The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Dec. 16, 2025

Filed:

Dec. 16, 2020
Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Ewout Van Den Berg, Bronxville, NY (US);

Zlatko Kristev Minev, White Plains, NY (US);

Paul Kristan Temme, Ossining, NY (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 10/00 (2022.01); G06N 10/20 (2022.01);
U.S. Cl.
CPC ...
G06N 10/00 (2019.01); G06N 10/20 (2022.01);
Abstract

Techniques for mitigating readout error for quantum expectation are presented. Calibration component applies first random Pauli gates to qubits at first output of first circuit prior to first readout measurements of the qubits. Estimation component applies second random Pauli gates to qubits at second output of second circuit prior to second readout measurements of the qubits, and generates an error-mitigated readout determination based on first random Pauli gates applied to qubits at first circuit output and second random Pauli gates applied to qubits at second circuit output. Calibration component determines calibration data based on first readout measurements. Estimation component determines estimation data based on second readout measurements. Estimation component determines normalization scalar value based on the calibration data, determines estimation scalar value based on the estimation data, and determines the error-mitigated readout determination associated with a circuit of interest based on the normalization scalar value and estimation scalar value.


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