Episode 7: Ieva Čepaitė

September 12, 2022 insideQuantum Season 1 Episode 7
Episode 7: Ieva Čepaitė
Show Notes Transcript

What will it take to make quantum computing practical, and how can we make the most of different types of hardware for solving different problems? Take a listen to Episode 7 of insideQuantum to find out!

This week we’re featuring Ieva Čepaitė, a PhD student at the University of Strathclyde in the Quantum Optics and Quantum Many-Body Systems (QOQMS) group, working on algorithms for near-term quantum devices. Ieva obtained her undergraduate degree from the University of Edinburgh, and is a contributing writer for Physics World magazine.

🟢 Steven Thomson (00:06): Hi there and welcome to insideQuantum, the podcast telling the human stories behind the latest developments in quantum technologies. I’m Dr. Steven Thomson and as usual, I’ll be your host for this episode. In previous episodes, we’ve talked about some of the mathematical theories underlying quantum technologies and we’ve spoken with experimentalists building the hardware for them. Today, we’re going to bridge this gap a little and talk about just how exactly these current generation quantum devices can be used to do useful things. In particular, we’re going to dig into the types of algorithms that can be run on these devices, what they’re good for and how these are developed. It’s a great pleasure to be joined today by Ieva Čepaitė, a PhD student at the University of Strathclyde, and also a writer for Physics World. Ieva, thank you so much for joining us here today.

🟣 Ieva Čepaitė (00:53): Thank you for having me.

🟢 Steven Thomson (00:55):

So before we get too far into the details, then, of near term quantum computing, let’s talk a little bit about your journey to this point, and let’s go right back to the beginning. What first got you interested in quantum physics?

🟣 Ieva Čepaitė (01:08): Well, I can’t really remember what the exact point was. I believe I read an article online about quantum computers sometime midway through my undergrad, and I had no clue what these things were. And I had only just begun learning quantum mechanics. And I got absolutely fascinated because I was doing a joint degree in computer science and in physics, and I found out that there was one research group in the computer science department at my university, at the University of Edinburgh, that was working on this kind of stuff. And I started emailing the head of this research group, Elham Kashefi. I think I emailed her about five or six times before she applied, because she’s usually very busy. Ad she said, yeah, you know, if you’re very interested, you can come along to the group meetings and ever since then I’ve kind of followed along and decided to invest my time in this topic because it’s just so interesting.

🟢 Steven Thomson (02:06): That’s amazing. That’s a very proactive way to have started as well, particularly as, as an undergrad, to reach out to our research group to identify what you want to do and who’s doing that, and then make it happen.

🟣 Ieva Čepaitė (02:17): It’s a, it’s a condensed version. I think I emailed a bunch of people from whatever emails I found online. No one replied because I imagine again, they’re very busy, so…but yes, that’s ultimately how I got into it.

🟢 Steven Thomson (02:31): So when is it that you decided you wanted to, to continue with this? Did you, did you know, straight away that quantum computing is something that you might want to work on longer term? Or was it over the course of working with this research group that you thought, “Hey, this is quite interesting. Maybe it’s worth looking into further.”

🟣 Ieva Čepaitė (02:48): Yeah, I think what attracted me to it is that it did seem to be a field that was growing, at the time when I got interested and it was 2016 or 2017. There were already plenty of work groups working on it in various areas, but there seemed to be a lot of unanswered questions and a lot of potential. And obviously it was interesting as many things are, I feel like it’s not exceptional, but it’s definitely something I found quite interesting. So I felt that if I dedicated time to it, it would probably be a good investment because there were many things I would like to work on, so whatever I ended up doing within this area would probably be fun.

🟢 Steven Thomson (03:28): What was it about quantum computing that, first attracted your attention? What was it that seemed so particularly interesting for you?

