Design of Task-Specific Optical Systems Using Broadband Diffractive Neural Networks

Abstract

We report a broadband diffractive optical neural network design that simultaneously processes a continuum of wavelengths generated by a temporally-incoherent broadband source to all-optically perform a specific task learned using deep learning. We experimentally validated the success of this broadband diffractive neural network architecture by designing, fabricating and testing seven different multi-layer, diffractive optical systems that transform the optical wavefront generated by a broadband THz pulse to realize (1) a series of tunable, single passband as well as dual passband spectral filters, and (2) spatially-controlled wavelength de-multiplexing. Merging the native or engineered dispersion of various material systems with a deep learning-based design strategy, broadband diffractive neural networks help us engineer light-matter interaction in 3D, diverging from intuitive and analytical design methods to create task-specific optical components that can all-optically perform deterministic tasks or statistical inference for optical machine learning.

36 pages, 5 figures

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Cited by in corpus (46)

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• Photonic extreme learning machine by free-space optical propagation
• Diffractive all-optical computing for quantitative phase imaging
• Intelligent Meta-Imagers: From Compressed to Learned Sensing
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• All-optical image denoising using a diffractive visual processor
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• Multiplane Quantitative Phase Imaging Using a Wavelength-Multiplexed Diffractive Optical Processor
• Cascadable all-optical NAND gates using diffractive networks
• Universal Polarization Transformations: Spatial programming of polarization scattering matrices using a deep learning-designed diffractive polarization transformer
• Classification and reconstruction of spatially overlapping phase images using diffractive optical networks
• Quadrature Photonic Spatial Ising Machine
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• Simultaneously sorting vector vortex beams of 120 modes
• Ultrahigh-fidelity spatial mode quantum gates in high-dimensional space by diffractive deep neural networks
• Multispectral Quantitative Phase Imaging Using a Diffractive Optical Network
• A Broad-Spectrum Diffractive Network via Ensemble Learning
• Broadband nonlinear modulation of incoherent light using a transparent optoelectronic neuron array
• All-Optical Phase Conjugation Using Diffractive Wavefront Processing
• Time-lapse image classification using a diffractive neural network
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• Integration of Programmable Diffraction with Digital Neural Networks
• Design of ultracompact broadband focusing spectrometers based on deep diffractive neural networks
• Inverse design of ultracompact multi-focal optical devices by diffractive neural networks
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• An optical diffractive deep neural network with multiple frequency-channels
• Computer-free, all-optical reconstruction of holograms using diffractive networks
• Unidirectional focusing of light using structured diffractive surfaces
• Unitary Learning for Deep Diffractive Neural Network
• A Diffractive Neural Network with Weight-Noise-Injection Training
• Resonant tunnelling diode nano-optoelectronic spiking nodes for neuromorphic information processing
• All-Optical Synthesis of an Arbitrary Linear Transformation Using Diffractive Surfaces
• Optimal universal bounds for waves with varied coherence based on supremum and infimum coherence spectra
• High speed and reconfigurable optronic neural network with digital nonlinear activation