The New Quantum Era

Sebastian Hassinger: 00:01

The New Quantum Era, a podcast by Sebastian Hassinger.

Kevin Rowney: 00:06

And Kevin Rowney

Sebastian Hassinger: 00:31

Welcome back to the podcast. Sebastian here with you for another solo episode. Today, I'm coming to you from the IEEE International Conference on Quantum Computing and Engineering at the Palais des Congres in Montreal, Quebec, Canada. This is a excellent conference, put on by IEEE Quantum. IEEE, of course, being Institute of Electrical and Electronics Engineers, which is a professional association, formed in the sixties, I think, that covers a bunch of different areas within the field of computer science, computer architectures, system architectures, electronics engineering, that sort of thing.

Sebastian Hassinger: 01:10

They recently formed IEEE Quantum. They've been putting on this conference for I think this is the 4th year. They started during the pandemic, if I recall correctly. And it's a really interesting, program because they're purposefully bringing together the sort of, ingredient fields that are coming together to to create quantum computing. So physicists, you know, quantum information scientists, information science specialists within computer science, computer engineering, system engineering, and in particular, high performance computing and supercomputing, specialists and communities.

Sebastian Hassinger: 01:48

And that's really interesting because looking forward, you know, there's there's physics challenges that still face us. There's engineering challenges, facing us, fabrication, etcetera. However, if we anticipate having quantum computers that actually are useful for certain purposes, the next set of challenges will be deploying those devices in useful solutions. And those the solutions are going to include, and Kevin and I have spoken about this in the past, you know, classical compute, resources in addition to quantum computing resources. And making all of those heterogeneous resources work, seamlessly is going to be really important because there's no point in in gaining some kind of performance advantage from a QPU if then the integration with the CPUs sort of, you know, evaporates that advantage and ends up being the same same overall system performance.

Sebastian Hassinger: 02:45

And so that's a a really strong topic within the Quantum Week, talks and even there's forming, birds of a feather sort of, interest groups. And I think there's even progress and and discussions of sort of eventual standards around, how to integrate quantum and classical compute resources, which I find really fascinating. And today's guest actually is really directly involved in those efforts. He's Martin Schulz. He's a professor at TU Munich or Technical University of Munich, and also on the board of directors of the Leibniz Supercomputing Center.

Sebastian Hassinger: 03:24

And in his roles at TU Munich and at, LRZ or the Leibnitz Supercomputing Center, he's really leading a set of efforts around this kind of, effort to define how quantum and classical resources are gonna be integrated into, meaningful and productive solutions. So we grabbed a room that was very, kindly provided by the IEEE Quantum, Week organizers, and we had this following conversation, which I thought was really interesting. So let's take a listen. I'm here with Martin Schultz. I'm at, the we're at the IEEE Quantum Week in Montreal, Canada.

Sebastian Hassinger: 04:40

And, we were gonna have a conversation about the work that Martin has been leading, in, his capacity as as sort of one of the leaders of the, you know, Quantum Valley effort. So, Martin, tell me about the like, what was the sort of initial impetus that that, caused that sort of set of activities to start?

Martin Schultz: 04:59

So the Munich Quantum Valley is a is a large, effort across multiple institutes, multiple universities. So it includes Fraunhofer Max Planck, TU Munich, where where I'm located, the, Ludwig Maximilians University, the ELLEN University, DLR, and then also the Bavarian Academy of Sciences, which includes the the compute center as well in Munich. And so this is a large, large effort that was born out of, the Bavarian high-tech agenda that's pushed by the state. And they kind of wanted to establish the quantum science in Bavaria with a very large grant that was then supplemented with other grants, also from the federal level, from the EU level. So it's a lot of stuff that that came together, and it started from the physics side, like most quantum projects started, with the idea of having multi modalities being developed in in Munich or the Munich area, and pushed it up.

Martin Schultz: 05:45

And then the question came, how do we connect this to the world? Right. We make this available? What do we need, in addition to just a pure hardware? And that's where we started talking more and more about software.

Martin Schultz: 05:55

And to be honest, in the beginning, it was a little bit of an of an afterthought, almost because it was a pure physics. Right. I mean, most of these projects are in

Sebastian Hassinger: 06:01

the beginning.

