Quantum Tools for Government Optimization Part 1

Welcome to “HSDF THE PODCAST,” a collection of policy discussions on government technology and homeland security brought to you by the Homeland Security and Defense Forum

 In this episode, We trace quantum from strange physics to useful tools, highlighting where annealing delivers value now and where sensing may outpace computing. We show how to scope a pilot, measure speed to solution, and decide when classical, AI, and quantum work best together.

 Featuring:

- Prachi Vakharia, President, Washington Institute for STEM, Entrepreneurship and Research 

- Allison Schwartz, Global Government Relations & Public Affairs Leader, D-Wave 

- Dr. Reggie Brothers, Operating Partner, AE Industrial (moderator)

 This discussion took place January 22nd, 2026, at HSDF’s Technology Innovation in Government Symposium

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Transcript

Setting The Stage For Quantum

SPEAKER_02 0:00

All right, so good afternoon. Oh wait, good afternoon. Okay, look, we've got some excellent panelists here, and we really want to engage you. So we need a little enthusiasm here because I think we've got a really interesting topic. I think you'll we're gonna learn a lot together about this. Let's just start at the beginning. So how many of you are familiar with quantum? That is, how many of you know them? Oh good, okay, so Okay, so that's pretty good. That's pretty good. Great. It's good to know. We weren't really sure what the uh what the familiarity would be. So as then for those of you who are familiar, you know that some of the early experiments were like in the late 1800s, right Heimerkurtz, and then uh, let's see, Max Planck in 1900 did some theoretical work, right? Um but the thing that was interesting about quantum is that even the the practitioners they didn't quite get it. Right? They didn't quite get it. So one of the problems with quantum is it's probabilistic in nature, right? Meaning that if you look at quantum, nature becomes random in some sense. So how many of you know what Einstein said about that? Einstein said he does not believe God plays dice. So even though he was one of the initial proponents of quantum, he has some questions about it. Another fundamental property of quantum is something called entanglement. How many of you have heard about some of the work recently in teleportation? That people have talked about teleportation. That's all about entanglement. But what did Einstein say about entanglement? He called it spooky action at a distance. So these pioneers all had questions about understanding this. What's really interesting about Cronum is that it's one of the most rigorously tested uh uh fields of physics of any. It gave us lasers, gave us all kinds of different um uh capabilities. But it's very hard to understand really what's uh what's going on here. So we'd like to do in this talk, because many of you have had some experience, many of you didn't raise your hands. We're gonna start up in the beginning. We're gonna talk about what is quantum, why is this interesting. There's three major areas where quantum is being used. So it's quantum computing, quantum sensing, and quantum communications. We'll be talking a little bit about the first two, that is computing and communic and sensing. Then we'll talk about applications, like why do you care about this? And then we'll go on a little bit further and talk about what are the things, other things going on right now, like education, for example, right? And at the very end, we'll start musing about what the future of quantum is and some research directions. So to get right into it, I want our really these are great panelists. I'd like our panelists to introduce themselves.

SPEAKER_00 2:39

Thank you, Reggie. So my name is Pratchivary. Uh, I wear a couple of hats. Today I'm representing Wiser. So Wiser is the largest quantum training program in the world. Uh, we train over 50,000 students across the world so far, 120 different countries. Uh we receive a government grant, which is from the Department of Commerce, to really focus on the Elevate region, which is in the mountain west in Colorado. Uh, but of course, we support the country nationally. Uh, beyond the education side, we focus on research. So a lot of organizations come to us and ask us well, you know, where do we start with quantum? Uh, one of our most recent partners is actually a company called Vanguard. I think everybody knows uh the investment bank there. Um, and one of the key questions they've asked is look, we've had our AI people try to get them trained up in quantum. They still don't know what to do here. How could we use quantum for the finance sector? So those are the kind of questions we help answer. Allison.

Defining Quantum For Non‑Physicists

SPEAKER_01 3:30

Uh good morning, everybody. Thank you to HSDF for having us and having this important topic discussion today. Um, I'm Alison Schwartz. I'm the head of global government relations for D Wave. It's a quantum computing company that is the computer cloud access full stack hardware, software, professional services. Um, we have both quantum annealers and gate model systems. We announced an acquisition today, and that's important because different problems need different types of compute. Um, annealers are best for optimization, and gate models, you'll need it for anti-corrosive materials and quantum chemistry and personalized medicine, but we'll get into that in the application side.

