited about in the field. [Laugh] It really was very, very broad. That part of it was very exciting. Also, my schedule when I was a student was much worse than now. You'd really stay pretty late in the evening and come in the morning very late. The coffee at 10 or so was a perfect time to start my day. [Laugh] I didn't have a lot of other duties or things to do. No drop-offs, nothing like that. You'd just stay pretty late, very quiet in the evening, do interesting stuff. If you did something fairly exciting, you'd print a figure, put it on the table, then the next morning, grab it and go downstairs to try to discuss it with people.
And that kind of pace of feedback, if you're open to presenting things that are very preliminary, you quickly throw out ideas you show to people that no one is interested or thinks is important. You get a sense of what is exciting. People say, "Oh, yeah, this is very exciting. Maybe there's something here." That pace of feedback just improves projects so quickly. If you only talk with your advisor, maybe once a week–Don was amazing. His door was open all the time. You'd just knock on the door, and you could go in any time, which would give you faster feedback, too. But coffee hour was happening every day with different experts there. You'd just discuss things, know what was right and wrong.
ZIERLER: What was Don's style like as a mentor in terms of giving you ideas, things to work on, and ultimately how that played into what your thesis work was on?
ZHAN: I think most other professors are much more organized about that than Don was. [Laugh] Maybe because of the stage of his career he was in. He was already pretty senior and just wanted to see interesting stuff. He didn't try to come in and say, "This is what I think the general direction or topics of your thesis should be about." Maybe because of that, by the end, I actually had big trouble figuring out what the title of the thesis would be because I could not find a single thing to connect the projects. And he was also super open to me working with other professors. There were many projects he just had no idea about. I tried to sometimes get help from him or talk to him, and he'd help me, but he was like, "What is this about? I didn't know you were working on this." [Laugh] A lot of the projects especially about glaciers and noise, he didn't really have a strong interest in. But he let me do them. He wasn't organized like most other professors, "Oh, yeah, I have a new student. Work at least in this general direction, and hopefully a thesis will come out this way," and then work with the student to do it.
ZIERLER: It was probably also confidence in you that you didn't need that level of oversight, that he was happy to let you go and pursue the things you wanted to do.
ZHAN: My understanding is that many people in Don's group did this kind of thing. It wasn't just me. And some people are naturally more focused. I don't think it's about capability but style. They don't feel like they want to work on many different topics, they want to just have a real focus on something. I saw students like that, and of course, Don would be very interested in guiding a student towards some of those projects, but I saw people who worked on many different things, so it wasn't just me. When I got ideas from coffee hour or talked to other professors, most likely it was still seismology-related, something related to seismic data. And of course, Don was really helpful in that. He actually didn't go to coffee hour all the time. He wasn't as regular, at least when I was here as a student, as people like Hiroo, Mark, or Rob. But when a good idea came back, he was always like, "Yeah, let's look at this," giving me input about whether he thought the data made sense.
ZIERLER: You mentioned that there were many projects, and you were struggling for a theme that connected them. What were the individual projects? What composed your thesis work?
ZHAN: There are so many I don't even quite remember now. In the very beginning, it was continuing the work I was doing in China about getting body waves from ambient noise, from seismic noise. Don was actually a bit interested in that. In the beginning, he didn't like ambient-noise seismology, even though it was a rapidly growing field because you couldn't see a waveform in it. It was just a bunch of noise. And when you do this so-called cross-correlation to get the so-called Green's function between sensors, it's mostly a surface wave, and he was not very interested in waveforms of surface waves. [Laugh] But when we were getting things like body waves out, he was very interested. That was one project. And he was also very interested in earthquake locations in Southern California.
He always asked me, "If you can do all this nice ambient noise stuff, can you locate earthquakes better?" We did one of those. That's probably the only project in the thesis that was mostly his interest, not mine. Everything else was maybe not his initial intention, but it became a bit part of our projects together. The other one was studying the earthquake focal mechanisms, orientations of the rupture, in the Tohoku region. Basically, Don had a bunch of tools I learned, and I found I could determine an earthquake's focal mechanism very accurately. Then, when I applied them to earthquakes in the Tohoku region, I found some surprises, and I think those meant the interface is not flat as people expected. Maybe there was a lot of curvature on it. Actually, quite significant ones. It was basically not a planar structure. He was excited about that, so that was another one that didn't have much connection with the others.
There was a study about some data people collected in the past on a glacier on an ice shelf. I was trying to get ambient noise correlations, but not to study Southern California structure, but study the ice structure as a way to evaluate if a similar technology could be used on an icy planet. That was Jennifer Jackson's interest. I was talking to her, and she was interested in whether we could put seismometers–I think at the time, we were talking about Europa. Planetary scientists are amazing because they didn't have any data, but they were able to come up with scenarios and say how the experiment would work or not. I said, "Maybe we should try a real-data case. The closest thing would be an ice shelf in Antarctica with thick ice over water, seeing if we could detect the water."