Martin Schultz: 06:02

And what came clear very, very quickly that we need more

Sebastian Hassinger: 06:05

Right. Than

Martin Schultz: 06:06

that. And so we started building a software stack, connecting it to, to to a web portal that can we can access things that we know for most quantum systems. But then very early on, we already thought, well, this is the web portal alone won't help us that much. We need to do this in a way that we can, support a wider workload, and quantum will be always very specific. I mean, we had a conference.

Martin Schultz: 06:28

We heard this in several talks as well. It's a very specific thing, which it hopefully can do very, very well, but we need to have the rest connected to it. So hybrid workflows Right.

Sebastian Hassinger: 06:36

Need

Martin Schultz: 06:37

to connect it into high performance computing, HPC. Right. We heard this morning also in another keynote a lot of connection also to AI. Right. And then how can we tie these three things together and make them really work together?

Sebastian Hassinger: 06:47

Right.

Martin Schultz: 06:47

So quantum Quantum and HPC integration was high on our agenda from the very beginning on. We started with activities there very early on with MOF sessions at various conferences. We have a workshop now that's in its 4th instance on bringing people together. Right. Also, that started, of course, very slow because it's not it wasn't people's forefront in the beginning Right.

Martin Schultz: 07:05

But it's coming more and more. Yeah. And we're really seeing these communities grow together, which is kind of exciting.

Sebastian Hassinger: 07:10

That's very exciting. And do you think in part that perspective came from I mean, LRC is a supercomputing resource that's, very heavily used by the academic community, as well as in collaboration with Industrial R and D, I think as well. Right? There's sort of industrial collaboration projects that go on it?

Martin Schultz: 07:30

So it has. So it has a very, very strong and strict public mission at the moment. So the projects have to be public and basic research. Industry can we're working with industry in collaborative projects. It has to be always an academic partner with it.

Martin Schultz: 07:42

It has to be a funded project from the outside. But then we have some industry collaborations Right. Of as well. That's actually one of the challenges we're looking at right now. How can we open this up to have more industry involved?

Martin Schultz: 07:53

Because we have requests from industry. Right. We wanna try this out. We wanna wanna wanna get things going. We wanna see how much does does works for us.

Martin Schultz: 08:01

That's actually kind of a, a challenge right now. How can we fit? Not so much a technical challenge as a political and Right. Societal challenge. How can we make this work, and what can we get the right bylaws in place to do Interesting.

Martin Schultz: 08:12

To do this. And we're pushing in this direction. Yeah. You

Sebastian Hassinger: 08:14

know? No. I mean, it's what I find fascinating is, you know, you have sort of you're thinking over the horizon of, getting these QPUs to the state that they can actually do useful work. And you're thinking about what does that solution what does that end to end solution look like? And, you know, I think you're not alone in that.

Sebastian Hassinger: 08:34

There's certainly a lot of efforts in the public sector. But in in many ways, I think you've got a head start on everyone. It seems like you're quite a bit, in in further along this road. I mean, you've taken, you've got an operational superconducting device from IQM now, and you actually have running, like, a running pipeline that combines classical and quantum hardware together for at least the, you know, the the obvious use case, which is a variational job where you're, using the 2 in in conjunction. Right?

Martin Schultz: 09:03

Right. And so we we we actually managed to do a first shot between the HPC system and, the the quantum so one of the quantum systems in direct, in in direct connection there. And so we have been getting to this with, kinda, we we have this concept as our quantum team calls this as a data series of hero runs. Mhmm. So we have, like, these goals, these goal posts that they're trying to reach and and and really really shooting for, and they manage to do this connection between the HPC system and the quantum system in a very additional thing.

Martin Schultz: 09:29

Very closely connected, very very integrated. They were just a couple of couple of meters apart from each other, basically, at this point, which is kind of the the exciting part.

Sebastian Hassinger: 09:37

Yeah.

Martin Schultz: 09:38

But, yes, we've been trying to do this for, we've been working towards this goal for for a while, and to be honest, also, the the emphasis has shifted. Right? In the very beginning, it was, how can you take a system and put it in a data center? Right? How do you even hook it up?

Martin Schultz: 09:50

Right. Or how do you What kind of environment do you need? How do you deal with the false floors which we have in centers, which is terrible for quantum systems because there's Lots of vibration. Leverage.

Sebastian Hassinger: 10:01

Exactly. The opposite of what, what a classical system is about.