SPEAKER_02 4:09

Thanks, Allison. So, Allison, I'm going to start with you. So, so you talk with a lot of people writing your business, and I'm sure when you talk to people and you say quantum, some people's eyes open up. Like, what is that, right? So, how do you tell what's the simple story? Like, what is quantum and why should they care about it?

SPEAKER_01 4:23

Sure. Um, so I will first start with I am not a quantum physicist. I'm a political scientist, and I came to quantum policy through FinTech. Um, so quantum is a different type of compute, especially from a quantum compute perspective. We are able to not just look at things that your regular computer looks at ones and zeros as the bits, qubits can look at one, zero, both, neither, all at the same time. My 11-year-old son says quantum is a mother's brain, because I say yes, no, maybe, all at the same time. But it allows us to look at a much wider variety of problem sets and provide an answer back. I will be the first person to say not all problems need quantum. Quantum is not going to replace high performance compute. There is a synergistic relationship with classical compute, high performance compute, AI, and quantum. And we can get into that afterwards.

SPEAKER_02 5:15

Perfect. Poshi, you've seen many of you have probably seen cats when you talk about quantum. Why have people seen cats with quantum?

SPEAKER_00 5:24

Have you all seen the cats, like why Schrdinger's cat? People have heard of Schrodinger's cat. Yeah. So for quantum really is a state of superposition. You know, is a cat alive or dead? This is an experiment that Schrdinger had, um, where he literally put uh a cat in a box, or theoretically put a cat in a box, I'm told, uh, put a radioactive decayer, and if the radioactive decayer does decay, then it activates a poison, and you know, the poison then gets eaten by the cat, the cat dies. But we don't know any state, we don't know of the state of the the cat at all until the box is opened. So this is a problem of uh superposition, and this is something that's beautiful in the quantum sector, is at some point it's zero and one, or it's zero and one at the same time, or it's neither.

Superposition Explained With Schrödinger’s Cat

SPEAKER_02 6:04

So that gets to kind of the problem here, right? You get fundamental properties of of quantum, superposition, um entanglement, uh, the randomness. These are some of the fundamental properties that we all try to exploit when we're trying to use this to do useful things. And that's why it gets complicated. So so let's get to um what's the current state? And I'm gonna leave to whoever wants to start here. What's the current state of the practice and what kind what kind of capabilities do you see as happening right now?

Hardware Modalities And Cooling Realities

SPEAKER_00 6:31

Okay, I can give you a baseline understanding of quantum computers themselves. Quantum computers, uh, the research has been going for the last decade. We call this a second revolution of quantum. The first one gave us some things like MRI machines, for example, uh, OLED TV screens. Uh, but this is a second revolution where we are tapping into and getting better at tapping into these properties of entanglement and superposition. And there's this whole race towards quantum computers, and there are different modalities that can hopefully get us there. So different groups are trying different things. One is a superconducting computer that requires fairly low temperatures, in fact, temperatures that are even lower than what you would find in space, for example. Uh, I have some friends at NIST, and you know, something that they're developing is works at 40 millikalvins, which again is much colder than space, 40 millikelvins. Um, and this is why, if you ever see a quantum computer, you know, typically it's represented not by the box that it's in, but actually something called a dilution refrigerator, which is this golden chandelier that comes down. So that is a machine that it's golden because gold has a you know high conductive uh metal, and it's able to then cool the uh the qubits itself, the device at the very tip, uh, using helium that's pumped into it. Uh, but how we represent quantum computers is through then the golden chandelier. Um there are other methods as well, photonics is a big one as well, uh, I'm sure, like with um yeah, photonics as well, and we uh iron-trapped uh ions, uh trapped ions, for example. Um if anyone tells you quantum computers are here in the next three years, five years, or twenty years, don't believe them. I don't think anyone really knows the answer.

SPEAKER_01 8:02

Some of them are here and there are problems that can be solved today. Yes, yes.

SPEAKER_00 8:04

And that leads me to D-Wave of well, how can we get started today?

