A look back at quantum computing in 2023 with Kevin and Sebastian

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Kevin Rowney (00:01.776)
Well, welcome back. Hey, it's Kevin. We've decided, me and Sebastian, for our next episode here to delve into essentially a retrospective of the past year or so of this journey of the new quantum era. What we're trying to do in this episode is just do a little commentary, a little highlighting of key events that we've seen appear here. And I hope inform not just, you know, people who are interested in the science and the experimental outcomes, but also in terms of the...

You know, engineering, even perhaps economic eventual potential here. I think we've got a hold of some threads of that conversation that, um, deep in, uh, the dialogue, uh, perhaps reveal new trends and new themes going forward, uh, for our podcast. So, yeah, Sebastian, I think that's the overview. What do you, what do you think? I mean,

Sebastian Hassinger (00:44.662)
That's right, Kevin. Yeah, absolutely. I mean, I thought when you raised this idea, Kevin, I thought it was a really good idea for a couple reasons. One, we just had a hiatus that was a little longer than we'd anticipated. So I thought providing some context for that and sort of resetting our listeners' expectations would be a good idea. But also the last year has been

Kevin Rowney (00:58.84)
Well, yeah. Ha ha.

Sebastian Hassinger (01:14.858)
a monumental one for quantum computing. I think we both have felt like there's some significant shifts in the type of work that we're seeing, the type of progress we're seeing from the field. And especially with Professor Vuletic last week, that episode really, I mean, he used the words, the beginning of the era of the logical qubit, and it really triggered something for us that touched that sort of sense of like

Kevin Rowney (01:23.804)
Quite so, yes.

Sebastian Hassinger (01:43.454)
something is shifting and it felt like a good time to sort of give an overview of that and talk a little bit about how our focus is going to shift going forward.

Kevin Rowney (01:54.608)
Yeah, it does feel like it's kind of a big deal what's been happening here. And we want to acknowledge, right? I mean, you'd have to be not paying attention at all to see. There's a rising, of course, tide of skepticism, right, about what quantum computing could be and whether or not it will deliver. And of course, these storms of, you know, factual technologies like ebb and flow, but back and forth across Silicon Valley, where we're both based, you know, I just, it's, you see these trends all the time. The skepticism is warranted.

Sebastian Hassinger (02:05.826)
Mm-hmm.

Kevin Rowney (02:22.64)
However, I mean, this does feel like there is actually a little glitz of hope here rising from some of these new events that we're going to cover in the overview today.

Sebastian Hassinger (02:30.846)
Yeah, which was interesting because I agree there was this growing tie of skepticism over the past year in part because of the rise of generative AI. It really took a lot of the oxygen out of the room in R&D focus in large enterprise and startup funding and all the other sources of fuel for innovation.

Kevin Rowney (02:52.144)
My gosh, right?

Sebastian Hassinger (03:00.486)
significant results for the deep learning kind of approaches to chemistry and biology that cast doubts on quantum's ability to keep up.

Kevin Rowney (03:08.42)
Absolutely right. Yeah. It feels like a lot of practitioners of science that, uh, you know, need or could potentially need, uh, quantum rigs to perhaps significantly advance their, their trade aren't really paying all that close attention right now to what's happening in quantum computing because they see the classical methods keep making advances seem suitable to task. And.

Sebastian Hassinger (03:31.735)
Right.

Kevin Rowney (03:33.788)
There's a whole new vocabulary of capabilities to address those same problems using transformers and related advances that they appear to be on the verge of revolutionizing, at least some aspect of the tradecraft of these highly specific technical domains.

Sebastian Hassinger (03:42.702)
That's right.

Sebastian Hassinger (03:52.938)
Yeah, that's exactly right. Yeah. I mean, that's, it's, it's interesting. That's a point that Aronson makes in blog posts and in conversation quite often that it's a, in a sense, there's a quantum classical arms race, right? Every time there's a, some sort of breakthrough or parent breakthrough in a quantum algorithm, um, or a technique, there's, there's an opportunity for the classical world to go, Oh, that's interesting. We can do that, but better or faster or whatever, right? There's a, there's a catch up that happens.

