Sebastian Hassinger (00:04)
Welcome back to the show, everybody. Thanks for joining us today. We are joined today by Professor Vladan Vlutic from MIT. He's the Lester Wolf Professor of Physics. He works in experimental atomic physics at the Center for Ultra Cold Atoms and the Research Laboratory of Electronics. And Professor Vlutic, welcome and thank you very much for joining us.
Vladan Vuletic (00:28)
Thank you very much. It's a pleasure to be here.
Kevin Rowney (00:29)
Good morning. Yeah, I hope we didn't massacre the pronunciation of your name. Please let us know if we got it right. All right, very good. Thank you. Thank you.
Vladan Vuletic (00:36)
Okay, we'll let it, this is my last.
Sebastian Hassinger (00:38)
Ruletic, my apologies. So Professor Ruletic, we were very excited about having you on because of course, one of the biggest events in the last year of quantum computing was the paper that you authored along with Misha Lukin's group that was published on the 6th of December in Nature. It's called Logical Quantum Processor Based on Reconfigurable Atom Arrays.
Before we get into that, can you give us a little bit of background on yourself? What your path was to quantum computing? What your area of study has been? That sort of thing?
Vladan Vuletic (01:18)
As long as I can remember, I always wanted to study physics, but certainly it was nowhere on the horizon. When I started, I studied in Germany and it was kind of by random chance. I was looking for a diploma thesis in Germany. It's like an extended master thesis. So I was looking for a field and you know, couldn't find anything. And I randomly walked into one advanced seminar where somebody called
Sebastian Hassinger (01:20)
Vladan Vuletic (01:45)
Ted Hensch was talking about a recent breakthrough that had been achieved at Stanford by Stephen Chu, where people had laser-cooled atoms for the first time. So they have taken laser beams inside a vacuum chamber and then cooled atoms to micro-Kelvin, hundreds of micro-Kelvin's temperature above absolute zero. So at minus 273 degrees Celsius and had trapped them actually in a laser trap. And I thought, I don't know what this is good for, but this is so cool.
Sebastian Hassinger (02:12)
Vladan Vuletic (02:14)
control atoms and have them down at very cold temperatures. When people come in our lab, they often are surprised, they expect something cryogenic like refrigerators and so on, but there's nothing cold except the atoms, right? And so when I, you know, this is now many years ago, I thought this is something very exciting, you know, the famous quote, I don't know what it is, but it is a newborn baby and it's going to be interesting. And...
Kevin Rowney (02:14)
Sebastian Hassinger (02:26)
Kevin Rowney (02:27)
Sebastian Hassinger (02:39)
Right. Yeah, yeah, yeah.
Vladan Vuletic (02:41)
So I joined that group. I worked on laser cooling and trapping at the time. I was very fortunate. I did my PhD then with Ted Henge. He later won the Nobel Prize for precision spectroscopy. And I, you know, I have a lot of luck in my path. While I was a graduate student, Steve Chu from Stanford, I was a Humbert Laureate. He came, he had nothing to do with the summer. He somehow found me and said, let's work together. We were thinking about some.
new ways of trapping atoms in magnetic traps. And he said, whenever you finish your PhD, please come to Stanford as a postdoc where I continue to do laser cooling. So all my life I've been doing laser manipulation, quantum manipulation of atoms. Of course, the field didn't start out with quantum
computing or anything like that.
Sebastian Hassinger (03:30)
Right. Were you involved in the Bose Einstein condensate work with cold atoms?
Kevin Rowney (03:31)
Vladan Vuletic (03:38)
I did some of that. We did also at some point have a Bose-Einstein condensate. My own interest was always a little bit more in direction of metal-light interactions, being able to control atoms. We work on precision experiments on cavity QED, etc., on precision metrology. But we do use laser-coated atoms, including Bose-Einstein condensate. So, yes, it was involved.
Sebastian Hassinger (03:53)
Right. I just heard it said in some ways that the cold atom arrays were, the community was very focused in general on the BEC work. And then once the Nobel Prize was accomplished, it sort of pivoted to quantum computing more, but it sounds like you took a different path.
Vladan Vuletic (04:18)
Yeah, slightly different. I mean, the quantum computing really only, you know, was put on the map by the famous, you know, Dave Wienlein, Chris Monroe experiment on Iron Trap quantum gates. That's when everybody became first aware, I think, that this was at least a least, at least a possibility. This was maybe five or something like that.
Sebastian Hassinger (04:36)
Right. That's right. Yeah.
