Research Topics

The nonequilibrium excited-state dynamics in organic conjugated molecules, molecular aggregates, and molecular crystals are crucial for their optoelectronic performance. Our research focuses on understanding the microscopic mechanisms of electronic processes, including energy transfer, transport, separation, and relaxation. By applying tensor-network-based quantum dynamics methods, we aim to reveal how electronic structure and electron–vibration coupling influence these dynamics, thereby bridging theoretical predictions with emerging experimental observations in molecular optoelectronics. Recently, we found that excitonic coupling can greatly influence the nonradiative decay rate in molecular aggregates, leading to an apparent "violation" of the classical energy gap law [1-2].

Exact simulation of high-dimensional quantum dynamics faces the quantum exponential wall, where computational cost scales exponentially with system size. To overcome this, we develop highly accurate and efficient tensor-network algorithms, particularly the time-dependent density matrix renormalization group (TD-DMRG) method, incorporating optimized operator factorization and time-evolution schemes. These methods enable the scalable and accurate treatment of electron–vibration coupled dynamics, providing powerful tools for photophysical processes in complex environments [3]. We recently developed a hybrid method that integrates tensor-network algorithms with the real-time path integral approach for simulating dissipative open-system dynamics [4].

Simulating quantum dynamics on quantum devices is an exciting frontier, yet current algorithms for closed and open quantum systems remain challenging. Furthermore, today’s hardware is limited by noise. Our goal is twofold: (1) to design quantum dynamics algorithms with genuine quantum advantage for future fault-tolerant quantum computers; and (2) to develop hybrid quantum–classical approaches that extract meaningful results on noisy intermediate-scale quantum (NISQ) devices. We are also exploring quantum-inspired classical algorithms and classically-inspired quantum algorithms, leveraging insights from both paradigms. Recently, inspired by the multi-set wavefunction formalism used in classical tensor network algorithms, we have proposed a multi-set variational quantum dynamics algorithm that extends quantum simulations to nonadiabatic problems [5].