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Hamiltonian dynamics on digital quantum computers without discretization error
Computer Sciencenpj Quantum Information

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 computingexpectation valuesHamiltoniansalgorithmgate countsimulation
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