Kevin Rowney (04:40)
It's such an interesting theme that we ask this question all the time of our guests of what led to their path into this domain of quantum computing. And so often this theme of some particular moment where there's been this just a transformative encounter with a really cool idea that just charms them into this path that perhaps almost against their will, they begin to march towards this new objective, leading to this interesting landscape of QC. So it's a fun theme.
Sebastian Hassinger (04:57)
Vladan Vuletic (05:07)
It is. And for me, it was always, if you want to call it the coolness factor, it's sometimes hard to describe what it is. You don't have your application in mind. It's more like, you know, this is so different from anything else I knew before that, you know, there must be new, new opportunities.
Kevin Rowney (05:11)
Yeah. Yes. Yeah.
Sebastian Hassinger (05:13)
Kevin Rowney (05:20)
Yes, charms and inspires in this deep way. Yeah, yeah. Wow.
Sebastian Hassinger (05:22)
Yeah, right, right. And so the collaboration with Lukin's group at Harvard goes quite a few years back as well, I believe. Is that right?
Vladan Vuletic (05:33)
Yeah, it goes back a lot of years. So I was assistant professor then at Stanford for three years before I came to MIT. And what attracted me to MIT, the Boston area, was that there had been established a Center for Ultra-Cold Atoms funded by NSF, which was a collaboration between MIT and Harvard and faculty there. And so about the same time when I joined MIT, Misha Lukin joined Harvard. He was a postdoc at Harvard ITEM.
We had an interesting account. I very well remember the first time I met him. I was visiting here, interviewing, and they sent me to meet Misha Lukin, this promising postdoc who was at Harvard. I walked into the lab and the first he said, hi, he said, are you sure your latest paper is correct? I just published a paper on an idea to do that. And so I managed to convince him that it was correct. And it was the start of a wonderful friendship.
Kevin Rowney (06:20)
Okay. Ha ha ha.
Sebastian Hassinger (06:26)
Okay, good. Physicists often go hard when they meet each other, I know.
Kevin Rowney (06:29)
Nice opener, yeah.
Vladan Vuletic (06:31)
and then we started working.
Kevin Rowney (06:36)
Vladan Vuletic (06:37)
Yeah. So it was a good entry. And then he started out as a theorist. I was an experimentalist. So we started working together, joining forces to bring about some synergy. And so over the years he has become more of an experimentalist. And I had some interesting theories. So Misha wrote a very influential paper, which at the time sounded a little bit crazy, which was this idea to use Rydberg atoms to do quantum gates.
Rydberg atoms had been studied extensively in the maybe 1980s by my former colleague Dan Kleppner here at MIT. So it was already fashionable then for spectroscopy and so on, but it seemed like these are very highly excited atoms, it seems like a really strange idea to use them for anything controlled like quantum gates. They have the feature that they are long lived states and Misha together with Peter Zoller and some other people recognized that and wrote this kind of crazy paper.
Sebastian Hassinger (07:18)
Vladan Vuletic (07:33)
I think also around 2000, to use Rydberg Gates, you know, Rydberg atoms for quantum gates. And so we started collaborating at a time we didn't really think about quantum gates yet because a single atom trapping hadn't been developed, but we used these Rydberg atoms in collaborative experiments to for the first time make individual photons interact. Photons normally pass through light, light passes through light, light doesn't interact with light to a very, very high degree, but when we passed it through
Sebastian Hassinger (07:54)
Vladan Vuletic (08:02)
cold medium of atoms in a particular way that involved Rydberg states, we could make single photons interact and we could for the first time demonstrate photons that were in a bound state. So we could make a molecule of two photons of light at a time.
Sebastian Hassinger (08:16)
Kevin Rowney (08:16)
Mm-hmm. Wow. And so this is just a really inspiring new architecture for quantum computing and so compelling. And I think people who are insiders perhaps understand exactly what you're talking about, these Rydberg states and so forth. But just for a more generalist audience, who maybe are more familiar with superconducting or other architectures, I mean, for a lot of novices like me, it's a surprise that this architecture can actually render robust.
computations. I'm just, how could we frame a basic overview, right, of how these arrays of these Rydberg states can produce computation?
Vladan Vuletic (08:56)
I'll do that. Maybe I'll go even step back and say, what do you need for quantum computing? You need qubits and they need to be identical. That's one key requirement. And then you have to be able to switch on and off interactions between these qubits. Qubits have two states that depend on the state of the qubit. And so you can take a few different routes. In superconducting qubits, you can engineer things very well. It's kind of obvious maybe that you can turn on and off interactions.
