Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Bell Sampling from Quantum Circuits

Published

Author(s)

Dominik Hangleiter, Michael Gullans

Abstract

A central challenge in the verification of quantum computers is benchmarking their performance as a whole and demonstrating their computational capabilities. In this work, we find a model of quantum computation, Bell sampling, that can be used for both of those tasks and thus provides an ideal stepping stone towards fault-tolerance. In Bell sampling, we measure two copies of a state prepared by a quantum circuit in the transversal Bell basis. We show that the Bell samples are classically intractable to produce and at the same time constitute what we call a circuit shadow: from the Bell samples we can efficiently extract information about the quantum circuit preparing the state, as well as diagnose circuit errors. In addition to known properties that can be efficiently extracted from Bell samples, we give two new and efficient protocols, a test for the depth of the circuit and an algorithm to estimate a lower bound to the number of T gates in the circuit. With some additional measurements, our algorithm learns a full description of states prepared by circuits with low T -count.
Citation
Physical Review Letters
Volume
133
Issue
2

Keywords

Quantum computing, complexity theory, quantum verification

Citation

Hangleiter, D. and Gullans, M. (2024), Bell Sampling from Quantum Circuits, Physical Review Letters, [online], https://doi.org/10.1103/PhysRevLett.133.020601, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=956230 (Accessed July 22, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created July 8, 2024, Updated July 18, 2024