Kevin Rowney (04:22.055)
Yes.

Sebastian Hassinger (04:22.926)
So there's a kind of continue, which by the way is great for everybody. All right.

Kevin Rowney (04:26.76)
It did, yes, it really is. But I really appreciate his sober-minded perspective. Both he's showing the skepticism, he's raising all of our standards with respect to how we evaluate and appraise, right, the merit of a given advance, an algorithm, a given piece of hardware. But also, I mean, you know, a guy like that, he's not just spouting bitter cynicism.

Sebastian Hassinger (04:31.639)
Yeah.

Sebastian Hassinger (04:51.859)
No, no.

Kevin Rowney (04:52.48)
I mean, he actually is a believer in the future of this entire domain. So that for us feels like a refreshing perspective, embracing what could be while still holding back on running down the path of some random marketing. Yeah.

Sebastian Hassinger (04:54.738)
Absolutely.

Sebastian Hassinger (05:00.161)
Yeah.

Sebastian Hassinger (05:10.315)
That's right. Yeah, the NFT scenario. So yeah, I mean, when we look back at the last year, in addition to those sort of maybe more skeptical or negative or pessimistic trends or thoughts, there were a number of sort of positive notes as well. And in particular,

Kevin Rowney (05:12.44)
Yeah, exactly. A web3 baloney. Yeah. God.

Sebastian Hassinger (05:36.602)
One of the things I've noticed is, and I've been talking about it a lot in the last year, is that as the potential there's more constriction on the private sector side, but it's been counterbalanced by an increasing investment from the public sector. And in many ways that feels very appropriate for this stage of this technology. It still has a lot of work to do in fundamental scientific research. And that historically is done more efficiently or better or more effectively.

Kevin Rowney (05:50.788)
Yes, yes.

Sebastian Hassinger (06:05.159)
by the public sector. So, you know, there's.

Kevin Rowney (06:06.98)
And interesting parallel with other, you know, black swan technologies that came out of, that seemed to come out of nowhere, you know, the early internet, even early, you know, chips, there was a huge amounts of, of public subsidy to get those launched. And so I'm sure there's people that want to, you know, see what private sector can do there, but I mean, also it feels like there's fundamental science to get done here that's still left unexplored.

Sebastian Hassinger (06:11.275)
Yeah.

Sebastian Hassinger (06:14.754)
Right.

Sebastian Hassinger (06:19.05)
Absolutely. Yeah.

Sebastian Hassinger (06:27.99)
That's right.

Sebastian Hassinger (06:31.47)
That's right. That's right. Yeah. So there's this global trend of national quantum initiatives that has really picked up steam over the last year. I've seen analysts who sort of track this as saying there's something like 30 to 40 billion dollars globally that's been publicly pledged by these national quantum initiatives. And Canada has a national quantum strategy. South Korea has a national quantum strategy. Austria, every country you can think of pretty much that has a significant...

Kevin Rowney (06:51.804)
Man.

Sebastian Hassinger (07:01.482)
um, you know, academic research base is now aggregating that community and, um, building either, uh, quantum data centers where they're, they're going to incubate and host, um, you know, their own, uh, sovereign attempts at building quantum devices, um, and, and provide those for, you know, for the use of their research community, um, and, or bringing in the, the act, the, the commercial, um, uh, players in, in the country to sort of

Kevin Rowney (07:23.824)
Yeah.

Sebastian Hassinger (07:31.11)
you know, solicit or source problem statements and then pair them up with researchers who can look for potential quantum advantage, sort of algorithmic research, right? So those two things are happening everywhere.

Kevin Rowney (07:39.884)
It's kind of an interesting, it's really interesting. I mean, it's a, there's a fascinating parallel or rather a contrast, right? Between what's happening here where there's broad embrace across numerous nation states all over, seeing if they could make sure they're part of a national initiative to embrace the future of quantum computing. But wow, I mean, you know, years and years ago, you know, the onset of

TCP IP and similar protocols. I mean, so many other nation states just missed the boat, right? Additionally, I mean, my gosh, I mean, the cloud computing, it just swept the landscape here in the U S and, wow, I mean, many major tech centers around the world, they have nothing on that front. So they somehow, maybe they were traumatized and don't want to miss the next boat, yeah.