🟣 Ieva Čepaitė (03:36): I think the ideas that I find the most interesting about it is everything to do with information, or the theory of information because quantum computers don’t just deal purely with quantum mechanics in the way that physicists like to talk about it or with computer science in the way that computer scientists like to talk about it. But it’s this strange interplay where you get to ask fundamental questions about, you know, what is information, what information is contained in the quantum system, how does it move around? What can you learn from it? So these are, these are very deep questions and I feel like the more you understand about the intersection of computing and quantum mechanics, the more you can probe these sort of questions. And that was primarily, I think that the sort of deep draw that I felt to the topic.

🟢 Steven Thomson (04:26): I think that’s becoming a running theme in some of our episodes, in fact, this idea that information as a concept runs much deeper than just computing as an application. That maybe, okay, computers, surely store information, they do things with information, but maybe information exists outside of computers and can be used to answer these bigger and bigger questions. And that that’s…I’m hearing a lot of that actually, from guests and also from people that I work with that this, this viewpoint seems to be expanding and growing and finding even more interesting applications.

🟣 Ieva Čepaitė (04:58): Yeah. I think every single field that has looked into quantum computing…So when I say field, maybe discipline is what I mean. Whether you’re a pure mathematician or a philosopher or a physicist or a computer scientist, the more you understand what quantum computer does or attempt to do, the more likely you are to get insights into your own research, I think. So it’s really something that…it’s a gift that keeps on giving in some way.

🟢 Steven Thomson (05:26): That’s a nice way to look at it. So if you hadn’t gone into quantum computing, then what else do you think you might have done instead?

🟣 Ieva Čepaitė (05:35): I honestly don’t know, I’ve been doing it for so long. I think I decided to do quantum computing quite early on in my career, long before I had to decide on anything else. So I don’t know, probably computer science of some sort potentially even…I’m not gonna say machine learning, not in the practical way, but maybe a more mathematical approaches to machine learning, because again, it’s this theory of information focused kind of thing. So yeah.

🟢 Steven Thomson (06:04): Yeah. Some common themes in there, I guess, between the machine learning community and the quantum computing community.

🟣 Ieva Čepaitė (06:10): Yeah. I…don’t quite like…so I’ll be honest, I don’t quite like a lot of what happens in machine learning or even in quantum machine learning these days, because a lot of it is focused on very incremental research, very small sort of practical things that don’t lead to a deeper understanding of what these algorithms actually do or what’s machine learning is. I think those are fine, but this is not what I’m interested in. I think it would be what I would like to work on more if I had the chance would be to understand sort of a more abstract larger scale…to develop a larger scale understanding of what it means for, you know, a quantum system to learn or what it means for a machine to learn and so on and so forth.

🟢 Steven Thomson (06:58): I mean, those sound like very, very big questions… 

🟣 Ieva Čepaitė (07:01): Yes. Yeah, they are.

🟢 Steven Thomson (07:04): So what would you say is the biggest challenge in your field at the moment, let’s say kind of near term five to ten years, that kind of time scale?

🟣 Ieva Čepaitė (07:13): The honest answer is usual is…I am someone who works on theory, I do not build quantum computers, I have never been an experimentalist. So, despite that I’ll admit that the most important thing is to actually build a quantum computer. So I will rely on the people who are the actual engineers working on these things, whether it’s ion traps, superconducting qubits, or whatever other technologies are out there, cold atoms… So that that’s always been, I think the biggest challenge, it remains the biggest challenge. I think that the theoretical side, both the people developing quantum algorithms and the people developing physics for quantum computers are far ahead of what we can actually do in practice. And so it remains to be seen how useful these theoretical ponderings are given that we can’t test many of them yet.

🟢 Steven Thomson (08:08): Yeah. So the theories are still waiting for the experimenters to catch up.

🟣 Ieva Čepaitė (08:14): Yes. Luckily it seems like the experiments are getting better over time, but it’s, it’s still taking quite a lot of time, so we need to be patient.

🟢 Steven Thomson (08:22): So can you tell us a little bit about what it is that you work on and where your work fits into this kind of big picture goal of building and using quantum computers?

