Transcript | Becoming a Quantum Coder— with ColdQuanta

Are you interested in being a quantum coder? The job market looks as large as the machines are cold. We’re all struggling in the industry to find talent. Do you have what it takes? You might even be able to get started with less experience than you think. Find out more about the path to this exciting career in this episode of The Post-Quantum World. I’m your host, Konstantinos Karagiannis. I lead Quantum Computing Services at Protiviti, where we’re helping companies prepare for the benefits and threats of this exploding field. I hope you’ll join each episode as we explore the technology and business impacts of this post-quantum era.

Our guest today is the quantum solutions manager at ColdQuanta, Peter Noell. Thanks for joining me.

Thanks, Konstantinos. Excited to be here.

Yes, it’s great to have you here, and we, of course, know each other. We’re starting to work on some things together, but I thought it would be great to have you in for this super-important topic, one I wanted to touch on for a while. Being a quantum coder is probably going to be the hottest job in this industry for the next decade or so. I expect to see it explode in both opportunities and people coming out of school looking to fill those opportunities. I thought it would be great to have you on to talk about how you ended up in this type of position and what insights folks can glean on how they can switch gears and join this career too.

But first, yes, tell us about the company you work for and about how the recent merger happened.

The company I work for is called ColdQuanta, and it was founded in 2007 in Boulder, Colorado. It’s not just a quantum computing company but also a quantum ecosystem company with a quantum-everywhere approach. On the quantum computing side of the house, the company recently, in the last year or so, launched Hilbert, its first quantum computer, which is based on the neutral-atom approach to quantum computing, which is, as you know, more of a newcomer to the quantum computing types. But we see a lot of advantages in terms of scalability, connectivity and more engineering challenges, rather than scientific, with the approach, so we’re excited about that.

But before starting at ColdQuanta, I was in grad school at the University of Chicago. I was in a joint program where I got my MBA in computer science, which is an awesome program that I can talk a bit more about why it was right for me. But during my summer internship, I interned at a company called Super.tech with just a couple of people there when I was interning. We had three full-time employees, who are also here at ColdQuanta, and in May of this year, ColdQuanta acquired Super.tech. I was planning to return full-time to Super.tech, and now I’m full-time at ColdQuanta.

It’s an exciting merger, because Super.tech was software-focused in the sense that Super.tech creates these optimisations and implements them for these quantum computers, and it’s hardware agnostic, so whether it’s superconducting, neutral-atom, trapped-ion, we optimise the software programs for the quantum computer, cutting down runtime, the number of gate operations, circuit depth. We try to squeeze every bit of juice out of these quantum computers.

Super.tech is continuing to maintain its focus on being hardware-agnostic, so we don’t necessarily think it will be winner-take-all in terms of which quantum computer modality will deliver quantum advantage. We’re continuing to implement these optimisations into our software stack, called SuperstaQ, continuously. And that’s not exactly what I focus on here, as my job title indicates — quantum solutions manager. I’m on the application side of things, talking to customers and seeing how quantum can benefit them.

That’s great, and listeners know both companies. Pranav and Fred have come on from the Super.tech side, and Paul has come on from the ColdQuanta side, so now you’re all one big, happy family and you get to add to the lore that has been told on this podcast.

And we’re definitely going to talk a little bit about your day job — providing applications. That’s super important for why we’re here. Before we get to some of those use cases and things that you’ve worked on, let’s talk a bit about your background. You also spent some time in the military.

I did. The place to start for my background would be as an undergrad at Notre Dame. There, I was an applied math and statistics major, and while that was my focus academically, I knew that I was going to be entering the military upon graduation, because I was doing the Army ROTC program there. I didn’t have to think about what the private-sector job would look like for me, because I was going to military service.

I did that for four years — was an infantry officer, and didn’t do anything math- or science-related during that time, but it was a great experience to gain some leadership experience and try something new and scratch an itch. Something that I knew I wanted to do was to serve, so I spent four years, mobilised to South Korea in a pretty interesting time, 2018, for U.S. and Korean relations. Then I exited the service in 2020 during the pandemic and entered grad school at UChicago.