Sebastian Hassinger (08:09.44)
Right.

Sebastian Hassinger (08:12.959)
Yeah.

Sebastian Hassinger (08:24.886)
Right, right. Well, yeah. And I mean, I think even more, those are good examples, I think even more close to home here is the classical chip supply chain, right? And we have the Chips Act in the US now as a way to try to counterbalance the extreme concentration of the supply chain down to two companies. Wait a minute.

Kevin Rowney (08:36.38)
There you go. Yeah.

Kevin Rowney (08:45.086)
Yeah, we started on the entire rig and then we offshored it and now we're like, wait a second.

Sebastian Hassinger (08:50.69)
So it seems to me like all these other nations are realizing, for one thing, I think there's a growing realization that the hardware race isn't done. I think maybe a few years ago there was a perception that the current modalities were incrementally going to make it to some sort of fault-tolerant quantum computing at scale. And now there's a little bit more doubt about that. So you see in Europe, for example.

Kevin Rowney (09:01.372)
By a long shot, yeah.

Sebastian Hassinger (09:18.898)
enormous efforts to get back into or redouble their existing hardware efforts to try to have, you know, sovereign efforts to build these, to realize these devices actually have commercial value, which I think, again, this is all healthy for the entire field, right? The more people we have working at this, as you use the term Black Swan, I think that's a very appropriate description of this market and this technology. So...

Kevin Rowney (09:36.988)
Absolutely, yeah.

Kevin Rowney (09:46.556)
Yes, yes.

Sebastian Hassinger (09:46.934)
The only rule with black swan kind of scenarios is the more attempts at cracking the code you have, the higher chance you have of actually getting something useful, right?

Kevin Rowney (09:57.449)
Yes, yes, yeah. And of course, I mean, every, you know, out of the blue, like marginal, uh, engineering event that has not yet entered the public awareness is, uh, is, uh, spun as a black swan. We're trying to acknowledge even that, that we're vulnerable to that same accusation that, you know, maybe the skeptics are right. Maybe there is a quantum winter heading right at us, but I don't know. I still think some of these, um, trends we've covered in the past year.

Sebastian Hassinger (10:09.79)
That's right. Of course.

Kevin Rowney (10:23.316)
are again, firm indicators of future hope.

Sebastian Hassinger (10:25.438)
Yeah. I mean, the other, the other sort of, um, overarching theme this year, you know, we've been riding on this, um, the NISQ era, right? Um, Preskill wrote the paper in I think 2015, I think 16, something like that. Um, it might be off, but, uh, but anyway, he coined the term NISQ, uh, near term, no noisy intermediate scale quantum device.

Kevin Rowney (10:38.641)
Yes.

Kevin Rowney (10:42.507)
Hmm? Yeah, yeah.

Kevin Rowney (10:50.824)
Oh, you see, that's right. That's, there you go. Yes.

Sebastian Hassinger (10:54.098)
With, you know, his hypothesis was that these devices would be useful in understanding better how to make these devices, which I think certainly is true. There's a proviso in his paper that potentially there might be some kind of commercial value that can be realized from certain techniques like VQE or other variational approaches to getting approximate or heuristic kind of.

Kevin Rowney (11:04.317)
Yes.

Sebastian Hassinger (11:22.114)
answers by pairing them with classical computing. And that's been a major theme of a lot of ISVs and pilot efforts at the enterprise level. And a lot of exploration has gone on in academia as well.

Kevin Rowney (11:24.776)
That's right. That's right.

Kevin Rowney (11:37.1)
And we've got more to say, I think, about VQE before we move on, but just maybe a brief tangent for the benefit of the audience. Some of our listeners, VQE is old news. Some are still appreciating these algorithms. So it's a hybrid classical quantum approach, right? Where it's because of intermediate scale, because of the noisy nature of contemporary quantum computing, what you're doing is setting up classically a state space on a quantum computer.