Because of that motivation, I did some work there. Then, there were people in France who proposed a new idea of how to use ambient noise to monitor subsurface change, how Earth is changing with time. At the time, I was very skeptical idea, but now I'm doing a lot of work and research in that direction. [Laugh] But I was very skeptical, and it was mostly because the changes were so tiny. I always knew that data was so complicated, it was like, "Can you really extract that?" There was a lot of discussion in the coffee hour about that, and I realized it may have been a reason I was biased. Then, I worked with Rob to write a paper saying, "If you don't consider this, this is how much uncertainty you may add to your problem." And the uncertainty at the time was comparable to what people had observed. At least a reasonable level of doubt should be put on some of these observations until it's proved this is not a big issue. It was very different.
And then, this last one may be quite interesting. By the time I was about to graduate, a big, deep earthquake happened in Eastern Russia in the Okhotsk Sea. It was the biggest deep earthquake, 8.2 or something. I learned a lot during the coffee discussions, and I wanted to figure out what kind of rupture process had taken place. As I said, I'd never worked on big earthquakes for my entire PhD, so I'd never written a single code doing earthquake imaging up to that point. But the conventional ways to work on them didn't seem to work that well on this earthquake. In the end, we found out that this earthquake was actually fairly complicated, even for such a deep event, because it actually had different physics from the shallow ones. But I was very interested in it, and I realized a lot of the methods people had developed for shallow earthquakes tried to handle all the complexities related to the fact that the earthquake was near the surface. There are so many complications.
I realized that for the deep earthquakes, you can really go to the essence of inversion and ignore all the other things. Keep it simple. You're still able to image the earthquake really, really well. And I was able, because of coffee, classes, understanding how other people worked, in about a week to write my own code to do the entire inversion myself from scratch. And I think it was one of my favorite papers in terms of revealing how an earthquake rupture actually happened because I knew what was actually essential in this inverse problem from listening to how all these different inverse problems worked. If you think about the core of this, it's actually fairly simple, and you can program it within a few days and get it to work very nicely. I remember that my wife, girlfriend at the time, was in Florida, and I went to visit her.
I said, "I'm not going to go outside while I'm here, I'm just going to do this program." I was literally in the living room, did the coding, and by the end, I said, "I got it. This is the model." [Laugh] There was some complication in the publication of that. It was essentially accepted by Nature and then not accepted, but that's a different story. But it was a nice paper about the earthquake. That really gave me the impression that I could also work on earthquake rupture processes. Then, during my post-doc and the early part of my tenure track here, I worked a bit on larger earthquakes, too.
ZIERLER: You mentioned that as a graduate student, you were struggling to see a unifying theme.
ZHAN: I was not struggling, I was enjoying it. It was only near the end when I needed to write the essays, I needed to write a title, and I was asking professors, "What should I put in the title?" No one knew. Don especially was like, "I have no idea how you're going to do this." But they all said, "It's okay, no one reads those essays." [Laugh]
ZIERLER: This is one of those staple-a-bunch-of-papers-together kinds of dissertations.
ZHAN: That's exactly what it was.
ZIERLER: Who was on your committee?
ZHAN: Don, Rob, Mark. I think Victor was there. Jennifer maybe. Victor was not, actually, because Victor arrived in the middle of my PhD. Jennifer was my academic advisor.
ZIERLER: Outside readers? Do they have those here?
ZHAN: No, we don't have such a thing. [Laugh]
ZIERLER: Who needs it with the Seismo Lab?
ZHAN: I think, again, partially maybe because this essay really became just stapling a bunch of papers together, the paper had been reviewed by people outside before publication. I think mostly, people just read the part that hasn't been published or is still in preparation, read the introduction and conclusion, and just have fun discussing various projects during the defense.
ZIERLER: Looking back, do you see any specific connections to your more recent work on telecommunications lines? Is there any connecting point there?
ZHAN: That's a really good question. The only direct connection, of course, is that I think near the end of my PhD, I started to realize this thing existed. The technology was just at the beginning, getting into the geophysics research domain. It was a little bit there in the industry part of it, but academia learned about it, I think, near the end of my PhD. We started to pay attention to it, get excited about it, but we also had the sense that it was not quite ready. You can say that was partly because of the style we do the research, very quantitative. Just seeing the signal doesn't mean you can use it. Is it a quantitatively reasonable signal to deal with, or is it just a bunch of higher noise when the earthquake waves arrive?
