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Here one can find a derivation of the commutator of the charge and magnetic flux in a superconducting circuit containing a Josephson junction from the commutation relation of quantum-field operators of electric field and vector potential. A…

Quantum Physics · Physics 2020-03-10 Mikhail A. Savrov

We suggest circuit realizations of emulators transforming memristive devices into effective floating memcapacitive and meminductive systems. The emulator's circuits are based on second generation current conveyors and involve either four…

Instrumentation and Detectors · Physics 2011-07-13 Yuriy V. Pershin , Massimiliano Di Ventra

A powerful time series analysis modeling technique is presented to describe cycle-to-cycle variability in memristors. These devices show variability linked to the inherent stochasticity of device operation and it needs to be accurately…

Mesoscale and Nanoscale Physics · Physics 2024-02-08 Francisco J. Alonso , David Maldonado , Ana M. Aguilera , Juan B. Roldán

Memristors are non-volatile nano-resistors. Their resistance can be tuned by applied currents or voltages and set to a large number of levels between two limit values. Thanks to these properties, memristors are ideal building blocks for a…

Mesoscale and Nanoscale Physics · Physics 2016-05-26 Steven Lequeux , Joao Sampaio , Vincent Cros , Kay Yakushiji , Akio Fukushima , Rie Matsumoto , Hitoshi Kubota , Shinji Yuasa , Julie Grollier

The key feature of a memristor is that the resistance is a function of its previous resistance, thereby the behaviour of the device is influenced by changing the way in which potential is applied across it. Ultimately, information can be…

Emerging Technologies · Computer Science 2020-05-22 Alexander E. Beasley , Mohammed-Salah Abdelouahab , René Lozi , Anna L. Powell , Andrew Adamatzky

Memristor device modeling is currently a heavily researched topic and is becoming ever more important as memristor devices make their way into CMOS circuit designs, necessitating accurate and efficient memristor circuit simulations. In this…

Emerging Technologies · Computer Science 2017-04-27 Timothy W. Molter , M. Alexander Nugent

There is an urgent need to enhance the storage density of memory devices to accommodate the exponentially increasing amount of data generated by humankind. In this work, we describe Magnonic Combinatorial Memory (MCM), where the bits of…

Other Condensed Matter · Physics 2025-09-15 Mykhaylo Balinskiy , Paulo Julio , Jeffrey Vargas , Diana Balaguer , Alexander Khitun

Memristors, uniquely characterized by their pinched hysteresis loop fingerprints, have attracted significant research interest over the past decade, due to their enormous potential for novel computation and artificial intelligence…

Applied Physics · Physics 2025-08-07 Erion Uka , Chun Zhao

With the increase of the speed of computers, timing and power requirements are becoming crucial for memory devices. The main objective of the paper is to modify 180nm CMOS sense amplifier design by using memristive devices and improve the…

Emerging Technologies · Computer Science 2019-08-28 Yerlan Amanzholov , Olga Krestinskaya

The MOS devices are the basic building block of any digital and analog circuits, where silicon (Si) is the most commonly used material. The International Technology Roadmap Semiconductor (ITRS) report predicts the gate length of the MOS…

Memristors, resistors with memory whose outputs depend on the history of their inputs, have been used with success in neuromorphic architectures, particularly as synapses and non-volatile memories. However, to the best of our knowledge, no…

Emerging Technologies · Computer Science 2020-01-14 Francisco Silva , Mikel Sanz , João Seixas , Enrique Solano , Yasser Omar

Resistive switching devices emerged a huge amount of interest as promising candidates for non-volatile memories as well as artificial synapses due to their memristive behavior. The main physical and chemical phenomena which define their…

Materials Science · Physics 2018-08-01 Tobias Gergs , Sven Dirkmann , Thomas Mussenbrock

In conventional digital computers, data and information are represented in binary form and encoded in the steady states of transistors. They are then processed in a quasi-static way. However, with transistors approaching their physical…

Applied Physics · Physics 2023-05-12 Zhao Yuanxi , Duan Wenrui , Li Huanglong

It is a significant and longstanding puzzle that the resistor, inductor, capacitor (RLC) networks obtained by the established RLC realization procedures appear highly non-minimal from the perspective of linear systems theory. Specifically,…

Systems and Control · Computer Science 2018-01-24 Timothy H. Hughes

The possibility of in-memory computing with volatile memristive devices, namely, memristors requiring a power source to sustain their memory, is demonstrated. We have adopted a hysteretic graphene-based field emission structure as a…

Mesoscale and Nanoscale Physics · Physics 2017-01-17 Y. V. Pershin , S. N. Shevchenko

We introduce a recurrent neural network model of working memory combining short-term and long-term components. e short-term component is modelled using a gated reservoir model that is trained to hold a value from an input stream when a gate…

Neural and Evolutionary Computing · Computer Science 2020-03-27 Anthony Strock , Nicolas Rougier , Xavier Hinaut

Memristors stand out as promising components in the landscape of memory and computing. Memristors are generally defined by a conductance equation containing a state variable that imparts a memory effect. The current-voltage cycling causes…

Applied Physics · Physics 2024-09-17 Agustin Bou , Cedric Gonzales , Pablo P. Boix , Antonio Guerrero , Juan Bisquert

A dynamic systems model is proposed describing memory resistors which include a filament conductive bridge. In this model the system state is defined by both a dynamic tunneling barrier (associated with the filament-electrode gap) and a…

Mesoscale and Nanoscale Physics · Physics 2011-06-28 Blaise Mouttet

It has been suggested that all resistive-switching memory cells are memristors. The latter are hypothetical, ideal devices whose resistance, as originally formulated, depends only on the net charge that traverses them. Recently, an…

Mesoscale and Nanoscale Physics · Physics 2020-08-12 J. Kim , Y. V. Pershin , M. Yin , T. Datta , M. Di Ventra

The increasing computational demands of deep learning models pose significant challenges for edge devices. To address this, we propose a memristor-based circuit design for MobileNetV3, specifically for image classification tasks. Our design…

Hardware Architecture · Computer Science 2025-04-04 Jiale Li , Zhihang Liu , Sean Longyu Ma , Chiu-Wing Sham , Chong Fu