Computing matrix inversion with optical networks

With this paper we bring about a discussion on the computing potential of complex optical networks and provide experimental demonstration that an optical fiber network can be used as an analog processor to calculate matrix inversion. A 3x3 matrix is inverted as a proof-of-concept demonstration using...

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Vydáno v:Optics express Ročník 22; číslo 1; s. 295
Hlavní autoři: Wu, Kan, Soci, Cesare, Shum, Perry Ping, Zheludev, Nikolay I.
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States 13.01.2014
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ISSN:1094-4087, 1094-4087
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Abstract With this paper we bring about a discussion on the computing potential of complex optical networks and provide experimental demonstration that an optical fiber network can be used as an analog processor to calculate matrix inversion. A 3x3 matrix is inverted as a proof-of-concept demonstration using a fiber network containing three nodes and operating at telecomm wavelength. For an NxN matrix, the overall solving time (including setting time of the matrix elements and calculation time of inversion) scales as O(N(2)), whereas matrix inversion by most advanced computer algorithms requires ~O(N(2.37)) computational time. For well-conditioned matrices, the error of the inversion performed optically is found to be around 3%, limited by the accuracy of measurement equipment.
AbstractList With this paper we bring about a discussion on the computing potential of complex optical networks and provide experimental demonstration that an optical fiber network can be used as an analog processor to calculate matrix inversion. A 3x3 matrix is inverted as a proof-of-concept demonstration using a fiber network containing three nodes and operating at telecomm wavelength. For an NxN matrix, the overall solving time (including setting time of the matrix elements and calculation time of inversion) scales as O(N(2)), whereas matrix inversion by most advanced computer algorithms requires ~O(N(2.37)) computational time. For well-conditioned matrices, the error of the inversion performed optically is found to be around 3%, limited by the accuracy of measurement equipment.With this paper we bring about a discussion on the computing potential of complex optical networks and provide experimental demonstration that an optical fiber network can be used as an analog processor to calculate matrix inversion. A 3x3 matrix is inverted as a proof-of-concept demonstration using a fiber network containing three nodes and operating at telecomm wavelength. For an NxN matrix, the overall solving time (including setting time of the matrix elements and calculation time of inversion) scales as O(N(2)), whereas matrix inversion by most advanced computer algorithms requires ~O(N(2.37)) computational time. For well-conditioned matrices, the error of the inversion performed optically is found to be around 3%, limited by the accuracy of measurement equipment.
With this paper we bring about a discussion on the computing potential of complex optical networks and provide experimental demonstration that an optical fiber network can be used as an analog processor to calculate matrix inversion. A 3x3 matrix is inverted as a proof-of-concept demonstration using a fiber network containing three nodes and operating at telecomm wavelength. For an NxN matrix, the overall solving time (including setting time of the matrix elements and calculation time of inversion) scales as O(N(2)), whereas matrix inversion by most advanced computer algorithms requires ~O(N(2.37)) computational time. For well-conditioned matrices, the error of the inversion performed optically is found to be around 3%, limited by the accuracy of measurement equipment.
Author Shum, Perry Ping
Wu, Kan
Soci, Cesare
Zheludev, Nikolay I.
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SubjectTerms Algorithms
Computer Communication Networks - instrumentation
Computer Simulation
Computer-Aided Design
Equipment Design
Equipment Failure Analysis
Models, Theoretical
Optical Devices
Signal Processing, Computer-Assisted - instrumentation
Telecommunications - instrumentation
Title Computing matrix inversion with optical networks
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