Kevin Rowney (09:01)
Vladan Vuletic (09:25)
with microwave pulses. What is hard for superconducting qubits is to make them very identical because they're always fabricated, they're artificial, so you have to have a very high degree of control in the fabrication to make them as identical as possible. If you come from the other side using atoms or ions, you get the identical, the identity for free, the identicallness for free because all atoms by definition are exactly the same. You know, they are just perfect qubits.
Kevin Rowney (09:27)
Sebastian Hassinger (09:31)
Nature's perfect cubits. Yeah.
Vladan Vuletic (09:54)
What is hard in the atoms is to do the switchable interactions, especially over distances where you can control. So if you put many atoms into Bose-Einstein condensate, they collide with each other. There are some interactions, but these interactions are very hard to control, and it's also hard to isolate identical qubits. And so what happened first in the ion trapping community was this idea to use Coulomb interactions. So these are long-range interactions so that you could turn on and off interactions in a...
Sebastian Hassinger (09:57)
Vladan Vuletic (10:22)
a particular wave of laser beams between separated ions. Ions are relatively easy to trap because they have an electrical charge. Electric forces are very strong. And so that's why ion trap quantum computing was the first one to succeed with gates because they had already, you know, due to the work of Dave Wineland and before Daymelt and so on, had these controlled atoms and interactions over distance. A distance here means micrometers, you know, a few micrometers, 10 micrometers.
Kevin Rowney (10:48)
Vladan Vuletic (10:51)
And for atoms, that's really an unsolved problem because atoms in the ground state only interact when you put them on top of each other, when they collide with each other. But if you put them a few micrometers apart where you can optically control them, you cannot, in general, there's almost no way to do interactions. And the one way to do it is to put atoms in very highly excited states. So everybody maybe knows the hydrogen atoms and remembers this in 1S orbital and the 2S orbital, 3S orbital.
Sebastian Hassinger (10:57)
Kevin Rowney (11:18)
Vladan Vuletic (11:20)
but there's also 100S orbital. And this 100S orbital is such that the electron is at a micron distance from the nucleus. So you could take a whole COVID virus and put it inside the atom and the electron would be going around. So it's a gigantic atom and what that means is that these atoms react to tiny electric fields because the electron is so far away from the nucleus it can be polarized very easily. And what that also means if you take two such Rydberg atoms, two atoms in this 100S state,
Kevin Rowney (11:21)
Sebastian Hassinger (11:28)
Kevin Rowney (11:31)
Ha ha ha! Shikanic, yes, yeah.
Sebastian Hassinger (11:34)
Vladan Vuletic (11:50)
and put them at a microscopic, well not macroscopic, but you know, kind of micrometer distances from one another, they start to interact very strong. And that's very important, so a typical scale is maybe hundreds of megahertz to gigahertz, and that's important because this energy scale also sets the inverse of that, given by Planck's constant sets the time, at which you can, the speed of gates. And these Rydberg atoms are very nice because they have large interaction strings.
Sebastian Hassinger (11:57)
Vladan Vuletic (12:18)
at hundreds of megahertz energy spacings or interaction strengths, this also sets a corresponding speed to be close to that, some defect or below that.
Kevin Rowney (12:28)
And I gather a range long enough that you can manipulate them to close together for interaction via laser.
Vladan Vuletic (12:34)
Exactly. So there were really two key breakthroughs. One is, you know, to control these Rydberg states. And then the other breakthrough was this ability to make deterministically arrays of many single atoms. It's interesting. So it was 20 years ago in 2003 when a group in Paris, Philippe Granger, for the first time trapped a single atom and saw it. So they used kind of something that was known from Bose-Einstein condensates. They used laser traps and laser cooling.
laser beam as focused as tightly as possible. So usually before that we used kind of bigger traps, big means maybe 100 micrometers or so where you can fit in many atoms to do, say both Einstein condensates. And what they tried is let's make a focus that is, you know, limited to the, by the fraction to the one micrometer scale. And they saw that they could trap a single atom half the time. And so that was kind of a break from, but maybe it wasn't really a.
Sebastian Hassinger (13:25)
Vladan Vuletic (13:29)
appreciate it as much as it should have been because it was still, if you have 50% of the time an atom inside and 50% not, you can't put 100 traps together and expect to have 100 atoms. Very unlikely. Right. And so...
Sebastian Hassinger (13:39)
Kevin Rowney (13:42)
But still a gigantic breakthrough at the time. I mean, the manipulation of a single atom, even imperfectly so, I mean, impressive, yes.
Sebastian Hassinger (13:44)
Vladan Vuletic (13:47)
It was very impressive that you could image it, you could use fluorescence from the single atom. Something that people had done in the ion community for a long time, since the 1990s, but this was now a breakthrough in the nuclear atom world for single atoms. And now the idea came in 2016, we did a paper with Misha, where we for the first time basically used the feedback mechanism to load many atoms, many traps with 50% probability.