The program I did was a joint MBA and computer science master’s program, which I thought was perfect for me because the MBA opens up a lot of options. Most veterans go into things like consulting and banking, which are great, but the addition of the computer science master’s opened a lot of doors for me, and I knew I wanted to do something different.

I met Pranav through UChicago and was struck by his work ethic and intelligence, so I knew that that was a team I wanted to be a part of. I interned at Super.tech and was returning for 2020 when I graduated.

Yes. Pranav is quite a great guy, and when you meet him, you just feel this confidence rolling off of him. It’s wonderful to be around. He’s pretty great. What we’re seeing here is that you started off with one of these core prerequisites: You’re involved in computational mathematics, and that’s one of the key prerequisites. Looking back, what would you say should be the prerequisites for someone who is interested in quantum coding?

Just having any coding basis, combined with an interest to learn, is enough. In undergrad, I had a lot of exposure to things like linear algebra, combinatorial optimisation, but the program I was in wasn’t too coding-centric — some in R and C++ — but grad school was a great opportunity to level the water there for me, and so I’ve gained a lot of experience in grad school with Python, and that was a great way to apply these ideas that you find in linear algebra and combinatorics to real-world applications.

The applications that I’ve been working on mostly have been optimisation problems. The way I view it is, the quantum applications could be broken into three categories, optimisation, simulation and machine learning, and what I’ve been focused on so far the most have been combinatorial optimisation problems.

Yes, I’ve been talking about that major trio quite often. It’s exactly that: optimisation, machine learning, simulation — 100%. What’s fascinating is, you had these basics like linear algebra, which is super important, then you — I don’t want to say put aside, but basically, put it aside for four years. I don’t imagine you were using that daily in the military, and then you came back to it and you started leveling off with all these decoding skills. That’s important for folks who did have some of those math prerequisites and they forgot about them or left them on the back burner. What was it like dusting them off after four years? Was it easy? Did you have to do some refresh?

 I had to do some refresh, and that’s one of the great things about working at a place like Super.tech and ColdQuanta, that it’s a great mix of an academic mindset with a commercial mindset — day-to-day, I have the latitude to just learn something new. If that’s all I did that day, then that could be a successful day, because it could lead to a couple weeks of working out some code that had some commercial applications. Working at a quantum company like ColdQuanta, you have the latitude to learn new things and refresh things that you’re rusty on.

A little bit like that Google percentage time for personal projects.

Yes. We have that going on this week. I don’t claim right now to have too much of a background in machine learning, but in the next few years, I definitely plan on adding that capability to my coding skill set.

On that note, what would you do to start approaching that? Machine learning will be important, obviously, as gate-based machines get better — even your own machine, Hilbert, and its predecessors, and its children. As they start to get better, machine learning will be more useful. What are you going to do now? What kind of educational approach would you do at this point in your career?

I don’t even think that I need a formal track, necessarily, to learn. It’s just being at the company around people like Pranav and some of the other team members we have here with that expertise. You’ll learn through osmosis, and there are a lot of structures in place day-to-day at the company here where you learn efficiently, where we have an hourlong lunch-and-learn or whatever it is to share knowledge among people at the company. Even if you don’t understand something right away, over time, you absorb it and ingrain the concepts.

For example, I didn’t have any formal quantum training prior to interning at Super.tech. In my second year, I took our cofounder at Super.tech Fred Chong’s class, so I do have a bit more formal quantum education, but just over that summer, being in the quantum environment, I was able to adapt what I knew to quantum concepts and frameworks.

Yes, that’s an optimistic thing to say. For those listening, you might be coming to this from more of the coding side, and you have that math background, but quantum is a mystery to you — and, let’s face it, it’s a mystery to most people — but you were able to learn some of those necessary things. What aspect to coding does that help you with? This is one of those questions that I know the answer to. Understanding quantum, how do you feel that that helps you do things like encoding or other aspects of writing actual code?

In terms of writing actual code, just getting repetitions is the way I learn — getting repetition, refining code. That’s one thing that we have great here: Starting in 2020 with Super.tech, Pranav and Victory Omole — he’s the first employee — they have a disciplined software-engineering procedure where our code base and workflow are streamlined and keep things clean and efficient. I don’t know if that was your question, exactly.

