Corrected quantum walk for optimal Hamiltonian simulation

TL;DR

This paper introduces a corrected quantum walk method for Hamiltonian simulation on quantum computers, achieving near-optimal complexity and improving existing techniques, with potential applications in quantum chemistry.

Contribution

The authors develop a correction technique for quantum walk-based Hamiltonian simulation that attains near-optimal complexity bounds across all parameter regimes.

Findings

Achieves complexity close to the theoretical lower bound.

Applicable to quantum chemistry simulations.

Improves scaling of Taylor series methods.

Abstract

We describe a method to simulate Hamiltonian evolution on a quantum computer by repeatedly using a superposition of steps of a quantum walk, then applying a correction to the weightings for the numbers of steps of the quantum walk. This correction enables us to obtain complexity which is the same as the lower bound up to double-logarithmic factors for all parameter regimes. The scaling of the query complexity is $O\left( \tau \frac{\log\log\tau}{\log\log\log\tau} + \log(1/\epsilon) \right)$ where $\tau := t\|H\|_{\max}d$, for $\epsilon$ the allowable error, $t$ the time, $\|H\|_{\max}$ the max-norm of the Hamiltonian, and $d$ the sparseness. This technique should also be useful for improving the scaling of the Taylor series approach to simulation, which is relevant to applications such as quantum chemistry.