Computer simulations have transformed our approach to understanding nature. Digital models of our world not only provide faster and cheaper ways for researchers to explore new frontiers, but also enable them to validate theories that are difficult to test in laboratory settings. Today, insights from computational models aid scientists at scales large and small: from predicting extreme weather events to identifying new medicinal molecules.
However, even today’s most advanced supercomputers can struggle to accurately replicate how the simplest molecules behave in chemical reactions. To efficiently model such reactions on classical computing architectures, scientists often rely on approximations of the physical properties involved, which can fail to fully capture the complex interactions of individual atoms and molecules.
Researchers like A*STAR National Scholar Karthik Shreekumar Panicker believe that quantum computing offers researchers a way to model real-world chemistry with greater precision. Rooted in the principles of quantum mechanics—the science of the tiny—quantum computers have the potential to simulate the energetics of atoms and subatomic particles with a higher degree of confidence. Such systems can benefit fields other than chemistry; quantum-powered insights can speed up the discovery of new drug candidates, catalysts and materials.
Piqued by a mutual interest in quantum physics and computational chemistry, Panicker aims to use his cross-disciplinary experiences to support the expanding field of quantum chemistry and the promise it offers for natural science. In this interview with A*STAR Research, Panicker shares some highlights from his scientific journey to date, his motivations in the dynamic world of science, and advice for other early-career researchers.
What brought you to your current research focus?
It all began in secondary school, when I had the opportunity to work on a computational chemistry research project. I was introduced to the world of theoretical research in chemistry: an eye-opening experience that I thoroughly enjoyed. However, I decided to follow my passion for physics and majored in it for my bachelor’s degree. After graduating, I knew I wanted to pursue a PhD in the field of quantum sciences, though I was unsure of the specifics involved.
Fortunately, during my one-year research assistantship at A*STAR, I received a lot of support and advice from experts in the field and my peers. My work during that year was in the field of quantum optics at IMRE under Victor Leong. This was my first hands-on research experience in quantum physics, and I got to explore and discuss new ideas in and around the subfield.
These insightful discussions helped me discover my true interest in quantum computing for chemistry, bringing my research full circle. Throughout this journey, the National Science Scholarship helped me gain valuable experience in diverse fields, allowing me to make informed decisions about my future.
What makes quantum computing an exciting field to explore?
The field has been quietly making strides over the years. Within the next decade or so, quantum computing is expected to mature enough to be able to make significant contributions to society. One major anticipated benefit from the technology is its ability to simulate chemical reactions on a more exact level, given that atoms and molecules operate on inherently quantum mechanical principles. This could revolutionise fields like drug discovery, materials design and so on.
It is also exciting to be part of an actively growing area of research that openly encourages new ideas. Considering my interests and background, pursuing this field for my PhD was a natural choice.
Tell us about your current work.
ChatGPT has captivated the world in recent times. At the University of Toronto, I’m currently working under Alán Aspuru-Guzik to harness its underlying model to design quantum circuits that can accurately simulate molecules in chemistry. Quantum circuits are specialised computational pathways that use the principles of quantum mechanics; where classical circuits rely on bits, which can only exist as one of two values (‘0’ and ‘1’), quantum circuits use qubits, which can exist as multiple values. It is this fundamental difference that allows quantum computers to be able to solve certain problems much faster than classical computers.
To date, precise molecular modelling has been prohibitively expensive on conventional computers. Finding a scalable way to do this on quantum computers would be a breakthrough.
What are some other research projects you’ve worked on at A*STAR?
I have predominantly worked on physics research projects throughout my time with the agency, albeit in different areas. It all started with a research project about thin-film solar cells which aimed to improve the fabrication processes involved. It was an integral experience that taught me about how communication and research is carried out within a large institute.
My research attachment with IMRE was about the use of integrated photonics for single-photon detectors. I learned a lot of hard skills during that year about how to set up a scientifically sound experiment, including the extremely hands-on task of creating all the necessary parts from the ground up. Over the years, I’ve gotten to develop different skills due to the different experiences I had. Perhaps this breadth of experience encouraged me to pursue interdisciplinary areas of research for my PhD.
As an early-career researcher, what excites you about your journey ahead?
The ever-evolving world of science makes it challenging to predict its future when I graduate. Science will continue answering questions while sparking new ones in the process. This can be equal parts nerve-wracking and thrilling. However, as a quantum computing researcher, I find Singapore’s commitment to invest in quantum technologies particularly exciting.
What advice would you give those pursuing their own STEM careers?
I think it can be succinctly expressed by an Oscar Wilde quote, which Stephen Fry summarised as: “If you know what you want to be, then you inevitably become it—that is your punishment. But if you never know, then you can be anything.”
It’s okay not to have your career path figured out at 18. Even most PhD graduates don’t end up working on the exact problem they wrote their thesis on. In my opinion, it’s best to have a broader understanding of your choices and learn to view problems from different perspectives.