It was very exciting, but there was also the sense that it wasn't quite ready, so we waited, watching to see what the best application would be when the technology was ready for research purposes. My PhD did shape how I wanted to use the telecom approach, what questions I was interested in. We did a little bit of using this kind of cable network to look at site response, traffic, human activity, those kinds of things. But it was never the mainstream. We were still interested in deeper structure, how the Earth works, how earthquake rupture works, all previously unobservable processes either in the ocean, in volcanoes, or hopefully even deeper. And that's kind of research direction we're currently going in our group. I just heard good news from my students, very excited, saying, "This is the first figure, but I wanted to show you this."
We're starting to see things tens of kilometers deep, reflections from tens of kilometers deep. I think most people, when thinking about that as being a very dense array at a small scale, they're thinking about very close to the surface. But I think my PhD shaped what kinds of questions we want to answer with this new network. If we feel like it's not going to work or help on those questions, we probably won't jump in. No matter how exciting the technology is, it's still a tool. Whether it can impact the question we're interested in is still the criteria on whether we should jump into it.
ZIERLER: When you were finishing up graduate school and considering post-docs, first, did you think about returning to China? Would the right job have been attractive to you? Or you knew you were committed to making a life in the United States?
ZHAN: I was committed to going back to China. I was thinking about doing a post-doc, then going back to China, following in my advisor's footsteps.
ZIERLER: What post-docs were you considering here?
ZHAN: At the time, I think, in China, their programs all required you to have at least two or three years of working experiments in the US. A post-doc counted for that. If you didn't have that, it wasn't good. That's why I was thinking about doing a post-doc in the US first, then going back to China.
ZIERLER: What programs were you looking at?
ZHAN: I was looking at places like Stanford, UC San Diego, Lamont. But mostly based on the seismologists there I could work with. It was not a particularly successful post-doc search. [Laugh] The only offer I got was from UC San Diego, and I went there. It turned out to be great because Peter is a great advisor.
ZIERLER: Is that connected with Scripps, the post-doc?
ZIERLER: It means the same thing? You say UC San Diego and geophysics, it means Scripps?
ZHAN: Yeah. It's Scripps, then there's a particular department, the IGPP, the Institute of Geophysics and Planetary Physics.
ZIERLER: Who did you work with there?
ZHAN: Peter Shearer.
ZIERLER: What was he working on at that point?
ZHAN: He had a completely different style of research. I would say he'd never, ever looked at a single seismogram directly. His way of research was always considering what was statistically significant, in some sense. Try to use as much data as possible to somehow combine and stack them together to reveal things that are systematic or statistically significant. A very different way of doing research. Don never did that. Don was always like, "Out of all the seismograms, I want the 1%, or 0.1%, or just a few of them that can tell me exactly what's happening. Those ones are the best." Maybe because the source is best, a simple, sharp source so that the image is cleaner, or for whatever reason. Peter never does that. Peter's like, "Okay, we've got these tens of thousands of stations around the globe and earthquakes happening all the time. We've got big arrays like the US array, the Earthscope project. How do we combine all the data together?" And that was a very different style of research. His first project for me was to say, "If you have a very dense array, can you start to image a scattered wave, scatters that we couldn't identify in the past, just because we have a dense array, to see fainter signals?" I learned a lot in that process.
ZIERLER: Was the oceanography aspect of Scripps relevant to you at all?
ZHAN: Not through Peter, but again, influenced by the style of research here. I was trying to reach out to others at Scripps. I talked to a few oceanographers. No real project actually emerged in the end.
ZIERLER: But the exposure was useful for you.
ZHAN: There was good exposure, especially about the ocean waves, how they interact with the solid Earth and generate seismic noise. There was a bit of exposure here, but there, there are a few scientists who are very interested in that process. One of my co-advisors was Peter Gerstoft, who's sort of partially in geophysics but partially in ocean acoustics. There's also another Peter, Peter Bromirski, who was almost solely interested in the ocean wave process and how seismic methods can help improve that. There was a bit of exposure there. They also have a very nice glaciology program there, and I did some glaciology here, a little bit, kind of on the edge, so I was also trying to get more exposure there. Again, no real project emerged, by I got some exposure on what kind of research they're doing by listening to their research projects. I would say it was harder than I thought to produce a project outside Peter's group than here. Because when I was at Caltech as a student, it was effortless. All these projects just emerged. My biggest job was to beat some of them down, figure out which ones are bad, and not work on them.
ZIERLER: Maybe you needed to appreciate that about Caltech, only by leaving.
ZHAN: Yeah, all these things, new ideas. Talk to people to figure out which ones don't work. There, I had a hard time saying, "What would be a feasible project by myself, by connecting Peter and a few other people?" It never actually happened.
ZIERLER: We know the next chapter, you ultimately do return to Caltech. But what's the surprise there? The expectation is you'll go back to China. What happens in the meantime?
