“We use fundamental quantum effects to construct algorithms”
With enthusiasm for abstract theory to new applications
From applied chemistry to the development of quantum algorithms at the Chair of Theoretical Physics – Nina Stockinger has always been interested in the natural sciences, but it only gradually became clear to her what she is most passionate about. When she realized that she wanted to delve deeper into theory and ultimately quantum computing, she pursued her path with even greater determination.
By Maria Poxleitner
“Group theory was the coolest.” Nina Stockinger sits at her desk in the shared office in the physics building at Friedrich-Alexander-Universität (FAU) in Erlangen. Surrounded by houseplants, a box of tea bags, and a small bowl of chocolates, the doctoral student has made her workspace by far the most comfortable. “A piece of chocolate is helpful for a little afternoon motivation,” says Nina and smiles. If she were to study again, she would probably choose physics, she reflects, pushing a brown strand of hair behind her ear. “But I didn't know back then that I would enjoy it so much.” Describing things mathematically and looking at them on an abstract level is something she finds “really nice!”. That an abstract theory such as group theory can be applied in many different ways, for example to describe molecules, the 26-year-old chemist also finds exciting.
Starting with a bachelor's degree in Applied Chemistry, Nina is now pursuing her Ph.D. at the FAU Chair of Quantum Theory: “In my group, we are working, among other things, on algorithms for quantum computers, which we want to use to calculate the electronic structure of molecules.” The electronic structure, which describes the distribution of electrons in the atoms of the molecule and thus its energy, is relevant for the development of materials, for example, or for predicting the reactivity of a chemical reaction, the chemist explains. The computational effort involved scales exponentially with the size of the molecule, Nina continues: “Even with a very small system, the computational effort is already so high that a conventional computer is often no longer able to determine the electronic structure with sufficient accuracy.” A quantum computer, however, can. There are already algorithms for so-called error-corrected quantum computers that can be used to determine the electronic structure – in theory, because: “It will still take time before error-corrected hardware is available. That's why we are trying to develop algorithms for quantum computers that are currently available or will be available in the near future.”
The fact that she is now pursuing a Ph.D. in theoretical physics does not mean that Nina – who loved trying out various experiment kits, growing crystals and reading scientific books as a child – did not enjoy experimenting in the lab. During her fourth semester of the bachelor's degree in Applied Chemisty at Technische Hochschule Nürnberg, there was a compulsory practical module. Nina went to the Fraunhofer Institute for Silicate Research in Würzburg. She really enjoyed working on a real research project and thinking about things that she could then try out directly in the lab, says the doctoral student. “The practical semester was super nice. I would say that was the best part of the degree.”
Nina Stockinger, 26
Position
Ph.D. student
Institute
FAU – Chair for Quantum Theory
THEQUCO
Degree
Chemistry
Nina is researching algorithms for so-called noisy intermediate-scale quantum (NISQ) computers. Specifically, she is studying algorithms for calculating the electronic structure of molecules, which, for example, plays an important role in chemical research and materials development.
The decisive drop
As the group leader, under whom she had worked at the Fraunhofer Institute, was appointed to a professorship at FAU in Erlangen, Nina was able to continue working on the project, first as a student assistant and then as part of an external bachelor's thesis – and not least contributed to a patent. The group researched nanoparticles made of silicon dioxide – “that is, what sand is made of” – which are combined to form a larger particle, a so-called supraparticle, the young chemist explains. “You can imagine it like a raspberry.” The special pore structure can absorb various substances, which can be exploited to create specific functionalities by adding particular building blocks, Nina continues. In the specific case of her bachelor's thesis, the aim was to develop a hydrogen sensor that could detect the invisible, odorless, and highly explosive gas. “Our aim was to develop an optical sensor that you can apply to pipes or gloves, for example, and then see directly through a color change whether hydrogen is leaking somewhere.” Nina's group spent a long time tinkering with the components needed for the hydrogen sensor. In addition to the right dye and suitable catalyst particles, the “raspberry” must absorb water for the sensor to work. She came across the latter by “just trying it out”, recalls the chemist with a laugh: “I was a bit desperate because it wasn't working. Then, I simply put a drop of water next to the particles and the water vapor, which was absorbed into the pore structure, finally caused the desired reaction.” As a student assistant, Nina discovered that water is required as a transport medium within the pore structure and is essential for the sensor's functionality. “For my bachelor's thesis, I optimized the sensor components, which resulted in the patent.”
