Deep, Complex, Invertible Networks for Inversion of Transmission Effects in Multimode Optical Fibres

Moran, O., Caramazza, P., Faccio, D. and Murray-Smith, R. (2018) Deep, Complex, Invertible Networks for Inversion of Transmission Effects in Multimode Optical Fibres. In: 32nd Conference on Neural Information Processing Systems (NeurIPS 2018), Montréal, Canada, 02-08 Dec 2018,

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Publisher's URL: https://papers.nips.cc/paper/7589-deep-complex-invertible-networks-for-inversion-of-transmission-effects-in-multimode-optical-fibres

Abstract

We use complex-weighted, deep networks to invert the effects of multimode optical fibre distortion of a coherent input image. We generated experimental data based on collections of optical fibre responses to greyscale input images generated with coherent light, by measuring only image amplitude (not amplitude and phase as is typical) at the output of \SI{1}{\metre} and \SI{10}{\metre} long, \SI{105}{\micro\metre} diameter multimode fibre. This data is made available as the {\it Optical fibre inverse problem} Benchmark collection. The experimental data is used to train complex-weighted models with a range of regularisation approaches. A {\it unitary regularisation} approach for complex-weighted networks is proposed which performs well in robustly inverting the fibre transmission matrix, which fits well with the physical theory. A key benefit of the unitary constraint is that it allows us to learn a forward unitary model and analytically invert it to solve the inverse problem. We demonstrate this approach, and show how it can improve performance by incorporating knowledge of the phase shift induced by the spatial light modulator.

Item Type:Conference Proceedings
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Murray-Smith, Professor Roderick and Moran, Mr Oisin and Faccio, Professor Daniele and Caramazza, Mr Piergiorgio
Authors: Moran, O., Caramazza, P., Faccio, D., and Murray-Smith, R.
College/School:College of Science and Engineering > School of Computing Science
College of Science and Engineering > School of Physics and Astronomy

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
6672319UK Quantum Technology Hub in Enhanced Quantum ImagingMiles PadgettEngineering and Physical Sciences Research Council (EPSRC)EP/M01326X/1S&E P&A - PHYSICS & ASTRONOMY
3009820Exploiting Closed-Loop Aspects in Computationally and Data Intensive AnalyticsRoderick Murray-SmithEngineering and Physical Sciences Research Council (EPSRC)EP/R018634/1Computing Science