Title: Qubit Assignment Using Time Reversal

Abstract

As quantum computers with large numbers of qubits become increasingly available, experiments executed on a given device may not utilize all available qubits. In this case, the outcome of executing a quantum program will depend on the ability to efficiently select a subset of high-performing physical qubits. For any given quantum program and device there are many ways to assign physical qubits for execution of the program, and assignments will differ in performance due to the variability in quality across qubits and entangling operations on a single device. Evaluating the performance of each assignment using fidelity estimation introduces significant experimental overhead and will be infeasible for many applications, while relying on standard device benchmarks provides incomplete information about the performance of any specific program. Furthermore, the number of possible assignments grows combinatorially in the number of qubits on the device and in the program, motivating the use of heuristic optimization techniques. We demonstrate a practical solution to the problem of qubit assignment by using simulated annealing with a cost function based on the Loschmidt echo, a diagnostic that measures the reversibility of a quantum process. We provide theoretical justification for this choice of cost function by demonstrating that the optimalmore » qubit assignment coincides with the optimal qubit assignment based on state fidelity in the weak error limit, and we provide experimental justification using diagnostics performed on Google’s superconducting qubit devices. We then establish the performance of simulated annealing for qubit assignment using classical simulations of noisy devices as well as optimization experiments performed on a quantum processor. Our results demonstrate that the use of Loschmidt echoes and simulated annealing provides a scalable and flexible approach to optimizing qubit assignment on near-term hardware.« less

Authors:

Peters, Evan  ^[1];

• Search DOE PAGES for author "Peters, Evan"
• Search DOE PAGES for ORCID "0000-0001-7083-6733"

Shyamsundar, Prasanth  ^[2];

• Search DOE PAGES for author "Shyamsundar, Prasanth"
• Search DOE PAGES for ORCID "0000-0002-2748-9091"

Li, Andy C.Y.  ^[2];

• Search DOE PAGES for author "Li, Andy C.Y."
• Search DOE PAGES for ORCID "0000-0003-4542-3739"

Perdue, Gabriel  ^[2]

• Search DOE PAGES for author "Perdue, Gabriel"
• Search DOE PAGES for ORCID "0000-0001-6785-8720"

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+ Show Author Affiliations

1. Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States); University of Waterloo, ON (Canada)
2. Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States)

Publication Date:

Thu Dec 22 00:00:00 EST 2022

Research Org.:

Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States)

Sponsoring Org.:

USDOE Office of Science (SC), High Energy Physics (HEP); USDOE Laboratory Directed Research and Development (LDRD) Program

OSTI Identifier:

1842749

Report Number(s):

FERMILAB-PUB-21-726-QIS; arXiv:2201.00445
Journal ID: ISSN 2691-3399; oai:inspirehep.net:2617641; TRN: US2301406

Grant/Contract Number:  

AC02-07CH11359; SC0019219

Resource Type:

Accepted Manuscript

Journal Name:

PRX Quantum

Additional Journal Information:

Journal Volume: 3; Journal Issue: 4; Journal ID: ISSN 2691-3399

Publisher:

American Physical Society (APS)

Country of Publication:

United States

Language:

English

Subject:

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; quantum algorithms; quantum benchmarking