Theory of quantum path computing with Fourier optics and future applications for quantum supremacy, neural networks and nonlinear Schrödinger equations

Title Theory of quantum path computing with Fourier optics and future applications for quantum supremacy, neural networks and nonlinear Schrödinger equations
Author Gülbahar, Burhan
Publication Date: 2020-07-03
Publication Place - Nature Research
Type Periodical
Language English
Digital Yes
Manuscript No
Library: Özyeğin University
Library Asset ID 2045-2322
Record ID 9e44350d-dec6-4192-8e3a-82dbd44a4ffa
Library Location Electrical & Electronics Engineering
Date 2020-07-03
Sample Text The scalability, error correction and practical problem solving are important challenges for quantum computing (QC) as more emphasized by quantum supremacy (QS) experiments. Quantum path computing (QPC), recently introduced for linear optic based QCs as an unconventional design, targets to obtain scalability and practical problem solving. It samples the intensity from the interference of exponentially increasing number of propagation paths obtained in multi-plane diffraction (MPD) of classical particle sources. QPC exploits MPD based quantum temporal correlations of the paths and freely entangled projections at different time instants, for the first time, with the classical light source and intensity measurement while not requiring photon interactions or single photon sources and receivers. In this article, photonic QPC is defined, theoretically modeled and numerically analyzed for arbitrary Fourier optical or quadratic phase set-ups while utilizing both Gaussian and Hermite-Gaussian source laser modes. Problem solving capabilities already including partial sum of Riemann theta functions are extended. Important future applications, implementation challenges and open issues such as universal computation and quantum circuit implementations determining the scope of QC capabilities are discussed. The applications include QS experiments reaching more than 2(100) Feynman paths, quantum neuron implementations and solutions of nonlinear Schrodinger equation.
DOI 10.1038/s41598-020-67364-0
Cilt 10
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Theory of quantum path computing with Fourier optics and future applications for quantum supremacy, neural networks and nonlinear Schrödinger equations

Author Gülbahar, Burhan
Publication Date 2020-07-03
Publication Place - Nature Research
Type Periodical
Language English
Digital Yes
Manuscript No
Library Özyeğin University
Library Asset ID 2045-2322
Record ID 9e44350d-dec6-4192-8e3a-82dbd44a4ffa
Library Location Electrical & Electronics Engineering
Date 2020-07-03
Sample Text The scalability, error correction and practical problem solving are important challenges for quantum computing (QC) as more emphasized by quantum supremacy (QS) experiments. Quantum path computing (QPC), recently introduced for linear optic based QCs as an unconventional design, targets to obtain scalability and practical problem solving. It samples the intensity from the interference of exponentially increasing number of propagation paths obtained in multi-plane diffraction (MPD) of classical particle sources. QPC exploits MPD based quantum temporal correlations of the paths and freely entangled projections at different time instants, for the first time, with the classical light source and intensity measurement while not requiring photon interactions or single photon sources and receivers. In this article, photonic QPC is defined, theoretically modeled and numerically analyzed for arbitrary Fourier optical or quadratic phase set-ups while utilizing both Gaussian and Hermite-Gaussian source laser modes. Problem solving capabilities already including partial sum of Riemann theta functions are extended. Important future applications, implementation challenges and open issues such as universal computation and quantum circuit implementations determining the scope of QC capabilities are discussed. The applications include QS experiments reaching more than 2(100) Feynman paths, quantum neuron implementations and solutions of nonlinear Schrodinger equation.
DOI 10.1038/s41598-020-67364-0
Cilt 10
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