🟣 Ieva Čepaitė (08:33): Yeah, so the stuff I’m working on in my PhD right now is quite practical. I’ve done some work on what is called adiabatic quantum computation. So, this is a way of doing, of solving optimization problems on quantum computers. And we were coming up with ways how to make these things more practically implementable, how to speed them up so that you can deal with problems that arise when these things are run too slowly, which is your qubits decohere, they lose information. So things like this. I’m also working on very sort of high level theoretical ways to speed up, for example, measurements in cold quantum computers. So that’s very specific, very applied to a particular quantum technology, but it’s still something that’s geared towards quantum computation or at least some form of quantum simulation, at the end of the day. Stuff I’ve done before is quite different, it was more on the computer science side, rather than the physics side, but it’s generally geared towards making quantum computers more practically approachable and available.

🟢 Steven Thomson (09:47): So it sounds like you’ve done quite a wide range of different things so far.

🟣 Ieva Čepaitė (09:52): Yes, yes. When I first started out in Edinburgh I was working on things to do with quantum cryptography. The group I was working with was quite into quantum verification protocols and things like that. So these are very highly theoretical computer science type things that people worry about. And during my PhD now I’ve started working more on the physics side, but still very much theoretical problems. Yes.

🟢 Steven Thomson (10:23): So your latest work there touches on the challenges of getting something useful out of a quantum computer. People like to say the current era of quantum computing is called the noisy intermediate scale quantum, the ‘NISQ’ era. Can you tell us a little bit about what that means and why it’s so important to, to do the type of work that you’re doing? What kind of challenges does this work overcome?

🟣 Ieva Čepaitė (10:46): Yeah, so NISQ is an interesting term. It’s something that implies that we can’t yet do very large scale quantum computations, which some people assume is required to actually show any sort of advantage in using quantum computers over classical machines. So NISQ is a bit of a contentious term. However, at the same time there is potential, given the size of the systems in NISQ. So, NISQ means like, as you said, noisy intermediate scale. And what that means is that we have enough qubits that…presumably if they all work well enough, we can already show some advantage over classical machines, but that’s with the assumption that they work well enough. And it’s a big assumption. So I would say that my work is…I wouldn’t say independent of whether we have NISQ or not, it should be useful regardless, but what many people are attempting to do now with relation to what I said about engineering and experiments, not quite being there yet in terms of giving us big enough or powerful enough quantum computers is how do we exploit the technologies that we do have these technologies that are what we call NISQ that are sort of a bit small, but potentially big enough to do something interesting.

How do you mitigate the problems that come with not having what we call error correction, not having large enough quantum computers to have them work properly, to have them do really, really big problems. How do we exploit things that are technically too small, but perhaps not. When I think about my work, it relates to this idea of quantum simulation, which maybe we’ll talk about a bit in a second, wherein we try to bypass quantum algorithms or things that people develop to be run, let’s say on any quantum computer, if it has the right operations, if it can do this operation, that operation, but we rely instead on just having some quantum system that can do some things. And we see given those things, is there some useful amount of information that we can extract from it? So that system can be a lot smaller than we need in theory for surpassing NISQ, and that’s, that’s kind of the main idea behind quantum simulation. It’s like the difference between an analog computer and a digital computer. You can program very, very specific things on an analog computer, but definitely not any algorithm, whereas on a digital computer, you can program any algorithm, but you also require it to often be more powerful than the analog version, if that makes sense.

🟢 Steven Thomson (13:27): Yeah, I see. Okay. So that gets into something I wanted to ask you about, which is this difference between digital and analog quantum simulation. So quantum simulation as a whole, I guess, is about taking some, some form of quantum system and trying to use it to do something useful, to make some measurements, to solve a problem, to perform a particular task. You’ve touched a bit on the difference there between analog and digital. Can you tell us a little bit more about like practically what are analog quantum computers versus digital quantum computers and what are both of them good for?

