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Published May 2023 | Published
Journal Article Open

Complexity of Implementing Trotter Steps

Abstract

Quantum dynamics can be simulated on a quantum computer by exponentiating elementary terms from the Hamiltonian in a sequential manner. However, such an implementation of Trotter steps has gate complexity depending on the total Hamiltonian term number, comparing unfavorably to algorithms using more advanced techniques. We develop methods to perform faster Trotter steps with complexity sublinear in the number of terms. We achieve this for a class of Hamiltonians whose interaction strength decays with distance according to power law. Our methods include one based on a recursive block encoding and one based on an average-cost simulation, overcoming the normalization-factor barrier of these advanced quantum simulation techniques. We also realize faster Trotter steps when certain blocks of Hamiltonian coefficients have low rank. Combining with a tighter error analysis, we show that it suffices to use (η^(1/3)n^(1/3)+(n^(2/3))/(η^(2/3)))n^(1+o(1)) gates to simulate uniform electron gas with n spin orbitals and η electrons in second quantization in real space, asymptotically improving over the best previous work. We obtain an analogous result when the external potential of nuclei is introduced under the Born-Oppenheimer approximation. We prove a circuit lower bound when the Hamiltonian coefficients take a continuum range of values, showing that generic n-qubit two-local Hamiltonians with commuting terms require at least Ω(n^2) gates to evolve with accuracy ϵ=Ω(1/poly(n)) for time t=Ω(ϵ). Our proof is based on a gate-efficient reduction from the approximate synthesis of diagonal unitaries within the Hamming weight-2 subspace, which may be of independent interest. Our result thus suggests the use of Hamiltonian structural properties as both necessary and sufficient to implement Trotter steps with lower gate complexity.

Additional Information

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI. Y.S. thanks Ryan Babbush for helpful discussions during the initial stages of this work. We thank Wim van Dam for his comments on an earlier draft. Y.T. acknowledges funding from the U.S. Department of Energy Office of Science, Office of Advanced Scientific Computing Research, (DE-NA0003525, and DE-SC0020290). Work supported by DE-SC0020290 is supported by the DOE QuantISED program through the theory consortium "Intersections of QIS and Theoretical Particle Physics" at Fermilab. The Institute for Quantum Information and Matter is an NSF Physics Frontiers Center. M.C.T. is supported by the Defense Advanced Research Project Agency (DARPA) under Contract No. 134371-5113608 and the Quantum Algorithms and Machine Learning Grant from Nippon Telegraph and Telephone (NTT), No. AGMT DTD 9/24/20.

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Additional details

Created:
August 22, 2023
Modified:
October 20, 2023