Quarks and qubits: how quantum computing could transform particle physics

0:07- Hello, and welcome to the Physics World weekly - podcast, - which is supported by American Elements. - Simulating quantum systems is something that classical computers - struggle with. - Not surprisingly, - quantum computers are expected to do a much - better job, - particularly when a quantum computer's - architecture - is designed to solve a specific type of - physics problem. - My guest in this episode of the Physics - World Weekly podcast - is Ross Jenkinson - of The UK's - University of Manchester.

0:46- He talks about the challenges and rewards - of using quantum computers - in particle physics, - a field where classical - supercomputers - can struggle - to simulate simple systems. - That conversation - is coming up after this message from American - Elements. - This podcast is brought to you by American - Elements, - the world's leading - manufacturer - of engineered and advanced - materials. - With a catalog of over 35,000 - products - available in both industrial bulk and laboratory - quantities, - American Elements is the largest supplier of its - kind.

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2:11- American Elements, - now invent. - Hi, Ross. Welcome to the podcast. - Hi, Hamish. Thank you very much for having - me. - Yeah. I'm really looking forward to talking about, - applications for quantum computing - in particle physics and, beyond. - So - maybe we could start off with, sort of - a basic question. - Why are quantum computers useful - for simulating - particle physics collisions? - And, you know, in comparison to - conventional - supercomputers.

2:52- Yeah. It's it's a great question. So but - first of all, how are quantum computers different? - So classical computers are kind of written in - this language of of binary bits. So zeros - and ones you might have seen in the - movies. Lots of zeros, lots of ones. But - crucially, - it's a zero or a one for any - given bit. Whereas a quantum computer, because of - the principle of superposition, - a quantum bit or a qubit as we - call it, can be in zero and one - at the same time. So what that means - is that we can evolve two possibilities - at once. And if you have two qubits, - then there's four possibilities. You have zero zero, - one one, zero one, and one zero. So - you have four possibilities - that you can evolve simultaneously.

3:34- And, actually, as you keep growing this number - of qubits, so you have n qubits, - then that scales as two to the power - of n. So that's mathematically, that's an exponential. - So when we say it grows exponentially, we - really we're not saying that colloquially. We mean - it really does mathematically grow exponentially. - The number of possibilities that you can simulate - and evolve at the same time. So this - is where a lot of the power of - quantum computing comes from.

4:01- And the reason why it's particularly good - at simulating - quantum field theories or or quantum mechanical systems - is because - when you have some quantum mechanical system, you - may have heard that things can happen simultaneously - to a particle. If it wants to go - from a to b, it might take one - path, but it might take a different one - and a different one. And actually what quantum - mechanics says is that it takes all of - these paths simultaneously.

4:25- And if something has a certain energy level, - it can be in multiple energy levels at - the same time. So when we start doing - quantum mechanics calculations, - you very quickly realize that this system size - called the Hilbert space - grows exponentially as well. So it's really, really - difficult for a classical computer - to simulate these things. Whereas, as I was - just saying, this is the natural language of - a quantum computer. It can simulate these things - in exactly the same way, also grows exponentially.

4:53- So they're really good. They're kind of a - natural way to simulate quantum mechanics. Perhaps that's - unsurprising that a quantum computer is really good - at simulating - quantum physics. - So that's the goal. That's what we're trying - to we're trying to do with using quantum - computers. Yeah. - And and what's the the the state of - the art at the moment? So, you know, - quantum computing is a fairly - new technology. - Are the the quantum processors that are available - today, - are they up for the job? Are they - able to, - to sim to simulate meaningful - particle physics systems, or do we still have - a way to go, - in terms of getting, - practical results - out of a quantum computer when it comes - to particle physics?

