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Related papers: Memcomputing: Leveraging memory and physics to com…

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Memcomputing logic gates generalize the traditional Boolean logic gates for operation in the reverse direction. According to the literature, this functionality enables the efficient solution of computationally-intensive problems including…

Emerging Technologies · Computer Science 2024-02-02 Y. V. Pershin

Many problems in science and engineering can be represented by a set of partial differential equations (PDEs) through mathematical modeling. Mechanism-based computation following PDEs has long been an essential paradigm for studying topics…

Machine Learning · Computer Science 2022-11-21 Shudong Huang , Wentao Feng , Chenwei Tang , Jiancheng Lv

The ever-increasing computation complexity of fast-growing Deep Neural Networks (DNNs) has requested new computing paradigms to overcome the memory wall in conventional Von Neumann computing architectures. The emerging Computing-In-Memory…

Hardware Architecture · Computer Science 2021-07-21 Kaining Zhou , Yangshuo He , Rui Xiao , Kejie Huang

Neuromorphic computing approaches become increasingly important as we address future needs for efficiently processing massive amounts of data. The unique attributes of quantum materials can help address these needs by enabling new…

Quantum mechanics---the theory describing the fundamental workings of nature---is famously counterintuitive: it predicts that a particle can be in two places at the same time, and that two remote particles can be inextricably and…

The ever-increasing computation complexity of fastgrowing Deep Neural Networks (DNNs) has requested new computing paradigms to overcome the memory wall in conventional Von Neumann computing architectures. The emerging Computing-In-Memory…

Hardware Architecture · Computer Science 2021-12-14 Kaining Zhou , Yangshuo He , Rui Xiao , Jiayi Liu , Kejie Huang

Quantum computer has an amazing potential of fast information processing. However, realisation of a digital quantum computer is still a challenging problem requiring highly accurate controls and key application strategies. Here we propose a…

Quantum Physics · Physics 2017-09-06 Keisuke Fujii , Kohei Nakajima

The combination of machine learning and quantum computing has emerged as a promising approach for addressing previously untenable problems. Reservoir computing is an efficient learning paradigm that utilizes nonlinear dynamical systems for…

Quantum Physics · Physics 2020-08-26 Jiayin Chen , Hendra I. Nurdin , Naoki Yamamoto

Quantum materials exhibit a wide array of exotic phenomena and practically useful properties. A better understanding of these materials can provide deeper insights into fundamental physics in the quantum realm as well as advance technology…

Quantum computing employs some quantum phenomena to process information. It has been hailed as the future of computing but it is plagued by serious hurdles when it comes to its practical realization. MemComputing is a new paradigm that…

Emerging Technologies · Computer Science 2025-12-05 Massimiliano Di Ventra

Quantum computing is an advancing area of research in which computer hardware and algorithms are developed to take advantage of quantum mechanical phenomena. In recent studies, quantum algorithms have shown promise in solving linear systems…

Computational Physics · Physics 2023-06-16 Katherine Asztalos , René Steijl , Romit Maulik

Learning with physical systems is an emerging paradigm that seeks to harness the intrinsic nonlinear dynamics of physical substrates for learning. The impetus for a paradigm shift in how hardware is used for computational intelligence stems…

Disordered Systems and Neural Networks · Physics 2026-04-28 Francesco Caravelli , Gianluca Milano , Adam Z. Stieg , Carlo Ricciardi , Simon Anthony Brown , Zdenka Kuncic

Numerical approximations of partial differential equations (PDEs) are routinely employed to formulate the solution of physics, engineering, and mathematical problems involving functions of several variables, such as the propagation of heat…

Quantum computers promise to solve important problems faster than conventional computers. However, unleashing this power has been challenging. In particular, design automation runs into (1) the probabilistic nature of quantum computation…

Quantum Physics · Physics 2023-11-08 Stefan Hillmich , Richard Kueng , Igor L. Markov , Robert Wille

We utilize machine learning models which are based on recurrent neural networks to optimize dynamical decoupling (DD) sequences. DD is a relatively simple technique for suppressing the errors in quantum memory for certain noise models. In…

Quantum Physics · Physics 2017-02-01 Moritz August , Xiaotong Ni

We provide algorithms for efficiently addressing quantum memory in parallel. These imply that the standard circuit model can be simulated with low overhead by the more realistic model of a distributed quantum computer. As a result, the…

As neural computation is revolutionizing the field of Artificial Intelligence (AI), rethinking the ideal neural hardware is becoming the next frontier. Fast and reliable von Neumann architecture has been the hosting platform for neural…

Neural and Evolutionary Computing · Computer Science 2024-12-31 Yigit Demirag

The quest for quantum computers is motivated by their potential for solving problems that defy existing, classical, computers. The theory of computational complexity, one of the crown jewels of computer science, provides a rigorous…

Statistical Mechanics · Physics 2010-09-10 C. R. Laumann , R. Moessner , A. Scardicchio , S. L. Sondhi

Quantum computer technology harnesses the features of quantum physics for revolutionizing information processing and computing. As such, quantum computers use physical quantum gates that process information unitarily, even though the final…

An enduring challenge in computer science is reducing the runtime required to solve computational problems. Quantum computing has attracted significant attention due to its potential to deliver asymptotically faster solutions to certain…

Quantum Physics · Physics 2025-03-25 Mischa P. Woods