Sebastian Hassinger (11:40.191)
Yeah.

Sebastian Hassinger (11:46.785)
Yeah.

Kevin Rowney (12:05.976)
and then using the quantum computer to quickly, in one short computation, solve for the principal eigenvalue and eigenvector. And then from that, the feedback classically then keep adjusting the next run of that one, trying to converge towards the best-fit solution for that. That was hypothesized. You have numerous near-term commercial inputs, sorry, commercial applications.

Sebastian Hassinger (12:33.025)
Yeah.

Kevin Rowney (12:33.712)
But it appears that our faith there was perhaps a little overeager. I mean, you just told me there was a product conference recently where a CEO of one of these quantum computing startups was like basically saying VQE is dead. I mean, it feels like there's at least in some segments of this conversation now pretty firm skepticism on the merit of that aspect of the NISQ program.

Sebastian Hassinger (12:58.796)
Yeah.

Sebastian Hassinger (13:03.434)
Yeah, I will say, I mean, I think that comment was delivered during a keynote at Q2B Paris last May. I think he was referring to sort of vanilla VQE because there are, you know, there are sort of new approaches VQE adapt and other variations on the variational climate solver. And also, frankly, the, you know, the underlying...

Kevin Rowney (13:10.531)
Oh yeah.

Kevin Rowney (13:16.484)
Uh-huh.

Kevin Rowney (13:24.716)
Okay. Yes. Okay. Yeah. Great.

Sebastian Hassinger (13:32.102)
sort of attempts to both increase the quality of the qubit. So just increasing gate fidelity, decreasing general noise, the extending T1 and T2 coherence times as an engineering level. But then things like, you know, we talked to Misty Wahl, the mitiq framework project. I think there's increasing sophistication in the types of error mitigation strategies that can take

Kevin Rowney (13:56.016)
Yes. Yeah.

Sebastian Hassinger (13:58.098)
a noisy environment and extract value from that through statistical means generally. And then, again, beyond error mitigation, there's the whole realm of error correction and creation of logical qubits, which is the path to true fault-tolerant quantum computing, which took significant steps forward in 2023.

Kevin Rowney (14:01.828)
Yes. Yes, yeah.

Kevin Rowney (14:21.96)
I'm so glad that you brought that up because that I think is one of the key threads that we'd like to focus more on in this dialogue, but also perhaps even going forward. In many of our future podcasts, this particular swath of technologies, engineering, of algorithms related to the robust implementation of logical qubits, I think that shows a really interesting forward route of the potential towards real expression of...

commercial quantum advantage within our lifetimes. Yeah, exactly. Yeah.

Sebastian Hassinger (14:55.158)
Yeah, hopefully. I plan on living a long time. But yeah, I think that's exactly right, Kevin. I mean, it's really, I mean, the history of error correction in quantum computing is fascinating in and of itself. Obviously, error correction factored in really strongly to the early days of classical computing and things like just repeating values for multiple bits

Did I get five of the same value in a row? If I got one or two different, I would still count the majority as my value. Simple parity checks and things like that really don't work in a quantum regime.

Kevin Rowney (15:27.709)
Yes.

Kevin Rowney (15:35.192)
Yeah, yeah, that's all easy to do when you can easily copy the contents of one register to another. That's exactly right. Yeah, but that old no cloning theorem from quantum computing, yeah, it tells a stern story. There is no quantum circuit, right? They can directly copy from one state psi to a duplicate state psi. So yeah, you can't even look at it to copy it, let alone do any measurement if you want to avoid collapsing.

Sebastian Hassinger (15:40.854)
That's right. Or just look at it. Like... Uh huh.

Sebastian Hassinger (15:52.546)
That's right.

Sebastian Hassinger (16:00.823)
That's right.

Sebastian Hassinger (16:04.554)
Yeah. And in fact, I mean, you know, when, when sure, uh, you know, unveiled the, the factoring algorithm, um, there was, you know, initial sort of shock and awe that he had, what he discovered. And then, and then the immediate response was, yeah, that'll never work because you need fault tolerant quantitative qubits and you can't error correct qubits. And of course, Peter.