Kevin Rowney (13:52)
Sebastian Hassinger (13:55)
Kevin Rowney (14:00)
Vladan Vuletic (14:14)
but then look at which atoms, which traps were filled and rearrange them in such a way to get a deterministic pattern. Similar way was done by Anton, similar things were done by Anton Brevet's group at the same time in Paris. And it's interesting in this field, often the ideas are around, but people maybe think they won't work very well. It's not like we invented this. This was kind of an idea that was in the community, but nobody thought it would be so promising and it would scale so well.
Kevin Rowney (14:20)
Sebastian Hassinger (14:41)
That's really cool.
Kevin Rowney (14:42)
And so I think the really essential message of the Nature paper, yes, that you and the team have produced is around this sort of parallelization architecture, these whole grids of neutral atoms that can be manipulated in parallel that produce the really compelling results on essentially concrete error correction that are detailed in the paper. I hope I got that summary right, but could we just sort of delve down into that concept a little bit more deeply?
Vladan Vuletic (15:12)
Yes, that's a very good point. So now we have these arrays of controllable atoms that can be moved around in laser beams. And basically, you should think of a 2D geometry. This is an array of traps and in 2D these atoms can be moved around. And we have also the ability to scale to large numbers of what we call now physical qubits, these atoms, each atom is a physical qubit. To hundreds of atoms at the moment, you know, some groups even go...
thousands, ten thousands. But now the idea is to encode into groups of these physical qubits, encode them as so-called logical qubits. Basically, you do redundant states. In a particular way, there are different codes proposed so that you encode one logical qubit in a group of physical qubits and atoms. And now what is very interesting about this technology is that a certain subset of the quantum gates that you need for universal quantum computation,
Kevin Rowney (15:58)
Vladan Vuletic (16:08)
they can be in certain geometries realized as transversal gates. What that means is that if you have, you know, N atoms representing one qubit and N atoms representing another one qubit, then you can kind of one by one place, one group of atoms next to the other group of atoms so that each atom physical qubit only interacts with one other physical qubit. And in that way, you can, you know, in a highly parallel process realize a logical qubit in the system.
Kevin Rowney (16:08)
Sebastian Hassinger (16:29)
Kevin Rowney (16:34)
Yeah, so this one array interacting with another array, qubit by qubit in parallel, this is a key bit of the architecture allowing us to conceive of essentially physical qubits collaborating together to realize a logical qubit that is error corrected. It seems like that's the big breakthrough on this paper is the concrete demonstration in silico, so to speak, of a real system that does this kind of manipulation required to render these highly accurate logical qubits.
Sebastian Hassinger (16:59)
Thanks for watching!
Vladan Vuletic (17:04)
Exactly, and it's an important feature. I mean, there are other ways to do this, but if you don't do it with transversal gates, they require many, many operations.
Sebastian Hassinger (17:12)
Kevin Rowney (17:13)
Yes, that's long and tedious. How are you going to get that done serially? I mean, that's just completely unrealistic, right? I mean, yeah.
Vladan Vuletic (17:18)
Exactly, it's hard and even the, I mean, this is all done with laser beams. When we first started this a few years back, right, we were imagining that we would need, you know, millions of laser beams individually controlled and very fast. So think of your LCD TV screen, right, that many bits, but now each laser has to be, you know, not controlled on a millisecond timescale, but on, you know, a nanosecond or 100 nanosecond timescale. So this is something even in optics that hasn't been solved yet, right, such a fast array.
Sebastian Hassinger (17:43)
Vladan Vuletic (17:45)
And so this parallelization makes this task much, much simpler because we can move whole arrays of bits around rather than having to do something different with each individual laser beam with each individual atom. It's also a big control problem, right, because if you, for each physical qubits need several control channels for physical qubits, that's completely unrealistic, right? And that's not how it works in electronics either, right?
Sebastian Hassinger (17:47)
Kevin Rowney (18:10)
Vladan Vuletic (18:11)
electronics we have millions of transistors but the number of wires going to the transistors is not millions. It's a much smaller number.
Sebastian Hassinger (18:13)
Kevin Rowney (18:18)
Yeah, I mean, the sort of crossbar architecture is sort of a common theme throughout all of this silicon ship thing. Yeah.
Vladan Vuletic (18:23)
Exactly. And so something like that is fortunately possible in the neutral atom systems, in the neutral atom versus massive polarization.