Annealing Vs Gate Models In Practice

SPEAKER_01 8:09

Yeah, there you go. Um, so again, I mentioned two different types. There's annealing quantum computers and gate model quantum computers. Um each of them have different capabilities, each of them are advancing on different timelines. So let's start with the annealer. Um the annealer is what D-Wave has first started to commercialize, and we actually have in-production applications today. We are currently optimizing um Entity Docomo's telecommunications network by 15%. We are currently optimizing automobile manufacturing. So for the defense industrial base, if you want to start to manufacture things better, faster, whatever you need to, um, there are manufacturing applications. Those are hybrid applications. So it is a hybrid solver that breaks it down, and the part of the problem that's too difficult for classical goes to the quantum processing unit. The gate model systems, which are more deterministic versus probabilistic, um, those are for quantum chemistry. Those are much farther away. Um, there are a lot of errors that happen. Qubits are fragile, and so you need to figure out, detect the error, mitigate the error. Um, D-Wave just acquired a company that has a technology that does error detection in real time through dual rail technology based out of Connecticut. So a lot of these systems are available in the cloud today. So for folks saying, how do I get started today? And what is the state of play? It's cloud access. There are some, you know, organizations that are purchasing systems, but for the most part, it's cloud access. And um, one of the most important things is the skills needed for algorithm development are things that, and I know we're going to talk about skills uh in a bit, uh, are things that can be developed today. And so that's kind of the state of play is understanding what are the right problems. Quantum doesn't solve everything. Quantum will never solve everything, no matter how big it gets. Um, but once you get these larger quantum systems, both on the gate and the annealer side, uh, you'll be able to solve a whole host of problems that are currently either outside the scope of today's classical or you could solve them faster. And in certain applications, that's important.

SPEAKER_02 10:12

So, what are some problems right now? You mentioned uh some optimization stuff around automobiles, right? What are some issues, some other problems that quantum annealing can solve?

SPEAKER_01 10:22

So think of everything as an optimization problem. Um, and let's be honest, when you look at national security, it's one big logistics optimization problem. So there have been applications, for example, for workforce scheduling for um uh airport security staff. That is a huge problem that takes way too much time to calculate the staff. And when folks were calling in sick, and especially during the pandemic, you had people who had to then quarantine for 14 days, but you had to have all of these parameters of you need certain females and males, and you need certain people with different types of backgrounds in each of the lanes, that adds on the complexity that Quantum and ELIN can solve. And we've actually worked with some folks uh to develop prototypes for that. So think of it from an optimization problem, but you can also turn things into an optimization problem. We have optimized some modeling for LLMs. Um, so the modeling of an AI that is taking forever and running and running and running, you can turn that into an optimization problem for some of them. And we've been able to do that so it's energy efficient. You heard in the video, energy efficient compute, it allows you to uh do that modeling much more energy efficiently, get the model better, and then you can deploy it through classical means.

SPEAKER_02 11:36

Thank you for that. Yeah um, Raji, what do you think are some of the other problems that the quantum can solve? Because that's particularly what you know, some of the D-Wave problems it can solve. What are some other channel problems it can solve?

Real Optimization Wins And Cloud Access

SPEAKER_00 11:48

Yeah, think of other examples. And here I'll switch the topic to quantum sensors. So, what makes quantum computers really hard today is that your qubit device itself is really, really sensitive to its environment. And that's a problem in quantum computers, it's called decoherence and where it loses its quantum state. Now, that could be a really great opportunity as a sensor. You want a sensor that's highly sensitive to its environment. And this is where we see quantum sensors today trying to do uh, well, that are already uh doing actually some really good work. Think of atomic clocks, actually. Those are the first ones, they're quantum sensors. This is, you know, that's how our planes get flown today. Um, and other quantum sensors that I'm seeing getting developed are for uh radiometers, for example, so that's for gravity detection, magnetometers, for example, that's for magnetic detection. And uh in fact, one example I can give you so my um my day job is uh with the US government's organization called ARPA I. If you know DARPA, ARPA I is the uh ARPA equivalent for the Department of Transportation. And there is something we're exploring is the application of quantum sensors to help us with navigation. So imagine if you have a loss of GPS or you have GPS jamming or spoofing. Well, how else do you know with precision or somewhat precision where your vessel is? And of course, navigation has a rich history of you know, like doing celestial navigation and finding all these other ways for navigation. One thing we're exploring is magnetic navigation, so MAC NAV. And this is something that the NGA as well, National Geospatial Intelligence Agency, has taken up as well, where there's an effort now to map magnetic fields, especially for flight travel. And for our case, this is for maritime. Well, how can we then navigate a ship picking up the magnetic field from the ocean if we have the magnetic fields mapped out already? Um, some of the theoretical accuracies there we'll see is about 300 meters, which I think is sufficient. You know, within 300 meters, you also have visibility there, so line of sight, and that helps you then navigate. Uh, but if again, if you have known GPS access, how do you find out your coordinates? Well, you could have 300 meter accuracy if you have a magnetic or gravometer device on you.

