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arXiv:2408.16175

Studies of the Fermi-Hubbard Model Using Quantum Computing

Adam Prokofiew, Sharma, Nidhish, Steven Schnetzer

Published Aug 28, 2024• 0 citations
arXivHTMLPDF

Abstract

The use of quantum computers to calculate the ground state (lowest) energies of a spin lattice of electrons described by the Fermi-Hubbard model of great importance in condensed matter physics has been studied. The ability of quantum bits (qubits) to be in a superposition state allows quantum computers to perform certain calculations that are not possible with even the most powerful classical (digital) computers. This work has established a method for calculating the ground state energies of small lattices which should be scalable to larger lattices that cannot be calculated by classical computers. Half-filled lattices of sizes 1x4, 2x2, 2x4, and 3x4 were studied. The calculated energies for the 1x4 and 2x2 lattices without Coulomb repulsion between the electrons and for the 1x4 lattice with Coulomb repulsion agrees with the true energies to within 0.60%, while for the 2x2 lattice with Coulomb repulsion the agreement is within 1.50% For the 2x4 lattice, the true energy without Coulomb repulsion was found to agree within 0.18%.

DOI
10.48550/arxiv.2408.16175

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A Quantum Monte Carlo method of calculating operator expectation values for the ground state of the nearest-neighbor Heisenberg model on large square lattices is presented, along with some comparisons of the results obtained from this method and alternative methods for 2D lattices. In the simulations the ground state is projected out from an arbitrary state and sampled in a valence\nbond basis spanning the spin singlet subspace. The projection method is then extended to be used on a simplified Hubbard model at half-filling, which is\naptly called the T0-less Hubbard model, for arbitrary relative strengths of the electron hopping and electron-electron repulsion energy parameters. Results for calculated ground state energies in 1D are presented. These calculations are performed using a spin-charge separated basis, in which the valence bonds\nare generalized to also carry charge.
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.
Simulating the Hubbard model is of great interest to a wide range of applications within condensed matter physics, however its solution on classical computers remains challenging in dimensions larger than one. The relative simplicity of this model, embodied by the sparseness of the Hamiltonian matrix, allows for its efficient implementation on quantum computers, and for its approximate solution using variational algorithms such as the variational quantum eigensolver. While these algorithms have been shown to reproduce the qualitative features of the Hubbard model, their quantitative accuracy in terms of producing true ground state energies and other properties, and the dependence of this accuracy on the system size and interaction strength, the choice of variational ansatz, and the degree of spatial inhomogeneity in the model, remains unknown. Here we present a rigorous classical benchmarking study, demonstrating the potential impact of these factors on the accuracy of the variational solution of the Hubbard model on quantum hardware, for systems with up to 32 qubits. We find that even when using the most accurate wavefunction ansätze for the Hubbard model, the error in its ground state energy and wavefunction plateaus for larger lattices, while stronger electronic correlations magnify this issue. Concurrently, spatially inhomogeneous parameters and the presence of off-site Coulomb interactions only have a small effect on the accuracy of the computed ground state energies. Our study highlights the capabilities and limitations of current approaches for solving the Hubbard model on quantum hardware, and we discuss potential future avenues of research.
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.