5:41- Yeah. So there's kind of a few different - things there. I mean, so - the current state of the art will depend - who you ask. Specifically, it depends which company - you ask. But if you wanted just to - get a large array of cubits, I think - there's a a company that has done 6,000 - cubits all in a all in a large - collection, and that's all well and good, but - they're not interacting. You can't use them to - calculate. In terms of a benchmark calculation, - so, yeah, chips are already being developed. You - have Google who have developed a chip that - they've called Willow, which is a 105 - qubits.

6:12- So that's pretty powerful. I mean, if you - think about that in terms of classical bits, - that's not very lot at all. A 105 - bits - of information isn't a lot. But when you - do two to the power of a 105 - and think about the kind of possibilities - there, that is actually really powerful. In fact, - they did a calculation, - and this is kind of cheating a little - bit because they deliberately built the chip to - do the specific calculation. So I don't want - to oversell it, but it was built to - do a calculation, and it did it in - five minutes. And they calculated that the world's - largest, most powerful classical computer - would have done it in ten septillion - years.

6:47- So it would have taken a a huge - amount of time for a normal computer to - do the same calculation. - So they are already doing really powerful, interesting - calculations - using quantum computing chips. But how - relevant is that for the particle physics stuff? - Well, we're still a while off. I I - would say from both a theoretical and an - engineering point of view, we're kind of in - the foothills of this really exciting journey. - We're we're starting to do - benchmark - example calculations, - But in order to actually get them to - simulate real particle interactions, - that's quite difficult. And, actually, - the classical methods we have are really powerful.

7:26- We've been we've been developing them for for - decades. I say we have been in development - since before I was born. - So really, really well tested stuff. In fact, - quantum electrodynamics, - which is one of the - basically applications of our of our quantum mechanical - methods - is one of the most well experimentally - verified methods - in all of science. It's it's experimentally verified - at the Large Hadron Collider to about one - part in 1,000,000,000,000.

7:55- So that's I mean, just to give some - scale as to how - unbelievably accurate that is. That's like measuring the - length of The United Kingdom from from Lands' - End, Saviano Groats, - down to the width of a red blood - cell. In fact, it's more accurate than that. - So one part in a 1,000,000,000,000. - So really, really good methods. And so we - don't have to just get quantum computing to - work. We have to get it to be - even better than that, basically.

8:19- And so this is where that kind of - power of this simultaneously - evolving things. And, actually, what classical methods do - is they kind of do slight approximations because - they they can't do that. So there's certain - regimes where they can do calculations very well. - But to actually evolve a quantum system in - real time and kind of, like, press play, - press pause, inspect it, we can't do that. - Whereas a quantum computer perhaps could.

8:43- And and Ross, you mentioned, - a a quantum computer that was created to - solve a specific problem, - and it did so very well. Is that - is that sort of the idea - in how quantum computers would be used, at - least initially, to to solve particle physics problems? - The the architecture - of the quantum computer would be designed - such that it was - somehow similar - to - a particle collision - that you were interested in? Is is is - that one way of, you know, sort of - accelerating - the use of of, - of quantum computers? Actually, - making the architecture - fit the problem.

9:25- Yeah. I mean, that's a really, really good - point. And that that is exactly - the the way forward, I think. So the - era that we're in at the moment is - called the NISQ era, n I s q, - stands for noisy intermediate scale quantum era. - So the noisy is really the the the - main part about that. And what that means - is that we can't error correct. So we - can't we take a bunch of qubits and - they're really susceptible to - changes because of their interaction with the environment.

9:51- They're really hard to isolate. - So what we have to do is we - have to kind of get a group of - qubits to all fact check each other constantly. - That's how we do quantum error correction, but - that is currently the engineering challenge that everyone - is trying to to overcome. - So we're kind of in that era at - the moment, and what that means is that - we don't have fault tolerant quantum computing, but - we also don't have we're not really close - to. We're probably twenty, thirty years away from - a fully programmable quantum computer. So if you - think about your laptop, you can do all - sorts on your laptop. It's it's very programmable.