Kevin Rowney (16:16.028)
Yes. You've done this amazing thing. Yeah.

Kevin Rowney (16:27.224)
Which for a while that was a devastating criticism, right? But then they repost.

Sebastian Hassinger (16:30.226)
Yes. The same year though, within a year, Peter published the first error correction algorithm, which is an astounding feat. That was one hell of a year that sure had. Yeah. So the Shor algorithm essentially spread the information out across a number of qubits and often referred to as ancillary qubits so that in aggregate there were ways to monitor

Kevin Rowney (16:38.428)
Man.

Harry Rappost, yeah, no doubt, no no.

Sebastian Hassinger (16:59.086)
bit flips and phase flips of the original value without affecting the original qubit. So the qubit value would be continuing even if you had to destroy some of the ancillary qubits and then recreate those as a distributed store of the information, which is a really interesting kind of approach to get around those constraints.

Kevin Rowney (17:00.924)
Yes.

Kevin Rowney (17:05.254)
Yes.

Kevin Rowney (17:22.424)
It is, it is. And that very innovation, that sort of whole idea of the Ansila qubit, I mean, that's now widely represented in many quantum computing architectures where there's this whole pool, right, of standalone on the side ancilla qubits that are brought into the mix, used as needed for assistance on error correction, error mitigation, temporary output results. And then you put them back in the pool and reset them and bring them back in.

Yeah, that was a really important prequel to a huge family of algorithms.

Sebastian Hassinger (17:57.39)
That's right. Yeah. And, and Shor's error correction approach, it's been modified a bit here and there. There's, there's a bacon Shor variation that Dave Bacon contributed to. I think there's others as well, but that was the basis. I believe certainly the, um, uh, the demonstration that Ken Brown's group did a couple of years ago, I think now, um, standing up a single logical qubit, um, and also.

I believe in part what Quantinuum did, no, sorry, those were color codes. So after Bacon-Shor and the Shor approach to error correction, there has been this, as with everything else in quantum, sort of expansion of the varieties and types and approaches to solving the same problem, essentially, to building logical qubits.

Kevin Rowney (18:48.112)
Yes. Yeah. And I know you know the history here well. So it's a, it, there's probably, God, there was so much rich intellectual history just in this one thread, right? Of, of error correction codes, right? There's that whole breakthrough by Kitaev, right? On the, the toric code, right? I mean, you know, basically quantum circuits interconnected in the shape of a, of a torus, right? A donut. You, you, you take a, essentially a square grid and connect opposite

Sebastian Hassinger (19:03.351)
That's right.

Sebastian Hassinger (19:14.257)
Yeah.

Sebastian Hassinger (19:17.75)
That's right. Yeah, it's actually, if I remember correctly, the original paper that Kitaev wrote was topological information systems. So he introduced the idea of a topological qubit at the same time as the surface code, which is topological mathematics in the form you just described for error correcting of physical qubits.

Kevin Rowney (19:41.948)
So cool. And I guess I think I've got this right at the time of publication. Again, people were just wow. They regarded it as a fascinating theoretical result, but we were, we were so far. Exactly. So far, we're any kind of engineering, right? That would render this as a real world thing, but here we are.

Sebastian Hassinger (19:53.422)
Probably impossible to implement.

Sebastian Hassinger (20:01.146)
Yeah. So yeah, in the last year, the Google team has demonstrated surface codes with a break even. So above the error correction threshold. And then of course, the Lukin and Vuletic team at MIT and Harvard, we just talked to Vuletic last week, or last episode, that was using surface

Sebastian Hassinger (20:30.582)
two huge steps forward for implementing what, as we were saying, was previously thought to be impossible to actually realize physically.

Kevin Rowney (20:41.16)
There it is. And both crossing this key threshold. And I guess that's another important, really a foundational element of the whole intellectual history behind this domain is, of course, this profound theorem by Dorit Aharonov. We did that interview with her some months ago, but that key theorem essentially indicating in very rigorous terms, the minimum standard of error commission.