ZHAN: I was trying to get some experience to say–actually, I arrived at Scripps at the end of 2013, and that was, of course, the season when all the job openings posted. I was like, "Yeah, let me try one or two." Because I still had to finish the two years before I went back to China. I said, "Okay, let me try. If I don't get anything, I will for sure go, continue what I was determined to do, and get some experience with the job market here." Do a little bit of training, in some sense. That's one aspect of Don, he didn't give you much career advice on how to write any of those applications. [Laugh] He didn't pay too much attention to that, so I felt like I needed to practice proposals and so on a little bit. But I applied, and I surprisingly got quite a few job interviews. And if you've got job interviews, you've got to prepare for them very carefully. And surprisingly, I started to get job offers from very good universities. That was when I started saying, "Okay, should I really go back to China? Because these are really top universities."
ZIERLER: Part of it was just confidence, that you thought going back to China was your best option, not that it was what you wanted to do personally. You just thought professionally, that was where you might have the most success. Then, once you got these excellent interview options, that sort of changed your mindset, it sounds like.
ZHAN: That's a good question. I don't remember much about that. I definitely feel like I was trying to get some exposure to the job-hunting process, some training, some proposal-writing experience. Some of these universities were really very good places. I was excited, like, "If I could get in there, it would probably be very good." But I don't think I had the confidence in that. Maybe it was the opposite of what you said. Maybe it was like, "Yeah, there's a very obvious path of doing good research by going back to China." There are many, many people who went back to China after me. At the time, there was still a big flux of people going back. Getting a good position at a physics department at a top university in China is not hard for a Caltech and Seismo Lab PhD.
And there are good resources there, good students. It was the obvious path without much difficulty to do good research. I think that's the way to say it. And I wasn't confident I could get a good position in the US at a top university. If you're at an okay university, maybe not a top research university, but maybe better in some other aspects, I feel like in China, you'd have a better chance of doing good research. Because you get good STEM students. And funding was also more abundant. I felt like if I chose between not a top university in the US versus a Chinese university, I would probably go back to China because the top ones had more resources at the time. But when it comes to the top universities in the US, it's a different situation. And I wasn't confident that I could get a top university position.
ZIERLER: When you were a graduate student here, did anyone give you any indication–did Mike Gurnis take you aside one day and say, "Go do really well with a post-doc, then maybe we'll talk about a faculty appointment?"
ZHAN: Absolutely not.
ZIERLER: When Caltech made this offer, that was a total surprise to you?
ZHAN: I was surprised I was even asked to come back to give that job talk. I was surprised to hear that.
ZIERLER: Do you know who was organizing that?
ZHAN: I have no idea. To be frank, if I knew any of that–I didn't even move so much stuff to San Diego. I remember I had a bunch of boxes of books, papers, and so on. It was so heavy. It really was a pain to move to San Diego, and there was no reimbursement of moving expenses for post-docs. You just had to do it, and it was a terrible experience. Then, two years later, it was all moved back without being opened. If I knew any of this, I would've found a friend and said, "Can you just hold onto this for a while?" Even better would be to try to buy a house ahead of the steep price hike. [Laugh] But I had absolutely no idea.
ZIERLER: What was your job talk on when you came back?
ZHAN: It was about deep earthquakes. But no one heard the complete story here because that was very much near the end of my PhD. Some of the work continued during my post-doc, so no one knows the complete story except maybe Don and Hiroo. Because that project was in collaboration with Hiroo. I also organized it a different way that I thought would be interesting to the audience, so I didn't panic and talk about completely new things outside Caltech.
ZIERLER: Sadly, when Don Helmberger passed in 2020, for you and the Seismo Lab, how did people remember him? How did they honor his legacy?
ZHAN: Yeah, that was really sad. It was also a big surprise. Because he was always a super fit person. He was an athlete when he was young. He was a champion of the 400-meter run in Minnesota, and he played football. He was always quite fit, he biked back and forth every day. It was a big surprise, and I think even more surprising because that was a few months into the pandemic, so there was a separation between people. I was like, "Yeah, I haven't seen Don for a few months," and suddenly the news came, and it was a big shock. I was very depressed for a while. Don, especially, was always trying to help. When you first become a tenure-track faculty member, the biggest challenge is trying to get external funding. My initial attempts were all pretty unsuccessful. [Laugh] That's very stressful when you're a young person. And Don really tried to help by using some of his connections. He had some great connections with the Air Force.
ZIERLER: Was this the nuclear verification research?