Martin Schultz: 10:05

Exactly. And so also the, and also then even if you have it on a floor, on a on a solid floor, how do you put in together then the the right water? They need slightly different water water chemistry, different water temperatures. How how they get the right power together, how they hook the the the networking together. We we focus at the beginning very much on the on the hardware side just to get this thing going, and then we had some duct tape or software in between them just to make it work.

Martin Schultz: 10:31

And there was a very early project that was funded by the Federal Ministry for Research, and there, we actually didn't buy a quantum computer. We actually worked with IQM on buying all the individual pieces and putting it together on our own. There was a very strong collaboration Right. Where IQM helped us really put these things in the right place, but our team actually worked with them hand in hand to install all the microwave cables and all and all these kind of things. We learned basically how this works.

Martin Schultz: 10:55

Yeah. Right?

Sebastian Hassinger: 10:56

That's such a valuable set of experiences, and really, there's no substitute for putting one of those devices together. They're they're kind of a magical combination of science and technology right now.

Martin Schultz: 11:07

Right. Exactly. It's really tough. And so we learned a lot in in this part of the project, and by now, the more newer systems we, quote unquote, buy. The hardware, of course, is not that easy.

Martin Schultz: 11:17

It's not like Yeah. You buy a rack, plug it in, and then run it. Yeah. But there's still there's more like of of a of a consumer seller relationship. Right.

Martin Schultz: 11:23

A vendor relationship. A vendor relationship. Now, we bring these things in and put them up, but we still have all the expertise from back ends. We know what they're bringing, and we understand that the technology. And so as part of that, we we have now actually 3 systems running.

Martin Schultz: 11:38

There's one production system running. That's the one you were referring to. It's a 20 qubit system called QXA. Right. There's a German demonstrator project, and we have 2 r and d systems also in in our r and d lab, with the Quantum Integration Center that the local team has been has been standing up and and maintaining.

Martin Schultz: 11:54

It has been really a real huge asset to have, like, the systems right there. There's an HPC system right next to it as well. We can still plug and play. There's not a production system Right. In that sense.

Martin Schultz: 12:05

Is that also superconducting? So we have 2 superconducting r and d systems in there, 1 5 bit, 1 20 qubit. They're actually in the same fridge. So they're we're using them in the fridge as more as racks at this point and not as separate systems. That's cool.

Martin Schultz: 12:19

I think this is the trend where we will have to see more and more. And then we earlier this year, beginning of the year, we also, got in an ion trap system. So we definitely wanna look for multiple modalities.

Sebastian Hassinger: 12:31

Is that from an existing vendor, or is that a

Martin Schultz: 12:33

Yes. There's an there's a system from from AQT, Alpine Quantum Computing, which are very close partners with the Right. The new quantum valley. I mean, they're just hour and a half away. So this is kind of the nice thing in the sense.

Martin Schultz: 12:43

That kind of rounds off the modality aspects of the the new quantum valley, which was always superconducting ion traps, and then also neutral atoms, which we also have a working relationship with a new vendor that would this is a spin off of the Max Planck Institute in Munich. And they're also on track installing a new 2 custom system at the compute center as well.

Sebastian Hassinger: 13:04

And are these systems sort of you call them r and d systems. Are are you is there sort of, whatever access into the the system itself? So, you know, some vendors, their system might be treated as a black box and you sort of you can send your circuits and get your results, but you don't really know what's going on inside. Is this more of an open system to sort of mirror the open software, development efforts that you're doing as well?

Martin Schultz: 13:29

So that's a that's a little bit longer story. So it's a yes or no. But like it always is. Right? Yeah.

Martin Schultz: 13:35

In the beginning, of course, when we set this up, we started working with the vendor software stacks because that's the the old team that was there, and we started looking in them. And also when vendors were very early on on this as well, so we had a lot of conversations on how these things could look like. We tried to understand each other's software stack. That's why we really focus still on the hardware and how to bring the hardware and set it up. Since then, we have shifted the focus since I don't wanna say, quantum's got commodity, but it's that we have these vendor relationships.

Martin Schultz: 13:59

There's a a service. Code. There's an agreement. When you bring this in, there's a contract. There's an acceptance procedure for these things now.

Martin Schultz: 14:07

And then their hardware is there, and we know how to hook this together on the other networking side now. So the focus shifted really on on the onto the software now to really make these systems efficient, workable. And this is gonna be the huge work going forward to kind of get these HPC these HPC QC integration going. Right. Without the software efforts, we we won't get there because we really have to connect these these pieces here Yeah.