Sebastian Hassinger (18:27)
Kevin Rowney (18:32)
So what one beam is controlling as a swarm, one whole row or column, right, of this grid and just moving it en masse and promoting a parallel operation of interaction. Do I have that right? Yeah.
Vladan Vuletic (18:45)
Correct, could be row, could be column, could be even a whole pattern, arbitrary pattern in 2D. So we do even a whole grid moving.
Kevin Rowney (18:50)
Oh, interesting. Yeah, yeah.
Sebastian Hassinger (18:53)
Hmm. Interesting. And one of the things that's so striking about the Nature Paper is that system architecture, it's funny because it, I mean, it's describing how you're organizing the optical space of your trap, but it looks very much like a chip architecture. You've got sort of ancillary cubits that are in reserve over in a reservoir, and you're moving them in and out of the entangling zone, and then...
Kevin Rowney (18:54)
Yes, yeah, yeah.
Sebastian Hassinger (19:19)
There's a storage zone. It starts to look like a real, like a real computer system, but in free space, it's really quite striking. Yeah.
Vladan Vuletic (19:23)
Kevin Rowney (19:26)
Like L1, L2 memory and so forth. Yeah, yeah, right.
Vladan Vuletic (19:28)
Yes, it is amazing. It's also kind of interesting. You think about that, you know, we, for each computation, we assemble the memory and microchip, do the computation and throw it away and build a new chip on the next round.
Kevin Rowney (19:41)
Oh my God. Yes. Yeah. Almost a parallel to the von Neumann architecture, almost exactly. Yeah. So it's, yeah. It's just, sorry, go ahead, Sebastian. Go ahead. Yeah. Just this interesting journey where you began with sort of seeing this original vision of this coolness factor of suspending this one single atom inside a laser beam.
Sebastian Hassinger (19:45)
Vladan Vuletic (19:50)
Almost exactly, yes.
Sebastian Hassinger (19:52)
That's really interesting. And, oh, go ahead. No, no, you first.
Kevin Rowney (20:07)
leading this long journey towards a realization of a full-fledged architecture inside qubits. I mean, quite a surprise you wouldn't have expected that natural egress to ensue. So.
Sebastian Hassinger (20:19)
So, you know, digging into the implementation a bit more, those transversal gates, as you said, those are, you can represent Clifford gates in transversal, right? But if I'm not mistaken, that doesn't include, it's not a universal set of gates, is that right?
Vladan Vuletic (20:35)
That's correct. So one needs another type of non-Clifford gates, and we are working on realizing that as well.
Sebastian Hassinger (20:43)
Okay. And do you think, cause often in error correction implementations, at least theoretical ones, cause we're still in the early days of these practical implementations, the protected state is often limited in some way. And, you know, um, C-naught or entanglement or, uh, other gates need to be, at least there isn't a logical qubit, um, representation or operation that, that performs that, uh, to Foley or C-naught gate is that do you think...
think that it'll be similar sort of challenge with this implementation.
Vladan Vuletic (21:17)
Well, I mean, non-Clifford gates are certainly harder to make in this system. You know, we are working on them. We are hoping to maybe have this year a first demonstration of those. My own feeling is that people are very excited about these LDPC codes, these other ways of implementing a logical qubits gates, etc. My feeling is that there's a lot to be gained
Sebastian Hassinger (21:20)
Vladan Vuletic (21:47)
from some kind of co-design between theoretical ideas and experimental capabilities, because certain things are very easy in our platform. For instance, certain things are harder. And, you know, for people who understand both sides of the problem and take this into account, my feeling is that there's, you know, kind of maybe orders of magnitude to be gained from adapting, you know, the theoretical ideas to the architecture, right? Because before these demonstrations,
Sebastian Hassinger (22:08)
Vladan Vuletic (22:15)
The theoretical concepts were also rather simplistic, right? They assumed, for instance, that all errors are the same magnitude, because what else would you assume if you know nothing about the system, right? But in practice, it's very, very different, right? Our single-qubit errors are, for instance, almost error-free. You know, they are kind of 10 to minus 4 errors. Our two-qubit errors are the ones that give us trouble. And even among the two-qubit errors, you know, we have much more phase errors, z errors, than x errors, for instance.
Sebastian Hassinger (22:42)
Vladan Vuletic (22:44)
just because these states are relatively long-lived and so on, but it's the phases of the lasers, for instance, that produce these errors and energy shifts of the atomic levels. So an architecture that includes this and takes this into account can outperform, I think, standard architectures.