That’s good info. I mean more along the lines of the knowledge you have now of how qubits actually work and what’s going on with the black sphere and all that. On a more practical day-to-day, when you’re coding, how does that help you?

 For example, one of the problem formulations that I work on, they’re called QUBOs — quadratic unconstrained binary optimisation — so understanding how those problems map to quantum computers, that allows me to formulate the QUBOs better for real-world problems, thinking about applications where the natural formulation is a QUBO. For example, things that are decision-based: yes or no, buy or don’t buy, sell or don’t sell, the long or the short. Those are some obvious ones that come to mind, but more creative implementations that we’ve been working on. It expands the range of applications that you can apply quantum for, just having that mindset.

Yes, and of course, it becomes about understanding the specific hardware you’re running on too.

That’s something that we’re trying to abstract away in the long term at Super.tech — where the user doesn’t have to even consider what hardware will be best. We’ve been working on quantum benchmarking with our SupermarQ suite of benchmarks, so part of that is to inform customers about what quantum hardware will be best for their specific applications. But beyond that, in the long term, we would like to see a world where the customer doesn’t even have to think about that. It’s all handled by our software stack.

For those who might not have heard about it, how SupermarQ works is, it runs very focused types of applications against known quantum computers, and it gives benchmarks, like the old days. What’s useful about that is you could see that, “I want to run this type of specific problem, and, look, it’s this piece of hardware that’s the best at it.” If you’re going to spend money on running shots on the cloud or whatever, you actually know which machine to go to, which is useful. Then it becomes a matter of understanding how to get the most out of that machine, and you’re hoping to abstract away that getting the most out of machines so people don’t have to go down to the pulse level and mess around, like the early days.

How do you envision that software approach? Is abstracting that away affecting this industry? Let’s face it: All coders have it easier now — like, you come in, you have an ID, you have little bits that you’re working on. It’s not like you have to boil the ocean as a developer at a huge company. How do you envision this kind of tool and other competitors improving the odds of getting hired and actually being productive sooner?

In terms of abstracting that away, it depends on customer sophistication levels. Some more sophisticated larger customers are willing to be a bit more in the weeds when it comes to quantum, but to make quantum a part of more people’s lives and more useful for them, you have to abstract away some of these difficult concepts that a lot of people just don’t have the time to learn because they’re focused on other aspects of their business. Was the second part of your question regarding quantum coders?

Yes. What can their outlook be like? Let’s say there are these young adults right now studying, and they’re going to be out in a couple years. If you can just give a little futuristic thought about what it might look like when they come out: Will some of this abstracting away make life easy? Will it almost be like they could step into a traditional software role now because that will be so set up?

Yes. It will progress to that point. In some ways, my role at ColdQuanta is having a foot in both camps: I’ve learned a bit about the quantum side, but I also can almost play the role of a non-super-quantum-literate person. I’m quantum-literate, but I’m not optimising for pulse-level control, like some of my colleagues are. There’s a world for both levels of quantum literacy, and you’ll see, moving forward in the next few years, that, yes, a lot of that does get abstracted away more by quantum physics — Ph.D.-level types, for sure.

Would you say that if someone wanted to come work at your company in the next few months, they’d have an easier time getting started because of your more mature software stack?

Yes — it’s not a prerequisite. It would be nice to have, but you don’t need an intense quantum background to start working at ColdQuanta, or a company like ColdQuanta. As you know, there’s definitely less supply than demand for talent right now in the quantum industry. There’s something like over a thousand jobs open in the industry, so any level of quantum knowledge, plus a solid coding background, you’ll find opportunities in the quantum industry, for sure.

 I agree, definitely. If someone were just entering college right now and they decided, “That’s what I want to do — I want to code quantum computers in four years,” there aren’t known tracks right now. You can’t just go and select “quantum coder.” I’ve been talking to universities. I’m pushing on them. I’m sure the CQE, the Chicago Quantum Exchange, is pushing on for that too. We all want this. We want a bunch of schools that are producing this ready-to-go, eager team. I’ll have a different question about someone who has already done school, but what would you say would be good advice for someone who wants to start from scratch?

