Nearly-optimal state preparation for quantum simulations of lattice gauge theories

• URL: http://arxiv.org/abs/2310.13757v2
• Date: Sun, 21 Jan 2024 01:00:55 GMT
• Title: Nearly-optimal state preparation for quantum simulations of lattice gauge theories
• Authors: Christopher F. Kane and Niladri Gomes and Michael Kreshchuk
• Abstract summary: We present several improvements to the recently developed ground state preparation algorithm based on the Quantum Eigenvalue Transformation for Unitary Matrices (QETU) We use QETU to prepare the ground state of a U(1) lattice gauge theory in 2 spatial dimensions. We also propose a novel application of QETU, a highly efficient preparation of Gaussian distributions.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We present several improvements to the recently developed ground state preparation algorithm based on the Quantum Eigenvalue Transformation for Unitary Matrices (QETU), apply this algorithm to a lattice formulation of U(1) gauge theory in 2+1D, as well as propose a novel application of QETU, a highly efficient preparation of Gaussian distributions. The QETU technique has been originally proposed as an algorithm for nearly-optimal ground state preparation and ground state energy estimation on early fault-tolerant devices. It uses the time-evolution input model, which can potentially overcome the large overall prefactor in the asymptotic gate cost arising in similar algorithms based on the Hamiltonian input model. We present modifications to the original QETU algorithm that significantly reduce the cost for the cases of both exact and Trotterized implementation of the time evolution circuit. We use QETU to prepare the ground state of a U(1) lattice gauge theory in 2 spatial dimensions, explore the dependence of computational resources on the desired precision and system parameters, and discuss the applicability of our results to general lattice gauge theories. We also demonstrate how the QETU technique can be utilized for preparing Gaussian distributions and wave packets in a way which outperforms existing algorithms for as little as $n_q \gtrsim 2-5$ qubits.

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