English
Related papers

Related papers: Learning Better Error Correction Codes with Hybrid…

200 papers

We show that quantum feedback control can be used as a quantum error correction process for errors induced by weak continuous measurement. In particular, when the error model is restricted to one, perfectly measured, error channel per…

Quantum Physics · Physics 2009-11-10 Charlene Ahn , H. W. Wiseman , G. J. Milburn

Recent progress in quantum computing has enabled systems with tens of reliable logical qubits, built from thousands of noisy physical qubits. However, many impactful applications demand quantum computations with millions of logical qubits,…

Quantum Physics · Physics 2026-05-26 Daiki Komoto , Kenta Kasai

Quantum computers have the potential to outperform classical computers for some complex computational problems. However, current quantum computers (e.g., from IBM and Google) have inherent noise that results in errors in the outputs of…

Software Engineering · Computer Science 2024-04-22 Asmar Muqeet , Shaukat Ali , Tao Yue , Paolo Arcaini

Quantum computers have the possibility of a much reduced calculation load compared with classical computers in specific problems. Quantum error correction (QEC) is vital for handling qubits, which are vulnerable to external noise. In QEC,…

Machine Learning · Computer Science 2025-12-15 Hideo Mukai , Hoshitaro Ohnishi

Quantum synchronizable error-correcting codes are special quantum error-correcting codes that are designed to correct both the effect of quantum noise on qubits and misalignment in block synchronization. It is known that in principle such a…

Quantum Physics · Physics 2014-11-17 Yuichiro Fujiwara , Peter Vandendriessche

A generalization of the stabilizer code construction presented by Gottesman is described, which allows for the construction of quantum error-correcting codes for continuous-variable systems. This formalism describes all continuous-variable…

Quantum Physics · Physics 2007-05-23 Richard L. Barnes

The ability to extract general laws from a few known examples depends on the complexity of the problem and on the amount of training data. In the quantum setting, the learner's generalization performance is further challenged by the…

Quantum Physics · Physics 2024-11-12 Leonardo Banchi , Jason Pereira , Marco Zamboni

As quantum computers continue to become more capable, the possibilities of their applications increase. For example, quantum techniques are being integrated with classical neural networks to perform machine learning. In order to be used in…

Quantum Physics · Physics 2024-11-03 Nidhi Munikote

Machine Learning classification models learn the relation between input as features and output as a class in order to predict the class for the new given input. Quantum Mechanics (QM) has already shown its effectiveness in many fields and…

Quantum error correction protects quantum information against environmental noise. When using qubits, a measure of quality of a code is the maximum number of errors that it is able to correct. We show that a suitable notion of ``number of…

Quantum Physics · Physics 2007-05-23 Emanuel Knill , Raymond Laflamme , Lorenza Viola

The encoding of classical data in a physical support can be done up to some level of accuracy due to errors and the imperfection of the writing process. Moreover, some degradation of the storage data can happen over the time because of…

Quantum Physics · Physics 2022-03-28 Giuseppe Ortolano , Ivano Ruo-Berchera

Optimization theory has been widely studied in academia and finds a large variety of applications in industry. The different optimization models in their discrete and/or continuous settings have catered to a rich source of research…

Quantum Physics · Physics 2026-03-16 Debbie Lim , Joao F. Doriguello , Patrick Rebentrost

In this work we extend the connection between Quantum Error Correction (QEC) and Lattice Gauge Theories (LGTs) by showing that a $\mathbb{Z}_N$ gauge theory with prime dimension $N$ coupled to dynamical matter can be expressed as a qudit…

Quantum Physics · Physics 2026-02-25 Luca Spagnoli , Alessandro Roggero , Nathan Wiebe

We investigate the performance of a quantum error-correcting code when pushed beyond its intended capacity to protect information against errors, presenting formulae for the probability of failure when the errors affect more qudits than…

Quantum Physics · Physics 2007-05-23 A. J. Scott

This paper proposes a hybrid quantum-classical algorithm to solve a fundamental power system problem called unit commitment (UC). The UC problem is decomposed into a quadratic subproblem, a quadratic unconstrained binary optimization (QUBO)…

Quantum Physics · Physics 2022-04-19 Reza Mahroo , Amin Kargarian

This thesis explores hybrid algorithms that combine classical and quantum computing to enhance the performance of classical algorithms. Two approaches are studied: a hybrid search and sample optimization algorithm and a classical algorithm…

Quantum Physics · Physics 2024-06-19 Roberto Campos

Concatenated coding provides a general strategy to achieve the desired level of noise protection in quantum information storage and transmission. We report the implementation of a concatenated quantum error-correcting code able to correct…

Quantum Physics · Physics 2009-11-10 Nicolas Boulant , Lorenza Viola , Evan M. Fortunato , David G. Cory

It is conjectured that quantum computers are able to solve certain problems more quickly than any deterministic or probabilistic computer. A quantum computer exploits the rules of quantum mechanics to speed up computations. However, it is a…

Information Theory · Computer Science 2009-08-15 Salah A. Aly

Among various classes of quantum error correcting codes (QECCs), non-stabilizer codes have rich properties and are of theoretical and practical interest. Decoding non-stabilizer codes is, however, a highly non-trivial task. In this paper,…

Quantum Physics · Physics 2025-01-15 Yoshifumi Nakata , Takaya Matsuura , Masato Koashi

Although recent advances in quantum machine learning (QML) offer significant potential for enhancing generative models, particularly in molecular design, a large array of classical approaches still face challenges in achieving high fidelity…

Machine Learning · Computer Science 2025-08-29 Afrar Jahin , Yi Pan , Yingfeng Wang , Tianming Liu , Wei Zhang
‹ Prev 1 8 9 10 Next ›