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Precision Chemistry

Quantum Computer Simulation of Molecules in Optical Cavity

Zirui Sheng, Yufei Ge, Jianpeng Chen, Weitang Li, Zhigang Shuai

Published May 12, 2025• 4 citations
Publisher

Abstract

High Resolution Image Download MS PowerPoint Slide Various phenomena have been observed in molecule–cavity coupled systems, which are believed to hold potential for applications in transistors, lasers, and computational units, among others. However, theoretical methods for simulating molecules in optical cavities still require further development due to the complex couplings between electrons, phonons, and photons within the cavity. In this study, motivated by recent advances in quantum algorithms and quantum computing hardware, we propose a quantum computing algorithm tailored for molecules in optical cavities. Our method, based on a variational quantum algorithm and variational boson encoders, has its effectiveness validated on both quantum simulators and hardware. For aggregates within the cavity, described by the Holstein–Tavis–Cummings model, our approach demonstrates clear advantages over other quantum and classical methods, as proved by numerical benchmarks. Additionally, we apply this method to study the H 2 molecule in a cavity using a superconducting quantum computer and the Pauli–Fierz model. To enhance accuracy, we incorporate error mitigation techniques, such as readout and reference-state error mitigation, resulting in an 86% reduction in the average error.

DOI
10.1021/prechem.4c00108

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High Resolution Image Download MS PowerPoint Slide Various phenomena have been observed in molecule–cavity coupled systems, which are believed to hold potential for applications in transistors, lasers, and computational units, among others. However, theoretical methods for simulating molecules in optical cavities still require further development due to the complex couplings between electrons, phonons, and photons within the cavity. In this study, motivated by recent advances in quantum algorithms and quantum computing hardware, we propose a quantum computing algorithm tailored for molecules in optical cavities. Our method, based on a variational quantum algorithm and variational boson encoders, has its effectiveness validated on both quantum simulators and hardware. For aggregates within the cavity, described by the Holstein–Tavis–Cummings model, our approach demonstrates clear advantages over other quantum and classical methods, as proved by numerical benchmarks. Additionally, we apply this method to study the H 2 molecule in a cavity using a superconducting quantum computer and the Pauli–Fierz model. To enhance accuracy, we incorporate error mitigation techniques, such as readout and reference-state error mitigation, resulting in an 86% reduction in the average error.
We explore the potential for hybrid development of quantum hardware where currently available quantum computers simulate open cavity quantum electrodynamical (CQED) systems for applications in optical quantum communication, simulation and computing. Our simulations make use of a recent quantum algorithm that maps the dynamics of a singly excited open Tavis-Cummings model containing N atoms coupled to a lossy cavity. We report the results of executing this algorithm on two noisy intermediate-scale quantum computers: a superconducting processor and a trapped ion processor, to simulate the population dynamics of an open CQED system featuring N = 3 atoms. By applying technology-specific transpilation and error mitigation techniques, we minimize the impact of gate errors, noise, and decoherence in each hardware platform, obtaining results which agree closely with the exact solution of the system. These results can be used as a recipe for efficient and platform-specific quantum simulation of cavity-emitter systems on contemporary and future quantum computers.
Abstract We explore the potential for hybrid development of quantum hardware where currently available quantum computers simulate open cavity quantum electrodynamical (CQED) systems for applications in optical quantum communication, simulation and computing. Our simulations make use of a recent quantum algorithm that maps the dynamics of a singly excited open Tavis–Cummings model containing N atoms coupled to a lossy cavity. We report the results of executing this algorithm on two noisy intermediate-scale quantum computers: a superconducting processor and a trapped ion processor, to simulate the population dynamics of an open CQED system featuring N = 3 atoms. By applying technology-specific transpilation and error mitigation techniques, we minimize the impact of gate errors, noise, and decoherence in each hardware platform, obtaining results which agree closely with the exact solution of the system. These results can be used as a recipe for efficient and platform-specific quantum simulation of cavity–emitter systems on contemporary and future quantum computers.
We explore the potential for hybrid development of quantum hardware where currently available quantum computers simulate open Cavity Quantum Electrodynamical (CQED) systems for applications in optical quantum communication, simulation and computing. Our simulations make use of a recent quantum algorithm that maps the dynamics of a singly excited open Tavis-Cummings model containing N atoms coupled to a lossy cavity. We report the results of executing this algorithm on two noisy intermediate-scale quantum computers: a superconducting processor and a trapped ion processor, to simulate the population dynamics of an open CQED system featuring N = 3 atoms. By applying technology-specific transpilation and error mitigation techniques, we minimize the impact of gate errors, noise, and decoherence in each hardware platform, obtaining results which agree closely with the exact solution of the system. These results can be used as a recipe for efficient and platform-specific quantum simulation of cavity-emitter systems on contemporary and future quantum computers.
Quantum mechanics has introduced a new theoretical framework for the study of molecules, enabling the prediction of properties and dynamics through the solution of the Schrödinger equation applied to these systems. However, solving this equation is computationally expensive, which has led to the development of various mathematical frameworks and computational methods designed to balance the available resources with the desired level of accuracy. In particular, quantum computers have emerged as a promising technology with the potential to address these problems more efficiently in the coming decades, whether through reductions in memory, time, and energy consumption, i. e.\textit{i. e.}i. e., reductions in computational complexity or by enhancing precision. This research field is known as Quantum Simulation. Given the current technological limitations of quantum computers, Variational Quantum Algorithms (VQAs), especially the Variational Quantum Eigensolver (VQE), stand out as a feasible approach to demonstrating advantages over classical methods in the near term. This feasibility arises from their lower demand for quantum gates and the reduced depth of the circuits required for their implementation. In this work, we present the application of quantum mechanics to the study of molecules, provide an introduction to the fundamentals of quantum computing, and explore the integration of these fields by employing the VQE in molecular simulations. Finally, we discuss the spatial and temporal complexity associated with the algorithm, highlighting its implications and challenges.
Quantum computing has emerged as a transformative paradigm capable of solving complex computational problems that are intractable for classical computers. Central to the advancement of this technology is the development of efficient quantum algorithms and high fidelity simulations that enable the design, testing, and optimization of quantum solutions before deployment on physical hardware. This study focuses on the design and implementation of quantum algorithms tailored for solving a variety of quantum problems, including quantum chemistry, optimization, and cryptography. Using state of the art simulation platforms such as Qiskit, Cirq, and Pennylane, algorithm performance was evaluated in terms of accuracy, execution time, scalability, and resilience to noise. Benchmarks demonstrate that algorithms such as the Variational Quantum Eigensolver (VQE) and Quantum Approximate Optimization Algorithm (QAOA) achieve significant speedups in problem specific domains, while hybrid quantum–classical methods provide robust pathways for near term quantum advantage. Simulation results reveal that algorithmic efficiency can be significantly improved through optimized circuit depth, qubit connectivity mapping, and advanced error mitigation techniques. The findings highlight the potential of simulation driven quantum algorithm development in accelerating the practical realization of quantum computing applications across disciplines such as materials discovery, molecular modeling, secure communications, and complex optimization tasks.