Martin Schultz: 14:30

In an efficient way that's easy to use, that is also seamless, that requires work on the quantum side, but also on the HPC side to really have this this integration part. And there, we kind of have, like, a stepwise approach because we don't wanna there's no way to to to kind of run ahead here. We're working with the vendor software stacks for now. Mhmm. They're working on special access nodes, which are already tightly integrated into our HPC systems.

Martin Schultz: 14:53

And then we have our software stack basically on top of that. Mhmm. And then back end connectors into their commercial software stack.

Sebastian Hassinger: 15:00

I see.

Martin Schultz: 15:00

I see. And that is kind of a a trade off for now because that still leaves a lot of work to do on the vendor side, and then we have our stack on top of that.

Sebastian Hassinger: 15:08

Right.

Martin Schultz: 15:09

And the idea now is to work with the vendors to slowly migrate these heavy vendors to act into something very thin and low level and push this over to the other side.

Sebastian Hassinger: 15:17

Interesting.

Martin Schultz: 15:18

And that stuff is working. A lot of these contracts that we have, when we buy these systems, have in there that this transition has to happen. And, you know, the vendors we're working with are very open for this. We have regular conversations on this. They're they're interested in having an interface into the compute center that is standardized.

Martin Schultz: 15:35

So they can actually sell a system, and everybody can just plug it in and is happy with it. Yeah. I don't think they want to maintain their own soft stacks and the infrastructure.

Sebastian Hassinger: 15:43

I always say, use your PhDs to work on the cubits. That's the hard part, not the classical software stack. We have people that do that. Those are solve problems.

Martin Schultz: 15:52

Well, it's also the hard part. Right? But but in fact, for for a different group of people, you're absolutely right.

Sebastian Hassinger: 15:57

This is a different expertise there. Businesses writing code.

Martin Schultz: 16:01

I won't comment on that.

Sebastian Hassinger: 16:05

Yeah. So are there existing frameworks or code bases that you've been leveraging? I mean, I know, you know, Kik, Cubic, Kibo, those are all sort of, they have control platform, open source control platforms, but also Kibo's got a whole set of open source libraries. There's, you know, there's there's open source projects from, the Unitary Fund, for example. So there is sort of a it's a small but, growing community of existing open source technologies.

Sebastian Hassinger: 16:36

Have you used any of those in your development?

Martin Schultz: 16:39

Bits and pieces. So we we're starting to bring things in where it makes sense. The the base infrastructure that we have, we're actually leveraging open projects from the HPC community or from the classic compute community.

Sebastian Hassinger: 16:51

Slurm?

Martin Schultz: 16:52

We we we do leverage Slurm. That's a separate story we can come back to. We're thinking whether Slurm is sufficient for us or whether we need some more or not.

Sebastian Hassinger: 16:59

I just like to say the word Slurm. It's a funny funny word. I don't know.

Martin Schultz: 17:03

Well, I don't know if you like this. The other ones we're looking in is a is a skater called Flux Mhmm. Which is out of, out of the DOE Labs. Okay. Livermore.

Martin Schultz: 17:11

Yeah. So Flux or Slurm? We'll see. Yeah. But, yeah, we we need to do more more more scheduling approach.

Martin Schultz: 17:17

It kind of allows us to do this integrated scheduling, but that's an open question of where where we wanna go. And there, we're watching very closely other software projects on the pure HPC side

Sebastian Hassinger: 17:27

Right.

Martin Schultz: 17:27

That need similar techniques, similar software components. And we we don't wanna do anything separate. We wanna kind of fit into the ecosystem. Yeah. Yeah.

Martin Schultz: 17:34

Yeah. So there's a tight relationship there to other software projects as well

Sebastian Hassinger: 17:38

to make this work. I mean, things like, scheduling, those tend to be more batch or, you know, less performant, dependent, sort of like it's queuing up and using a resource when it becomes available. You also mentioned AI, and also, obviously, the the whole talk of, of state preparation or error mitigation or error correction, all of those need, I think, really, really high performance, and tight integration between classical and and quantum. So you don't incur overheads that eliminate whatever kind of advantage you might get from the quantum algorithm. What what sort of, integration strategies are you do you have in mind for those sort of tighter I mean, more demanding kind of use cases?