🟣 Ieva Čepaitė (14:05): Yeah. So I often refer to a very particular example, which I think is quite intuitive in understanding the difference between the two. So, say you’d like to investigate how different air pressures or different weather conditions affect the wing of an airplane. Now, simulating all those different particles of air and all the different ways in which wind can move…it’s a very complex fluid dynamic system. If you want to write a simulation for it, you have to make many approximations. You have to…you need a very powerful computer in order to run it. So that makes your job really difficult for something as simple as figuring out, you know, how does weather affect an airplane wing? What you can do instead is to actually build the wing of an airplane and put it it in an air tunnel, and then just see what happens basically.

And it’s, it’s pretty much just as good as a simulation and in many ways, depending on what you’re trying to find out. And I kind of view analog, quantum computers, where…quantum simulators, as they’re sometimes called, as the same thing. So you have some quantum system which exists already. It’s not a simulation of a quantum system, it it’s physically there. You can’t do all of the quantum gates or quantum operations you might want to do, which is what you’d need for an actual quantum computer as we call them. But you can certainly do some things. There’s some native physics that happens already, just if you have a bunch of particles and that you let them interact in some way, they’re gonna behave interestingly, and you can tune those interactions. Maybe you have some magnetic field, maybe you have some something that you can do to those particles.

And once you do it, you can observe them, investigate what happens. And that is just as good as running a particular algorithm. It’s a very specific algorithm because you’re constrained in what you can do to it in the same way as the wing in the air tunnel can only be a wing in an air tunnel, but it still can give you very interesting results. It can give you a lot of information that you wouldn’t otherwise get. Whereas if you try to do the same thing with a quantum algorithm, you can write the simulation on the quantum algorithm in the same way, but it requires you to make this translation, to go “okay, my magnetic field now has to be a set of operations and I have to turn each my qubits in a particular way”. And that’s all fine, but usually means that you need a much more complicated and much larger system to actually do the exact same thing. So in a way, analog quantum computation is just a way to extract something useful from quantum technologies, but not perhaps implement anything you’d ever want to implement.

🟢 Steven Thomson (16:52): I see, so the analog quantum simulation then is like, you…you set up a quantum system, you prepare it in some way, and then you just allow that system to evolve. You let the system do whatever operations it’s naturally suited to. Whereas the digital case is much more, in a sense, finally tuned. You prepare a system, but then you also care very carefully control every single operation that you do to it, which maybe gives you more flexibility in the operations you can do, but it means you have to really know how to do every single thing you have to kind of almost manually make every one of these operations yourself. And that is, a difficult and challenging task.

🟣 Ieva Čepaitė (17:31): Yeah, pretty much. It’s, it’s just a degree of control that’s different. In a quantum simulator, you have some control, but it’s minimal. In a digital quantum computer, you technically should have any type of control you ever want to have.

🟢 Steven Thomson (17:47): And do you think it’s fair to say that the sort of digital quantum computing is perhaps more familiar to people who come from our computer science background, but the analog quantum computing is maybe more familiar to people from the many-body physics community?

🟣 Ieva Čepaitė (18:02): Definitely. Yes. And this is something that I see very often because I tend to interact with both communities quite heavily, since I come from both backgrounds in some sense. And I feel like each one is very unfamiliar on average with the other side, let’s put it this way.

🟢 Steven Thomson (18:23): I fully agree with that. As someone coming from the many-body background who joined a group, working mostly on quantum information and computing, it took me quite some time to understand what a lot of my colleagues were talking about. To any listers who have a background in many-body theory, you’ll know that there’s an object called the Hamiltonian that is, kind of the, the core of a lot of what we do in many-body quantum physics. And this doesn’t exist in digital quantum computers. And this kind of blew my mind, that you could do quantum physics in this very different way without a Hamiltonian. People would draw me diagrams of digital quantum computers, and I would say, but, but where is the Hamiltonian? I don’t understand. I don’t, I just cannot comprehend what you’re doing here. And yeah, it just does seem like a very different sort of different underlying philosophy. In the one case you’re allowing quantum mechanics to do the work for you in the analog simulation case, in the digital case, you’re really, you are really being hands on. You really have complete control over everything, but then that brings with it its own challenges because having that control is quite difficult as I understand it.