10:22- Right? - So because that's so far away, you're exactly - right. We can instead build devices that are - kind of purpose built. Imagine - like a calculator. A calculator is a really - useful device. A calculator is really good at - maths, but it's not gonna tell you the - weather. You know? So if you wanted to - have a purpose built device, you can exactly - do that. Firstly, with the architecture, so, yeah, - so you can you can design it in - such a way - using a certain medium that it might be - specifically good - at. So, for example, when I talk about - these qubits, they seem like quite abstract ideas, - but the actual candidates for qubits are things - like cold atoms, - trapped ions, - photons.

11:00- Each one of them has pros and cons. - And so for specific calculations, you might want - to use different ones. - So there's lots of investment in which one's - gonna be the best for a fully programmable - quantum computer, but actually they all have their - own advantages. - So yeah. And and one of the things - that I do in my research is - I say, well, it's all well and good - trying to build a quantum computer, but if - you put one in front of me, the - world - at the moment doesn't have a set of - algorithms to run on it, to actually do - the stuff that we want to do. So - I'm coming up with - architecture in the theoretical sense. I'm coming up - with circuits and algorithms that we could actually - put onto a quantum computer to get it - to do the stuff we want to do.

11:42- And so that's the kind of stuff that - we have to build - kind of in parallel to the engineering challenges - for lots of companies are trying to overcome. - And and what about the idea of, you - know, you mentioned that conventional supercomputing - is very advanced - when it comes to, understanding - particle physics or doing simulations on particle physics. - Is I mean, is part of the way - forward to to only use the quantum processor - to do a specific calculation - that would take ages on the supercomputer, - and then sort of feed that information back - into the supercomputer, and back and forth, and - back and forth. So you would use the - quantum computer - as a sort of, well, auxiliary - processor or something that can do one thing - very well.

12:34- Yeah. Is that a way forward? - Yeah. 100%. So it's kind of a hybrid - computing, part quantum, part classical. That's really important. - Firstly, because there's a bunch of stuff that - classical computers are very good at, and we've - already got them to do. And, actually, the - quantum computer, we don't need it to do - and it and actually quite difficult. So for - example, readout, - reading out a measurement, we know how to - do that classically. It might be quite hard - to do quantum mechanically. So as long as - we get the kind of hard part of - the calculation - kind of bootstrapped - onto a quantum computer, then that's where the - real advantage lies. It's also worth saying, again, - there's a lot of hype and and rightly - so, and I'm very excited about it. It's - why I've chosen to research it for my - my job. Right? But it's important not to - overstate that - quantum computers will never completely replace classical computers.

13:21- I don't think we will ever live in - a world where no one has phones, laptops, - whatever equivalent there is that's running on this - kind of classical baseline of digital bits, - and everything is quantum. I don't think that - would be the case. I think the most - optimal way will be a hybrid of the - two, exactly like you say. - And and what in terms of, - sort of general areas of particle physics that - could benefit from quantum computing. You you mentioned - quantum - electrodynamics, - but then there's quantum chromodynamics, - which is - extraordinarily - difficult - to to do any calculations, really.

14:00- You know, this is the the the physics - that describes, - how quarks behave inside protons and neutrons. - It that is a very difficult problem, computationally. - Will - quantum computing help with that? - Is it is that sort of a quantum - computing friendly problem where lots of progress could - be made? - Yeah. Absolutely. So for a few different reasons. - So so firstly, - quantum - chromodynamics - quite often in certain energy limits - doesn't play well with perturbation theory, which is - our usual toolbox for quantum mechanics, which basically - just means that if you have a small - enough coupling constant, you can - expand your maths in different terms that are - in less and less important.

