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Neural Network for Image-to-Image Control of Optical TweezersA method is discussed for using neural networks to control optical tweezers. Neural-net outputs are combined with scaling and tiling to generate 480 by 480-pixel control patterns for a spatial light modulator (SLM). The SLM can be combined in various ways with a microscope to create movable tweezers traps with controllable profiles. The neural nets are intended to respond to scattered light from carbon and silicon carbide nanotube sensors. The nanotube sensors are to be held by the traps for manipulation and calibration. Scaling and tiling allow the 100 by 100-pixel maximum resolution of the neural-net software to be applied in stages to exploit the full 480 by 480-pixel resolution of the SLM. One of these stages is intended to create sensitive null detectors for detecting variations in the scattered light from the nanotube sensors.
Document ID
Document Type
Technical Memorandum (TM)
Decker, Arthur J.
(NASA Glenn Research Center Cleveland, OH, United States)
Anderson, Robert C.
(NASA Glenn Research Center Cleveland, OH, United States)
Weiland, Kenneth E.
(NASA Glenn Research Center Cleveland, OH, United States)
Wrbanek, Susan Y.
(NASA Glenn Research Center Cleveland, OH, United States)
Date Acquired
September 7, 2013
Publication Date
July 1, 2004
Subject Category
Instrumentation And Photography
Report/Patent Number
Meeting Information
2004 Annual Meeting(Denver, CO)
Funding Number(s)
WBS: WBS 22-708-04-04
Distribution Limits
Work of the US Gov. Public Use Permitted.
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