🟣 Ieva Čepaitė (19:25): Yes, that’s, that’s exactly it. In, in effect, as you are a physicist, you will know every system works with a Hamiltonian. All that we do when we use quantum operations or quantum gates, which often make no mention of a Hamiltonian, we’re just approximating. So we’re going, you know, this thing that exists, well, we’re gonna turn it into this completely other picture and pretend that it’s no longer Hamiltonian, which works if you want to work very abstractly. If you want to write algorithms, that’s actually very useful because you can, you have something called quantum logic, which helps you write quantum algorithm. And, and if you’re a computer scientist is definitely far more intuitive, but under the hood, once you go to implement these quantum algorithms on an actual quantum computer, they are going to be converted back into Hamiltonians under the hood, whether you like it or not. And that brings with it some difficulties, because that translation is the thing that is what causes a lot of errors and to what’s difficult to actually control and to work with.

🟢 Steven Thomson (20:29): So is there a…is there a place in the world for both types of quantum computer, for the digital and for the analog, or is it a case that analog is where we started and digital is where we are trying to get to?

🟣 Ieva Čepaitė (20:42): I think that…this is my personal opinion, but I believe that in the perfect world, there would be a combination of the two, just because with how difficult quantum technologies are to build, it would be strange not to exploit how easy quantum simulating protocols often are. So there are certain things you can do without reference to digital algorithms at all. And as long as you don’t think about it in the digital perspective, you can do them very easily and then switch over maybe to the digital picture at some point, because that’s where need to run something very, very specific that requires this, these high control operations. So I think based on what I’m seeing, definitely in the near term and, and perhaps in the slightly longer term, I imagine there will be a combination of the two, and you’re going to need expertise from both fields to kind of come together and make it work.

🟢 Steven Thomson (21:40): Can these different types of quantum computing, can they be run on the same architectures or would you have to have a digital quantum computer sitting in one corner of the room and an analog one in the other corner of the room?

🟣 Ieva Čepaitė (21:53): They can definitely run on the same system. Like I said, everything is a Hamiltonian under the hood. So technically everything is a simulator first and foremost. And then on top of that, we impose structure and we go, well, if you do this Hamiltonian that translates to this logic quantum gate. And so you could bypass calling it a logic quantum gate and just be, this is that Hamiltonian. So, you can definitely do both on the same device. I think what’s far more interesting and what’s already happening, as far as I’ve seen, is that you connect different types of physical systems in order to allow for a more interesting or, or easier quantum computation. So all…it’s, it’s a giant play box. You can do whatever you want, basically.

🟢 Steven Thomson (22:38): Nice. So then of the work that you’ve done so far in this type of field, in this type of area, what are you most proud of so far in your career?

🟣 Ieva Čepaitė (22:50): That’s a difficult question, I think, regardless of actual papers or outputs research output, I’m quite happy with having a really good overview, I think, of the entire research community. As in, I have had interest in, as I’ve said, computer science and now many body physics, and I’m slowly heading more into pure math, which we’ll see where that goes. But being able to run around and then sort of slide between all of these different perspectives has been very helpful in identifying exactly where each one is maybe missing something or what’s, you know, what could be exploited from each perspective. As an example, I think that the algorithms community definitely could be looking a lot more at Hamiltonians and at the native physics of the devices they’re working with. It might help them speed up the algorithms that they’re working on, but obviously that requires a change of perspective and that’s not something people are looking into that much. So I’m quite happy because I feel like I’m very well positioned to sort of see what can be done to combine all of these things together.

