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Quantum speed-up using quantum annealing to solve the 1D Fermi-Hubbard model

Kunal Vyas, Fengping Jin, Kristel F. L. Michielsen

Published Jan 1, 2025• 0 citations
Publisher

Abstract

The Fermi-Hubbard model has occupied the minds of condensed matter physicists for most part of the last century. With a simplistic form of the Hamiltonian, the model can potentially provide explanation to interesting phenomena in correlated electrons. The interest of our current work is the model in one dimension. The one-dimensional Fermi-Hubbard model has been extensively studied and there exist analytical results for determining its ground-state energy in the thermodynamic limit. We want to find the ground-state from the perspective of quantum computing. In particular, we employ the protocol of quantum annealing and perform high-performance simulations of the same using the Jülich Quantum Computer Simulator (JUQCS) for systems with up to 40 qubits. We learn that the time required to find the ground-state would scale sublinearly with system size for the half-filling cases considered.

DOI
10.34734/fzj-2025-03471

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The Fermi-Hubbard model has occupied the minds of condensed matter physicists for most part of the last century. With a simplistic form of the Hamiltonian, the model can potentially provide explanation to interesting phenomena in correlated electrons. The interest of our current work is the model in one dimension. The one-dimensional Fermi-Hubbard model has been extensively studied and there exist analytical results for determining its ground-state energy in the thermodynamic limit. We want to find the ground-state from the perspective of quantum computing. In particular, we employ the protocol of quantum annealing and perform high-performance simulations of the same using the Jülich Quantum Computer Simulator (JUQCS) for systems with up to 40 qubits. We learn that the time required to find the ground-state would scale sublinearly with system size for the half-filling cases considered.
The Fermi-Hubbard model has occupied the minds of condensed matter physicists for most part of the last century. With a simplistic form of the Hamiltonian, the model can potentially provide explanation to interesting phenomena in correlated electrons. The interest of our current work is the model in one dimension. The one-dimensional Fermi-Hubbard model has been extensively studied and there exist analytical results for determining its ground-state energy in the thermodynamic limit. We want to find the ground-state from the perspective of quantum computing. In particular, we employ the protocol of quantum annealing and perform high performance simulations of the same using the Juelich Quantum Computer Simulator (JUQCS) for systems with upto 40 qubits. We learn that the time required to find the ground-state would scale sublinearly with system size for the half-filling cases considered.
The Fermi-Hubbard model has occupied the minds of condensed matter physicists for most part of the last century. With a simplistic form of the Hamiltonian, the model can potentially provide explanation to interesting phenomena in correlated electrons. The interest of our current work is the model in one dimension. The one-dimensional Fermi-Hubbard model has been extensively studied and there exist analytical results for determining its ground-state energy in the thermodynamic limit. We want to find the ground-state from the perspective of quantum computing. In particular, we employ the protocol of quantum annealing and perform high performance simulations of the same using the Juelich Quantum Computer Simulator (JUQCS) for systems with upto 40 qubits. We learn that the time required to find the ground-state would scale sublinearly with system size for the half-filling cases considered.
The Hubbard model has occupied the minds of condensed matter physicists for most part of the last century. This model provides insight into a range of phenomena in correlated electron systems. We wish to examine the paradigm of quantum algorithms for solving such many-body problems. The focus of our current work is on the one-dimensional model that is integrable, meaning that there exist analytical results for determining its ground state. In particular, we demonstrate how to perform a gate-based quantum computer simulation of quantum annealing for the Hubbard Hamiltonian. We perform simulations for systems with up to 40 qubits to study the scaling of required annealing time for obtaining the ground state. We find that for the half-filled cases considered, there is a polynomial quantum speedup over algorithms based on the Bethe-ansatz equations.
The Hubbard model has occupied the minds of condensed matter physicists for most part of the last century. This model provides insight into a range of phenomena in correlated electron systems. We wish to examine the paradigm of quantum algorithms for solving such many-body problems. The focus of our current work is on the one-dimensional model that is integrable, meaning that there exist analytical results for determining its ground state. In particular, we demonstrate how to perform a gate-based quantum computer simulation of quantum annealing for the Hubbard Hamiltonian. We perform simulations for systems with up to 40 qubits to study the scaling of required annealing time for obtaining the ground state. We find that for the half-filled cases considered, there is a polynomial quantum speedup over algorithms based on the Bethe-ansatz equations.
Quantum simulation and near-term quantum algorithms have gained significant momentum over the past few years, with researchers exploring quantum-based approaches to solve classically intractable problems. Out of many research problems, certain problems are well suited for quantum algorithms. Fermi Hubbard model based on lattice structures is one of the quantum-mechanical models used in many-body and condensed matter physics to capture the essence of electron-correlated systems. In this work, we show one of the first kinds of experiments on simulating the ground state properties of 1D and 2D Fermi Hubbard-based lattice models compared with the reference ground state energy values using Qiskit Nature. We utilize the Variational Quantum Eigensolver (VQE) and different gradient-based optimizers to achieve results that closely converge towards the exact values, showcasing the potential of variational quantum algorithms.
We want to illustrate how to find the ground state of the one-dimensional Hubbard model. We start by introducing the classical algorithms that can do this, like exact diagonalization, Lanczos algorithm and the Bethe-ansatz equations. Subsequently, we show how to solve the problem on a gate-based quantum computer using the quantum annealing algorithm. The procedure involves transforming the fermionic Hamiltonian using the Jordan-Wigner transformation, preparing the initial state for quantum annealing using Givens rotations, and constructing the circuit for the time evolution according to the Schrodinger equation using the second-order product-formula algorithm. We conclude by presenting some results and analysis of performance for the quantum annealing algorithm.