Martin Schultz: 18:21

Yeah. So there's there's gonna be different time levels and and and time loops, basically. As you said, there's just different granularities that that we need to have. And so from the the very coarse grain, we're gonna start with the job scheduling systems where you said you want a quantum system. You wanna have access to that, use prediction mechanisms that allow us to predict when resources are free and how can we overlap Right.

Martin Schultz: 18:42

Of different jobs. And then there will be kind of an intermediate level scheduler. That's kind of at least our vision right now, which then actually does the decision once there's a kernel to offload, which system actually does it go to, where is where the free resources in that sense. And then, you're obviously right, then there will be another level because we think of a hierarchical multilevel scheduling, where towards the device side, you will have these very tight feedback loops.

Sebastian Hassinger: 19:04

Right.

Martin Schultz: 19:05

And the question is how much we can, how tight are these loops. Whereas in some technologies like superconducting, we may not be able to do this purely in software. You have to push things in in hardware because the loops are so tight. Yeah.

Sebastian Hassinger: 19:18

Yeah. Yeah.

Martin Schultz: 19:18

Other technologies like ion trap, they're a little bit slower and have other qualities instead of that, and then we may be able to bring it into software.

Sebastian Hassinger: 19:25

Right.

Martin Schultz: 19:26

And our goal is to develop the software stack in a way that it actually can run on the HPC system itself, and connect the HPC system directly to the control.

Sebastian Hassinger: 19:34

Like making RPC calls or something too.

Martin Schultz: 19:37

Perhaps even lower weight than that to really directly drive this from there. And then you can actually run a feedback loop directly into your HPC system, where you have the resources. We also can use GPU acceleration or FPGA acceleration on on the node itself. Interesting. And for signals like Iron Trap, I think this will allow us to bring us a lot of stuff in.

Sebastian Hassinger: 19:56

And neutral atoms as well.

Martin Schultz: 19:57

Neutral atoms as well. Exactly.

Sebastian Hassinger: 19:58

The lower clock speeds. That makes a lot of sense. But you're right. Something like superconducting, you know, you're probably looking at something like, you know, quantum machines DGX or whatever, where there's a GPU that's actually part of the control system that can do things like error correction at a speed that makes sense for for that.

Martin Schultz: 20:15

But even then, you may need some other intermediate loop, kind of, for some kind of conditional executions, and things like that that you want between the the device selection and this low level part. So we have, potentially, another level of of scheduling in between here. So this hierarchical scheduling that really informs from the all over from the grip from the coarse grain to the fine grain and has this this common overview, I think, will be really a key technology. And that some of our our teams are working on that right now.

Sebastian Hassinger: 20:40

That's really great. How how large is the effort? How many people are are actually writing writing code with you?

Martin Schultz: 20:47

So this is, again, a a very difficult question to fully ascertain. The whole quantum valley is about, 3, 350 people working on it, but that includes all the physics parts Yeah. As well. The software in total, I would say, is about 30, 35 LTEs.

Sebastian Hassinger: 21:04

Significant Yeah. Open source effort.

Martin Schultz: 21:06

It's and there's a large part in the, in the compute center at LRC. There's a special team, the, the quantum computing department, which has these people and which work directly on the machines and which are also a little bit more geared towards the software development. And then we're working with the university side, we're a little bit more the research y side is. So we're finding this avenue of how to take research, harden it, and then and then put it put it into the stack.

Sebastian Hassinger: 21:30

And is there any thinking about, like, integration of cloud based systems, for example, for, you know I mean, in classical HPC, there's an idea of bursting out to the cloud if you need additional capacity temporarily. Is there sort of a similar kind of thinking around maybe a specialized QPU for some aspect of the of a of a workload in the future, obviously, when these things can do productive work? Is there kind of that that thinking as well, that that, remote, or cloud based resource?

Martin Schultz: 22:00

That is possible. So the FOBSTA stack itself as well, it'll be flexible as modular as you can plug in different components. And at the end, there's a series of back ends. Mhmm. And the it is also not only intended for us in Munich.

Martin Schultz: 22:13

We would install this on the HPC system, as I mentioned, to have the stack running on the HPC node itself, but that's not a must. You can run the same stack also as a cloud service or on a separate system if you want to, depending on what your what your compute center setup is. And one of these back ends could also be a remote back end Cool. To to another system Yeah. If that's the setup you want.

