Tunable Photoinduced Liquid Crystal Retarders for All-Optical Diffractive Deep Neural Networks DOI

Quanzhou Long,

Lisheng Yao,

Junjie Shao

et al.

ACS Photonics, Journal Year: 2024, Volume and Issue: 11(11), P. 4778 - 4785

Published: Nov. 5, 2024

An all-optical diffractive deep neural network (D2NN) consists of deep-learning-based design passive layers and uses light to perform massive computations at the speed with zero extra power consumption, exhibiting advantages large bandwidth, high interconnection, parallel processing capability. In this paper, we introduce a novel approach utilizing 5-layer D2NN constructed photoinduced liquid crystal (LC) alignment technology create LC-based tunable phase retarders as artificial layers. The architecture leverages microscale multidomain LC optical neurons manipulate geometric incident light. We systematically simulate pixel-level displacements enhance tolerance during experiments, achieving robust resilience against misalignment interference 2-pixel in x y directions. By actively tuning external voltage, optimize strategy for all layers, incorporating specially designed concave or convex lenses each retarder precise x, y, z Through training handwritten dataset from MNIST, demonstrates simulated accuracy 94.17% 2 pixel tolerance. Experimental validation achieves classification 89% 500 random digits test dataset. This research showcases potential miniaturization, integration, compatibility visible light, underscoring practical applicability an diverse real-world applications.

Language: Английский

Optoelectronic Devices for In‐Sensor Computing DOI Creative Commons
Qinqi Ren, Chaoyi Zhu,

Sijie Ma

et al.

Advanced Materials, Journal Year: 2024, Volume and Issue: unknown

Published: July 14, 2024

Abstract The demand for accurate perception of the physical world leads to a dramatic increase in sensory nodes. However, transmission massive and unstructured data from sensors computing units poses great challenges terms power‐efficiency, bandwidth, storage, time latency, security. To efficiently process data, it is crucial achieve compression structuring at terminals. In‐sensor integrates perception, memory, processing functions within sensors, enabling terminals perform structuring. Here, vision are adopted as an example discuss electronic, optical, optoelectronic hardware visual processing. Particularly, implementations devices in‐sensor that can compress structure multidimensional information examined. underlying resistive switching mechanisms volatile/nonvolatile their operations explored. Finally, perspective on future development provided.

Language: Английский

Citations

28
Mesoscopic ultrafast nonlinear optics—the emergence of multimode quantum non-Gaussian physics DOI Creative Commons
Ryotatsu Yanagimoto, Edwin Ng, Marc Jankowski

et al.

Optica, Journal Year: 2024, Volume and Issue: 11(7), P. 896 - 896

Published: April 5, 2024

Over the last few decades, nonlinear optics has become significantly more nonlinear, traversing nearly a billionfold improvement in energy efficiency, with ultrafast nanophotonics particular emerging as frontier for combining both spatial and temporal engineering. At present, cutting-edge experiments place us just above mesoscopic regime, where hundred photons suffice to trigger highly dynamics. In contrast classical or deep-quantum optics, mesoscale is characterized by dynamical interactions between mean-field, Gaussian, non-Gaussian quantum features, all within close hierarchy of scales. When combined inherent multimode complexity optical fields, such hybrid quantum-classical dynamics present theoretical, experimental, engineering challenges contemporary framework optics. this review, we highlight unique physics that emerges at outline key principles exploiting features engineer novel functionalities. We briefly survey experimental landscape draw attention outstanding technical materials, dispersion engineering, device design accessing operation. Finally, speculate on how these capabilities might usher some new paradigms photonics, from quantum-augmented information processing nonclassical-light-driven phenomena all-optical measurement sensing. The unlocked significant opportunities theory experiment alike, review intended serve guide navigating

Language: Английский

Citations

9
Photonic circuit of arbitrary non-unitary systems DOI Creative Commons

Hussein Talib,

P. Sewell, Ana Vuković

et al.

Optical and Quantum Electronics, Journal Year: 2025, Volume and Issue: 57(1)

Published: Jan. 11, 2025

Abstract A design framework to implement non-unitary input–output operations a practical unitary photonic integrated circuit is described. This achieved by utilising the cosine-sine decomposition recover unitarity of original operation. The recovered operation decomposed into fundamental building blocks, forming network based on directional couplers and waveguide phase shifters. individual blocks are designed optimised three-dimensional full-wave simulations scaled up using approach. paper investigates scalability robustness Our study demonstrates that proposed approach performing matrix completion can be applied any arbitrary matrices. allows for implementation perform various linear functions in neuromorphic photonics computing, sensing, signal processing communications.

Language: Английский

Citations

0
Advanced Design and Multi-Parameter Optimization of Reconfigurable Photonic Disk Array Switches for High-Performance Programmable Pics DOI

Mohammadmahdi Khakbaz Heshmati,

Farzin Emami

Published: Jan. 1, 2025

Language: Английский

Citations

0
Monolithically integrated asynchronous optical recurrent accelerator DOI Creative Commons
Bo Wu,

Haojun Zhou,

Junwei Cheng

et al.

eLight, Journal Year: 2025, Volume and Issue: 5(1)

Published: May 5, 2025

Language: Английский

Citations

0
Multimode communication with programmable photonic integrated mesh DOI Creative Commons
Minjia Chen, Qixiang Cheng

PhotoniX, Journal Year: 2024, Volume and Issue: 5(1)

Published: Oct. 2, 2024

Abstract The programmable photonic integrated mesh is arising as a powerful tool to deal with crosstalk in the multimode optical communication link.

Language: Английский

Citations

0
Tunable Photoinduced Liquid Crystal Retarders for All-Optical Diffractive Deep Neural Networks DOI

Quanzhou Long,

Lisheng Yao,

Junjie Shao

et al.

ACS Photonics, Journal Year: 2024, Volume and Issue: 11(11), P. 4778 - 4785

Published: Nov. 5, 2024

An all-optical diffractive deep neural network (D2NN) consists of deep-learning-based design passive layers and uses light to perform massive computations at the speed with zero extra power consumption, exhibiting advantages large bandwidth, high interconnection, parallel processing capability. In this paper, we introduce a novel approach utilizing 5-layer D2NN constructed photoinduced liquid crystal (LC) alignment technology create LC-based tunable phase retarders as artificial layers. The architecture leverages microscale multidomain LC optical neurons manipulate geometric incident light. We systematically simulate pixel-level displacements enhance tolerance during experiments, achieving robust resilience against misalignment interference 2-pixel in x y directions. By actively tuning external voltage, optimize strategy for all layers, incorporating specially designed concave or convex lenses each retarder precise x, y, z Through training handwritten dataset from MNIST, demonstrates simulated accuracy 94.17% 2 pixel tolerance. Experimental validation achieves classification 89% 500 random digits test dataset. This research showcases potential miniaturization, integration, compatibility visible light, underscoring practical applicability an diverse real-world applications.

Language: Английский

Citations

0