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:
Feb. 22, 2022

Filed:

Mar. 02, 2021
Applicant:

Arizona Board of Regents on Behalf of the University of Arizona, Tuscon, AZ (US);

Inventors:

Zheshen Zhang, Tucson, AZ (US);

Chaohan Cui, Tucson, AZ (US);

Quntao Zhuang, Tucson, AZ (US);

William Horrocks, Tucson, AZ (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04B 10/00 (2013.01); H04B 10/61 (2013.01); H04B 10/70 (2013.01); G06N 10/00 (2022.01); G06N 3/08 (2006.01); G06N 3/067 (2006.01); H04B 10/63 (2013.01); H04J 14/00 (2006.01);
U.S. Cl.
CPC ...
H04B 10/616 (2013.01); G06N 3/067 (2013.01); G06N 3/08 (2013.01); G06N 10/00 (2019.01); H04B 10/63 (2013.01); H04B 10/70 (2013.01);
Abstract

A quantum receiver for decoding an optical signal includes a beamsplitter for interfering the optical signal with a local-oscillator field to generate a displaced field, and a single-photon detector for detecting the displaced field. The quantum receiver also includes a signal-processing circuit for determining, based on an electrical output of the single-photon detector, a measurement outcome. The signal-processing circuit also determines, based on the measurement outcome and a feed-forward machine-learning model, a next displacement. The quantum receiver also includes at least one modulator for modulating, based on the next displacement, one or both of the optical signal and the local-oscillator field. Like a Dolinar receiver, the quantum receiver implements adaptive measurements to reduce the error probability of the decoded symbol. The use of machine-learning reduces the latency of the signal-processing circuit, thereby increasing the number of measurements that may be performed for each received symbol.


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