Martin Schultz: 22:34

And you you can also mix and match that, obviously.

Sebastian Hassinger: 22:36

That's great. Yeah. I'm just imagining because, you know, I think that we're going to see probably more diversity in hardware efforts in the future rather than less because we're still in this very exploratory stage. So the idea of being able to stand up an experimental qubit or experimental system in a university somewhere and still be able to use it in that integrated kind of of environment is, very powerful, I think.

Martin Schultz: 23:00

So we're actually using this also inside the Munich Quantum Valley, because we said we're developing also the the the the Valley is developing also these these computers. So the Max Planck Institute Right. For quantum opsing is doing neutral atoms. And then there's the Walter Meissner Institute, who's doing superconducting qubits and also experimental qubits there as well. Yeah.

Sebastian Hassinger: 23:18

Exactly. Yeah.

Martin Schultz: 23:18

And those will never be at the compute center because they need it in their labs. Exactly. And so we have already in the stack now to dose 1 connection. We we demonstrated this from the HPC system going to, a small demonstrate at Walter Meissner as well Excellent. Across campus that works.

Martin Schultz: 23:33

Excellent. Don't get all the benefits of the tight loop and integration, but it works in therefore responsible.

Sebastian Hassinger: 23:39

About the efficiency. Right? If you can if you can, not have to replicate all the work you've done to do those integrations and just tie into it. It doesn't matter necessarily that you don't get the performance as long as you're being able to reuse those tools and those frameworks. It's just shortening the time to actually get it into the hands of the people you want to experiment with it.

Sebastian Hassinger: 23:56

Exactly. That's exciting. So, what, like, at what stage do you think you may be making some of this code available to a broader a broader set of of open source communities?

Martin Schultz: 24:09

So we're thinking about it's doing relatively soon. We have a first repository open. To be honest, this is not one of the most exciting repositories yet, but it was a starting point.

Sebastian Hassinger: 24:18

Yeah.

Martin Schultz: 24:19

But we have the idea is to open this up in the in the coming months, I would say.

Sebastian Hassinger: 24:23

That's exciting.

Martin Schultz: 24:24

Particularly focusing first on some of the interfaces that we need. We have an interface definition that works for the vendors, how to hook in. We're working currently with selected vendors to get first feedback, and this is one of the first things we're gonna open up to get broader feedback. Yeah. Perhaps even kind of a sort of a standardization going around it or homogenization, let's say, this way.

Sebastian Hassinger: 24:43

That's what I wanted to ask you is is how do you balance I mean, you need standardization in order to make these types of frameworks work, frankly. Right? I mean, you have to agree on standards, in order to be able to make systems talk to one another. But we're also in this very, early stage where there seems to be far more unknowns than knowns at this stage in quantum computing. So is there is there something in your, architectural design that's sort of baking in that uncertainty?

Sebastian Hassinger: 25:10

That's making it, like, maybe easy to pivot in the future if something new comes along?

Martin Schultz: 25:15

So we're trying to do that. I mean, is this prediction of the future? Why do we don't know? But a lot of us were involved in large software efforts and standard softwares in the past, where we had we've seen how this evolved over time. So, personally, I'm involved in the message passing interface standard, the MPI standard, and I've been leading the the MPI forum for for a while now.

Martin Schultz: 25:36

And we have seen, really, how something that was initially intended to be the right thing has kind of morphed over time with the new technologies. Right. And then we were able to retrofit the standard and sometimes looked a little bit clunky, but it worked fairly well. But I think we have learned in this process as to how do you design something beginning to actually what you just said, allow for these uncertainties Right. To happen.

Martin Schultz: 25:57

And we're trying to learn from this and bake this into the interfaces.

Sebastian Hassinger: 26:00

That's great.

Martin Schultz: 26:01

But then also, to be honest, right now, we are not yet afraid of breaking things as long as we don't break it too much.

Sebastian Hassinger: 26:07

Yeah. Yeah.

Martin Schultz: 26:07

So there's still the we won't release a 1.0 version very much on purpose. It will be a 0.1 or 0.2. Yeah. And by the time you get to a 10, that's where we're gonna start freezing and have a more formal change process in place. But right now, I think it's more of an experimental thing.

Martin Schultz: 26:20

We're getting feedback from everybody, and we're baking this in stone.