🟢 Steven Thomson (24:09): Yeah, I think it’s really good to have that sort of perspective because, as I mentioned coming very much from one field and learning a bit about the other, the…the language that people use in both fields can be very, very different and there can be quite a high barrier to entry if you don’t have a little bit of background in both. Even just to understand the words, the phrases, the things that, you know, the, the jargon, the things that are absolutely common in one field that to someone in another field is…sounds completely alien, but really isn’t right, as you say. Some of the underlying physics here is the same, regardless of where you’re coming from, how you like to talk about it, but it does feel like there’s a bit of a barrier sometimes between the different communities. And it can be hard for someone from one community to really understand what the other one is talking about. Even if the physics would really interest them if only they could understand it.

🟣 Ieva Čepaitė (24:58): Yeah, indeed. Yeah. And I fully understand that everyone needs to specialize. I don’t think it’s fair to expect every person working in the field to know everything about everything, but at the same time, there is a lot of space left at the intersections I think, to play around with.

🟢 Steven Thomson (25:17): Okay. Well then, talking about communicating between different parts of the field, then let’s take the concept of communication a little bit wider. You’re also a writer for Physics World. How did that come about?

🟣 Ieva Čepaitė (25:32): Yeah, so that was not a very interesting story. I got sent an email saying, “Hey, Physics World is thinking of starting this student contributor network” where, you know, if you sign up, you get to write articles and obviously you don’t get paid or anything, but it’s nice, you know, you get some practice, you get to read cool papers and obviously your work is out there. So that’s pretty nice. And I wrote in, I’d already been doing writing and, and science communication a bit in undergrad, so they were quite happy to have me. And I believe I was part of the first cohort. It’s now been almost two years – maybe I’m lying – of this quantum side of the Physics World, student contributing network. And I think they’ve been doing quite well.

🟢 Steven Thomson (26:18): So how does it work? Are you…do you volunteer to write about papers that you find particularly interesting or do they assign you with papers and ask you to write about them?

🟣 Ieva Čepaitė (26:27): Yeah, so there are generally papers that are sort of advertised as being potentially interesting to write about. And there there’s quite a few of those coming out all the time. So as long as they’re published and in peer reviewed you can basically raise your hand and go, you know, I find this interesting, I’d like to write about this, and then you have some time to write about it. You can also suggest your own, of course. And as long as the editors agree with you, then you’re quite free to write about anything you want to write about

🟢 Steven Thomson (26:55): And do the editors sort of work with you and provide you with some training and some feedback through this process?

🟣 Ieva Čepaitė (27:00): Yeah. So it’s, it’s…you do get through a, a few rounds of editing for each article. At the end of the day, this, they do get approved by a head editor and, and there, there are quite a lot of edits from the first draft onto the last. They do look quite different, but, um, but there is a lot of it is quite independent. A lot of it is, if I write an article, then some other contributor…some other student might volunteer to edit it and we go back and forth a couple of times. And then the final edits are suggested by the head editor. And then, then it gets published. I also work with at least one of the authors of the original paper, just to make sure that everything is represented correctly.

🟢 Steven Thomson (27:37): That’s really interesting. So you also get some editing experience as well as just writing.

🟣 Ieva Čepaitė (27:42): Yes. Yeah. You can edit and write as many articles as you have time for basically.

🟢 Steven Thomson (27:48): Nice. So then why, why did you originally get interested in science communication? Why is this something that you felt was important and interesting to do?

🟣 Ieva Čepaitė (27:57): The more philosophical answer, which is probably a correct one, is that I find the idea of doing research without being able to communicate what that research is a little bit pointless in the sense that…and, and this is the extreme example, but say you make some huge discovery and you are incapable of communicating it to anyone around you, either through writing or through talking to them. It basically means that once you die, this discovery dies with you. So I think it’s quite paramount to leave a very explicit and a very good description of exactly what science you’re doing and, you know, to hope that A, you inspire others to follow along from whatever it is you’ve done. And B just to make sure that, well, this is the second point, I guess, that the public also understands – people who are not doing research, people who are not doing science – that they understand the value of the research that they understand, obviously, where their money is going, because much of the research that we’re doing is being funded by the public. So in this very rambly way that I’ve answered, there’s two sides to it. One of which is just to inform other researchers. And the other side is to inform the public. I think the more knowledge is out there, the better. And that’s kind of the goal.

