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The growing demand for edge computing and AI drives research into analog in-memory computing using memristors, which overcome data movement bottlenecks by computing directly within memory. However, device failures and variations critically…

Emerging Technologies · Computer Science 2025-07-16 Zhicheng Xu , Jiawei Liu , Sitao Huang , Zefan Li , Shengbo Wang , Bo Wen , Ruibin Mao , Mingrui Jiang , Giacomo Pedretti , Jim Ignowski , Kaibin Huang , Can Li

Emerging non-volatile memory (NVM), or memristive, devices promise energy-efficient realization of deep learning, when efficiently integrated with mixed-signal integrated circuits on a CMOS substrate. Even though several algorithmic…

Neural and Evolutionary Computing · Computer Science 2018-04-23 Vishal Saxena , Xinyu Wu , Kehan Zhu

Large-scale cryogenic Input-Output (IO) infrastructure is a requirement for realising fault-tolerant quantum computing in solid-state modalities. Such IO scaling presents significant challenges in thermal modelling, hardware design and…

Quantum Physics · Physics 2025-03-17 Scott A. Manifold , George B. Long , Jonathan J. Burnett

A topological insulator (TI) interfaced with a magnetic insulator (MI) may host an anomalous Hall effect (AHE), a quantum AHE, and a topological Hall effect (THE). Recent studies, however, suggest that coexisting magnetic phases in TI/MI…

Magnetic skyrmions are magnetic quasi-particles with enhanced stability and different manipulation mechanisms using external fields and currents making them promising candidates for future applications for instance in neuromorphic…

Materials Science · Physics 2023-03-30 Thomas Brian Winkler , Jan Rothörl , Maarten A. Brems , Hans Fangohr , Mathias Kläui

Preparing thermal states on a quantum computer can have a variety of applications, from simulating many-body quantum systems to training machine learning models. Variational circuits have been proposed for this task on near-term quantum…

Quantum Physics · Physics 2021-11-09 Jonathan Foldager , Arthur Pesah , Lars Kai Hansen

In analog neuromorphic chips, designers can embed computing primitives in the intrinsic physical properties of devices and circuits, heavily reducing device count and energy consumption, and enabling high parallelism, because all devices…

Image and Video Processing · Electrical Eng. & Systems 2025-03-31 Tommaso Rizzo , Sebastiano Strangio , Alessandro Catania , Giuseppe Iannaccone

Large-scale quantum computing requires cryogenic electronic controllers such as control/readout circuit and routing circuit. However, current technologies face high power dissipation problems, hindering large-scale qubit integration. Here,…

Mesoscale and Nanoscale Physics · Physics 2026-03-17 Yosep Park , Yungyeong Park , Hyeonseok Choi , Subeen Lim , Yeonghun Lee

In this paper, we investigate the use of variational quantum algorithms for simulating the thermodynamic properties of dinuclear metal complexes. Our study highlights the potential of quantum computing to transform advanced simulations and…

Quantum Physics · Physics 2024-10-28 Ana Clara das Neves Silva , Clebson Cruz

Topological photonic insulators show promise for applications in compact integrated photonic circuits due to their ability to transport light robustly through sharp bendings. The number of topological edge states relies on the difference…

Applied Physics · Physics 2024-01-19 Weiyuan Tang , Mudi Wang , Shaojie Ma , C. T. Chan , Shuang Zhang

Chiral edge states are highly sought-after as paradigmatic topological states relevant to both quantum information processing and dissipationless electron transport. Using superconducting transmon-based quantum computers, we demonstrate…

Strongly Correlated Electrons · Physics 2022-09-30 Jin Ming Koh , Tommy Tai , Ching Hua Lee

Practical implementations of quantum technologies require preparation of states with a high degree of purity---or, in thermodynamic terms, very low temperatures. Given finite resources, the Third Law of thermodynamics prohibits perfect…

As the first experimentally discovered intrinsic magnetic topological insulator, MnBi2Te4 has attracted widespread attentions, providing a unique platform for the exploration of topological quantum phases, such as quantum anomalous Hall…

We perform the characterization and modeling of a floating-gate device realized with a commercial 350-nm CMOS technology at cryogenic temperature. The programmability of the device offers a solution in the realization of a precise and…

Applied Physics · Physics 2021-10-25 Michele Castriotta , Enrico Prati , Giorgio Ferrari

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

In magnetic topological insulators, spontaneous time-reversal symmetry breaking by intrinsic magnetic order can gap the topological surface spectrum, resulting in exotic properties like axion electrodynamics, the quantum anomalous Hall…

Electronic topological phases of matter, characterized by robust boundary states derived from topologically nontrivial bulk states, are pivotal for next-generation electronic devices. However, understanding their complex quantum phases,…

Strongly Correlated Electrons · Physics 2025-03-18 Xiang Li , Yixiao Chen , Bohao Li , Haoxiang Chen , Fengcheng Wu , Ji Chen , Weiluo Ren

Thermoelectric coolers (TECs) offer a promising solution for direct cooling of local hotspots and active thermal management in advanced electronic systems. However, TECs present significant trade-offs among spatial cooling, heating and…

Applied Physics · Physics 2024-07-17 Jiajian Luo , Jaeho Lee

We demonstrate quantum Hall resistance measurements with metrological accuracy in a small cryogen-free system operating at a temperature of around 3.8K and magnetic fields below 5T. Operating this system requires little experimental…

Mesoscale and Nanoscale Physics · Physics 2015-08-27 T. J. B. M. Janssen , S. Rozhko , I. Antonov , A. Tzalenchuk , J. M. Williams , Z. Melhem , H. He , S. Lara-Avila , S. Kubatkin , R. Yakimova

Kernel functions are vital ingredients of several machine learning algorithms, but often incur significant memory and computational costs. We introduce an approach to kernel approximation in machine learning algorithms suitable for…