Sebastian Hassinger: 26:23

That's smart. That's smart because, I mean, I think, you know, there's potentially more diversity coming down the road in terms of the the execution models and maybe in terms of the intermediate representations. And and certainly, everyone has sort of a general assumption that we're going to be climbing up the abstraction stack. So it may end up not, you know, passing around, gates and circuits, but something higher level abstractions that are are actually how you describe your workloads. Right?

Sebastian Hassinger: 26:49

So that that that flexibility is important,

Martin Schultz: 26:51

I think. And also for the intermediate representation, we're trying to work here also very much with the community in looking into into, standards that exist that have started coming up. So LSE joined, the QIR consortium Yeah. To kind of see there, well, how can we extend this? How can we make this use?

Martin Schultz: 27:08

A lot of our stack for the middle part is already based on QIR or is being transformed to be based on QIR. But then you're right. I think what we have the most uncertainty is actually towards the higher end, towards the abstractions, and nobody knows really what there will be. Right? I think that's that's a really huge push forward right now.

Martin Schultz: 27:25

But then once they can get it into a QIR, and then our compiler can pick it up Right. Then I think we're getting a little bit more on safe orders, and that's kind of the interface we're trying to sell.

Sebastian Hassinger: 27:34

That's another topic, compiling and transpiling. I mean, there's so many differences between it feels like to get optimum performance from any particular piece of hardware, you have to be very, very, conversant in the exact idiosyncrasies of that hardware.

Martin Schultz: 27:49

Right.

Sebastian Hassinger: 27:49

Is your compiler sort of also architected to to, to be extensible so you can have extensions for their their hardware specific? Yeah. Okay.

Martin Schultz: 27:58

Yeah. Absolutely. It has to be this way.

Sebastian Hassinger: 28:01

Yeah.

Martin Schultz: 28:01

So what we are trying to do, and what I think we have, achieved is a core infrastructure

Sebastian Hassinger: 28:07

Mhmm.

Martin Schultz: 28:07

That is completely agnostic of the particular technology in the back, which allows you to basically take a circuit, trans get a circuit through a pipeline, change things on the fly, and at the end, have this interface to the back end part. To be honest, it's not even particularly not even quantum specific. Right? This is a disaggregated accelerator

Sebastian Hassinger: 28:26

Mhmm.

Martin Schultz: 28:27

With just in time compilation Mhmm. Mhmm. With something on the computer science side, we have had Right. Other examples for them trying to retrofit on the data.

Sebastian Hassinger: 28:34

Ways in which we can show the physics community that we we're not, you know, we may not get some of the stuff you're talking about. We're pretty smart too.

Martin Schultz: 28:40

It has to be a give and take. Right? I mean, we have to have to work together in this one. Exactly. And this is perhaps even the been the most fascinating things over the last 2 years.

Martin Schultz: 28:50

If you can come back to the the software in a segment, I just wanna put this in here. In the beginning, when the Quantum Valley started, it was where the the physics community and kind of us on the computer science community trying to talk to each other. Mhmm. Mhmm. There was totally different languages.

Martin Schultz: 29:03

Yes. There was if you talk about a benchmark, they meant something totally different. It would be mainly the benchmark. Yeah. And also there was another idea of this is difficult what you do on the other side as well.

Martin Schultz: 29:12

Right? And in the last 2, 3 years, particularly in this Quantum Valley, where we had everybody on the same campus, we had regular meetings. We had what we call technical exchange meetings. Where we brought people from the physics side, from the electrical engineering, from the computer science, all together into one room. We established a common language, established a common understanding.

Martin Schultz: 29:31

We also it was became clear we all need each other in the right way, and these interfaces has been a step, and that has been the most fascinating part over the last 2, 3 years, that we really grew into one community that can take this on.

Sebastian Hassinger: 29:43

That's the part that absolutely keeps me completely fixated on this this, this industry, because it's exactly that. I mean, it's it's, you know, not only have we rewound the clock to, you know, hand setting registers, like, we're we're right down at the metal. So we get to repeat the entire evolution

Martin Schultz: 29:59

Yeah.

Sebastian Hassinger: 30:00

Of classical computing, which is fascinating in and of itself. It's like, what if we did classical computing over again, but we had, the cloud and open source software and higher level languages already. Right?

Martin Schultz: 30:10

Exactly.

