Estimating properties of a quantum state by importance-sampled operator shadows

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Guo, Naixu, Pan, Feng, Rebentrost, Patrick
Format: Preprint
Published: 2023
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866907839464734720
author Guo, Naixu
Pan, Feng
Rebentrost, Patrick
author_facet Guo, Naixu
Pan, Feng
Rebentrost, Patrick
contents Measuring properties of quantum systems is a fundamental problem in quantum mechanics. We provide a simple method for estimating the expectation value of observables with an unknown quantum state. The idea is to use a data structure to sample the terms of observables based on the Pauli decomposition proportionally to their importance. We call this technique operator shadow as a shorthand for the procedure of preparing a sketch of an operator to estimate properties. Only when the numbers of observables are small for multiple local observables, the sample complexity of this method is better than the classical shadow technique. However, if we want to estimate the expectation value of a linear combination of local observables, for example the energy of a local Hamiltonian, the sample complexity is better on all parameters. The time complexity to construct the data structure is $2^{O(k)}$ for $k$-local observables, similar to the post-processing time of classical shadows.
format Preprint
id arxiv_https___arxiv_org_abs_2305_09374
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Estimating properties of a quantum state by importance-sampled operator shadows
Guo, Naixu
Pan, Feng
Rebentrost, Patrick
Quantum Physics
Measuring properties of quantum systems is a fundamental problem in quantum mechanics. We provide a simple method for estimating the expectation value of observables with an unknown quantum state. The idea is to use a data structure to sample the terms of observables based on the Pauli decomposition proportionally to their importance. We call this technique operator shadow as a shorthand for the procedure of preparing a sketch of an operator to estimate properties. Only when the numbers of observables are small for multiple local observables, the sample complexity of this method is better than the classical shadow technique. However, if we want to estimate the expectation value of a linear combination of local observables, for example the energy of a local Hamiltonian, the sample complexity is better on all parameters. The time complexity to construct the data structure is $2^{O(k)}$ for $k$-local observables, similar to the post-processing time of classical shadows.
title Estimating properties of a quantum state by importance-sampled operator shadows
topic Quantum Physics
url https://arxiv.org/abs/2305.09374