ZHAN: Yeah. He had been doing those things for a long time. He was on some boards, he knew people, knew what kind of research would be interesting. He really tried to help me to write some proposals in this direction, and I eventually got some funding. Of course, I was also trying some other things. This was one of those things where I wasn't extremely excited, but if I got the funds, I could develop methods that could be used for other things. That was extremely helpful. It was a big shock and very sad when Don passed. I never knew a lot of the details. Initially, I always thought it was COVID because at the time, COVID was really kind of at the peak. It kind of changed how I dealt with COVID. I was being extra careful. It felt like it was getting really close to me, affecting someone I was really close to. That was a difficult time.
ZIERLER: When you joined the faculty, was your main area of research at that point the deep earthquakes? That was what you wanted to focus on?
ZHAN: Deep earthquakes was the first thing I focused on. But I knew it would not be at the end of even that five-year tenure-track period. That was very clear. I think that's the part I'm actually surprised by myself. That part was kind of planned, in some sense. I had been working on deep earthquakes for two years at that point, from 2013 after the big earthquake in Okhotsk, and then for two years, 2015, when I came back. And I saw a lot of good opportunities there. A lot of good research could be done. Probably just because there were big earthquakes, and also there were new methods we could apply to them. It was a long-time puzzle I felt I could make some contribution to. It was also clear to me that it was not the project I wanted to present, say, for my tenure case, or where I see my career going in the long term. But I wanted to work on it because I felt like there were a few exciting things there I wanted to work on. But I wasn't sure of what the thing I would be working on was. At the time, DAS was on the radar, but I was by no means determined to start it. But my experiments here–I did a lot of detailed waveform modeling, but I also saw the amazing stuff Rob is doing with these dense node arrays and how Peter was doing this amazing large data processing, a stacking kind of processing. I got the sense that the future was in dense array.
ZHAN: It just gave me the sense of an unbiased vision about seismic wave propagation. That's kind of the essence of all my three mentors' research. Don was able to look at a few seismograms and figure out what they meant because his mind was trained about wave propagation. He was doing wave simulations in his head. If he saw a few points, that was enough to constrain what the entire thing was like. Rob basically showed if you have a dense array, 5,000 sensors, you could see how the wave actually propagates. Peter was using much larger arrays, not like a nodal array, but hundreds of stations across the entire US, thousands of sensors around the globe, many, many earthquakes to really detect things you couldn't see systematically in single seismograms. Again, it's a wave field, combining data at different times and different locations together to interpolate what the wave field is like. Because with a sparse array, you cannot do that in a few events without the mental wave simulation Don was able to do. Don was, of course, unique in that aspect. Most other people couldn't do that. That gave me the sense there was a lot of value in dense arrays.
ZIERLER: When Zach Ross arrived, did that pull you into the artificial intelligence work at all?
ZHAN: Even up to this point, I've never done anything directly on that. I still don't quite understand how it works. [Laugh] I see it as an amazing way to accelerate some of the processes and also extract information that may be hard to extract otherwise.
ZIERLER: Because the data is just so enormous?
ZHAN: Yeah. The data is so enormous, and the idea of learning, training, and then applying to other datasets efficiently was truly amazing. I think the combination of dense arrays and machine learning is sort of a natural process. But no matter what, it's the kind of science question I feel like you need a large, dense network to get that information out. And what do you need to do that? You can do nodes, you can do DAS, you can apply machine learning to it. Maybe a few years from now, there will be other things coming in that will also serve the same purpose. And we will likely also look into that, too. [Laugh]
ZIERLER: What was the original connecting point that would lead you into the telecommunication line work?
ZHAN: I think around 2015, '16, the first two years, that was when I was doing my deep earthquake study, amongst other studies. I was starting to do some dense array algorithms, like how to best use dense arrays. But I was still watching and saying, "What should I invest in with my research time?" At the time, we heard exciting research, especially on small-scale problems. Some of the national labs or universities started to use DAS for geothermal field research, a few kilometers in size. Some of them started to use it for studying near-surface processes, of which permafrost is one. We listened to talks to see what they could do with these small-scale problems.
But I always wanted to have something that was bigger-scale, and I also saw the big logistical challenge in some of this research. Most of them, I think except the Stanford one because they have a campus cable that extends a few kilometers–they have a bigger campus than us. [Laugh] That was a very nice experiment. But even including that, on the order of a few kilometers or even hundreds of meters in size, you had to deploy your own cable, and that was a headache. I could see the frustration in some of the PIs of the projects. They spent 99% of their time dealing with that. It just didn't seem to be a viable solution for the kinds of questions we were interested in here, large-scale regional, hopefully in the future, global, problems. Deploying your own cable that way is just unlikely to happen. Not scalable. I still remember that day, an evening at home, I was just thinking a lot about this project, like, "How can we do something different?"