Sebastian Hassinger (20:55.135)
Yeah.

Kevin Rowney (21:07.98)
on physical qubits that would, if you can reduce them to a threshold, achieve an ever increasing accuracy of logical qubits.

Sebastian Hassinger (21:17.642)
Right, it boiled down to essentially being able to correct errors faster than they were being generated.

Kevin Rowney (21:23.396)
Yes. Yeah. I cringe at my level of rigor and what I just said as the summary of Dorit's fantastic paper. So if she's listening, apologies. Yeah.

Sebastian Hassinger (21:31.177)
Yes. What really stuck with me was the language she was using sounded almost like phase change. Remember that the, uh, she was saying past a certain point, it's almost like a different form of, and it was, she was talking about information, but it sounded almost like a phase change from one form of matter to another. It was really striking.

Kevin Rowney (21:39.909)
Yeah, yeah.

Kevin Rowney (21:47.537)
Yes.

Kevin Rowney (21:53.218)
That was one of our cooler podcasts, I thought.

Sebastian Hassinger (21:55.11)
It really was. And of course, you know, there's been, I mentioned color codes. There's also been variation on the surface code called Gottesman, Kitaev, Preskill, who another guest of ours, John Preskill, contributed to. And then more recently, again, another big step forward in the last few years, but in terms of realizing this was LDPC or low density parity codes used in a quantum setting, which

Kevin Rowney (22:09.498)
Hm.

Sebastian Hassinger (22:24.502)
These go back to 1960 and were originally proposed for use on noisy communication channels. And as I understand, it's iteratively encoding and decoding. So it's almost nested parity checks essentially in a classical setting. But a number of years ago, Sergey Bravyi, who's at IBM Research started looking at applying them to quantum information.

And this past year in late summer, I think it was either August or July or August, they posted a paper to the archive, the IBM research team led by Bravyi about using LDPC on a bi-planar chip. So two physical chips bonded together with a total of 288 physical qubits resulting in 12 logical qubits. Which is quite a, I mean,

What was interesting to me was, A, it was a very nice ratio. That ratio of 288 to 12 is quite a bit better than other superconducting implementations of surface code, which are typically in the, you know, maybe in order of magnitude higher in terms of physical qubits to logical qubits.

Kevin Rowney (23:39.8)
And it was it was for equivalent error rate or?

Sebastian Hassinger (23:42.95)
It's distance 12, so pretty substantial. It's pretty robust. And the other thing was how much, for a theory paper, how much it described what the physical implementation might be. I mean, they described the chip topology to a certain degree of detail, which made me think that probably the fab at Yorktown Heights is working on this right now, which is exciting. You know, that's great, because a lot of these

Kevin Rowney (23:44.668)
Yeah. Aha.

Kevin Rowney (24:04.78)
If they're talking to a fab right now. Yeah. Yes.

Sebastian Hassinger (24:11.986)
Over the years, a lot of these, as you said before, a lot of these have been theoretical proposals without any real path stipulated for a physical manifestation. So it's nice seeing a breakthrough paper that's also saying, and here's how you could do this. Quite exciting.

Kevin Rowney (24:23.716)
Hahahaha!

Kevin Rowney (24:28.784)
Yes. Yeah. Wow. So cool. Yeah. I mean, there's this whole pile of results quite recently. So I think that's the, yeah, I'm sure it's clear already. This is the major theme that we want to trace going forward is watching these for new evidence of new jumps forward on the support for these logical qubits, leading to higher and higher accuracy, greater and greater T1 and T2 time. Just a lot of interesting room for optimism here.

Sebastian Hassinger (24:47.842)
That's right.

Sebastian Hassinger (24:57.61)
Yeah, yeah. And you know, it's worth mentioning to revisiting the last episode again with Professor Vuletic. You know, why were we so struck by the result of that paper, which was 48 logical qubits made out of 280, I think, atoms. The reason is because about 50 qubits is, perfect qubits, let's say fault-tolerant qubits,

is about the limit of what you can classically simulate. So it's a... That's right.

