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:
Apr. 13, 2021

Filed:

Nov. 29, 2017
Applicant:

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

Inventors:

Jay M. Gambetta, Yorktown Heights, NY (US);

Vojtech Havlicek, Ceska Kamenice, CZ;

Paul Kristan Temme, Ossining, NY (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 99/00 (2019.01); G06N 3/04 (2006.01); G06N 3/08 (2006.01); G06F 15/80 (2006.01); G06F 9/30 (2018.01); G06N 10/00 (2019.01); G06N 20/00 (2019.01);
U.S. Cl.
CPC ...
G06N 3/04 (2013.01); G06N 3/0472 (2013.01); G06N 3/0481 (2013.01); G06N 3/08 (2013.01); G06N 10/00 (2019.01); G06F 9/3001 (2013.01); G06F 15/80 (2013.01); G06N 20/00 (2019.01);
Abstract

Techniques using short depth circuits as quantum classifiers are described. In one embodiment, a system is provided that comprises: quantum hardware, a memory that stores computer-executable components and a processor that executes computer-executable components stored in the memory. In one implementation, the computer-executable components comprise a calibration component that calibrates quantum hardware to generate a short depth quantum circuit. The computer-executable components further comprise a cost function component that determines a cost function for the short depth quantum circuit based on an initial value for a parameter of a machine-learning classifier. The computer-executable components further comprise a training component that modifies the initial value for the parameter during training to a second value for the parameter based on the cost function for the short depth quantum circuit.


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