She generally enjoyed the lab work during her studies, although she could have done without some of the courses. "In organic chemistry, you sometimes handle really toxic substances. And I'm also rather clumsy in everyday life...,” says Nina with a laugh. On the other hand, the theory behind it was often neglected more than she would have liked: “It never really went that deep.” She didn't have any theoretical chemistry or quantum mechanics in her bachelor's degree. That frustrated her a little. “At some point, we were always told that it was getting too theoretical, and we weren't going to do it anymore. But that's where I actually found it interesting! Because it's the most fundamental thing, everything in chemistry is based on quantum mechanics.” So she started borrowing books herself and watching YouTube videos to learn more about quantum mechanics.
By the time she finished her bachelor's degree, Nina knew she wanted to focus on theoretical chemistry for her master's. In her eyes, the best opportunity to specialize was the chemistry master's program at the Technical University of Munich (TUM), which allowed her to focus clearly on theoretical and physical chemistry. “That's why I really wanted to go there,” says the doctoral student. However, she applied to several universities: “I was missing a lot of subjects. That's why I first had to make sure that I was accepted at all." At TUM, she was able to make up for the missing subjects with a letter of motivation and an admissions interview. The latter was “actually really relaxed,” says Nina: “The most important thing for the examiners was to see that you are motivated and want to go through with it.”
“I was really up for it and really wanted it”
The young chemist knew exactly what she was getting into and her motivation could not have been higher. In the first semester of her master's degree, she had to do a lot, Nina recalls. She had to catch up, especially in basic mathematics and quantum mechanics. “But it did not feel like I had to learn; I was really up for it and really wanted it,” she emphasizes. From the second semester on, she was “fully into it.”
Quantum computing did not play a role for Nina at that time. It was not until her third semester of her master's program that she discovered her enthusiasm for it. Since she enjoyed the mathematical subjects, she was interested in the quantum computing lecture offered by the Department of Computer Science. The fact that fundamental quantum physics and application potential come together in this field excites the young theorist: “I find it super exciting that fundamental quantum effects, such as superposition and entanglement, are used to construct algorithms.” Algorithms that promise concrete applications, for example in chemistry. The first lecture was followed by “Advanced Quantum Computing” and a lecture on tensor networks, a method that can be used, among other things, to efficiently describe complex quantum systems. “I really enjoyed both lectures, and I knew then that I definitely wanted to go in this direction.” What she also liked about the quantum computing courses was that, unlike in some areas of theoretical chemistry, you had to do more programming yourself and rarely used existing programs. Even now, in her day-to-day work on her doctoral thesis, she writes a lot of code herself: “It's much more fun. You can be much more creative and fix mistakes yourself.”
Nina wrote her master's thesis in the same group where she is now pursuing her doctorate. “I definitely wanted to go into the field of algorithms,” she says, and the focus on quantum algorithms for the chemical sector fit well with her chemistry background. She believes that it would not have been so easy for her to write her master's thesis at FAU while enrolled at TUM without Munich Quantum Valley. The professors already knew each other very well, she says.
The doctoral student is thriving in her theoretical research on quantum algorithms. She has never regretted switching to theory. “It was definitely the right decision!” However, she has not completely given up her experimental side. Every once in a while, she does microscopy – just for fun, she admits with a laugh. She had a lot of fun doing it during her bachelor's degree, and at some point, she bought her own microscope to examine onion skin, pond water, and other things she finds around her. Now, however, her free time is dominated by padel tennis, a relatively new sport that, as Nina explains, is a bit like tennis with walls. She and her boyfriend tried it for the first time last year. “And now we're really addicted to it!” Nina laughs. They play padel every other day, ideally every day, for two, sometimes three hours. “And on weekends, when we're here, we play, too.” She particularly likes the long rallies possible thanks to the integrated walls: “Sometimes a hard ball comes, and you think it's over, but then it continues. That's always really cool. You're totally focused when you're playing.” The perfect opportunity to clear your head before getting back to all those formulas, programming codes, and computer simulations the next morning.
Published 31 July 2025; Interview 29 April 2025