Sebastian Hassinger: 30:11

And then added to that, we also get to have this dialogue with the science community, the physical sciences, in and, you know, opening their eyes to what we can do to help them in along this journey. It's really it's a fantastic set of of challenges and and, you know, sort of intellectual, puzzles to solve.

Martin Schultz: 30:30

Absolutely. It's also why I like this this conference where we are right now, the the Quantum Week, which has exactly this is not a physics conference. It's not a computer science conference, but it really brings people together. And I think, also, that helps establish this common language and the cooperation they need.

Sebastian Hassinger: 30:44

Exactly. You know, and I think the IEEE is very smart. I've seen this conference evolving over the last, whatever it is, 4 years now. It is exactly that. It's carving out that middle space and now, you know, birds of a feather, sessions of the type you described with, you know, Oak Ridge or, other supercomputing centers, you know, all collaborating around these discussions are now leading to, as you said, potentially early standardization discussions, which will just take more of the friction out and more, you know, enable more, innovation on top of the work that's going on.

Martin Schultz: 31:18

Exactly. Yeah. Yeah.

Sebastian Hassinger: 31:19

That's fantastic. So, back to the birds of a feather thing. Do you, do you have sort of a first, international collaborator or partners that, you know, like an Oak Ridge or another center out there that that is, sort of waiting for the release of your software to try to join in to the collaboration?

Martin Schultz: 31:38

So we definitely have interest from partners to to look into this, or most particularly to work on the interfaces with us. Right. So we've been talking to to a lot of partners, including in the DOE, but also in the German ecosystem. Also, the European ecosystem, there's a lot of effort going on

Sebastian Hassinger: 31:53

here as well. PC. Yeah. Yeah.

Martin Schultz: 31:54

On how to homogenize this. Particularly in EuroHPC, there's this and as you know, this program of these first 6, Swanon Computers being seeded by EuroHPC, one will be in Munich in the Leipmann supercomputing center. The tender is still out, so we don't know yet what it's gonna be, but it will be, what we know as superconducting system as well. But there's 5 other centers, and the European team made it very clear we want one software stack, not 6. Yeah.

Martin Schultz: 32:19

And we're working towards that step in regular meetings within Europe as well. And so that's kind of our target for the, for the software stack to to bring out. But then also larger, we're really trying to push the idea of HPC QC integration. There is a working group as part of the IEEE quantum work that we also have above here, and that's that's really very broad. That includes already, Oak Ridge and Los Alamos National Labs, and the and and Icheck, in Ireland.

Martin Schultz: 32:47

Right. Yeah. And then plus, Marshalls from Lazy and then myself from from the 2nd side.

Sebastian Hassinger: 32:51

We gotta get, Iced involved from Japan as well. They're building out their g quads.

Martin Schultz: 32:55

Yeah. So we have been talking to the Japanese community as well. They have been a part of our work. We need to make this international. Right?

Sebastian Hassinger: 33:01

Absolutely.

Martin Schultz: 33:02

And for this working group, the 5 of us are really just the starting point. Yeah. And we wanna broaden this out, and so that's why the BoF session on Thursday here, hopefully, will help to bring in more people. Absolutely. And the idea is, at some point, also start your own own workshop series on this to kind of bring more and more people in.

Martin Schultz: 33:17

Yeah.

Sebastian Hassinger: 33:17

I'll be there. Excellent. Wonderful. Well, thank you very much, Frank. I think this is a excellent effort.

Sebastian Hassinger: 33:23

And I'm really impressed, as I said, when I was at the tutorial last year. And the ideas were great, but I had no idea you're gonna make this much progress in 1 year. So very impressive.

Martin Schultz: 33:34

It was a very busy year, but it was a lot of fun.

Sebastian Hassinger: 33:36

Yes. That's great. Thank you very much.

Kevin Rowney: 33:40

Okay. That's it for this episode of The New Quantum Era, a podcast by Sebastian Hassinger and Kevin Rowney. Our cool theme music was composed and played by Omar Costa Hamido. Production work is done by our wonderful team over at Podfi. If you are at all like us and enjoy this rich, deep, and interesting topic, please subscribe to our podcast on whichever platform you may stream from.

Kevin Rowney: 34:09

And even consider, if you like what you've heard today, reviewing us on iTunes and or mentioning us on your preferred social media platforms. We're just trying to get the word out on this fascinating topic and would really appreciate your help spreading the word and building community. Thank you so much for your time.