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. 24, 2024

Filed:

Dec. 20, 2021
Applicant:

Massachusetts Institute of Technology, Cambridge, MA (US);

Inventors:

Saumil Bandyopadhyay, Cambridge, MA (US);

Ryan Hamerly, Cambridge, MA (US);

Dirk Robert Englund, Brookline, MA (US);

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06N 10/70 (2022.01); G02F 1/21 (2006.01); G06N 10/40 (2022.01); H04B 10/70 (2013.01);
U.S. Cl.
CPC ...
G06N 10/70 (2022.01); G02F 1/212 (2021.01); G06N 10/40 (2022.01); H04B 10/70 (2013.01);
Abstract

Programmable photonic circuits of reconfigurable interferometers can be used to implement arbitrary operations on optical modes, providing a flexible platform for accelerating tasks in quantum simulation, signal processing, and artificial intelligence. A major obstacle to scaling up these systems is static fabrication error, where small component errors within each device accrue to produce significant errors within the circuit computation. Mitigating errors usually involves numerical optimization dependent on real-time feedback from the circuit, which can greatly limit the scalability of the hardware. Here, we present a resource-efficient, deterministic approach to correcting circuit errors by locally correcting hardware errors within individual optical gates. We apply our approach to simulations of large-scale optical neural networks and infinite impulse response filters implemented in programmable photonics, finding that they remain resilient to component error well beyond modern day process tolerances. Our error correction process can be used to scale up programmable photonics within current fabrication processes.


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