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Wave-Optic Propagation Computation Enabled by Machine Learning Algorithms (WOPA)

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA9451-19-P-0517
Agency Tracking Number: F18B-004-0118
Amount: $149,631.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: AF18B-T004
Solicitation Number: 18.B
Solicitation Year: 2018
Award Year: 2019
Award Start Date (Proposal Award Date): 2018-10-29
Award End Date (Contract End Date): 2018-10-29
Small Business Information
1850 W 205th Street
Torrance, CA 90501
United States
DUNS: 612439146
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Alkan Gulses
 Research Scientist
 (310) 320-1066
Business Contact
 Emmanuel Gorce
Phone: (310) 320-1066
Research Institution
 University of Southern California
 Prof. Keith Jenkins Prof. Keith Jenkins
Ming Hsieh Department of Electrical Engineering 3601 Trousdale Parkway Student Union 301
Los Angeles, CA 90089
United States

 (213) 740-4149
 Nonprofit College or University

To address the U.S. Air Force need for Developing innovative wave-optics Propagation methods to model laser systems that are faster, efficient and more accurate, Luminit, LLC, and University of Southern California (USC) propose to develop Wave-Optic Propagation Computation Enabled by Machine Learning Algorithms (WOPA). The proposed algorithms will be based on cutting off redundant frequencies upon artificial neural network training techniques. This way, we aim to speed up the algorithms of DFT by using the existing data to educate the system. In Phase I, Luminit and USC work on the feasibility of two different (machine-learning-based) approaches, and comparison to traditional Fourier transform-propagation-inverse transform approach. Phase II will be more concentrated on software issues and application to data from High Energy Laser (HEL) systems. At the end, an innovative software package, utilizing machine learning and neural network algorithms to the ubiquitous wave-optical beam propagations.

* Information listed above is at the time of submission. *

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