Deep Learning

Snapshot computational spectroscopy enabled by deep learning
Spectroscopy is a technique that analyzes the interaction between matter and light as a function of wavelength. It is the most convenient method for obtaining qualitative and quantitative information about an unknown sam…
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Snapshot computational spectroscopy enabled by deep learning
Deep learning enabled inverse design of bound states in the continuum with ultrahigh Q factor
Bound states in the continuum (BIC) can be easily engineered to obtain ultrahigh quality resonances that can greatly enhance sensing and lasing performance, thereby gaining significant attention in the field of nanophoto…
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Plasmonic nanostructure characterized by deep-neural-network-assisted spectroscopy [Invited]
The lateral geometry and material property of plasmonic nanostructures are critical parameters for tailoring their optical resonance for sensing applications. While lateral geometry can be easily observed by a scanning e…
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Computational spectrometers enabled by nanophotonics and deep learning
Abstract A new type of spectrometer that heavily relies on computational technique to recover spectral information is introduced. They are different from conventional optical spectrometers in many important aspects. Trad…
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Comparison of Different Neural Network Architectures for Plasmonic Inverse Design
The merge between nanophotonics and a deep neural network has shown unprecedented capability of efficient forward modeling and accurate inverse design if an appropriate network architecture and training method are select…
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Deep neural network for designing near- and far-field properties in plasmonic antennas
The electromagnetic response of plasmonic nanostructures is highly sensitive to their geometric parameters. In multi-dimensional parameter space, conventional full-wave simulation and numerical optimization can consume s…
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Neural network enabled metasurface design for phase manipulation
The phase of electromagnetic waves can be manipulated and tailored by artificial metasurfaces, which can lead to ultra-compact, high-performance metalens, holographic and imaging devices etc. Usually, nanostructured meta…
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A Bidirectional Deep Neural Network for Accurate Silicon Color Design
Abstract Silicon nanostructure color has achieved unprecedented high printing resolution and larger color gamut than sRGB. The exact color is determined by localized magnetic and electric dipole resonance of nanostructur…
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