Estimating Trotter Approximation Errors to Optimize Hamiltonian Partitioning for Lower Eigenvalue Errors

• URL: http://arxiv.org/abs/2312.13282v2
• Date: Mon, 1 Jan 2024 20:48:32 GMT
• Title: Estimating Trotter Approximation Errors to Optimize Hamiltonian Partitioning for Lower Eigenvalue Errors
• Authors: Luis A. Mart\'inez-Mart\'inez, Prathami Divakar Kamath and Artur F. Izmaylov
• Abstract summary: Trotter approximation error estimation based on perturbation theory up to a second order in the time-step for eigenvalues provides estimates with very good correlations with the Trotter approximation errors. The developed perturbative estimates can be used for practical time-step and Hamiltonian partitioning selection protocols.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: One of the ways to encode many-body Hamiltonians on a quantum computer to obtain their eigen-energies through Quantum Phase Estimation is by means of the Trotter approximation. There were several ways proposed to assess the quality of this approximation based on estimating the norm of the difference between the exact and approximate evolution operators. Here, we would like to explore how these different error estimates are correlated with each other and whether they can be good predictors for the true Trotter approximation error in finding eigenvalues. For a set of small molecular systems we calculated the exact Trotter approximation errors of the first order Trotter formulas for the ground state electronic energies. Comparison of these errors with previously used upper bounds show almost no correlation over the systems and various Hamiltonian partitionings. On the other hand, building the Trotter approximation error estimation based on perturbation theory up to a second order in the time-step for eigenvalues provides estimates with very good correlations with the Trotter approximation errors. The developed perturbative estimates can be used for practical time-step and Hamiltonian partitioning selection protocols, which are paramount for an accurate assessment of resources needed for the estimation of energy eigenvalues under a target accuracy.

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