🟢 Steven Thomson (29:26): I think we can definitely agree with that sentiment. Have you found that doing science communication has fed back into your research life in terms of communication skills or experience that simplifying difficult concepts, anything like that?

🟣 Ieva Čepaitė (29:41): Definitely. So writing, I’ve…I’ve never found writing particularly difficult. So I don’t know if it’s, if I’ve just always sort of had a knack for it, or if writing for Physics World has actually helped because writing my own research and writing science communications articles are quite different types of writing, but what does happen is once I’ve found an article I find interesting and I want to write about it, I tend to spend quite a lot of time researching it and obviously reading the original paper, the original article in depth. And that does mean that I end up learning a lot about a lot, because in order to be able to communicate something in simple terms, you need to have a pretty good understanding of it. So that’s been very, very useful for my own career.

🟢 Steven Thomson (30:25): Is science communication then something that you would recommend other researchers get involved with?

🟣 Ieva Čepaitė (30:30): Yes. If you have the time it’s, it’s certainly not for everyone. And I do find it’s stressful sometimes because, not for myself, but I find that many of my colleagues are stressed because you need to…often as a researcher, you need to demonstrate an ability to communicate science very well. And I don’t think everyone has natural talent for it. And I don’t know if it should be expected given that, you know, as a researcher, your main job is to do research, but if you have any time and if it’s of any interest, I definitely recommend it if only to help, yes, your own writing skills and definitely to broaden your own understanding of the field you’re working in, and to broaden your understanding of what questions people often ask about it. That’s also quite useful.

🟢 Steven Thomson (31:15): Is this Physics World contributor scheme, is this still running? Is this an annual scheme or can anyone apply it to any time?

🟣 Ieva Čepaitė (31:22): It’s still running. So people go in and out as they finish their PhDs or as they become interested and apply. I’m genuinely not sure when you can apply, perhaps you can just email in at any time, but I’ve seen people come and go throughout the last two years or so. So if you’re interested, perhaps just send an email into the quantum network. [Editor note: The scheme is still running, and if you’re a PhD student and want to join, you can find more information on how to take part here -]

🟢 Steven Thomson (31:46): Okay. So there’s one question that I like to ask every guest on this show, and I ask this to everyone regardless of their gender identity. And that’s that physics has historically been a very male dominated research field, a very…a research field dominated mostly by white cisgender men, in fact, and you’re very early in your career at this point. So I guess I have a sort of two-pronged question here. One is that over the years that you’ve been in the field, have you seen any evidence that things are evolving and changing for the better? And secondly, as a relatively early career researcher, do you look at the field and see that it is welcoming to people who are not just white cisgender men?

🟣 Ieva Čepaitė (32:31): Yes. So my experience has been pretty normal. I’d say I’ve not had any sense that I’m not welcome or that my gender has anything to do with my abilities perhaps in science or anything like that. At the same time, it is true that the less examples of people like you, you see in higher positions, the more difficult it is mentally, I think to convince yourself that you belong there. So it’s, it’s a very difficult topic to broach in general, because there’s so many complex things that go into it. I feel like obviously the, the fact that STEM is, is dominated by white cisgender men on average is a historical artefact. And we’re not that far from the age where no one but men was allowed into, say physics ,that I would expect, you know, a massive change to be visible, but there is a change.

There’s obviously been an increase of women in physics. And there’s definitely been an increase of people from various backgrounds and from various races. Whether or not this will persist and how long it will take for, you know, this, this change to become more visible. I really don’t know. It does seem like some people still have a harder time than me, and it depends on what environment they’ve landed in. I do think at least a part of it, and this is important to mention, is not down to, let’s say, higher education, as much as it is down to the influences you feel growing up from very little up to, you know, when it comes time to make the decisions, whether you wanna do, let’s say a physics PhD, and those factors are much harder to control no matter what you do. So it’s, it’s an interesting topic.