14:50- Whereas in quantum chromodynamics, that's often not the - case, and so what they do is they - call they do something called lattice QCD, - which is really interesting in and of its - own right and very, very well experimentally tested, - and - the theory there is really good. - But wouldn't it be great if we could - real time evolve of these these quarks and - these quantum chromodynamic particles - and actually inspect it in real time, real - time quantum field theory. That's the kind of - the stuff that I'm interested in. And it's - also worth saying that there's lots of other - things in quantum chromodynamics that expand - massively. So, for example, color - color flow. So color, this red, green, or - blue, is how we label quarks. Each one - of them has their own color. It's the - charge of QCD, - kind of like how electric charge is the - charge of QED. Right? So you have this - this color, - And the number of color states as as - as your your your gluons and your quarks - and all of these, they explode in these - jets.

15:44- That grows factorially. So it's actually even worse - than exponentially. So it's it's impossible - impossible to do - on a classical computer - a 100% accurately. Again, there's a lot of - really good work that's being done to try - and model these parton showers. But if we - can get a a quantum computer to attack - this problem, I think it would be really, - really useful. Yeah? - And and another, sort of computational technique that, - I suppose is of great interest to, - particle physicists is - artificial intelligence. Can - you talk a bit about how, - artificial intelligence - is is being used and could be used - by, - particle physicists, - you know, maybe in the context of quantum - computing?

16:33- Yeah. Absolutely. I mean, firstly, just at the - the kind of easy level of, like, how - do I use AI on a day to - day basis and the way that it's transformed - my life. I mean, throughout my PhD, I - didn't have access to AI. And so when - I coded something that would be time consuming - or doing a literature review, obviously, I still - go away and read lots of papers. But - finding papers, I would essentially just be using - Google or looking in journals.

16:56- AI right now is really useful for physicists - across the world for accelerating the coding process. - You still have to double check it because - it can often be be incorrect, but also - giving you a group of papers to go - away and read, and you can decide whether - they're relevant. And often, it does a pretty - good job of giving you a batch of - papers to familiarize yourself with the field. So - that's kind of the the low entry level - way that AIB is used by me at - least on a day to day basis. They're - kind of like blue skies idea, the stuff - that I'm also working on in terms of - AI and machine learning.

17:29- Is can we apply these to kind - of fit quantum algorithms in a way that - often quantum mechanics is is really counterintuitive. - So maybe we're thinking about it in the - wrong way when we try and come up - with quantum circuits. In fact, it is very - common that someone comes up with a quantum - algorithm that is essentially just a classical algorithm, - but written in the language of qubits and - actually isn't - using things like superposition and entanglement to actually - gain any kind of advantage.

18:00- And so that circuit is never gonna actually - be better than a classical computer. - So - maybe AI - can work to kind of come up with - new quantum circuits. And in fact, that is - being done. There are research groups around the - world that are kind of trying to come - up with almost a large language model, but - for quantum algorithms. - So that's a really interesting and a niche - area that that - excites me a lot. But also machine learning - says something that I want to try and - do is - when we evolve these quantum systems and there's - there's infinite number of possibilities, - and formally, you have to - sum up every single possibility. So how do - you do an infinite sum? Well, it's very - difficult.

18:40- And so often, - computationally, that's impossible. So you have to come - up with tricks and you have to think, - okay. Well, which paths are actually important and - which ones aren't important? - Or maybe a machine learning model could learn - that for us. And maybe in the process - of doing that, it will reveal something about - quantum mechanics that we don't yet know. So - these are the kind of ways I want - to apply AI and machine learning.

19:05- And what what about your colleagues, - you know, who run particle physics experiments? I - would imagine that - AI and machine learning - is becoming really important - in in helping them deal with the the - sort of deluge of data that comes out - of, - an experiment on the Large Hadron Collider, for - example? - Yeah. I mean, this is, again, great question, - brilliant point, and and actually quite relevant to - another thing that I'm working on, actually. So, - basically, - Abelard, Hadron Collider, for those who don't know, - it it's billions of particle interactions per second - when it when it's running. So these datasets - are some of the biggest datasets in the - world, and it's not just one bit of - data for each particle. You you get its - momentum. You can get scattering angles. You get - all all sorts of things. So this dataset - is really massive. And so - scouring through it and trying to find interesting - bumps in the data that you weren't predicting - that might reveal new physics, - That's a really difficult thing. Again, it has - been done very well. I mean, the Higgs