Kevin Rowney (23:05)
It feels to me like there's just such a rich and fascinating detail, both of the theory and the experimental apparatus required to render that. And I think a lot of our audience, like me and Sebastian, we love that kind of detail. But for the part of our audience, which is trying to figure out just from listening, what is the commercial potential of this entire domain? You know, there's a lot of skepticism about whether or not quantum computing could actually in any time soon achieve its commercial potential.
But this particular outcome, this nature paper, does seem to indicate there's a lot of, I think, renewed room for optimism, yes? I mean, realizing, yes? I mean, an implementation of many physical qubits, rendering highly accurate logical qubits. It feels like it's a breakthrough with commercial relevance. Maybe not in the short term, but still, it's pointing the way towards an outcome that could be real in some amount of time. What's your perspective on that point?
Vladan Vuletic (23:59)
I would agree with you. I mean, I myself, you know, even five years ago would have been a skeptic. And I remember, you know, that seven or eight years ago, you know, I was reviewing theory papers, you know, and I was thinking, you know, we will never have 100. What are you talking about? You know, there are theorists and they were proposing protocols and I was just thinking, you know, whatever, you know, we'll never have that. But I think there's a lot of room for optimism.
Kevin Rowney (24:15)
You're rolling your eyes at somebody's...
You're like, whatever.
Vladan Vuletic (24:28)
On the qubits number, sheer number, you know, this system very straightforwardly scale up to say 100,000 qubits, maybe a million qubits, non-physically. So that's just no, because the atoms are really non-interacting in the ground state and therefore you can add as many atoms as you want without disturbing the ones that you have. You know, so they scale very well in qubit number. We have now for the first time demonstrated, or not the first time, in Google.
Sebastian Hassinger (24:33)
Kevin Rowney (24:36)
Sebastian Hassinger (24:43)
Vladan Vuletic (24:56)
There were several other groups doing beautiful, you know, first experiments on error correction. But I think, you know, the logical qubit error is upon us. It's no longer NISQ. When people were talking, you know, there's the next, you know, five to 10 years will be all NISQ, and we have to think that NISQ application, I don't think that's the case. I think, you know, we have a new era, early era of logical qubits.
Kevin Rowney (24:58)
that almost this paper represents the transition from the Nisq'eira to something entirely new. Yeah, yeah, very inspiring.
Sebastian Hassinger (25:22)
Vladan Vuletic (25:24)
Yes, I think it's one. There are other indications, there are other competitors who do very well.
Sebastian Hassinger (25:30)
Kevin Rowney (25:32)
And I'm sure, I mean, just I'm a naive amateur here, but I mean, I still speculate. I mean, given that you've got two dimensional crossbar arrays now of laser controlled atoms, could you ascend to a third dimension and have greater interaction potential and better density?
Vladan Vuletic (25:49)
You could, and Antoine Breuway's group in Paris has actually demonstrated three-dimensional structure, so you can do the trapping. We do like the 2D geometry though because it solves the access problem, so we can use the third dimension for sending in the laser beams. Three dimensions you have to be much more careful. At the moment we are not running out of space, especially since we can move the atoms. So just, you know, on a kind of crossed hair you can already fit something like
Kevin Rowney (25:53)
Sebastian Hassinger (26:04)
Kevin Rowney (26:11)
Vladan Vuletic (26:19)
So, in a millimeter square, you can fit all the cubits that we will be able, this can be a million, million cubic cubits in just millimeter square area.
Kevin Rowney (26:19)
Sebastian Hassinger (26:23)
Yeah. Incredible. And, and in terms of that scale, does that start to pose problems for, for the control system architecture? If you get up to a million, like a thousand by a thousand grade. Yeah.
Vladan Vuletic (26:36)
Yes, right. It depends on how many logical qubits you have, right? And so basically the blocks, you know, if you have big blocks of fewer logical qubits, it's easier to manage. I think there will be trade-offs. So roughly speaking, I'll give you a prediction. I'll stick my neck out. In two years, we'll have 100 logical qubits with 10 to minus 6 errors, or maybe 10 logical qubits with 10 to minus 8 errors, something like that.
Sebastian Hassinger (26:41)
Kevin Rowney (27:04)
Wow. When that end up, great.
Vladan Vuletic (27:05)
Sebastian Hassinger (27:08)
It's so incredible because as you said, that sort of era of logical qubits, what is really striking about that is that, that sort of 50 qubits with good execution, good fidelity on two gates operations, that's not classically simulatable in any kind of reasonable way. So if you're talking about 100, that's well into a regime that we cannot touch classically at all. So.
If there are useful applications for quantum computers, we should be able to find them at that scale. Oh.
