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Memristors are passive elements that allow us to store information using a single element per bit. However, this is not the only utility of the memristor. Considering the physical chemical structure of the element used, the memristor can…

Emerging Technologies · Computer Science 2017-05-10 David Alejandro Trejo Pizzo

In this extended abstract, we have introduced a highly memory-efficient state vector simulation of quantum circuits premised on data compression, harnessing the capabilities of both CPUs and GPUs. We have elucidated the inherent challenges…

Quantum Physics · Physics 2023-10-02 Boyuan Zhang , Bo Fang , Qiang Guan , Ang Li , Dingwen Tao

Memristors are promising next-generation memory candidates that are nonvolatile, possess low power requirements and are capable of nanoscale fabrication. In this article we physically realise and describe the use of organic memristors in…

Emerging Technologies · Computer Science 2012-12-17 Victor Erokhin , Gerard David Howard , Andrew Adamatzky

We investigate memory effects in non-Markovian dynamics on superconducting quantum processors provided by IBM Quantum. We use a collision-model approach to implement suitable single- and two-qubit dynamics with a gate-based quantum circuit.…

Quantum Physics · Physics 2026-04-24 Charlotte Bäcker , Krishna Palaparthy , Walter T. Strunz

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

We show theoretically that networks of membrane memcapacitive systems -- capacitors with memory made out of membrane materials -- can be used to perform a complete set of logic gates in a massively parallel way by simply changing the…

Emerging Technologies · Computer Science 2015-07-09 Yuriy V. Pershin , Fabio L. Traversa , Massimiliano Di Ventra

We investigate the real-time current response of strongly-correlated quantum dot systems under sinusoidal driving voltages. By means of an accurate hierarchical equations of motion approach, we demonstrate the presence of prominent memory…

Strongly Correlated Electrons · Physics 2015-06-15 Xiao Zheng , YiJing Yan , Massimiliano Di Ventra

Quantum batteries have recently emerged as promising candidates for microscopic energy-storage technologies exploiting uniquely quantum mechanical effects. In this work, we introduce the concept of a quantum capacitor, a quantum device…

Quantum Physics · Physics 2026-05-12 Saeed Haddadi

Memristive devices are promising elements for energy-efficient neuromorphic computing and future artificial intelligence systems. For diffusive memristors, the device state switching occurs because of the sequential formation and…

Materials Science · Physics 2022-02-14 D. P Pattnaik , Y. Ushakov , Z. Zhou , P. Borisov , M. D Cropper , U. W. Wijayantha , A. G. Balanov , S. E Savel'ev

Non-Markovian quantum processes exhibit different memory effects when measured in different ways; an unambiguous characterization of memory length requires accounting for the sequence of instruments applied to probe the system dynamics.…

Quantum Physics · Physics 2019-04-11 Philip Taranto , Simon Milz , Felix A. Pollock , Kavan Modi

Memristors are among the most promising elements for modern microelectronics, having unique properties such as quasi-continuous change of conductance and long-term storage of resistive states. However, identifying the physical mechanisms of…

Mesoscale and Nanoscale Physics · Physics 2022-05-25 Oleg G. Kharlanov , Boris S. Shvetsov , Vladimir V. Rylkov , Anton A. Minnekhanov

Memristive neural networks (MNNs), which use memristors as neurons or synapses, have become a hot research topic recently. However, most memristors are not compatible with mainstream integrated circuit technology and their stabilities in…

Emerging Technologies · Computer Science 2019-01-03 Zhiri Tang , Ruohua Zhu , Peng Lin , Jin He , Hao Wang , Qijun Huang , Sheng Chang , Qiming Ma

Nanoscale metal oxide memristors have potential in the development of brain-inspired computing systems that are scalable and efficient1-3. In such systems, memristors represent the native electronic analogues of the biological synapses.…

Mesoscale and Nanoscale Physics · Physics 2016-12-21 Cheng-Chih Hsieh , Anupam Roy , Yao-Feng Chang , Davood Shahrjerdi , Sanjay K. Banerjee

Coupling a qubit coherently to an ensemble is the basis for collective quantum memories. A driven quantum dot can deterministically excite low-energy collective modes of a nuclear spin ensemble in the presence of lattice strain. We propose…

Quantum Physics · Physics 2019-12-02 Emil V. Denning , Dorian A. Gangloff , Mete Atatüre , Jesper Mork , Claire Le Gall

Reservoir computing is a machine learning paradigm that uses a high-dimensional dynamical system, or \emph{reservoir}, to approximate and predict time series data. The scale, speed and power usage of reservoir computers could be enhanced by…

Neural and Evolutionary Computing · Computer Science 2022-11-16 Forrest C. Sheldon , Artemy Kolchinsky , Francesco Caravelli

This paper presents a survey of the currently available hardware designs for implementation of the human cortex inspired algorithm, Hierarchical Temporal Memory (HTM). In this review, we focus on the state of the art advances of memristive…

Hardware Architecture · Computer Science 2018-05-09 Olga Krestinskaya , Irina Dolzhikova , Alex Pappachen James

The development of solid-state quantum technologies requires the understanding of quantum measurements in interacting, non-isolated quantum systems. In general, a permanent coupling of detectors to a quantum system leads to memory effects…

Mesoscale and Nanoscale Physics · Physics 2018-04-11 Johannes Bülte , Adam Bednorz , Christoph Bruder , Wolfgang Belzig

Compared to quantum logic gates, quantum memory has received far less attention. Here, we explore the prognosis for a solid-state, scalable quantum dynamic random access memory (Q-DRAM), where the qubits are encoded by the spin orientations…

Quantum Physics · Physics 2007-05-23 S. Bandyopadhyay

Nanofluidic memristors have demonstrated great potential for neuromorphic system applications with the advantages of low energy consumption and excellent biocompatibility. Here, an effective way is developed to regulate the memristive…

Chemical Physics · Physics 2025-10-21 Zhe Liu , Hongwen Zhang , Di Liu , Tianyi Sui , Yinghua Qiu

Memristive reservoirs draw inspiration from a novel class of neuromorphic hardware known as nanowire networks. These systems display emergent brain-like dynamics, with optimal performance demonstrated at dynamical phase transitions. In…

Disordered Systems and Neural Networks · Physics 2023-06-23 Ruomin Zhu , Jason K. Eshraghian , Zdenka Kuncic
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