Working in Quantum. Insights and behind-the-scenes with ParityQC’s Florian Dreier

In our Working in Quantum interview series, we put the spotlight on the people that are part of the flourishing quantum computing industry. This time we talk with Florian Dreier, team member of the Use Case department in our Innsbruck headquarter and one of the two main authors of our breakthrough paper about a world-record implementation of quantum algorithms (“Connectivity-aware Synthesis of Quantum Algorithms”).

Florian studied mathematics at the University of Innsbruck. During his PhD, he focused on both theoretical and applied research, in particular inverse problems in medical imaging. After a Postdoc position at the Department of Mathematics in Innsbruck, he became a Postdoctoral Researcher in the Lechner research group in March 2023 and also supports the team at ParityQC.

What’s your role here at ParityQC?

At ParityQC, I work as a Quantum Software Engineer in the Use Case department, where we are focusing on identifying and developing applications for quantum computing. We are currently developing our ASQ software (Automated Solution Path for Quantum Computing), a tool that benchmarks quantum algorithms for solving optimization problems. Besides these software engineering tasks, my work also includes the theoretical exploration of compilation strategies based on the ParityQC Architecture, aimed at efficiently implementing quantum algorithms on quantum hardware.

Tell us a little about your academic and career path.

My academic path started at the University of Innsbruck, where I earned a bachelor’s degree in mathematics. I then completed a master’s degree before pursuing a PhD there. During my PhD, I focused on both theoretical and applied research, with a particular emphasis on inverse problems related to the wave equation and their applications in medical imaging.

What fascinated you about quantum computing as a mathematician, and which challenges were you facing when entering the quantum field?

What fascinated me when I was entering this new field was the way information can be encoded and processed using quantum effects. Unlike classical computers, which rely on electrical circuits, quantum computers utilize the behavior of physical quantum systems — such as superposition and entanglement — to represent and manipulate data in fundamentally new ways. As a mathematician, I was particularly drawn to the rigorous theoretical proofs demonstrating that certain problems can be solved exponentially faster in a quantum framework compared to a classical one. However, when I started to work in the field, I found navigating the mathematical notations and formalism of quantum computation to be quite challenging. It took me some time to decode and fully grasp the meaning behind these notations and concepts.

Is there an aha moment or a project that particularly fascinated you?

When I joined ParityQC I initially focused on a detailed mathematical exploration of the ParityQC Architecture. Simultaneously, I contributed to the development of our ASQ software. As a newcomer to quantum computing, this combined experience helped me a lot to gain a better understanding of quantum computing. My learning wasn’t marked by a single ‘aha’ moment, but rather a continuous, step-by-step process of building conceptual understanding of this field.

I also collaborated with colleagues from other departments on efficient implementations of quantum algorithms for problems such as integer factorization. This work led us to explore fundamental questions regarding the implementation of basic arithmetic operations such as addition and multiplication on real quantum hardware, which I found to be particularly interesting.

You recently co-authored a paper outlining an implementation of fundamental quantum algorithms with record efficiency (“Connectivity-aware Synthesis of Quantum Algorithms”). Why did you and the other authors decide to focus on this problem? Did you have an ‘eureka’ moment, and how did the process develop?

This problem emerged during the investigation of efficient implementations of quantum algorithms for integer factorization. Initially, we focused on quantum platforms with linear nearest neighbor connectivity (LNN). Subsequently, I developed more interest in implementing these algorithms on quantum devices with all-to-all connectivity. I recall one of this ‘eureka’ moments which I had during a train ride from Innsbruck to my hometown in Upper Austria. While traveling, a crucial missing step for our implementations popped up in my head which led to the optimality of our results for quantum devices with all-to-all connectivity. At that time, the constructions differed from the ones we had for quantum devices with LNN connectivity. However, we received key support from people of the Lechner lab at the University of Innsbruck which enabled us to unify both approaches and even make them applicable to quantum hardware with almost arbitrary qubit connectivity.

Can you tell us a little more about the paper and what these results mean for ParityQC and for the quantum computing industry in general?

In this paper, we introduced a general method for implementing prominent quantum algorithms on quantum hardware. What is so special about our approach is that on one hand, it optimizes the resources we need to perform quantum algorithms on quantum hardware by outperforming all known state-of-the art methods. On the other hand, it can be applied to quantum hardware platforms with almost arbitrary qubit connectivity.  For specific cases, we even proved the optimality of our implementations in terms of the number of operations required to perform these algorithms on a quantum computer. This efficiency and broad applicability make our results highly relevant to the quantum computing industry, particularly given the presence of gate errors and limited qubit connectivity.

In the paper, you presented mathematical proofs spanning around 20 pages – quite an impressive and demanding achievement. How long did it take you to complete it, and how did you manage to maintain focus throughout such a long and intense task?

It took approximately four months to complete the proofs, from initial development to finalization. This timeframe also includes a period of reformulation, as we were able to extend our initial results during the writing process, which naturally required additional time. I generally find I can sustain focus on extended, intense tasks, particularly when driven by a desire to solve such mathematical challenges.

What’s next for you now and what challenges might you be facing next in your work?

My next tasks include the further development and testing of our ASQ software. In the use-case department, we are now also focusing on exploring quantum algorithms beyond near-term quantum computers (NISQ) for solving optimization problems with super-Grover speedup. Understanding these methods and their proofs will require a certain amount of time and detailed technical work.

Where do you see quantum computing in 10 years? And what will be the biggest challenge by then?

I hope to see quantum computing have more impact on our daily lives in 10 years, enabling its usage for the first real-world industrial applications from which society can truly benefit. I believe the biggest challenge is to engineer and construct such quantum computers to be capable of solving problems with many parameters, allowing us to achieve a significant advantage.

What motivates you, even when things get difficult?

I view difficult situations as challenges. The feeling of successfully overcoming something exigent – or even just parts of it – is rewarding and gives me a sense of accomplishment, which keeps me thriving for more. To regain motivation when I’m struggling, I find it helpful to switch to other tasks and focus on something else before coming back to the initial problem.

When you look back: What would have helped you the most in the early days of your career?

During my PhD, I was mostly working alone on the same problem for weeks or even months. I can observe now that collaborating with people and listening to their perspectives makes work much more efficient and can save a lot of time. Even if a colleague does not have an immediate answer, just articulating your thoughts aloud can be incredibly helpful in clarifying and organizing them.

Which non-technical skill do you think is most important in the quantum industry?

While technical expertise is fundamental, I believe communication skills are one of the most crucial non-technical skills in the fast-growing quantum industry. This is because translating complex quantum concepts into understandable terms for collaborators, investors as well as the public is essential for driving innovation and securing support.

What inspires you to come to the ParityQC office (or log in) every day?

I really enjoy the opportunity to work in such a fascinating field and constantly learn alongside a highly motivated team. I also appreciate being part of the Use Case department, which consists of 8 people from 5 different countries – it’s really cool!

If you’re interested in joining ParityQC and contributing to our breakthroughs, don’t forget to check out our open roles on LinkedIn and in our Careers page!