20:06- particle in 2012 was discovered using classical techniques. - So - it's - doing really well, - but machine learning absolutely is being used - to essentially try and spot patterns - in the data - in a much quicker, much more efficient way, - and perhaps in a in a novel way - using techniques that we might not have thought - of - in order - to discover - new particles or new structures - in the standard model. So, for example, something - I'm working on is, can we map this - to a quantum computer? So can we take - the final - state particles, - take their momenta, - map it onto a bunch of qubits, - and then entangle those qubits in such a - way that we try to mirror some of - the correlations that you might expect between these - final state particles.

20:55- So we entangle - pairwise entangle the final state particles, and then - we run a machine learning code on this - network of qubits. - And - can this quantum computing and machine learning work - together to potentially give us an advantage over - traditional machine learning methods. - So some really exciting stuff there, but absolutely - machine learning and AI is being used - and being used increasingly more in particle physics - and a lot of my colleagues at the - LHC.

21:24- So it sounds like, - so so the LHC at the moment, I'm - I'm not sure if it's is it shut - down for the high luminosity - upgrade or is it Yeah. It's about to. - About to. Right. So, you know, that's going - to take a few years. And, I mean, - I would imagine that when the LHC is - back and up and running, - I mean, is it going to be a - different world for particle physicists? Because all these - machine learning and AI techniques - will have been - developed - and, - matured.

21:58- And also, you know, we we've got another - few years of quantum computing - progress to be made. I mean, you I - I mean, it sounds to me like you, - and your colleagues should be very excited - about, - a new sort of paradigm in how you - can, - interpret data from the LHC, and lots more - data, - that that is a result of the of - the upgrade. I mean, it it must be - very exciting. - Yeah. Well, exactly. And that point, if I - made it there at the end, is is - the crucial one. I mean, it's coming at - the right time. There's this high luminosity upgrade - is gonna give even more data. So that - would almost be quite scary if we weren't - equipped with the right tools to combat that, - and that's exactly what AI and machine learning - give us access to. And also, it's worth - saying that, I mean, a lot of my - work, I don't work directly with datasets of - a large Hadron Collider often, and the kind - of stuff that interests me - in parallel is this simulation using quantum computers - to simulate - particle interactions.

22:56- So we can build that on a a - tabletop experiment. - Obviously, we need probably thousands and thousands at - least of qubits. - So that might be a little while away, - but I can think of the algorithms now - and say one day when you give me - a tabletop of qubits, this is what I'm - gonna run and I'm gonna simulate - a particle interaction. And so we can kind - of attack it from two angles, top down - at the LHC. Look at all this data. - Let's go deep diving into it. And bottom - up from tabletop quantum computing experiments.

23:24- Let's try and build a simulation of these - and see if we can expect it from - below. So we can kind of pincer movement, - the the standard model of the universe, and - try and understand more about it. - And, Ross, I wanted to to shift gears - a bit and and talk about - how quantum computers could be used to - to, I suppose, solve one of the the - the biggest challenges - facing physicists at the moment, and that is - developing - a viable - quantum - theory of gravity. You know, at the moment, - quantum mechanics is - an extraordinarily - successful theory.

24:04- And, Einstein's - general theory of relativity does a great job - at describing gravity. - But, it has proven very difficult to bring - those two things together in a in a - theory that works. So how could quantum computers - help, - with that challenge? - Yeah. I mean, exactly like you say that - they're kind of fundamentally incompatible despite being two - of the most well verified theories in all - science. It is quite counterintuitive, but general relativity - speaks in this language of continuous space and - time and deterministic - results.

24:39- And quantum mechanics speaks in this language of - discretized space, quantized - space, and energy levels, and and not deterministic - at all. It's it's inherently probabilistic, and so - they're completely different languages. The mathematical toolbox that - you use for them both are completely different. - So for that reason, they're incompatible, but they're - also if you try and quantize gravity or - gravitize quantum, you end up with a bunch - of divergences, - so infinite terms.