Kevin Rowney (25:32.316)
Yeah, so we're approaching some sort of like threshold of perceived at least supremacy. Yeah, that's right. That it'd be, it's competition feasible to have a fully entangled matrix of 50 qubits. That's a very challenging classical simulation to run. I mean, still I acknowledge the Aaronson skepticism on that one, I mean, but wow, this, it does look like we're about to cross a threshold.

Sebastian Hassinger (25:45.186)
Right.

Sebastian Hassinger (25:53.27)
Yeah, well, and I think the skepticism is warranted just because the paper is not, it's not fully operational logical qubits, right? They, as Vultic said, they sort of, they set up the logical qubits and then they were able to measure the error syndrome, but they didn't go through to the next step, which is correct and adjust and continue, right? So it's only step one of a process that's gonna need to be iterative and performant.

Kevin Rowney (26:02.725)
Yes.

Kevin Rowney (26:16.252)
Yes.

Sebastian Hassinger (26:22.806)
which is still a significant set of challenges.

Kevin Rowney (26:25.476)
Yeah, but even with caveats, I mean, still, I mean, that was another one of our cooler, I thought, podcast interviews. That was just such a good time. Such interesting results from that team. And I don't know if anybody's listening and seen the little videos online, but to sort of watch the parallel dance of these qubits interacting with these like en masse parallel operations of an array of qubits doing a C-not against another array of qubits. Just amazing stuff, right?

Sebastian Hassinger (26:30.964)
Oh absolutely.

Sebastian Hassinger (26:34.655)
Absolutely.

Sebastian Hassinger (26:42.519)
Yeah.

Sebastian Hassinger (26:53.462)
Yeah, yeah. Yeah, it's really cool and it's also, it's another sort of major theme that I wanna continue to explore, which is the atom-based systems. We've talked to, you know, Dana Anderson from Infleqtion, we talked to Alex Keesling, now we've talked to Professor Buletic, we've talked about trapped ions with Chiara Decaroli versus the electron-based ones, let's say.

Kevin Rowney (27:10.888)
Yep.

Kevin Rowney (27:22.417)
Yes.

Sebastian Hassinger (27:22.622)
the superconducting circuits, it's really fascinating to me that the stability, it seems like the stability of the atom-based systems are giving them sort of a leg up in terms of implementing these longer running or longer, you know, systems are capable of doing longer calculations. But on the other hand, superconducting has such a clear advantage for, you know, wall clock speed, right? And so resolving that, I mean,

Kevin Rowney (27:41.092)
Yes.

Kevin Rowney (27:47.816)
Sure.

Sebastian Hassinger (27:51.454)
If you get a hundred or 200 logical qubits in a neutral atom array, right. But you have to, you know, swizzle everything around with tweezers and stuff. Is that going to produce a competitive, you know, or a performance advantage over classical computing, or are you going to need the speed of superconducting computing or quantum computing? I'm not sure.

Kevin Rowney (28:05.904)
Yes, yeah.

Kevin Rowney (28:11.432)
Sure, right. And then still the trapped ions, diamond vacancies, there's so many other architectures out there. And I hope we don't sound like we're favoring, you know, one thread of research versus another. I think there's some really great active and but professional and friendly rivalries between these camps. And so we don't want to like throw shade at any one particular direction. I mean, there's all of these have got immense potential. Yeah, but it's just great to sort of see these different competing approaches.

Sebastian Hassinger (28:14.654)
Mm-hmm. Yeah.

Sebastian Hassinger (28:19.969)
No.

Sebastian Hassinger (28:28.342)
Absolutely.

Sebastian Hassinger (28:36.129)
Yeah.

Sebastian Hassinger (28:40.17)
Yeah. Well, and I think if it hasn't come across yet, it would be surprising, because I think our listeners know that we share intense enthusiasm for this space. You were saying, I mean, every episode I brought up, you said, that was another great episode. We did. I... No, fantastic.

Kevin Rowney (28:40.208)
Raise the bar for each other and onward we go.

Kevin Rowney (28:53.453)
Ha ha

Kevin Rowney (29:00.429)
I'm not just saying that for marketing, this is a really good time for me. I don't know.

