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With high integration density and excellent optical properties, silicon photonics is becoming a promising platform for complete integration and large-scale optical quantum information processing. Scalable quantum information applications…

Quantum Physics · Physics 2022-08-11 Lantian Feng , Ming Zhang , Jianwei Wang , Xiaoqi Zhou , Xiaogang Qiang , Guangcan Guo , Xifeng Ren

The field of microelectromechanical Systems (MEMS) for photonic integrated circuits (PICs) is reviewed. This field leverages mechanics at the nanometer to micrometer scale to improve existing components and introduce novel functionalities…

This paper proposes a machine learning method to characterize photonic states via a simple optical circuit and data processing of photon number distributions, such as photonic patterns. The input states consist of two coherent states used…

Memory-centric computing aims to enable computation capability in and near all places where data is generated and stored. As such, it can greatly reduce the large negative performance and energy impact of data access and data movement, by…

Hardware Architecture · Computer Science 2023-09-15 Onur Mutlu

We propose and analyze the design of a programmable photonic integrated circuit for high-fidelity quantum computation and simulation. We demonstrate that the reconfigurability of our design allows us to overcome two major impediments to…

Quantum Physics · Physics 2015-09-30 Jacob Mower , Nicholas C. Harris , Gregory R. Steinbrecher , Yoav Lahini , Dirk Englund

It has long been known that photonic science and especially photonic communications can raise the speed of technologies and producing manufacturing. More recently, photonic science has also been interested in its capabilities to implement…

Neural and Evolutionary Computing · Computer Science 2024-05-15 Mohammad Ahmadi , Hamidreza Bolhasani

This tutorial-review on applications of artificial neural networks in photonics targets a broad audience, ranging from optical research and engineering communities to computer science and applied mathematics. We focus here on the research…

Machine Learning · Computer Science 2024-08-07 Pedro Freire , Egor Manuylovich , Jaroslaw E. Prilepsky , Sergei K. Turitsy

Physical computing systems provide a promising route toward hardware-native machine learning, but their computational capabilities remain difficult to characterize in a principled, task-independent, and data-efficient way. We extend the…

Machine Learning · Statistics 2026-05-22 Rahul Uma Ramachandran , Serge Massar

Optical communication achieves high fanout and short delay advantageous for information integration in neural systems. Superconducting detectors enable signaling with single photons for maximal energy efficiency. We present designs of…

Neural and Evolutionary Computing · Computer Science 2018-11-14 Jeffrey M. Shainline , Sonia M. Buckley , Adam N. McCaughan , Jeff Chiles , Richard P. Mirin , Sae Woo Nam

Electronically reprogrammable photonic circuits based on phase-change chalcogenides present an avenue to resolve the von-Neumann bottleneck; however, implementation of such hybrid photonic-electronic processing has not achieved…

In embedded vision systems, parallel computation of the integral image presents several design challenges in terms of hardware resources, speed and power consumption. Although recursive equations significantly reduce the number of…

Computer Vision and Pattern Recognition · Computer Science 2015-10-20 Shoaib Ehsan , Adrian F. Clark , Wah M. Cheung , Arjunsingh M. Bais , Bayar I. Menzat , Nadia Kanwal , Klaus D. McDonald-Maier

Analog photonic solutions offer unique opportunities to address complex computational tasks with unprecedented performance in terms of energy dissipation and speeds, overcoming current limitations of modern computing architectures based on…

Large language models (LLMs) are rapidly pushing the limits of contemporary computing hardware. For example, training GPT-3 has been estimated to consume around 1300 MWh of electricity, and projections suggest future models may require…

Hardware Architecture · Computer Science 2025-05-12 Renjie Li , Wenjie Wei , Qi Xin , Xiaoli Liu , Sixuan Mao , Erik Ma , Zijian Chen , Malu Zhang , Haizhou Li , Zhaoyu Zhang

Photonics is a promising architecture for the realisation of quantum information processing, since the two-photon interaction, or non-linearity, necessary to build logical gates can efficiently be realised by the use of interference with…

Quantum Physics · Physics 2011-12-06 Thomas Jennewein , Marco Barbieri , Andrew G. White

Over the past few years, silicon photonics-based computing has emerged as a promising alternative to CMOS-based computing for Deep Neural Networks (DNN). Unfortunately, the non-linear operations and the high-precision requirements of DNNs…

The marriage of two vibrant fields---photonics and neuromorphic processing---is fundamentally enabled by the strong analogies within the underlying physics between the dynamics of biological neurons and lasers, both of which can be…

Neurons and Cognition · Quantitative Biology 2014-07-11 Bhavin J. Shastri , Alexander N. Tait , Mitchell A. Nahmias , Paul R. Prucnal

Computational imaging modalities support a simplification of the active architectures required in an imaging system and these approaches have been validated across the electromagnetic spectrum. Recent implementations have utilized…

Classical Physics · Physics 2016-08-24 Thomas Fromenteze , Xiaojun Liu , Michael Boyarsky , Jonah Gollub , David R. Smith

Stochastic computing allows a drastic reduction in hardware complexity using serial processing of bit streams. While the induced high computing latency can be overcome using integrated optics technology, the design of realistic optical…

Emerging Technologies · Computer Science 2021-02-04 Hassnaa El-Derhalli , Lea Constans , Sebastien Le Beux , Alfredo De Rossi , Fabrice Raineri , Sofiene Tahar

Programmable photonic circuits are versatile platforms that route light through multiple interference paths using reconfigurable optoelectronic elements to perform complex discrete linear operations. These circuits offer the potential for…

Over the past decade alternative technologies have gained momentum as conventional digital electronics continue to approach their limitations, due to the end of Moore's Law and Dennard Scaling. At the same time, we are facing new…

Emerging Technologies · Computer Science 2020-06-16 Armin Mehrabian , Volker J. Sorger , Tarek El-Ghazawi