If you knew for sure that you wanted to get into quantum computing, you can’t go wrong with physics or computer science or both. If you have the latitude to do both as a major, that would set you up very nicely. Any STEM background combined with some coding experience, you’ll be able to do well if you have a strong interest, but if you know that’s what you want to do, then computer science or physics or both would be the way to go, no doubt.

Yes, and you could see that natural marriage is there. There has to be way to turn that into a curriculum, if that could be followed.

Totally, and UChicago just started a quantum-specific program. They have a molecular-engineering program as well. Something like that would be great.

Yes, and then they have their other certificate that they do. Yes, I have that too.

For someone like me, if you have STEM background or a program like the MPCS, the Master’s Program in Computer Science, at UChicago, it’s great for me, because they don’t assume any prior coding experience — just strong STEM skills and a willingness to learn — and they’ll build you from the ground up there.

Yes, that’s good to know for anyone interested in that school. That sounds terrific.

 Yes, so if you already have a bachelor’s degree or something but are now, like, “I’m interested in this,” then that would be the route to go.

Yes, that leads us to this next question naturally — so that’s one way, if you have a bachelor’s degree and you want to do a program like that. Let’s say someone, they’ve spent many years as a coder, and now they just want to get into quantum. What would you say would be a good approach for them to be hirable in the short term?

They are hirable if they had many years of coding experience. I know a lot of people in our Madison office worked at companies like EPiQC up there and video game companies — so, different coding experiences, for sure, but they had the skills necessary to get started building software there. If you can self-teach some quantum concepts, that’s great, but just getting started at a company like ColdQuanta and being in an environment where you are in every day and absorb this new information for you, you’re going to do great.

That’s very exciting. I hope you guys are ready for the résumés now after this episode.

Yes, and we’re hiring.

Well, look at that. This is well-timed for you too, then.

We talked a little bit about this, and getting started, and this is all super optimistic and exciting. Now, let’s talk a little bit about the day-to-day, the types of applications you’re working on, to give a taste to listeners of what it’s like.

Most of the applications that I’m working on are these optimisation problems at the moment, so we’re talking with interested customers and seeing what problems for them take too long to solve, or they’re getting suboptimal solutions. Those are the two things that, in the near term and the long term, quantum will be good for.

Day-to-day, I am exploring what these customers need. You hear a lot in the quantum community about, “There are going to be so many applications,” but then you dive in, and right now, people are still discovering what they are. As time progresses, they’ll become more and more evident, and you’ll find them in areas that you didn’t know to look initially.

The one people always say is portfolio optimisation. And there are a lot of different flavors to what that can be, but talking to customers and saying, “What does portfolio optimisation mean for you? Does that mean you’re interested in improving something like direct indexing, where you follow an index and you track an index of your portfolio, but you can customize it in different ways,” for ESG-type purposes or for tax-loss harvesting — things like that that we found there’s some interest there and some applicability for quantum too. That’s one that I’ve been looking at.

Also, fraud detection, that’s massive for credit card companies, so we’ve been exploring ways there to uncover fraudulent transactions and rings of fraudulent transactions. Those are some of the more interesting ones that I’ve been working on.

We haven’t done a lot of research yet in drug discovery and chemistry. It has mostly been in finance, logistics and energy optimisation — we’ve worked with an energy company to optimize their power grid, and that’s exciting work there.

Yes, that makes sense. The other areas are very specialised. It’s hard to get up to speed on the chemical side. It’s a bit much.

Exactly. The theme we have here is mostly physicists and computer scientists — a nice mix in the best of both worlds, in my opinion — but we don’t have the chemists to work on specific applications for that at the moment.

Another area of interest is in government work — defense — which for me is interesting. Being a former military member, there are a lot of interesting applications. They’re not necessarily in the infantry, which is where I was, but things more on the navy and air force side of the house rather than the army — missile defense or things of that nature — we see some potential applications there too.

Yes, and there are other areas that border on the security aspect — not necessarily just national security, but more like securing companies and quantum computers to spot anomalies and things. Your background seems to have influenced some of this, and you have an MBA too. Does that help you in talking to financial customers? Do you find that you’re dusting that off regularly because you can pull out of them what they want?

