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Related papers: Principles of Neuromorphic Photonics

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While software implementations of neural networks have driven significant advances in computation, the von Neumann architecture imposes fundamental limitations on speed and energy efficiency. Neuromorphic networks, with structures inspired…

Neuromorphic photonics promises sub-nanosecond latency, ultrawide bandwidth, and high parallelism, but practical scalability is constrained by fabrication tolerances, spectral alignment, and tuning energy. Here, we present a large-scale,…

Photonic platforms represent a promising technology for the realization of several quantum communication protocols and for experiments of quantum simulation. Moreover, large-scale integrated interferometers have recently gained a relevant…

Neuromorphic computing takes inspiration from the brain to create energy efficient hardware for information processing, capable of highly sophisticated tasks. In this article, we make the case that building this new hardware necessitates…

Emerging Technologies · Computer Science 2020-03-26 Danijela Markovic , Alice Mizrahi , Damien Querlioz , Julie Grollier

Neuromorphic computing and spiking neural networks aim to leverage biological inspiration to achieve greater energy efficiency and computational power beyond traditional von Neumann architectured machines. In particular, spiking neural…

Neural and Evolutionary Computing · Computer Science 2023-04-17 Nicholas J. Pritchard , Andreas Wicenec , Mohammed Bennamoun , Richard Dodson

Neuromorphic sensors, also known as event cameras, are a class of imaging devices mimicking the function of biological visual systems. Unlike traditional frame-based cameras, which capture fixed images at discrete intervals, neuromorphic…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Federico Becattini , Lorenzo Berlincioni , Luca Cultrera , Alberto Del Bimbo

Inspired by the human brain's structure and function, neuromorphic computing has emerged as a promising approach for developing energy-efficient and powerful computing systems. Neuromorphic computing offers significant processing speed and…

Emerging Technologies · Computer Science 2023-11-28 Jonathan Naoukin , Murat Isik , Karn Tiwari

On-chip integration of 2D materials with exceptional optical properties provides an attractive solution for next-generation photonic integrated circuits to address the limitations of conventional bulk integrated platforms. Over the past two…

Optics · Physics 2025-04-17 David J. Moss

Spiking Neural Networks (SNNs) offer an event-driven and more biologically realistic alternative to standard Artificial Neural Networks based on analog information processing. This can potentially enable energy-efficient hardware…

Emerging Technologies · Computer Science 2019-02-06 Indranil Chakraborty , Gobinda Saha , Kaushik Roy

Recently, both industry and academia have proposed several different neuromorphic systems to execute machine learning applications that are designed using Spiking Neural Networks (SNNs). With the growing complexity on design and technology…

Neural and Evolutionary Computing · Computer Science 2022-02-21 Phu Khanh Huynh , M. Lakshmi Varshika , Ankita Paul , Murat Isik , Adarsha Balaji , Anup Das

Radio astronomy relies on bespoke, experimental and innovative computing solutions. This will continue as next-generation telescopes such as the Square Kilometre Array (SKA) and next-generation Very Large Array (ngVLA) take shape. Under…

Instrumentation and Methods for Astrophysics · Physics 2026-01-13 Nicholas J. Pritchard , Richard Dodson , Andreas Wicenec

The explosion of artificial intelligence and machine-learning algorithms, connected to the exponential growth of the exchanged data, is driving a search for novel application-specific hardware accelerators. Among the many, the photonics…

Emerging Technologies · Computer Science 2023-07-19 Nicola Peserico , Bhavin J. Shastri , Volker J. Sorger

Neuromorphic hardware architectures represent a growing family of potential post-Moore's Law Era platforms. Largely due to event-driving processing inspired by the human brain, these computer platforms can offer significant energy benefits…

Neural and Evolutionary Computing · Computer Science 2019-05-30 James B Aimone , William Severa , Craig M Vineyard

