Achieving quantum practicality via resource-efficient simulations of strongly correlated molecules on quantum computers 公开

Abstract

In this dissertation, we aim to demonstrate practical applications of quantum computers in the quantum simulation of many-body problems. The first contribution is the development of a multireference selected quantum Krylov (MRSQK) algorithm. MRSQK generates a target state by constructing a basis of non-orthogonal Krylov basis states via efficient unitary time evolution using a set of reference states. This approach eliminates the need for numerical optimization of parameters and addresses the linear dependency problem through a basis selection procedure. Benchmarks on various systems demonstrate the feasibility of MRSQK to use compact Krylov bases for predicting both ground state and excited state energies. The second contribution is the proposal of a quantum unitary downfolding formalism based on the driven similarity renormalization group (QDSRG). The QDSRG is a polynomial-scaling downfolding method that retains the accuracy of classical multireference many-body theories while avoiding the evaluation of costly higher-order reduced density matrices. This method effectively reduces the dimensionality of the problem and minimizes the required quantum resources, which enables resource-efficient simulations on small-scale quantum computers using large computational basis sets. We model the bicyclobutane isomerization pathways to trans-butadiene on IBM quantum devices, demonstrating the viability of QDSRG to leverage near-term quantum devices for estimating molecular properties with chemical accuracy. We then extend the QDSRG method to a state-averaged formalism (SA-QDSRG) that is capable of treating near-degenerate states which pose great challenges for many quantum chemical methods. The SA-QDSRG allows for simulating a conical intersection on the excited-state energy surfaces of ethylene as well as resolving complex energetics of a nonradiative photodynamical process on small-scale quantum processors. This highlights the versatility and potential of the QDSRG downfolding approach.

Table of Contents

1 Introduction

2 A multireference quantum Krylov algorithm for strongly-correlated electrons

3 Leveraging small scale quantum computers with unitarily downfolded Hamiltonians

4 Simulating conical intersections on quantum computers with unitarily downfolded Hamiltonians

5 Conclusions and perspectives

About this Dissertation

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School	Laney Graduate School
Department	Chemistry
Degree	Ph.D.
Submission	Dissertation
Language	English
Research Field	Physics, Molecular Chemistry, Physical Physics, Quantum
关键词	strongly correlated systems quantum computation quantum chemistry electronic structure theory quantum information quantum simulation quantum algorithms
Committee Chair / Thesis Advisor	Francesco A. Evangelista, Emory University
Committee Members	Fang Liu, Emory University Raphael F. Ribeiro, Emory University

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