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Hamiltonian dynamics on digital quantum computers without discretization error

Computer Science

Hamiltonian dynamics on digital quantum computers without discretization error

E. Granet and H. Dreyer

Discover a groundbreaking algorithm by Etienne Granet and Henrik Dreyer that computes expectation values of time-evolved observables on digital quantum computers without any discretization error! This innovative method uses a finite number of gates while achieving arbitrary precision, poised to revolutionize the approach to non-sparse and time-dependent Hamiltonians.... show more
Abstract
We introduce an algorithm to compute expectation values of time-evolved observables on digital quantum computers that requires only bounded average circuit depth to reach arbitrary precision, i.e., it produces an unbiased estimator with finite average depth. This comes with a known attenuation factor that scales the measured expectation values and increases the number of shots, but the average gate count per circuit for simulation time t is O(t^2 μ^2), where μ is the sum of Hamiltonian coefficients, independent of precision. With shot noise, the average runtime is O(t^2 μ^2 ε^-2) to reach precision ε. The algorithm is particularly advantageous for non-sparse Hamiltonians and generalizes seamlessly to time-dependent Hamiltonians. These features make it suitable for near-term, noisy hardware with moderate circuit depth. We demonstrate performance on electronic structure (stretched H2O) and a 2D Ising model, outperforming Trotter and randomized compilation methods.
Publisher
npj Quantum Information
Published On
Sep 07, 2024
Authors
Etienne Granet, Henrik Dreyer
Tags
quantum computing
expectation values
Hamiltonians
algorithm
gate count
simulation
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