25:02- So - for example, if you try to quantize gravity - and think of a particle, call it the - graviton, - it's infamously unrenormalizable. - I know there are some people who might - take issue with that, but that's kind of - general consensus. Right? So it's it's really difficult. - So this is where I'm gonna come back - to trying to do the bottom up approach - because - there are some theories - that are dual theories of quantum and gravity. - Now they're not theories of our universe. They're - theories of kind of toy models, - but it's this idea - called the holographic - principle.

25:34- And the idea is if you come up - with some - quantum theory and you calculate a bunch of - quantities in this quantum theory, - it's actually equivalent - to a gravitational theory that's not quantum whatsoever - in one dimension higher, - so an extra space time dimension, - and you calculate the same quantities, you get - the same results. - So, again, one is not contingent on the - other, but two different theories give the same - results, almost to imply - that if you have a gravitational theory, - the more fundamental version is this quantum mechanical - theory that exists in fewer dimensions.

26:12- So, for example, something you could do on - a tabletop is something called the SYK model, - the SAC devier Kitaev model. - And that's actually a zero plus one dimensional - theory, which means a zero space dimensions - and one time dimension. So it starts to - get very wacky, very hard to picture. It - says, imagine you have a bunch of particles, - essentially. They're called Majorana fermions. - You have a bunch of these particles. - They don't exist in space because space doesn't - exist, but we can still label them in - the kind of abstract, - and they do - change with time and their correlation has changed - with time. And all you do is you - randomly couple different groups of these particles.

26:49- And then there's your quantum theory and you - calculate a few things and it's quite a - simple theory, - something that we could try and build using - qubits in a lab. - What actually happens is really interesting is that - the results you get are equivalent - to something called j t gravity. So this - is this is a one plus one dimensional - theory. So one dimension of space, so it - exists on a line basically - and varies in time. - So you have this - baseline quantum model, this SYK model, - almost giving rise to gravity and giving rise - to a dimension of space because the two - theories give the same results.

27:26- So this is really interesting. Obviously, we don't - live on a line. We don't live in - a one plus one dimensional universe, so it's - not useful for us in our understanding of - our universe. But if we can build a - tabletop experiment - that doesn't have gravity in it at all, - just has entanglement and cubits, - and from that get results that mimic gravity, - then perhaps we can make the argument that - gravity and actually space itself - and perhaps even time - are emergent properties of quantum entanglement.

27:56- So this is the idea of emergent space - time, and this is the kind of way - that we could attack quantum gravity. Rather than - gravitize quantum or quantize gravity, let's - use fundamental quantum building blocks to build space - and time itself. - And that that takes me nicely to to - my final question for you, Ross. And I - I suppose it's - a more general question about the intersection between - quantum mechanics - and, general relativity.

28:28- Quantum information theory, which is the sort of - the conceptual framework - behind - quantum computers, is being used - to study - that interface. - And - it it it seems to be throwing up - some really interesting things. - I mean, I I wrote an article probably - about a year ago about something called, - indefinite - causal order, which is a really strange thing - when you when you start, - combining, - quantum mechanics - and general relativity.

29:03- And, - quantum information theory is, you know, it's been - shedding light on the nature of - space time, - black holes, and, you know, all those sort - of wonderful things. Can you talk a bit - about - what sort of insights quantum information theory can - give us into the, you know, the universe - in general, I suppose, beyond - the quantum world. Yeah. And it's really, really - interesting. So information is kind of this abstract - concept, but it's - often proposed as being fundamental in the universe - and and information is always conserved.

29:35- And so when you have information about, for - example, a thermodynamic - room of particles, you you apply something called - statistical mechanics to that, and you can get - some conclusions about the information in the room, - often this thing called entropy. Right? So may - have heard of entropy before. There's quantum mechanical - equivalent. Imagine you have lots of quantum particles - and you can do this the field of - quantum information.