Logistics And Workforce Scheduling Use Cases

SPEAKER_01 13:49

There's also a report for folks to take a look at. Um, the Last Administration's Department of Transportation did a quantum workshop that looked at quantum sensing and compute and actually identified at a whole host. I think it was almost like 12 or 13 different use cases, both in the transportation and sensing side of things for compute and quantum sensing. So I highly recommend folks look at that report because that was actually enlightening to see all the different use cases in both.

SPEAKER_00 14:15

Yeah. And Alison was a fantastic panelist. I certainly recommend that as an organization as well, to bring the quantum experts and bring your users together and figure out where are these use cases and build a matrix of you know where can you find the highest value in quantum.

SPEAKER_02 14:28

So we mentioned a couple of different things, right? We mentioned quantum sensing, excuse me, we mentioned um uh quantum annealing, we mentioned quantum computing using gates, right, qubits, right? Um so let's talk about maturity, because you made the comment that someone if someone thinks quantum computing is gonna be here three, four, five, twenty years, it's unclear, and you count it well, we have quantum annealing now, right? So let's talk about m maturity and let's talk about what some of the differences are in these things.

Quantum Sensing Opportunities And NAV

SPEAKER_01 14:53

Yeah, so NIST has not done, well, nobody has really done a true objective TRL level assessment. There is a one from NIST from June of 2021 that looked at kind of when do you need to do standards, and they did a very high-level kind of TRL level assessment of the different quantum technologies. Quantum Annealer's maturity level was a TRL level of eight. Um, and a lot of that is because we have it commercially deployed, we have it forwardly deployed, we have applications that we're building. The gate model systems, there are two different types. There's the NISC, noisy intermediate scale quantum. That is really noisy, qubits pop out of their magical state. How do we fix it? And that is those areas are kind of in the TRL level of four, five. Um, but there is a concern that you're never going to be able to scale those systems. The errors are gonna get too great. When you have an error, you get no answer at all. So you actually have to go for error detection and correction versus error mitigation. And those at according to NIST at that time, again 2021, that they were looking at those at a TRL level of a one or a two. Um, we are, I I do policy, so I'm actually urging Congress and the National Quantum Initiative Act to um have NIST do true TRL level assessments and keep those updated because this is advancing so quickly. I've been with the company now over five years. When I started, we just put one of our systems, you know, our newest system in the cloud. Since then, we've had multiple hybrid solvers, another system come in the cloud, other companies have advanced their technologies. This is the company we just bought is the first post-NISC quantum gate model system. So it's not about correcting the errors, it's about detecting them and mitigating them right then in their dual rel technology. So this is the there are different stages, um, and we really do need an objective uh readiness level assessment.

SPEAKER_00 16:54

Uh yeah, if I can add, DARPA is doing a quantum benchmarking initiative right now. This is um now a tiered and phased approach, but it's they're really testing different quantum companies and their quantum. But only gate model systems. Yeah, as well as the applications. Yeah. It's limited, but it's a resource one could use as well.

SPEAKER_02 17:10

And then what about quantum sensing? What's the maturity of quantum sensing?