It adds some credibility, and going forward, for my career, that definitely helps in terms of upward mobility and eventually taking a leadership position in the quantum realm. That definitely helps. For my current role, I’m more interested in exploring these applications and doing some coding day-to-day. That’s what I want to do right now: build out my quantum literacy, and learn a bit more about machine learning and simulation. That’s what I’m focused on in the near term, but going forward, having the MBA is certainly going to be a big part of my career.

If you could project a couple of years out, what dream application would you like to be working on as machines get a little better? There must be something in the back of your mind that’s, like, “I just know this is going to be great, but we’re not ready yet.”

 For me, the dream application — you see this a lot, that people are fascinated by it. It’s the traveling-salesperson problem, the various applications of that. I don’t know how much you know about it, but the current best algorithm, the best that it guarantees the solution will be at worst is 50% worse than the optimal solution, and it has been that way since like the ’70s, so finding some practical improvement for applications of that is so fascinating for me because it seems like people have been stuck on it for so long. Obviously, there are so many applications for that, especially in logistics.

You picked a good one, because I believe that one’s going to be within two years, easy. I have a feeling.

Yes. That one’s going to unlock so many things.

Yes, and D-Wave’s very next hybrid solver that they’re going to release, that might even be the key. It’s looking like a beefy improvement.

Yes, that’s the one.

You definitely already painted a optimistic picture, which is awesome. Do you have any last advice you’d like to give to any neophytes out there?

Just focus on improving your coding skills, and teach yourself some quantum. IBM has some great resources with Qiskit. If you just work through their Qiskit textbook and teach yourself some things like that, you’ll set yourself up for success in the job market.

That’s great, and folks should remember that there’s something else that they’re good at too, and you might be able to bring that too, to a position. If it is something like a financial background or whatever, it can also come in very handy.

That’s a great point. Having the MBA too, the academic component of the MBA —different techniques for portfolio optimisation that I learned on the MBA side of the house, but I’m now trying to optimize on the CS side of the house — that has been valuable for me too. Don’t underestimate that, and don’t underestimate soft skills from the army that you pick up there, things like that. Any parts of your background, you’ll be able to add value to your quantum company.

Great. Peter, thanks so much for coming on. I enjoyed talking to you today. I hope our listeners are inspired to give this a try soon.

Thanks for having me on, Konstantinos.

 Now, it’s time for Coherence, the quantum executive summary, where I take a moment to highlight some of the business impacts we discussed today in case things got too nerdy at times. Let’s recap.

Peter Noell took us through his personal journey to quantum application development, and we got to see a few recurring themes. You don’t necessarily need experience as a quantum coder to enter the field. It all depends on which prerequisites you bring to the table. Linear algebra and coding experience are a solid start. It may be possible to then pick up enough quantum knowledge for coding using a self-taught approach. Machine learning skills are sure to be helpful immediately. Plenty of soft skills come in handy here too. Customers will need code explained to them, for instance, and if you have any vertical experience in an industry, it may help you understand business needs around the problems a use case is trying to solve.

Depending on the company you want to work for, there may be a system in place to help you become productive quickly. Do they use a software tool that helps abstract away some coding complexity? It looks like these types of platforms may only get better, and coders in a couple of years will have it even easier. This is for so-called experienced hires, of course.

Those interested in entering college now must be proactive and choose or create a major that makes sense. A dual major in physics and computer science is a no-brainer. We’d love for universities to step up here and create majors and curriculums designed with quantum coding as a career specifically in mind. Remember, Peter didn’t have a quantum coding degree to select, but he’s now developing real use cases in the field.

Does a career in quantum coding sound appealing to you? Do you feel you have what it takes? If so, ColdQuanta is hiring, and so are we here at Protiviti.

That does it for this episode. Thanks to Peter Noell for joining to discuss the path to a quantum coding career, and ColdQuanta. Thank you for listening. If you enjoyed the show, please subscribe to Protiviti’s The Post-Quantum World and leave a review to help others find us. Be sure to follow me on Twitter and Instagram @KonstantHacker. You’ll find links there to what we’re doing in Quantum Computing Services at Protiviti. You can also DM me questions or suggestions for what you’d like to hear on the show. For more information on our quantum services, check out Protiviti.com, or follow ProtivitiTech on Twitter and LinkedIn. Until next time, be kind, and stay quantum curious.