Neuromorphic computing, inspired by biological neural systems, has emerged as a promising approach for ultra-energy-efficient data processing by leveraging analog neuron structures and spike-based computation. However, its application in…

Signal Processing · Electrical Eng. & Systems 2025-05-29 George N. Katsaros , Konstantinos Nikitopoulos

Photons for quantum technologies have been identified early on as a very good candidate for carrying quantum information encoded onto them, either by polarization encoding, time encoding or spatial encoding. Quantum cryptography, quantum…

Integrated photonics computing has emerged as a promising approach to overcome the limitations of electronic processors in the post-Moore era, capitalizing on the superiority of photonic systems. However, present integrated photonics…

Optics · Physics 2023-08-15 Yuepeng Wu , Hongxiang Guo , Bowen Zhang , Jifang Qiu , Zhisheng Yang , Jian Wu

Recent advances of quantum technologies rely on precise control and integration of quantum objects, and technological breakthrough is anticipated for further scaling up to realize practical applications. Trapped-ion quantum technology is a…

Quantum Physics · Physics 2025-09-03 Alto Osada , Koichiro Miyanishi

The field of infrared (IR) photonics is currently undergoing remarkable progress, moving rapidly towards practical sensing applications demanded by medical therapy and diagnostics (theranostics). The Developments can be divided into three…

Applied Physics · Physics 2026-02-10 Borislav Hinkov , Johannes Kunsch , Werner Mäntele , Lukasz Sterczewski , Ángel Sánchez-Illana , Jaume Béjar-Grimalt , Víctor Navarro-Esteve , David Perez-Guaita , Alexander Mittelstädt , Philippa Clark , Valentino Lepro , Sergius Janik , Thorsten Lubinski , Luis Felipe das Chagas e Silva de Carvalho , Hugh James Byrne , Filiz Korkmaz , Michael Kaluza , Mattia Saita , Lars Melchior , Alicja Dabrowska , Georg Ramer , Bernhard Lendl , Nathalie Woitzik , Klaus Gerwert , Peter Gardner , Hugues Tariel , Olivier Sire , Margaux Petay , Elisabeth Holub , Markus Brandstetter , Kristina Duswald , Verena Karl , Florian Meirer , Lukas Kenner , Gabriela Flores Rangel , Boris Mizaikoff , Mohamed Sy , Aamir Farooq , Liudmila Voronina , Marinus Huber , Tarek Eissa , Katharina Dietmann , Lorenzo Gatto , Mihaela Žigman , Joseph Rebel , Frank Fleischmann , Jakub Mnich , Jarosław Sotor , Bassam Saadany , Matthias Budden , Thomas Gebert , Marco Schossig , Shankar Baliga , Timothy Olsen , Christopher Harrower , Ivan Zorin , Chiara Lindner , Shigeki Takeuchi , Sven Ramelow , Paul Gattinger , David Stark , Réka-Eszter Vass , Killian Keller , Alessio Cargioli , Mattias Beck , Jérôme Faist , Robert Weih , Josephine Nauschütz , Julian Scheuermann , Jordan Fordyce , Johannes Koeth , Ka Fai Mak , Alexander Weigel , Ryszard Piramidowicz , Stanisław Stopiński , Mircea Guina , Jukka Viheriälä , Felix Jaeschke , Polina Fomina , Alexander Novikov , Viacheslav Artyushenko , Ivan Sinev , Nikita Glebov , Berkay Dagli , Hatice Altug

Optical imaging of the brain has expanded dramatically in the past two decades. New optics, indicators, and experimental paradigms are now enabling in-vivo imaging from the synaptic to the cortex-wide scales. To match the resulting flood of…

Image and Video Processing · Electrical Eng. & Systems 2024-02-15 Gal Mishne , Adam Charles

With the proliferation of ultra-high-speed mobile networks and internet-connected devices, along with the rise of artificial intelligence, the world is generating exponentially increasing amounts of data - data that needs to be processed in…

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