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Multi-electrode arrays covering several square millimeters of neural tissue provide simultaneous access to population signals such as extracellular potentials and spiking activity of one hundred or more individual neurons. The…

Neurons and Cognition · Quantitative Biology 2024-11-11 Johanna Senk , Espen Hagen , Sacha J. van Albada , Markus Diesmann

Imaging flow cytometry systems aim to analyze a huge number of cells or micro-particles based on their physical characteristics. The vast majority of current systems acquire a large amount of images which are used to train deep artificial…

Neural and Evolutionary Computing · Computer Science 2023-03-21 Muhammed Gouda , Steven Abreu , Alessio Lugnan , Peter Bienstman

Software-implementation, via neural networks, of brain-inspired computing approaches underlie many important modern-day computational tasks, from image processing to speech recognition, artificial intelligence and deep learning…

Optics · Physics 2021-02-19 J. Feldmann , N. Youngblood , C. D. Wright , H. Bhaskaran , W. H. P. Pernice

Any large-scale spiking neuromorphic system striving for complexity at the level of the human brain and beyond will need to be co-optimized for communication and computation. Such reasoning leads to the proposal for optoelectronic…

Emerging Technologies · Computer Science 2021-06-29 Bryce A. Primavera , Jeffrey M. Shainline

Four-wave mixing (FWM) in optical fibre is a leading technique for generating high-quality photon pairs. We report the generation of photon pairs by spontaneous FWM in photonic crystal fibre pumped by a 1.5 GHz repetition-rate…

We investigate the spatial and spectral properties of broad-area vertical-cavity surface-emitting lasers (VCSEL) with frequency-selective feedback by a volume Bragg grating (VBG). We demonstrate wavelength locking similar to the case of…

Pattern Formation and Solitons · Physics 2015-06-04 Yoann Noblet , Thorsten Ackemann

Controlling the longitudinal phase space of high-brightness relativistic electron beams is crucial for advancing a broad spectrum of charged-particle-based instrumentation and scientific frontiers. A generalized method for achieving this…

This letter addresses the synthesis of reflective cells approaching a given desired Floquet's scattering matrix. This work is motivated by the need to obtain much finer control of reflective metasurfaces by controlling not only their…

Can we use spiking neural networks (SNN) as generative models of multi-neuronal recordings, while taking into account that most neurons are unobserved? Modeling the unobserved neurons with large pools of hidden spiking neurons leads to…

Neurons and Cognition · Quantitative Biology 2023-01-10 Shuqi Wang , Valentin Schmutz , Guillaume Bellec , Wulfram Gerstner

Sparse coding algorithms trained on natural images can accurately predict the features that excite visual cortical neurons, but it is not known whether such codes can be learned using biologically realistic plasticity rules. We have…

Neurons and Cognition · Quantitative Biology 2011-11-01 Joel Zylberberg , Jason Timothy Murphy , Michael Robert DeWeese

We demonstrate a versatile technique for generating continuously wavelength-tunable laser waveforms, with mJ pulse energies and ultrashort pulse durations down to few-cycle in the ultraviolet C and visible spectral ranges. Using the…

Neuromorphic photonic computing has emerged as a competitive computing paradigm to overcome the bottlenecks of the von-Neumann architecture. Linear weighting and nonlinear spiking activation are two fundamental functions of a photonic…

Intracellular lasers are emerging as powerful biosensors for multiplexed tracking and precision sensing of cells and their microenvironment. This sensing capacity is enabled by quantifying their narrow-linewidth emission spectra, which is…

Mapping input signals to a high-dimensional space is a critical concept in various neuromorphic computing paradigms, including models such as Reservoir Computing (RC) and Extreme Learning Machines (ELM). We propose using commercially…

Spectrally correlated photon pairs can be used to improve performance of long range fiber based quantum communication protocols. We present a source based on spontaneous parametric down-conversion producing polarization entangled photons…

Optics · Physics 2014-03-28 Thomas Lutz , Piotr Kolenderski , Thomas Jennewein

The possibility of using an optocoupler "pulsed fiber laser - photo thyristor" as a switch in excitation circuits of copper vapor lasers (CVL) is investigated. It is shown that such switch has a nanosecond speed, is able to pass monopolar…

Other Condensed Matter · Physics 2018-07-09 A. S. Kyuregyan

Spiking Neural Networks (SNNs) offer a biologically inspired alternative to conventional artificial neural networks, with potential advantages in power efficiency due to their event-driven computation. Despite their promise, SNNs have yet…

Neural and Evolutionary Computing · Computer Science 2024-11-27 Wangdan Liao , Weidong Wang

Passively mode-locked vertical external-cavity surface-emitting semiconductor lasers (VECSELs) composed of a gain chip and a semiconductor saturable absorber have been drawing much attention due to their excellent performance figures. In…

Multi-photon resonant spectroscopies require tunable narrowband excitation to deliver spectral selectivity and, simultaneously, high temporal intensity to drive a nonlinear-optical process. These contradictory requirements are achievable…

Coherent optics has profoundly impacted diverse applications ranging from communications, LiDAR to quantum computations. However, building coherent systems in integrated photonics previously came at great expense in hardware integration and…