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In this article we introduce an algorithm for mitigating the adverse effects of noise on gradient descent in variational quantum algorithms. This is accomplished by computing a {\emph{regularized}} local classical approximation to the…

Quantum Physics · Physics 2024-03-07 Lars Simon , Holger Eble , Hagen-Henrik Kowalski , Manuel Radons

While it seems possible that quantum computers may allow for algorithms offering a computational speed-up over classical algorithms for some problems, the issue is poorly understood. We explore this computational speed-up by investigating…

Quantum Physics · Physics 2010-06-09 Alastair A. Abbott , Cristian S. Calude

Quantum sensing is an important application of emerging quantum technologies. We explore whether a hybrid system of quantum sensors and quantum circuits can surpass the classical limit of sensing. In particular, we use optimization…

Extracting useful signals is key to both classical and quantum technologies. Conventional noise filtering methods rely on different patterns of signal and noise in frequency or time domains, thus limiting their scope of application,…

Quantum Physics · Physics 2023-02-28 Yang Shen , Ping Wang , Chun Tung Cheung , Joerg Wachtrup , Ren-Bao Liu , Sen Yang

Classical verification of quantum learning allows classical clients to reliably leverage quantum computing advantages by interacting with untrusted quantum servers. Yet, current quantum devices available in practice suffers from a variety…

Quantum Physics · Physics 2024-11-15 Yinghao Ma , Jiaxi Su , Dong-Ling Deng

Quantum computers require error correction to achieve universal quantum computing. However, current decoding of quantum error-correcting codes relies on classical computation, which is slower than quantum operations in superconducting…

Quantum Physics · Physics 2025-06-11 Pan Zhang

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…

We present a simple model of quantum communication where a noisy quantum channel may benefit from the addition of further noise at the decoding stage. We demonstrate enhancement of the classical information capacity of an amplitude damping…

Quantum Physics · Physics 2015-06-26 Garry Bowen , Stefano Mancini

Quantum advantage requires overcoming noise-induced degradation of quantum systems. Conventional methods for reducing noise such as error mitigation face scalability issues in deep circuits. Specifically, noise hampers the extraction of…

Quantum Physics · Physics 2023-12-05 Yonglong Ding , Ruyu Yang

The decoherence phenomenon inevitably exists in quantum computing processes. Consequently, dynamic suppression of decoherence for instance via dynamical decoupling, quantum error correction codes (QECC) etc. is crucial in accurately…

Quantum Physics · Physics 2023-11-30 Lian-Ao Wu

In the current quantum computing paradigm, significant focus is placed on the reduction or mitigation of quantum decoherence. When designing new quantum processing units, the general objective is to reduce the amount of noise qubits are…

Quantum Physics · Physics 2026-02-17 Viacheslav Kuzmin , Wilfrid Somogyi , Ekaterina Pankovets , Alexey Melnikov

The unavoidable presence of noise is thought to be one of the major problems to solve in order to pave the way for implementing quantum information technologies in realistic physical platforms. However, here we show a clear example in which…

Quantum Physics · Physics 2010-11-03 Filippo Caruso , Susana F. Huelga , Martin B. Plenio

Quantum Image Processing (QIP) is a field that aims to utilize the benefits of quantum computing for manipulating and analyzing images. However, QIP faces two challenges: the limitation of qubits and the presence of noise in a quantum…

Quantum Physics · Physics 2024-09-27 Yifan Zhou , Yan Shing Liang

Motivated by successful classical models for noise reduction, we suggest a quantum technique for filtering noise out of quantum states. The purpose of this paper is twofold: presenting a simple construction of quantum cross-correlations…

Quantum Physics · Physics 2017-11-27 Boaz Tamir , Eliahu Cohen

Background noise in many fields such as medical imaging poses significant challenges for accurate diagnosis, prompting the development of denoising algorithms. Traditional methodologies, however, often struggle to address the complexities…

Image and Video Processing · Electrical Eng. & Systems 2025-02-03 Amirreza Hashemi , Sayantan Dutta , Bertrand Georgeot , Denis Kouame , Hamid Sabet

Quantum computers will allow calculations beyond existing classical computers. However, current technology is still too noisy and imperfect to construct a universal digital quantum computer with quantum error correction. Inspired by the…

Quantum Physics · Physics 2020-10-27 Ana Martin , Lucas Lamata , Enrique Solano , Mikel Sanz

The method is introduced for fast data processing by reducing the probability amplitudes of undesirable elements. The algorithm has a mathematical description and circuit implementation on a quantum processor. The idea is to make a quick…

Quantum Physics · Physics 2025-04-24 Karina Zakharova , Artem Chernikov , Sergey Sysoev

The speed-up provided by quantum algorithms with respect to their classical counterparts is at the origin of scientific interest in quantum computation. However, the fundamental reasons for such a speed-up are not yet completely understood…

Quantum Physics · Physics 2007-05-23 C. Di Franco , M. Paternostro , M. S. Kim

In this paper we present a quantum algorithm that uses noise as a resource. The goal of our quantum algorithm is the calculation of operator averages of an open quantum system evolving in time. Selected low-noise system qubits and noisy…

Quantum annealing is a generic algorithm using quantum-mechanical fluctuations to search for the solution of an optimization problem. The present paper first reviews the fundamentals of quantum annealing and then reports on preliminary…

Disordered Systems and Neural Networks · Physics 2010-06-10 Masayuki Ohzeki , Hidetoshi Nishimori
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