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Related papers: Quantum learning machines

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Quantum communication theory sets the maximum rates at which information can be encoded and decoded reliably given the physical properties of the information carriers. Here we consider the problem of readout of a digital optical memory,…

Quantum Physics · Physics 2013-07-18 Cosmo Lupo , Stefano Pirandola , Vittorio Giovannetti , Stefano Mancini

Quantum systems have an exponentially large degree of freedom in the number of particles and hence provide a rich dynamics that could not be simulated on conventional computers. Quantum reservoir computing is an approach to use such a…

Quantum Physics · Physics 2020-11-11 Keisuke Fujii , Kohei Nakajima

We propose a novel notion of a quantum learning machine for automatically controlling quantum coherence and for developing quantum algorithms. A quantum learning machine can be trained to learn a certain task with no a priori knowledge on…

Quantum Physics · Physics 2008-03-31 Jeongho Bang , James Lim , M. S. Kim , Jinhyoung Lee

We consider quantum learning machines -- quantum computers that modify themselves in order to improve their performance in some way -- that are trained to perform certain classical task, i.e. to execute a function which takes classical bits…

Quantum Physics · Physics 2009-12-15 Daniel Manzano , Marcin Pawlowski , Caslav Brukner

Machine learning has been used in high energy physics for a long time, primarily at the analysis level with supervised classification. Quantum computing was postulated in the early 1980s as way to perform computations that would not be…

We consider quantum-classical hybrid machine learning in which large-scale input channels remain classical and small-scale working channels process quantum operations conditioned on classical input data. This does not require the conversion…

Machine Learning algorithms are extensively used in an increasing number of systems, applications, technologies, and products, both in industry and in society as a whole. They enable computing devices to learn from previous experience and…

Quantum Physics · Physics 2025-02-17 Lucas Lamata

Here we will give a perspective on new possible interplays between Machine Learning and Quantum Physics, including also practical cases and applications. We will explore the ways in which machine learning could benefit from new quantum…

Quantum Physics · Physics 2021-08-24 Lorenzo Buffoni , Filippo Caruso

The heat dissipation in quantum metrology represents not only an unavoidable problem towards practical applications of quantum sensing devices but also a fundamental relationship between thermodynamics and quantum metrology. However, a…

Quantum Physics · Physics 2023-02-02 Yaoming Chu , Jianming Cai

We introduce a general statistical learning theory for processes that take as input a classical random variable and output a quantum state. Our setting is motivated by the practical situation in which one desires to learn a quantum process…

Quantum Physics · Physics 2025-02-27 Marco Fanizza , Yihui Quek , Matteo Rosati

The laws of thermodynamics apply equally well to quantum systems as to classical systems, and because of this quantum effects do not change the fundamental thermodynamic efficiency of isothermal refrigerators or engines. We show that,…

Quantum Physics · Physics 2015-06-17 Jordan M. Horowitz , Kurt Jacobs

The idea of information encoding on quantum bearers and its quantum-mechanical processing has revolutionized our world and brought mankind on the verge of enigmatic era of quantum technologies. Inspired by this idea, in present paper we…

Quantum Physics · Physics 2014-04-18 Michael Siomau

For the past two decades, researchers have attempted to create a Quantum Neural Network (QNN) by combining the merits of quantum computing and neural computing. In order to exploit the advantages of the two prolific fields, the QNN must…

Quantum Physics · Physics 2015-12-15 Kok-Leong Seow , Elizabeth Behrman , James Steck

At its microscopic level, the universe follows the laws of quantum mechanics. Focusing on the quantum trajectories of particles as followed from the hydrodynamical formulation of quantum mechanics, we propose that under general…

Quantum Physics · Physics 2024-02-27 Tomer Shushi

Model-independent estimation of the properties of quantum states is a central challenge in quantum technologies, as experimental imperfections, drifts, and imprecise models of the actual quantum dynamics inevitably hinder accurate…

Recent developments in Quantum Machine Learning have seen the introduction of several models to generalize the classical perceptron to the quantum regime. The capabilities of these quantum models need to be determined precisely in order to…

Quantum Physics · Physics 2022-05-31 Fabio Benatti , Giovanni Gramegna , Stefano Mancini

Artificial intelligence and machine learning have been widely adopted both in the industry and in everyday life, but at the cost of high compute demands. Recent studies show that implementing machine learning in physical systems in the deep…

Quantum Physics · Physics 2026-05-12 J. C. López Carreño , S. Świerczewski , A. Opala , A. Salavrakos , B. Piętka , M. Matuszewski

Quantum computing is the process of performing calculations using quantum mechanics. This field studies the quantum behavior of certain subatomic particles for subsequent use in performing calculations, as well as for large-scale…

Quantum Physics · Physics 2023-12-07 David Peral García , Juan Cruz-Benito , Francisco José García-Peñalvo

We consider a basic model of digital memory where each cell is composed of a reflecting medium with two possible reflectivities. By fixing the mean number of photons irradiated over each memory cell, we show that a non-classical source of…

Quantum Physics · Physics 2015-03-19 Stefano Pirandola

Efficiently characterising quantum systems, verifying operations of quantum devices and validating underpinning physical models, are central challenges for the development of quantum technologies and for our continued understanding of…