Decoding Tomorrow: The Push to Simplify Quantum Computing

Why did you become a researcher?

It really started because I thought writing my master's thesis was a lot of fun. I had taken courses in some specific mathematical methods with applications in computer science, and I was eager to try them out in a real project. When I finished my thesis, I just wanted to keep going—and becoming a PhD student was the natural next step. After a couple of tries, I was accepted at the University of Copenhagen, and one thing led to another from there.

 

Which other career plans have you had?

My original plan was actually to become a chef. I completed the basic training and even apprenticed at a restaurant in Copenhagen for a while. I still really enjoy cooking, but I’m glad I don’t do it for a living.

What question would you most like to answer?

I'm very interested in understanding what exactly distinguishes quantum computing from classical computing. Today, we have quantum algorithms that solve some specific problems significantly faster than the best-known classical ones—but we don’t actually know whether that’s because these problems inherently require quantum computers, or simply because we haven’t found good enough classical algorithms yet.

More practically, I’m also deeply interested in how we can best program quantum computers. Programming technology has advanced enormously over the past 25 years—while in the 1950s you probably needed a math degree with a specialization in computing to code, now it’s something ordinary people can pick up pretty quickly. But when it comes to quantum programming, we’re still stuck in the 1950s. You probably need a master’s degree incomputer science, math, or physics—and a lot of specialization—to even get started. I want to help change that.

How do you hope others can benefit from your research?

A big part of my work is using tools from algebra to transform typically quite complicated but concrete mathematical models into much simpler—though often more abstract—concepts. My hope is that this leads to a more conceptual understanding of quantum computing, where the key isn’t whether you've passed “Functional Analysis II,” but whether you truly grasp the physical principles behind the mathematics.

What do you have in your office that most people don’t?

My sister-in-law Mathilde crocheted a raccoon with a tiny scarf for me—it lives on my office shelf. Raccoons (and cats) are my favorite animals. They’re super chaotic. A lot like my kids.

Who do you admire?

Professionally, I really admire people like Dorit Aharonov and Peter Selinger (professors in computer science at Hebrew University and mathematics at Dalhousie University, respectively). They have the rare ability to produce technically impressive results and explain them in ways that others can actually understand. That’s not just hard—it’s also incredibly important for communicating research within the academic community.

On a personal level, I’ve learned a great deal from working closely with Chris Heunen (Professor of Quantum Programming at the University of Edinburgh) over the last five years. He’s an impressive and very kind person in every way.

What do you do when you’re not doing research?

I have a wife, two small children, and a house we just moved into—so most of my free time goes to family life. I love cooking and do it almost every day. I also try to make time for playing nerdy card games with my friends whenever I can.