At the time, I think Mark had maybe just become the JPL chief scientist. I got a little bit more exposure to the JPL side of resources. I forget exactly how I got into this one, but I realized this Deep Space Network in the Mojave Desert must have cable connecting it, and they spread it tens of kilometers apart from each other. The entire circle is something like 60 kilometers of cable. It's out in the middle of nowhere so they can really build big antennas, but they need communication to get the data back. I said, "For this, you need real-time telecommunication. There's must be a cable there." And I initially was thinking it must be a cable connecting from there to JPL. That would be great. I started to search online. I forget the exact process. Either I found a map somewhere online about the Deep Space Network or just very excitedly emailed Mark and said, "Can you find out what is available there?" And we realized there was indeed a cable there. That was the point I was like, "This is it."
ZIERLER: What does that allow you to do, having that length of cable?
ZHAN: A large-scale DAS demonstration. Not something hundreds of meters or a kilometer in scale, but something at least having the potential to expand and get closer to the scale we care about, regional seismology. Of course, later, I realized on the small scale, all these hydrology problems, there's a lot of value there, too. Now, I realize that. But at the time, we were interested in regional seismology problems. If you have something that, at least in the future, can expand to 60 kilometers, it's a pretty substantial size.
ZIERLER: What kinds of questions can the perspective of regional seismology answer as opposed to a hyperlocal, right-at-the-epicenter kind of perspective?
ZHAN: If you're interested in things like regional earthquakes, detecting earthquakes in the deep structure, the rule of thumb is, your array should be on a comparable size of whatever thing you're interested in. The rule of thumb is, the antenna size should be on the same scale of the process you're looking at. If you have something on the order of tens of kilometers, you can look at whole crust, which is on the order of 30 kilometers. You may be able to capture changes along tens of kilometers distance I would not expect, given the seismic wave, by looking at the sea change over a kilometer distance. It would probably not tell you much about the earthquake rupture process if you only have a kilometer lens. You need something that is tens of kilometers in size for an earthquake, say, 100 kilometers away, a big enough span for you to image the process. Otherwise, it's as if you have 1,000 identical sensors without any difference. It's just noise, a little bit. You don't have any true new resolution there. That's the point. I was like, "Okay, at least this is on the order of tens of kilometers. It might become very interesting, and we can start from there." Also, of course, with JPL being such a close connection with Caltech, I felt like the process of accessing it would be much easier than otherwise. And that's been indeed true. That's been the key to the success, I think.
ZIERLER: You mentioned some difficulty with external funding in the beginning. What were the key funding agencies for the telecommunications work?
ZHAN: It was JPL funding.
ZIERLER: That made it easy.
ZHAN: Of course, in the beginning, I had to use my startup Caltech internal funding to do this. But once it started, we got one of what was at the time called a PDF, President and Director Fund. The Caltech president and JPL director got had this pool of funding to support this kind of collaborative research. That was the beginning of it. That was an extremely helpful fund to get this DAS part of my research started. And at the time, other funding started to come in. The saying is that NSF, USGS funding, you really need to try multiple times to get one project funded. At the time, other things were also coming in, but the DAS thing was just in the beginning, so the internal funding was extremely helpful. If I had to wait to write a proposal to NSF, that's a year, and then get another cycle of two years, I would have wasted too much time.
ZIERLER: Especially as an assistant professor. You don't have that time to waste.
ZHAN: Yeah. And I had no experiments in this domain in the past. We just had this idea, saw this opportunity, to demonstrate how DAS worked for regional problems.
ZIERLER: Was anybody else thinking along these lines? Were you in competition with any other research groups?
ZHAN: Of course. As I said, we were not the first to look at this. Stanford and Berkeley were both looking into this direction. But I think we're unique in the sense that we're really thinking about regional problems and regional geophysics problems. I think they're a lot more focused. Still things related to energy or industry applications, geothermal. The Stanford one is particularly related to the oil and gas industry. We were kind of more unique in a way. We were basically already thinking, "Okay, we have this Southern California-sized network. What is the new technology to improve the network?" But it needed to be dealing with related problems to that. Southern California network, what do you do? earthquakes, structure, maybe some hazard and mitigation, earthquake early warning. You need to look at this large aperture, at least see how the technology has the potential to expand for this large area. I guess for any research field, there's always competition, but I think we found a unique angle that suited us best. That's still the way we're doing it.
ZIERLER: What were the outcomes of the project?
ZHAN: The project outcome was really, in terms of publication, one paper, the first DAS paper from the group showing that you can really use this kind of dense array to image across a structure. It's not like we imaged something amazing, but it showed that it can work. And that's the demonstration of a few things. First, you can really use telecom cable on a pretty long distance for this, if you can find the cable. And that's how we convinced Pasadena to contribute. They said, "If the JPL cable didn't get damaged by doing this, we're probably okay, too." [Laugh] That's a big factor. This was a very new technology, and people were concerned. But I showed them, "This is what we've seen at JPL. And they didn't lose any of their communication with their space missions." [Laugh] That was a big component to that.