SPEAKER_00 17:13

Yeah, that's a great question. So, quantum sensors, that's what gets me really excited. I think quantum sensors are ready to come out of university. And certainly I see a role for us now as prospective users to start helping the academic community in our country to help bring these technologies out of the lab. You know, typically what I'm seeing now, a lot of them are falling through this valley of death where they're at TRL level three, four, and they start need to be doing early pilots. So I certainly encourage everybody else, everyone else here to have a look at quantum sensors. Again, there are a variety of different quantum sensors. Something that I see that excite me, for example, are vapor cell clocks. So right now we have atomic clocks, again, that's a type of quantum clock. There is now some work at NIS Boulder that's happening that's looking at, well, can we make that at a vapor cell level, which would be exciting? It opens up a lot of applications.

SPEAKER_02 17:57

I'm sorry, could you so why is that important? Why is the atomic clock important?

Maturity, Benchmarks, And TRLs

SPEAKER_00 18:01

Yes. Uh so quantum sensors over classical sensors, they can be fantastic because of their sensitivities. Like I said, a quantum, uh, a qubit device itself or anything in an atom in a quantum state can be very, very sensitive to its environment. Now, can we tap that sensitivity because it knows its environment so well? Can we have that then have it tell us, well, what is that environment looking like? And you know, quantum magnetometers, for example, we are seeing them push boundaries at like nano Tesla, Pico Tesla levels. They can be very small, they have no drift, they don't need cooling. Some of them, like the magnetic um, one example is the nitrogen vacancy diamond uh magnetometer. So this is where work done at Harvard University starting in 2008, where they literally took a diamond. Uh so diamond is all carbon, carbon, carbon. You remove some of the carbon atoms and then instead place a nitrogen and a vacancy in where a carbon atom may have been. So you change the bond structure a little bit. Uh, but then when you hit it with uh a 532 nanometer, a green light, it shines out a fluorescence light over to you, and that can tell you a magnetic field. Uh the reason I tell you all of this physics behind it is it's very exciting because it's very stable. Some of the magnetometers we have today, the classical ones, they need cooling. Um need cooling, or some of them have high drift, or some of them don't have sensitivities. But the quantum one again, they open up amazing applications for you.

SPEAKER_01 19:20

I think it's I think the biggest thing to take away from what Procci has just said is when we say quantum, everybody thinks it's one monolithic thing and it's not. There are tons of different technologies under sensing. There are multiple different technologies under compute, each of them have different uh use cases, each of them have different strengths. And the issue really is to come to the table and say, this is my problem. Is quantum able to solve it? And then we can come in and say, nope, quantum's not right for that problem. Yes, quantum can help with some of that problem, not all of it. Not everybody needs to be a quantum physicist, and uh we don't expect that. I mean, I look at my phone and I don't know how it works. I just know when it does and I know when it doesn't. Um and so quantum can be the same way.

SPEAKER_02 20:04

So if if I'm uh if I'm in TSA, let's say, and I need to schedule my agents, what would I do? How would I come to you? And then if I came to what would I do after that?

Sensors Poised For Deployment

SPEAKER_01 20:15

Yeah, so um obviously that TSA scheduling um application that we built with um a large system integrator was pulling and ingesting all the different information and all the different components and the constraints. It's those constraints that make it so complex. And then we can run those um scenarios multiple times. Um the speed in which quantum can compute cannot be uh cannot be the same as classical. We can look at a lot of different things in a nonlinear fashion, do it faster, and provide an answer. Sometimes it's the same answer, just faster, sometimes it's a better answer. Um, and so being able to look at it, so you come to us, we kind of understand your problem. If we are not the best person, we bring in a partner. So that's why for the government contracting folks in the audience, we do work with partners in order to understand kind of the mission sets that you all are experts in. And we train either you to develop that algorithm or we help with our professional services team develop it with you. Um and we can start small, you know, one airport and then multiple or regional airports and navigate through that. Um, you know, one of the things when it comes to speed, there is a missile defense application that um one of our partners helped create down in Huntsville, Alabama, and it looked at a notional multiple ballistic missile attack in uh Hawaii. It looked at 67 million scenarios and provided an answer back in 13 seconds. That's the power of quantum. And there are some problems that you don't need that speed for a solution. There are some problems you have to have a faster speed to solution. So it really is kind of understanding your problem set. When do you need an answer by and if quantum can help?