It’s one that probably requires many, many hours of discussion and investigation, but if I were to conclude, I’d say it is getting better. It’s hard to say how quickly or whether this will continue necessarily, although I think it will. And I think I would encourage people within groups if they have anyone from a minority there, part of the group, for example, if, if you are a guy in a you know, physics PhD, and there’s one girl in your group, to kind of perhaps be aware if there is any sort of…if, if the environment feels maybe unwelcoming in any way to people who are different, because these very small things do tend to contribute, in my experience, you know, little comments and behaviors. But other than that, nothing much to add.

🟢 Steven Thomson (35:27): Well, I think that is probably good advice for everyone in the field, just to, to be aware of the environment that you are in, the environment you might be involved in creating and try to make that better for everyone. I think that’s, that’s a piece of advice that anyone can take forward that will improve the entire field for everybody in it.

🟣 Ieva Čepaitė (35:48): Yes. Yeah. I feel like there’s…I wish I could say more, but I also don’t wanna start on a tirade. So this is probably…I’m very happy with this answer for now. 

🟢 Steven Thomson (35:59): Well, one final question to wrap up, then. I think if you could go back in time and give yourself just one piece of advice, what would it be?

🟣 Ieva Čepaitė (36:10): This one’s very specific to me, but maybe others will find it useful, which is to do a lot more mathematical physics. I definitely wish I’d done more pure math. Not because I want to be a mathematician, but because I feel like it has helped me every time I’ve tried to get into a topic I never understood before, with the first perspective of, you know, looking at it more from mathematical physics side or, or just from a very rigorous mathematical side, it’s helped me get there a lot faster and a lot more easily. So perhaps this is just the kind of person I am, but I feel like this it’s, it’s very useful if you want to become a physicist and to sort of look at the math a lot more carefully. I think it makes things easier down the line.

🟢 Steven Thomson (37:01): I suspect there might be a lot of mathematicians out there who would agree with you that physics needs to learn…physicists need to learn more maths .

🟣 Ieva Čepaitė (37:08): I mean, are they wrong?

🟢 Steven Thomson (37:09): No, I wouldn’t…I wouldn’t say they’re wrong. 

🟣 Ieva Čepaitė (37:13): They are very different disciplines. And there is a reason they’re different disciplines that, you know, physicists are not mathematicians, but I do feel like for many especially theorists, maybe I should stress for theorists…I think the math becomes more and more useful the further down your career, you go. So push it a little more earlier on, so it hurts less later. 

🟢 Steven Thomson (37:35): I think that is also good advice. Okay. Then I think we will leave it there for today. So if our audience wants to learn a little bit more about you and what you do, where can they find you on the internet?

🟣 Ieva Čepaitė (37:47): So I am quite active on Twitter. If you’d like to find me, it’s, uh, it’s a funny name. It’s the word ‘hyper’, ‘hyperbo’ as in hyperbole and then my name Ieva. I’ve spelled it out, if anyone manages to find me good luck. That’s probably the best find best way to, to see what I’m up to. And all other links are in the profile.

🟢 Steven Thomson (38:13): All right, perfect. We will make sure to include a link to your transfer profile on our website, and then anywhere else we put the transcript for this episode. Thank you very much Ieva Čepaitė for your time today.

🟣 Ieva Čepaitė (38:25): Thank you very much, Steven.

🟢 Steven Thomson (38:27): Thank you also to the Unitary Fund for supporting this podcast. If you’ve enjoyed today’s episode, please consider liking, sharing and subscribing wherever you like to listen to your podcasts. It really helps us to get our guest stories out to as wide an audience as possible. I hope you’ll join us again for our next episode. And until then, this has been insideQuantum, I’ve been Dr. Steven Thomson, and thank you very much for listening. Goodbye!