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Quantum error correction is a set of methods to protect quantum information--that is, quantum states--from unwanted environmental interactions (decoherence) and other forms of noise. The information is stored in a quantum error-correcting…

Quantum Physics · Physics 2024-10-01 Todd A. Brun

Errors in quantum computers are of two kinds: sudden perturbations to isolated qubits, and slow random drifts of all the qubits. The latter may be reduced, but not eliminated, by means of symmetrization, namely by using many replicas of the…

Quantum Physics · Physics 2007-05-23 Asher Peres

Stochastic resonance is a general phenomenon usually observed in one-dimensional, amplitude modulated, bistable systems.We show experimentally the emergence of phase stochastic resonance in the bidimensional response of a forced…

Error mitigation has enabled quantum computing applications with over one hundred qubits and deep circuits. The most general error mitigation methods rely on a faithful characterization of the noise channels of the hardware. However,…

In a recent paper ([1]=quant-ph/0606035) it is shown how the optimal recovery operation in an error correction scheme can be considered as a semidefinite program. As a possible future improvement it is noted that still better error…

Quantum Physics · Physics 2007-05-23 M. Reimpell , R. F. Werner , K. Audenaert

Error correction code (ECC) is an integral part of the physical communication layer, ensuring reliable data transfer over noisy channels. Recently, neural decoders have demonstrated their advantage over classical decoding techniques.…

Information Theory · Computer Science 2022-09-28 Yoni Choukroun , Lior Wolf

Despite significant progress in quantum computing in recent years, executing quantum circuits for practical problems remains challenging due to error-prone quantum hardware. Hence, quantum error correction becomes essential but induces…

Quantum Physics · Physics 2025-09-04 Tobias Forster , Nils Quetschlich , Mathias Soeken , Robert Wille

Humans excel at lifelong learning, as the brain has evolved to be robust to distribution shifts and noise in our ever-changing environment. Deep neural networks (DNNs), however, exhibit catastrophic forgetting and the learned…

Machine Learning · Computer Science 2023-02-23 Fahad Sarfraz , Elahe Arani , Bahram Zonooz

Synchronous oscillations in neuronal ensembles have been proposed to provide a neural basis for the information processes in the brain. In this work, we present a neuromorphic computing algorithm based on oscillator synchronization in a…

Neural and Evolutionary Computing · Computer Science 2019-05-01 Jaesung Choi , Pilwon Kim

As transistor-based memory technologies like dynamic random access memory (DRAM) approach their scalability limits, the need to explore alternative storage solutions becomes increasingly urgent. Phase-change memory (PCM) has gained…

Hardware Architecture · Computer Science 2025-12-02 Mahek Desai , Rowena Quinn , Marjan Asadinia

Recurrent neural networks are used to forecast time series in finance, climate, language, and from many other domains. Reservoir computers are a particularly easily trainable form of recurrent neural network. Recently, a "next-generation"…

Machine Learning · Computer Science 2023-03-28 Sarah E. Marzen , Paul M. Riechers , James P. Crutchfield

We propose a method for applying the quantum error-correction method for errors that occur during quantum gates. Using a perturbation treatment of the noise that allows us to separate it from the ideal evolution of the quantum gate, we…

Quantum Physics · Physics 2016-04-13 Leonardo Andreta de Castro , Reginaldo de Jesus Napolitano

While analog neural network (NN) accelerators promise massive energy and time savings, an important challenge is to make them robust to static fabrication error. Present-day training methods for programmable photonic interferometer…

Emerging Technologies · Computer Science 2022-10-14 Sri Krishna Vadlamani , Dirk Englund , Ryan Hamerly

Nonlinear photonic sources including semiconductor lasers have recently been utilized as ideal computation elements for information processing. They supply energy-efficient way and rich dynamics for classification and recognition tasks. In…

Optics · Physics 2023-06-27 T. Wang , C. Jiang , Q. Fang , X. Guo , Y. Zhang , C. Jin , S. Xiang

In recent years, half precision floating-point arithmetic has gained wide support in hardware and software stack thanks to the advance of artificial intelligence and machine learning applications. Operating at half precision can…

Numerical Analysis · Mathematics 2024-09-19 Longfei Gao , Kevin Harms

Near-term quantum computers provide a promising platform for finding ground states of quantum systems, which is an essential task in physics, chemistry, and materials science. Near-term approaches, however, are constrained by the effects of…

In the context of optical signal processing, quantum and quantum-inspired machine learning algorithms have massive potential for deployment. One of the applications is in error correction protocols for the received noisy signals. In some…

A critical component of any quantum error-correcting scheme is detection of errors by using an ancilla system. However, errors occurring in the ancilla can propagate onto the logical qubit, irreversibly corrupting the encoded information.…

Quantum Physics · Physics 2019-05-14 S. Rosenblum , P. Reinhold , M. Mirrahimi , Liang Jiang , L. Frunzio , R. J. Schoelkopf

Quantum error correction is important to quantum information processing, which allows us to reliably process information encoded in quantum error correction codes. Efficient quantum error correction benefits from the knowledge of error…

Quantum Physics · Physics 2018-06-12 Ming-Xia Huo , Ying Li

Neutral atom arrays have recently emerged as a promising platform for quantum information processing. One important remaining roadblock for the large-scale application of these systems is the ability to perform error-corrected quantum…