29:56- And within that, there are definitions of entropy - about how much we know about this quantum - system, how much we don't know, what if - we only look at part of it, what - does that teach us about potentially entanglement between - different regions, things like that. And this toolbox - has been developed for a little while and - it's really interesting, and it kind of can - give us a bunch of stuff to do - with quantum computers. - But then in parallel, the field of black - holes was developing their own little toolbox to - try and understand the event horizon and what - happens to things that falls inside a black - hole. And then really surprisingly, - some of the results - again seem to match. It seemed to be - that, actually, we can start using these ideas - of quantum information theory on black holes themselves.

30:34- And, actually, - our current understanding, and this is really bleeding - edge physics at the moment, so this might - change, but But our current understanding is if - something falls into a black hole, that information - isn't lost forever. - It's actually encoded in some sense on the - surface of the black hole - on the event horizon. And Leonard Susskind would - be an advocate for saying it goes inside - and outside the black hole. This is the - idea of black hole complementarity.

30:59- So there's some really interesting stuff here, but - the idea is it's preserved. It's encoded, almost - encrypted, and it's done so redundantly. - So you don't need the entire surface of - the black hole to reconstruct all of the - information, almost as if it's error correcting in - some way. And then that information is slowly - released back into the universe over billions of - billions of years - through Hawking radiation. So some really interesting stuff, - and all of this has been found out - by applying this toolbox of quantum information - to black hole physics and to these extreme - environments where there's interesting quantum mechanical effects and - strong gravitational effects. So this could be a - good playground to understand quantum gravity, for example.

31:40- So this is a kind of idea that - we can apply quantum information to perhaps surprising - areas of physics and learn quite a lot. - Yeah. That that that is really interesting. I - mean, is this this, - black hole? Is it that firewall? - I I I remember there's a lot of - work about that. - Maybe five years ago, there was a flurry - of, - of papers. And, yeah, I remember - really struggling - to get my head around, - exactly what was going on. But, yeah, I - mean, that is a really interesting it's is - that is that the black hole information paradox?

32:18- Exactly. So the information paradox originally was when - when Stephen Hawking - came up with, oh, hold on. That there's - some kind of radiation that's leading out. But - he said that radiation cannot - contain the information. The information's inside the black - hole. Right? - So but the problem is if if a - black hole is radiating, it's it's slowly shrinking. - So eventually, that black hole will disappear. So - if the information is not in the radiation - and it's the black hole is gone, where's - the information?

32:43- So this was the information paradox. And he - actually had a bet, with with, with Preskill - about this. - And he said, Preskill said that, no. The - information must be in in in your radiation, - in the Hawking radiation. And Stephen Hawking disagreed, - but eventually conceded that that he was correct. - And that that is where we're at at - the moment. We think the information is indeed - in the Hawking radiation. So it is really - interesting. Really interesting. And, again, this could change, - but this is what's so exciting about the - field.

33:12- Yeah. Yeah. Yeah. It it it's all coming - back to me now. And then you've got - this no is it the no hair theorem? - Yeah. Is that is that at the heart - of the paradox that the black hole - can't - hold this information or that it shouldn't be - there or Yeah. There can't be kind of, - this kind of fuzzy thing that happens on - the edge. But this is all all kind - of intertwined, and and the firewall that you - mentioned earlier is kind of, again, up for - debate. So some people would would believe that - you can't cross the event horizon because you - would you would tear up. It would kind - of become infinite temperature. That isn't really the - prevailing theory at the moment. I think it's - slightly more common to say that if you - invoke the equivalence principle, which means that if - you're in free fall, you're not supposed to - be able to tell if that you're in - a particularly special environment, including that of the - event horizon. So for us if it was - a small black hole, the tidal effects would - rip you apart, so you could definitely tell.

