Simultaneous Perturbation Stochastic Approximation of the Quantum Fisher Information


Date

2021-03

Publication Type

Journal Article

ETH Bibliography

yes

Citations

Altmetric

Data

Abstract

The Quantum Fisher Information matrix (QFIM) is a central metric in promising algorithms, such as Quantum Natural Gradient Descent and Variational Quantum Imaginary Time Evolution. Computing the full QFIM for a model with d parameters, however, is computation-ally expensive and generally requires O(d(2)) function evaluations. To remedy these increasing costs in high-dimensional parameter spaces, we propose using simultaneous perturbation stochastic approximation techniques to approximate the QFIM at a constant cost. We present the resulting algorithm and successfully apply it to prepare Hamiltonian ground states and train Variational Quantum Boltzmann Machines.

Publication status

published

Editor

Book title

Journal / series

Volume

5

Pages / Article No.

567

Publisher

Verein zur Forderung des Open Access Publizierens in den Quantenwissenschaften

Event

Edition / version

Methods

Software

Geographic location

Date collected

Date created

Subject

Organisational unit

03781 - Renner, Renato / Renner, Renato check_circle

Notes

Funding

Related publications and datasets

Is new version of: