The physics of optical computing [PDF]
Nature Reviews Physics, 2023 There has been a resurgence of interest in optical computing over the past decade, both in academia and in industry, with much of the excitement centered around special-purpose optical computers for neural-network processing. Optical computing has been a topic of periodic study for over 50 years, including for neural networks three decades ago, and a ...
P. McMahon
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Physics‐Informed Neural Network for Nonlinear Dynamics in Fiber Optics [PDF]
Laser & Photonics Reviews, 2021 A physics‐informed neural network (PINN) that combines deep learning with physics is studied to solve the nonlinear Schrödinger equation for learning nonlinear dynamics in fiber optics.
Xiaotian Jiang +5 more
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Atomic physics and quantum optics using superconducting circuits [PDF]
Nature, 2011 Superconducting circuits based on Josephson junctions exhibit macroscopic quantum coherence and can behave like artificial atoms. Recent technological advances have made it possible to implement atomic-physics and quantum-optics experiments on a chip ...
J Q You, Franco Nori, You J Q
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Recent advances in metasurface design and quantum optics applications with machine learning, physics-informed neural networks, and topology optimization methods [PDF]
Light: Science & Applications, 2023 As a two-dimensional planar material with low depth profile, a metasurface can generate non-classical phase distributions for the transmitted and reflected electromagnetic waves at its interface. Thus, it offers more flexibility to control the wave front.
Wenye Ji +6 more
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Physics and artificial intelligence: illuminating the future of optics and photonics
Advanced PhotonicsMd Sadman Sakib Rahman, Aydoḡan Ozcan
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Dispersed Systems: Physics, Optics, Invariants, Symmetry
Symmetry, 2022 Disperse systems are widely used in technology (medicine, food science, oil refining, metallurgy, etc [...]
O. Kudryashova
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The Optics in Physics textbooks
Optica Pura y Aplicada, 2021 Se agradece también al Ministerio de Ciencia, Innovación y Universidades de España por el apoyo financiero parcial en los proyectos PGC2018-101814-B-I00 y PGC2018-101948-B-I00.
Álvarez Jubete, E. +2 more
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Physics-informed neural networks for inverse problems in nano-optics and metamaterials. [PDF]
Optics Express, 2019 In this paper, we employ the emerging paradigm of physics-informed neural networks (PINNs) for the solution of representative inverse scattering problems in photonic metamaterials and nano-optics technologies.
Yuyao Chen +3 more
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Electron–phonon physics from first principles using the EPW code [PDF]
npj Computational Materials, 2023 EPW is an open-source software for ab initio calculations of electron–phonon interactions and related materials properties. The code combines density functional perturbation theory and maximally localized Wannier functions to efficiently compute electron–
Hyungjun Lee +18 more
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Physics-informed neural networks with hard constraints for inverse design [PDF]
SIAM Journal on Scientific Computing, 2021 Inverse design arises in a variety of areas in engineering such as acoustic, mechanics, thermal/electronic transport, electromagnetism, and optics. Topology optimization is a major form of inverse design, where we optimize a designed geometry to achieve ...
Lu Lu +5 more
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