Sebastian Hassinger (29:05.258)
I mean, I have enjoyed every single one of the conversations that we've recorded. Absolutely. So, yeah.

Kevin Rowney (29:09.8)
Yeah, so yeah, if we left anything out in our year long review, please forgive. Cause we, uh, geez, every single one was, uh, was a joy to be frank.

Sebastian Hassinger (29:19.215)
Absolutely. So yeah, I mean, I think that's, that's kind of the, the overview I was thinking about presenting Kevin. I mean, um, you know, I think looking ahead, we're going to continue to try to pick, um, guests who can tell us about their efforts to, to push that, that line forward towards, um, better and better results, either.

Kevin Rowney (29:39.388)
That's right.

Sebastian Hassinger (29:42.506)
you know, higher fidelity or larger systems and you can, can simulate otherwise classically or potentially things that are actually operating faster than you can do classically or both. And I think that's, that's really exciting for the year ahead.

Kevin Rowney (29:54.469)
Yes.

There it is. I think it's such a gigantic theme and we will continue to touch on that in the year going forward. I think also you've helped me realize that there's this whole, I think, under acknowledged trend as well that we'll cover more and more on quantum sensing, right? I mean, could there be at some point in the near future, brand new breakthrough technologies, the likes of which we can't really conceive of yet around sensors that use some sort of short quantum computation to come to.

Sebastian Hassinger (30:12.13)
Mm.

Sebastian Hassinger (30:23.18)
Right.

Kevin Rowney (30:26.168)
I don't know, some really interesting engineering outcomes. So that theme too, I think is under appreciated within the industry.

Sebastian Hassinger (30:27.863)
Yeah.

Sebastian Hassinger (30:32.674)
I agree. I agree. It's funny because I think in large part, it's a category that's benefiting from the engineering advances that are primarily seen through the lens of computing, but there's no reason why these devices can't be put to other, I mean, these are incredible quantum technologies generally, so there's bound to be other applications as well.

Kevin Rowney (30:53.232)
Well, there it is. So I think that's a good wrap up there. I mean, really, if anybody's listening, they're still, to this day, skeptical about QC. I think paying close attention still to this podcast and how there's the fact that numerous national labs making significant commitments in this area, big breakthroughs in the support of logical qubits, numerous research centers that have booted up all over the world. VC dollars still seem to be flowing.

And still there's that quantum sensor trend that I think is an underappreciated trend. I think across the board, there's many reasons to consider this to this day, a vibrant, active and fascinating space.

Sebastian Hassinger (31:35.874)
Absolutely. Now you are marketing for the podcast.

Kevin Rowney (31:40.831)
Just by natural enthusiasm. I've had a bit too much caffeine this morning, maybe. I don't know.

Sebastian Hassinger (31:44.25)
Me too. So yeah, we'll continue to try to crank out episodes every two weeks. We've had a couple of hiccups in the past with hiatuses that were extended by either the end of the academic semester or year, which often causes challenges around booking and also illness. We both got sick in January, so that slowed us down. Yeah. Mine was RSV. I went...

Kevin Rowney (32:06.94)
Parallel cases of COVID, good times. Oh man. Oh, okay. I didn't know. All right. Yeah. Moving on.

Sebastian Hassinger (32:13.214)
Yes, I'm always a train setter. I'm done with COVID. Yeah. But you know, it also bears mentioning if anybody would like to be a guest or would like to suggest a guest, I'll put our contact email in the show notes along with all the links of the papers that we refer to on this episode. And we would love to get suggestions from the audience or even topics open to everything.

Kevin Rowney (32:30.714)
Great idea.

Kevin Rowney (32:39.228)
Sure. Yeah. No doubt.

Sebastian Hassinger (32:43.086)
Thanks Kevin.

Kevin Rowney (32:43.964)
Thank you, see you man.

Creators and Guests

Sebastian HassingeršŸŒ»
Host
Sebastian HassingeršŸŒ»
Business development #QuantumComputing @AWScloud Opinions mine, he/him.
A look back at quantum computing in 2023 with Kevin and Sebastian
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