34:03- But if it was a really supermassive black - hole, you could pass the event horizon and - not even notice. We could be doing it - right now. The Earth could be falling into - some supermassive black hole, and we wouldn't know. - So this is - kind of what we think - is happening. Obviously, if you look at someone - from afar - because of general relativity and different different - perspectives, different frames, you would see something different.

34:25- You would never see them pass the event - horizons black of the black hole because time - dilates infinitely. So that light - is never gonna reach you of them of - them passing the black hole. So this is - kind of, again, leading back into the Susskind - view of complementarity. - You you you almost pass the event horizon - and don't pass the event horizon, and something - is also true for information. - So really, really cool stuff. - Yeah. It is I mean, it is astonishing, - or at least I find it astonishing that - you can you can have these sort of - quantum conversations - about a black hole, which is, you know, - something that's huge and, you know, - the - incredibly violent - gravitational - field that it has. You would have thought - it would it would be the least quantum - thing in the world.

35:10- Yet, you know, you've got all these subtle - effects, - that you that I suppose quantum mechanics forces - you Yeah. To to think about. - Well, that's what I mean. - Everywhere. Even in the the vacuum of empty - spaces, - motivation to explain Hawking radiation. Even the vacuum, - right at the boundary of a black hole - at the event horizon, There's interesting stuff happening - there. There's an interaction between these really cool - environments.

35:40- Well, that's great, Ross. Thanks so much for - for coming on the podcast and and talking - to us about quantum computing and particle physics, - quantum gravity, and black holes as well. - So so what's some - you mentioned some of your research, - at the moment. Is there anything in particular - that you're working on now that you'd like - to share with our audience? - Yeah. So, I mean, so I I finished - my PhD last year, actually, and it was - mostly related in kind of causality for quantum - field theory. So the mathematical framework of of - our best theory of quantum mechanics. And now - I'm pivoting into - actually kind of more applications for quantum computers.

36:20- So hopefully later this year, I'll have some - papers out that are gonna be about the - kind of algorithms that we can use to - simulate - quantum field theories - on qubits. So hopefully, stay tuned for that. - And I think, I mean, I think we've - got a good careers message here. I mean, - we we love to talk about careers - on the Physics World podcast. - And, - you know, it sounds to me that, - you you can do particle physics. - And then, I mean, maybe you're not going - to do this or maybe you will, that - you can move into a career - in quantum computing - fairly seamlessly. I mean, is that right? Would - you I mean, if somebody came to you - and said, well, you know, I'm really interested - in particle physics, - but I wanna get a job at a - quantum computing company. I mean, it sounds to - me like, - doing a PhD in particle physics be a - good idea.

37:12- Yeah. Yeah. I mean, the the boundaries are - definitely getting more and more blurred as time - goes on, as we've discussed the ideas of - AI, machine learning, even qubits starting to be - applied in particle physics. And so it becomes - very interdisciplinary. - And, actually, my my masters that I did - before my PhD - was half in quantum computing and half in - particle physics. And so I always kind of - balanced it because I'm interested in both. And - so I've I've managed to be be very - lucky in that I get to study both - fields simultaneously. But, yeah, you can absolutely - absolutely pivot.

37:44- Well, that's great, Ross. Well, thanks again for - coming on the podcast. Thank you very much - for having me. - That was Ross Jenkinson of the University of - Manchester. - Thanks, Ross, for a fascinating discussion. - This podcast is brought to you by American - Elements, - the world's leading - manufacturer - of engineered and advanced materials. - With a catalog of over 35,000 - products available in both industrial bulk and laboratory - quantities, - American Elements is the largest supplier of its - kind.

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38:57- American - Elements. - Now invent. - I'm afraid that's all the time we have - for this week's podcast. - I'm Hamish Johnston, and our producer is Fred - Iles. - The music you hear in Physics World's podcasts - is called one three seven, and it was - composed and performed by the physicist - Philip Moriarty. - We'll be back again next week.