ZIERLER: That's wonderful.
ZHAN: Yeah. It's really, really important, to have something that can show people, "This is how it works."
ZIERLER: More broadly in your research agenda, when did you start thinking about translation or societal benefit, thinking about what you might offer for, for example, climate-change research, megacities, things like earthquake mitigation? When did you start to think about the application side of the research?
ZHAN: This part, I didn't really know when I first started, and after starting the DAS project, it wasn't immediately clear. Because you can imagine when you're dealing with a new type of data, it was very hard in the beginning. Very, very challenging. Because you have no idea what the data is telling you. You give me a seismogram from a seismic station, I can immediately say, "Oh, P, S, this wave, this is why this part is complicated. This complication may be telling you about structure. That is probably the source, the Earth's big process." You have the intuition. You know what to look at, what is noise, what is signal. When you look at DAS data, first, it's enormous. You have trouble to see them. You don't have the right tools to visualize them. It's impossible for you to plot individual seismograms of any kind. Every array, there are thousands of them. [Laugh] I always joke that I could never do what Don is doing for seismic data. There's no way to do that.
And our eyes are also not trained to look at this. A lot of it is, "Okay, that's probably car noise, but what is this other thing on the side of it? Is that artifact?" Because it's c able, who knows what it's doing? [Laugh] "Or is that some kind of seismic wave generated by the cars? Is that an earthquake? Why does it look like this? What are these things behind it? Why do I not see it on conventional stations nearby?" There was a steep learning curve there. But once we realized that, we started to see, "Oh my God, these are things we couldn't see in conventional stations." Or you see it, but you had no idea what they were because they only appeared at a short distance. In a conventional station, when you separate it by 10 kilometers, you'd never see it again. But when you have a dense array, you see all of them, and you can see the differences from place to place.
And that's the point we realized, "Okay, this is not going to be just providing denser observations similar to the conventional." You actually can see a lot more, and especially at scales we couldn't observe in the past, higher frequency, shallower structure. And the convergence, how fast you can extract information is amazing. Again, these correlations are learned in different methods of study that you need, like, a year of data for two stations to give you a good measurement. At least a few months. That was always the mindset. But when I asked my students to try some of this, they said, "I got it in a day. I could see it looked beautiful in a day." It definitely exposes the new time resolution you can have. It's the realization of this new spatial resolution you can have, new time resolution you can have.
It started to make us see, "You can see a lot of other things in this." That was the point we started getting into the new–also the ocean ones, the ones in the ocean. We were like, "Yeah, seismologists have been talking about ocean waves generating seismic noise since the 1950s and 60s, and it all works beautifully, but no one has ever seen it work in situ." And with the cable, they would see the wave propagating. We suddenly realized, some of these things, you really can observe.
ZIERLER: That must've been so exciting.
ZHAN: Yeah, it was extremely exciting. It's very confusing in the beginning. When we got our first submarine DAS data, offshore at Belgium, a student and I were just struggling, "What are these things?" But once you figure it out, it all becomes clear that you're observing something people have never observed before, and you realize the potential of this, either for seismology or for oceanography purposes. And as I said, I was very skeptical of observing Earth change because people are always talking about 0.05% level change over a year of time scales. But then, when we were looking at DAS for hydrology purpose, because you're so focused on the exact zone you care about, instead of a 10-kilometer average over a large depth, long distance, you realize you're talking about, like, 3% of change.
All the previous studies are so smoothed out that it looks very small. But if you look at the right place, the right depth and time resolution, multiple percent change. And you look at the individual, which only lasts a few days of time, and you can see it because you have the temporary resolution. It just couldn't be wrong. I think I also benefitted from my own experience in the past. I know what kind of artifact could be there, and when I see it's way above that and the features that are different from the artifacts, I'm immediately convinced, "This is not artifact." I know it's true. That's kind of the point I realized, all these new things we can do. This really emerged probably a year or two after we actually started to work on that. It wasn't immediately clear at all.
ZIERLER: Moving closer to the present, when COVID hit, drawing on your own experiences as an international student, I wonder if you were particularly sensitive to how difficult this was for graduate students and post-docs, particularly international ones who don't have family here, how they dealt with the social isolation.
ZHAN: Yeah. Several of them basically deferred or worked remotely for a little bit. Their exposure to in-person interaction, learning things you don't learn in class, that aspect was completely missing. As I told you, I felt like I learned by random sampling instead of systematic sampling from coffee hour. Probably equally or even more important. And that random sampling part of it is essentially completely missing. There's also damage to the culture of students working together, senior students helping new students. That's probably also quite damaged. I think that's going to be an important job we need to do in the next few years.