Kevin Rowney (27:38)
It sounds like you're edging up Sebastian to the supremacy word, which triggers some people. But yeah.
Sebastian Hassinger (27:42)
Vladan Vuletic (27:46)
Yeah, I would say by now I'm convinced that the risks are on the algorithm side, not on the hardware side. I think we will get the hardware up there into a regime where we clearly cannot classically simulate. Whether you call that supremacy, I don't think it's supremacy or quantum, maybe quantum advantage is a better word because you would really like practical advantage. But even so, right. But we don't really know. You know, we have Shor's algorithm.
Sebastian Hassinger (27:53)
Kevin Rowney (27:54)
Sebastian Hassinger (27:59)
Yeah, I agree. I agree.
Kevin Rowney (28:06)
Vladan Vuletic (28:13)
And that one requires thousands of logical qubits and 10 to minus 12 errors. I think the next two years will show whether there's a path towards that. But it would be really sad if we all had a Shor's algorithm. I would be very, very sad about that.
Kevin Rowney (28:27)
Sebastian Hassinger (28:29)
Yeah, it would. But I mean, minus the sort of horizontal application algorithms, there's certainly a lot of promise in simulations of natural systems. And in fact, I think, were you involved in the experiment that Lukin's group was part of with the simulation of the quantum spin fluid on the neutral atom array? Yeah, that's what I thought. So that's an example of...
Vladan Vuletic (28:51)
Yes, I was involved.
Sebastian Hassinger (28:54)
Even in an analog state where you're not even doing logical operations in a neutral atom array, you can do something that would be very hard if not impossible to simulate classically. Do you think that sort of ability to do quantum simulations will continue to progress as we get 100 logical qubits? You can do even more complex system simulations?
Vladan Vuletic (29:16)
I agree. I mean, in the quantum simulation world, first of all, you know, the clearest first application is to other quantum systems, is to science. That's kind of very obvious, you know, that there's a path there. And among those, you can distinguish, you know, the quantum simulation, the kind of analog quantum simulations, like the spin liquid that we did, where you try to simulate another one Hamiltonian in physics, physicist's language by another, you know, similar Hamiltonian.
Sebastian Hassinger (29:25)
Vladan Vuletic (29:45)
in the system where you really try to evolve in an analog way the system. I think there can be qualitative insights, maybe new quantum phases of matter, maybe new types of matter can be discovered. The interest, one interesting path is to do digital simulation of analog systems. So you can think of using these logical qubits to look at, you know, gauge theories, say high energy theories that are not understood.
Sebastian Hassinger (30:12)
Vladan Vuletic (30:14)
try to simulate them digitally. That's harder because you first need to have good logical qubits, good quantum gates and so on. But then you can use this for simulation. But on the other end, they can potentially go much further. Because once you have error correction, you can take many more steps. Right now, quantum simulation is limited by the coherence, what we call the coherence of the system. How long does it stay quantum? And that's limited. But once makes a switch to digital quantum simulation, has a higher threshold, once you're there,
Sebastian Hassinger (30:27)
Vladan Vuletic (30:44)
simulate more deeply. So I'm convinced that science applications will be abandoned
as these systems become available.
Sebastian Hassinger (30:51)
Yeah. Yeah, yeah, very much so. That's interesting. That's interesting. And at a hundred logical qubits, is that starting to get interesting in the scale of the, of the molecule that you can simulate, for example, or there, are there material science and potentially even small molecule pharmaceutical applications that start to get interesting?
Kevin Rowney (30:58)
Vladan Vuletic (31:15)
That's the hope. The papers I'm aware of still require more like thousands logical qubits, but very smart people are working on this. And I think it's kind of interesting when you work on an experimental side, nothing triggers interest and also the new depth as a system that is almost capable of doing it. It's very different with how much energy you work on same thing if you think it's 10 years away, somebody could do that.
Sebastian Hassinger (31:17)
Kevin Rowney (31:40)
Yeah, yeah. Hehehehe.
Sebastian Hassinger (31:43)
Vladan Vuletic (31:45)
do that in the lab. So we are really hoping for the whole community to come together worldwide to think about these problems, what becomes possible. And I hope that there will be new ideas and new breakthroughs that maybe allow one to use smaller systems at 100 logical qubit level to do something worthwhile and new and interesting.
Kevin Rowney (32:07)
So let's see, I mean, for the future of your lab and the team that worked on this paper, are you guys doubling down on this and moving forward with larger scale or is there some new frontier dimension of the research that you're not pursuing for your next achievement?
