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Optical neuromorphic computing offers a promising route to high speed, energy efficient information processing. However, photonic neurons, as the critical components for enhancing computational expressivity, still face significant…

Optics · Physics 2025-08-25 Junyan Chen , Jingsong Fu , Jie Xu , Yixiang Qin , Axin Du , Kaiyang Wang , Limin Jin , Can Huang

The development of alternative platforms for computing has been a longstanding goal for physics, and represents a particularly pressing concern as conventional transistors approach the limit of miniaturization. A potential alternatice…

Atomic Physics · Physics 2023-02-08 Gerard McCaul , Kurt Jacobs , Denys I. Bondar

Reversible opto-mechanical molecular switch based on a single azobenzene molecule suspended via thiolate links between realistic models of gold tips is investigated. Using a combination of the transfer matrix technique and density…

Materials Science · Physics 2015-06-16 M. Zemanová Diešková , I. Štich , P. Bokes

The breaking of reciprocity is a topic of great interest in fundamental physics and optical information processing applications. We demonstrate non-reciprocal light transport in a quantum system of hot atoms by engineering the dissipative…

Quantum Physics · Physics 2021-06-09 Xingda Lu , Wanxia Cao , Wei Yi , Heng Shen , Yanhong Xiao

We report a strong nonlinear optical response of 2D MoSe$_2$ nanoflakes (NFs) through spatial self-phase modulation (SSPM) and cross-phase modulation (XPM) induced by nonlocal coherent light-matter interactions. The coherent interaction of…

Using numerical modeling we study emergence of structure and structure-related nonlinear conduction properties in the self-assembled nanoparticle films. Particularly, we show how different nanoparticle networks emerge within assembly…

Soft Condensed Matter · Physics 2010-10-07 Milovan Suvakov , Bosiljka Tadic

Dedicated analog neurocomputing circuits are promising for high-throughput, low power consumption applications of machine learning (ML) and for applications where implementing a digital computer is unwieldy (remote locations; small, mobile,…

Neural and Evolutionary Computing · Computer Science 2025-11-18 Ye min Thant , Methawee Nukunudompanich , Chu-Chen Chueh , Manabu Ihara , Sergei Manzhos

Among several approaches to tackle the problem of energy consumption in modern computing systems, two solutions are currently investigated: one consists of artificial neural networks (ANNs) based on photonic technologies, the other is a…

Disordered Systems and Neural Networks · Physics 2022-11-03 B. Paroli , G. Martini , M. A. C. Potenza , M. Siano , M. Mirigliano , P. Milani

We report about the experimental observation and characterization of nonlinear optical properties of individual silicon nanowires of different dimensions. Our results show that the nonlinear light has different components, one of them…

Mesoscale and Nanoscale Physics · Physics 2017-04-13 Peter R. Wiecha , Arnaud Arbouet , Houssem Kallel , Priyanka Periwal , Thierry Baron , Vincent Paillard

We report an unconventional resistive switching effect on high-density self-assembled Ag-nanowire networks tailored by a fuse-like operation. We propose a mechanism to rationalize the observed phenomenology by analyzing the electrical…

Materials Science · Physics 2025-01-29 Juan I. Diaz Schneider , Cynthia P. Quinteros , Eduardo D. Martínez , Pablo E. Levy

We demonstrate a new concept for reconfigurable nanophotonic devices exploiting ultrafast nonlinear control of shaped wavefronts in a multimode nanomaterial consisting of semiconductor nanowires. Femtosecond pulsed laser excitation of the…

Optics · Physics 2014-09-30 Tom Strudley , Roman Bruck , Ben Mills , Otto L. Muskens

In current molecular communication (MC) systems, performing computational operations at the nanoscale remains challenging, restricting their applicability in complex scenarios such as adaptive biochemical control and advanced nanoscale…

Signal Processing · Electrical Eng. & Systems 2025-03-03 Jianqiao Long , Lei Zhang , Miaowen Wen , Kezhi Wang , Natalio Krasnogor , Jichun Li

Nanomagnetic implementations of Boolean logic [1,2] have garnered attention because of their non-volatility and the potential for unprecedented energy-efficiency. Unfortunately, the large dissipative losses that take place when nanomagnets…

Mesoscale and Nanoscale Physics · Physics 2016-02-18 Noel D'Souza , Mohammad Salehi Fashami , Supriyo Bandyopadhyay , Jayasimha Atulasimha

We investigate transport properties through nano-ribbons of thin topological insulators irradiated by high frequency light with circular polarization. By using high frequency regime, a coherent and quantized transport through the…

Mesoscale and Nanoscale Physics · Physics 2023-04-19 Zahra Askarpour , Hosein Cheraghchi

We analyze the effect of a gate on the conductance of molecules by separately evaluating the gate-induced polarization and the potential shift of the molecule relative to the leads. The calculations use ab initio density functional theory…

Materials Science · Physics 2007-05-23 San-Huang Ke , Harold U. Baranger , Weitao Yang

Digital computing currently uses irreversible logic gates whose energy dissipation is fundamentally limited. Reversible logic gates can provide an energy-efficient alternative since they can operate with reversible processes that have no…

Superconductivity · Physics 2020-02-05 Waltraut Wustmann , Kevin D. Osborn

Switching anisotropic molecules from strongly-absorbing to strongly-amplifying through a transparent state is shown to be possible by application of dc or ac control electric fields without the requirement of the population inversion. It is…

Quantum Physics · Physics 2015-06-26 A. K. Popov , V. V. Slabko

Electronic transport across n-Si-alkyl monolayer/Hg junctions is, at reverse and low forward bias, independent of alkyl chain-length from 18 down to 1 or 2 carbons! This and further recent results indicate that electron transport is…

The great majority of electronic and optoelectronic devices depends on interfaces between n-type and p-type semiconductors. Finding such matching donor-acceptor systems in molecular crystals remains a challenging endeavor. Structurally…

Designing a neural network architecture for molecular representation is crucial for AI-driven drug discovery and molecule design. In this work, we propose a new framework for molecular representation learning. Our contribution is threefold:…

Machine Learning · Computer Science 2022-10-18 Jiye Kim , Seungbeom Lee , Dongwoo Kim , Sungsoo Ahn , Jaesik Park
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