By Herschel Rabitz

The notion of performing control operations to reach an objective is often a subject thought of as lying in the domain of engineering, but control is pervasive in the sciences. For example, the common action in a chemistry laboratory of choosing which chemicals to use can be viewed as a step in controlling a chemical reaction. Our research has a strong, but not exclusive, focus on control at the quantum mechanical level. In this context, we generally seek to alter the outcome of evolving molecular quantum dynamics phenomena dictated by Schrödinger’s equation, often by applying a shaped laser pulse referred to as a photonic reagent (i.e., applied to the molecule) in analogy with using a chemical reagent. Our research spans the regimes of seeking the limits of what may be achieved by controlling quantum phenomena out to finding high value applications. Theoretical analyses, computational modelling, and experimental realizations are all active research components. The fundamentals of this subject include exploration of why quantum control can work and also determination of how it works, where the latter topic includes revealing the mechanism by which quantum dynamics is manipulated.

The theoretical study of these topics calls for various mathematical analyses while computational efforts entailing molecular quantum dynamics simulations often involve algorithm development aiming to significantly reduce the high cost of modelling large polyatomic molecules undergoing quantum mechanical motion. Special concepts from artificial intelligence are being utilized for this purpose, where rather than traditionally having big data to work with, we have big quantum equations to be reduced in computational complexity.

Our experimental studies aim to assess the predictions of the aforementioned theoretical and computational findings as well as perform high value applications of quantum control. As one example, we are creating a unique microscope with the capability of viewing the smallest biologically relevant features in a single cell while also identifying which molecules are being observed. This experimental development is a major endeavor, drawing on all aspects of our collective studies. While undertaking many of the research ventures described above, new areas of study frequently arise, currently ranging from unraveling the secrets of quantum statistical mechanics out to devising concepts that can take quantum computing a step closer to practical realization. Our research group members act in an interactive mode, frequently crossing the boundaries between theory and experiment.

1. Quantum Information Sciences – Benjamin Lienhard
2. Utilizing machine learning to accelerate in the solution of dynamical equations in the sciences – Yiyou Chen
3. Solving the Schrödinger Equation by tracking the physical objective – Eden Michael and Yiyou Chen
4. Evaluating concepts from large language models (LLM) to capture the general behavior of dynamical systems – Yiyou Chen
5. Machine learning guided optimal control of quantum dynamics – Shaojun Gui and Tak-San Ho
6. Quantum Statistical Mechanics of complex systems – Peyman Azodi
7. Microscope project – Katerina Kanevche and Amr Sobeh
8. Exploring the origin of self-similar behavior of control across the sciences – Tak-San Ho
9. Determining the mechanisms by which a control manipulates quantum dynamics – Michael Kasprzak and Yiyou Chen
10. Electron transport is complex molecules and materials – Arzu Kurt