ZIERLER: There's a long road to recovery.
ZIERLER: When it came time for tenure review for you, was there an opportunity to reflect in your late-early career? [Laugh] What opportunities did you have to sort of take stock of what you had accomplished to make that case when you came up for tenure? Or was it more like a stapled-papers kind of dissertation?
ZHAN: [Laugh] No, you can't do that. But it's still broad.
ZIERLER: You were searching for themes.
ZHAN: Yeah, but I was not really trying to get into a single theme. And definitely, it made it even more clear that the technology is the technology. It's not the questions you want to work out.
ZIERLER: They're tools.
ZHAN: Tools, exactly. And there are things you can make an impact on with these tools. And this impact is not necessarily only from that tool. There are combinations of other things. I feel like there's the more conventional seismology size of things. That's sort of my fundamental training, and I'm still very excited about those and the opportunities we see as all these different kinds of dense arrays are coming up. I think that's still a critical direction to go. But then, there are also these new directions of seismology application to other things, oceanography, hydrology, vulcanology, glaciology. That's another theme there. I feel like I was organizing it sort of reflecting my own interest in this. Both getting new insight about this old conventional seismology problem with new tools, but also because of the new capabilities we have in space and time, all the new things we can do.
I feel like we're in a unique position to really do that, not only because I know how to extract information from DAS, but because we're at Caltech. It's easy to talk to oceanographers, hydrologists like Ruby Fu, also some scientists at JPL. You really can make it happen when you have their information. And you don't have to really become an expert by yourself in any of this. And it's impossible. All of this takes years to accumulate the expertise. And you don't have to do that. Caltech seems to be a very good place to do that. That's sort of the same. We'll just keep doing our seismic stuff. I'm very confident as we build more and more dense arrays, it's going to really reveal new things about earthquakes and subsurface structures. On the other hand, all these new things, students are super excited about. If they want to learn both, oceanography and geophysics, yeah, that's great. We're going to educate a new generation of scientists who sit right at the boundary of these.
ZIERLER: I'll ask one last question to wrap up this excellent series of discussions. Looking to the future, in the immediate future, you're headed to Antarctica. Best-case scenario, what will be the results of that research mission, and how might that define the next stage of your career?
ZHAN: I think the Antarctica mission is a really exciting one. If everything goes well, I think we're going to have the first demonstration of how DAS is going to systematically revolutionize glacier seismology. I don't think it's going to show too much about this in California or other places, but it's really specific to glaciology problems. Basically, if we are able to detect, through kilometers of ice, with a DAS unit, the subsurface structure, maybe there's water there, maybe we can detect a temperature change in a well-deployed cable, that'll show you, "Now, you can do really dense arrays on ice." And that's been really hard to do in general. Nodes and sensors are still big players in this. This year, there are a few thousand sensors being deployed on the Thwaites Island Glacier, so it's an ongoing project at the moment. But you can think, similar things can be done more quickly in many other glaciers.
I think that's going to be really amazing. I'm actually hoping to jump outside of my comfort zone and work with engineers to figure out the best way of doing that. The South Pole, there was cable deployed 20 years ago. We're going to be sitting in the room, connecting stuff. The hard part is the field work part, shooting and other stuff. But once you go to a really interesting ice stream that's contributing a lot of the ice loss, you want to go deploy your own cables in an extremely cold environment, and you want to file those things quickly, how do you do that? I feel like the JPL engineers should be able to help me build something that can be mounted on the back of a piston bully or something. You drive around, dig a trench behind you, bury the cables or drill a deep hole in the ice, then some kind of arm sticks into the ice and fires it without you going out of the piston bully. [Laugh] If we're able to do something very fast and very scalable, I think it's going to really revolutionize how we do array deployment on ice.
ZIERLER: And for JPL, I bet they're also going to be thinking of the value of this work as they think about icy worlds around Jupiter, Neptune, and Saturn.
ZHAN: Yeah. This kind of deployment of cable is probably also useful for the moon. The rovers we're deploying to the moon are getting bigger, so we can think about similar processes. That's actually one of my big interests at the moment, how to bring DAS to the moon. What would it take? It probably would take a long time, but what are the steps we need to take? I think some of the glacier experiment may inform us about that. What kind of deployment do we need to do to get good data? In most cases, maybe not just laying the cable on the surface, but how much work does it need to be to make the deployment, what kind of cable should be used, what kind of source should be used? I feel like the glacier study and the planetary are two very exciting places to do some new research.
ZIERLER: I'll check back in 10 years to see where we are.
ZIERLER: Zhongwen, I want to thank you for spending this time with me. It's been a great series of discussions.
ZHAN: Yeah, it was very nice. Thank you so much.