Nonadiabatic Nuclear-Electron Dynamics: A Quantum Computing Approach

Multiset Variational Quantum Dynamics Algorithm for Simulating Nonadiabatic Dynamics on Quantum Computers

Accelerating quantum dynamical simulations with quantum computing has received considerable attention but remains a significant challenge. In variational quantum algorithms for quantum dynamics, designing an expressive and shallow-depth parametrized quantum circuit (PQC) is a key difficulty. Here, we propose a multiset variational quantum dynamics algorithm (MS-VQD) tailored for nonadiabatic dynamics involving multiple electronic states. The MS-VQD employs multiple PQCs to represent the electronic-nuclear coupled wave function, with each circuit adapting to the motion of the nuclear wavepacket on a specific potential energy surface. By simulating excitation energy transfer dynamics in molecular aggregates described by the Frenkel-Holstein model, we demonstrate that the MS-VQD achieves the same accuracy as the traditional VQD while requiring significantly shallower PQCs. Notably, its advantage increases with the number of electronic states, making it suitable for simulating nonadiabatic quantum dynamics in complex molecular systems.

Prioritizing quantum computing use cases in the drug discovery and development pipeline

Recent innovations in quantum computing hardware and algorithms have raised expectations that practical, real-world applications are within reach. In this context, we explore the potential impact of quantum computing on the drug discovery and development pipeline. Specifically, we discuss use cases from our research programs and outline approaches for prioritizing them based on our assessment of potential benefit from quantum computation. We identify and discuss specific classes of quantum chemistry problems that present challenges for classical computing methods, and where we have made initial efforts to develop and apply quantum computing algorithms. Finally, we offer a perspective on opportunities that will become available as we enter the early-fault tolerant era.

Nonadiabatic Molecular Dynamics with Fermionic Subspace-Expansion Algorithms on Quantum Computers

We introduce a novel computational framework for excited-state molecular quantum dynamics simulations driven by quantum-computing-based electronic-structure calculations. This framework leverages the fewest-switches surface-hopping method for simulating the nuclear dynamics and calculates the required excited-state transition properties with different flavors of the quantum subspace expansion and quantum equation-of-motion algorithms. We apply our method to simulate the collision reaction between a hydrogen atom and a hydrogen molecule. For this system, we critically compare the accuracy and efficiency of different quantum subspace expansion and equation-of-motion algorithms and show that only methods that can capture both weak and strong electron correlation effects can properly describe the nonadiabatic effects that tune the reactive event.

A Quantum Algorithm from Response Theory: Digital Quantum Simulation of Two-Dimensional Electronic Spectroscopy

Multidimensional optical spectroscopies are powerful techniques to investigate energy transfer pathways in natural and artificial systems. Because of the high information content of the spectra, numerical simulations of the optical response are of primary importance to assist the interpretation of spectral features. However, the increasing complexity of the investigated systems and their quantum dynamics call for the development of novel simulation strategies. In this work, we consider using digital quantum computers. By combining quantum dynamical simulation and nonlinear response theory, we present a quantum algorithm for computing the optical response of molecular systems. The quantum advantage stems from the efficient quantum simulation of the dynamics governed by the molecular Hamiltonian, and it is demonstrated by explicitly considering exciton-vibrational coupling. The protocol is tested on a near-term quantum device, providing the digital quantum simulation of the linear and nonlinear response of simple molecular models.

Toward Accurate Post-Born-Oppenheimer Molecular Simulations on Quantum Computers: An Adaptive Variational Eigensolver with Nuclear-Electronic Frozen Natural Orbitals

Nuclear quantum effects such as zero-point energy and hydrogen tunneling play a central role in many biological and chemical processes. The nuclear-electronic orbital (NEO) approach captures these effects by treating selected nuclei quantum mechanically on the same footing as electrons. On classical computers, the resources required for an exact solution of NEO-based models grow exponentially with system size. By contrast, quantum computers offer a means of solving this problem with polynomial scaling. However, due to the limitations of current quantum devices, NEO simulations are confined to the smallest systems described by minimal basis sets, whereas realistic simulations beyond the Born-Oppenheimer approximation require more sophisticated basis sets. For this purpose, we herein extend a hardware-efficient ADAPT-VQE method to the NEO framework in the frozen natural orbital (FNO) basis. We demonstrate on H2 and D2 molecules that the NEO-FNO-ADAPT-VQE method reduces the CNOT count by several orders of magnitude relative to the NEO unitary coupled cluster method with singles and doubles while maintaining the desired accuracy. This extreme reduction in the CNOT gate count is sufficient to permit practical computations employing the NEO method─an important step toward accurate simulations involving nonclassical nuclei and non-Born-Oppenheimer effects on near-term quantum devices. We further show that the method can capture isotope effects, and we demonstrate that inclusion of correlation energy systematically improves the prediction of difference in the zero-point energy (ΔZPE) between isotopes.