Sebastian Hassinger (32:07)
Kevin Rowney (32:22)
Vladan Vuletic (32:22)
Yes, definitely to make these things bigger, better, higher quantum gates. So we are trying to push to qubit gate fidelity was 99.5% for this work and in previous work. This was important because it was above the or below the threshold for the surface code, which is 1%, right? So this is basically the break even. So we are beyond the break even point. We're actually making the system larger, improve things.
Kevin Rowney (32:50)
You cross the threshold of the threshold theorem, yes.
Vladan Vuletic (32:52)
across the threshold, but the small, you know, the better we make the physical two-qubit error, the better it scales. It scales exponentially ultimately, right? So we are really one frontiers to push for 99.9 two-qubit gate fidelity, which would put us a factor of 10 below the surface code threshold and would allow him to still logical errors to be smaller. That's one frontier. The other frontier is to go to larger field of view systems. What we call, you know, basically
Sebastian Hassinger (32:56)
Vladan Vuletic (33:19)
focusing in laser beams, so we have microscopes and there's an active area that you can use, which we call field of view. So we would like, that's a few hundred micrometers in the first generation. We are building a new generation experiment that will be one, two millimeters square field of view where you can fit all these atoms. So we're no longer limited by the area, we'll be just limited by laser power, for instance, of how many traps we can. And then we are working on geometry.
Sebastian Hassinger (33:38)
Right, right, right.
Vladan Vuletic (33:48)
Very important next goal is to show a FAS called mid-circuit readouts, so really to close the feedback loop on error correction. What we haven't done in this paper is actually close the loop. We have shown that you can detect errors, but we haven't actually used this information to feed back in real time to make the calculation depth much deeper. So that's one of the next goals to put into a full feedback loop, as far as I know.
Sebastian Hassinger (33:54)
Right. I saw you did demonstrate feed forward, though, on your circuits. So there's still just mid-circuit measurement, and syndrome detection are still required. Interesting.
Vladan Vuletic (34:18)
So we have done all these separately, but we haven't done in a full loop where we do multiple rounds of error correction.
Sebastian Hassinger (34:26)
Right, right. That's interesting.
Kevin Rowney (34:33)
Wow, this has been such a fun conversation. We really appreciate it. And I hope you can see, we also enjoy the cool factor here. But also there is, again, a route towards the concrete outcomes here that feel like it's not just theory. There's perhaps a route towards an outcome that can make a difference in the broader world. So we really appreciate this time. I wonder, are there any other topics with respect to this paper or the achievements of the group that we've missed in this conversation that you want to cover?
Sebastian Hassinger (34:40)
Vladan Vuletic (35:03)
I want to say, just point out how remarkable this quantum error correction is. I mean, in classical systems, it's kind of obvious you encode something redundantly, and then if more than half of the qubit or bits are in one state, you say, okay, that must be the correct state, and it's very unlikely the other thing happened. But in quantum mechanics, we're not really allowed to touch the qubits. We can't know their state. So you know, the fact that you can do this and compare this
to experts like me or my colleagues in quantum physics who don't work in quantum error correction, if you ask them, is this possible, the instinct will be no, it can't be possible, can't look at it.
Sebastian Hassinger (35:40)
Kevin Rowney (35:41)
You can't look at them and you can't copy them, but you have to make sure they're running correctly. So yeah, that's kind of a handful.
Vladan Vuletic (35:48)
So I would say this is one of the really remarkable intellectual breakthroughs in science overall. I mean, kind of at a similar level, almost like, you know, how is genetic information encoded? There's a DNA or something, right? It's really a remarkable, remarkable journey where, you know, some very abstract ideas, right, which are hard to understand even for specialists.
Sebastian Hassinger (35:48)
Vladan Vuletic (36:13)
you know, except that people really work in quantum error correction, now come together with a physical system. So maybe there's hope that, you know, we can draw for other quantum physics experiments inspiration from this. You know, I also work in meteorology, trying to measure time better and other quantities better, right? It would be very nice if there was a cross fertilization of these quantum error correction ideas into all these other fields where we are trying to control quantum systems.
Sebastian Hassinger (36:18)
Kevin Rowney (36:40)
Ah, so interesting.
Sebastian Hassinger (36:41)
Yeah, yeah, it really is. We had a conversation with John Preskill where we talked a little bit about it from Qubit and sort of that concept of the back and forth collaboration between quantum information theory and other aspects of quantum mechanics and quantum physics. It really is such an exciting sort of cross-pollination between science and technology where both sides are making huge leaps forward. So we really appreciate your time. Thank you very much.
Kevin Rowney (37:09)
Very grateful, thank you.
Vladan Vuletic (37:11)
Thank you so much. It was a great pleasure.