English
Related papers

Related papers: Quantized Detector Networks: a Quantum Information…

200 papers

QDN (quantized detector networks) is a description of quantum processes in which the principal focus is on observers and their apparatus, rather than on states of SUOs (systems under observation). It is a realization of Heisenberg's…

Quantum Physics · Physics 2009-11-13 George Jaroszkiewicz

Quantized detector networks (QDN) deals with quantum information exchange between observers and their apparatus rather than with systems under observation. Partial observations in QDN involve subsets of the elementary signal detectors which…

Quantum Physics · Physics 2008-03-11 G. Jaroszkiewicz

We formulate and study, in general terms, the problem of quantum system identification, i.e., the determination (or estimation) of unknown quantum channels through their action on suitably chosen input density operators. We also present a…

Quantum Physics · Physics 2007-05-23 Maxim Raginsky

We provide a systematic approach to quantum mechanics from an information-theoretic perspective using the language of tensor networks. Our formulation needs only a single kind of object, so-called positive *-tensors. Physical models…

Quantum Physics · Physics 2020-03-19 Andreas Bauer

The purpose of this paper is to provide a brief review of some recent developments in quantum feedback networks and control. A quantum feedback network (QFN) is an interconnected system consisting of open quantum systems linked by free…

Quantum Physics · Physics 2013-07-25 Guofeng Zhang , Matthew R. James

With the overwhelming success in the field of quantum information in the last decades, the "quest" for a Quantum Neural Network (QNN) model began in order to combine quantum computing with the striking properties of neural computing. This…

Quantum Physics · Physics 2014-09-01 M. Schuld , I. Sinayskiy , F. Petruccione

"Quantum sensing" describes the use of a quantum system, quantum properties or quantum phenomena to perform a measurement of a physical quantity. Historical examples of quantum sensors include magnetometers based on superconducting quantum…

Quantum Physics · Physics 2017-08-31 C. L. Degen , F. Reinhard , P. Cappellaro

Quantum networks of quantum objects promise to be exponentially more powerful than the objects considered independently. To live up to this promise will require the development of error mitigation and correction strategies to preserve…

There is a multitude of interpretations of quantum mechanics, but foundational principles are lacking. Relational quantum mechanics views the observer as a physical system, which allows for an unambiguous interpretation as all axioms are…

Quantum Physics · Physics 2025-06-16 Dorian Daimer , Susanne Still

Quantum coherence is a fundamental property of quantum systems, separating quantum from classical physics. Recently, there has been significant interest in the characterization of quantum coherence as a resource, investigating how coherence…

It is suggested that a quantum neural network (QNN), a type of artificial neural network, can be built using the principles of quantum information processing. The input and output qubits in the QNN can be implemented by optical modes with…

Quantum Physics · Physics 2007-05-23 M. V. Altaisky

The development of quantum information theory has renewed interest in the idea that the state vector does not represent the state of a quantum system, but rather the knowledge or information that we may have on the system. I argue that this…

Quantum Physics · Physics 2009-11-10 Louis Marchildon

Quantum cybernetics and its connections to complex quantum systems science is addressed from the perspective of complex quantum computing systems. In this way, the notion of an autonomous quantum computing system is introduced in regards to…

Neural and Evolutionary Computing · Computer Science 2014-02-06 Carlos Pedro Gonçalves

Quantum machine learning (QML) is rapidly transitioning from theoretical promise to practical relevance across data-intensive scientific domains. In this Review, we provide a structured overview of recent advances that bridge foundational…

Quantum Physics · Physics 2026-02-25 Vinit Singh , Amandeep Singh Bhatia , Mandeep Kaur Saggi , Manas Sajjan , Sabre Kais

Quantum machine learning aims to release the prowess of quantum computing to improve machine learning methods. By combining quantum computing methods with classical neural network techniques we aim to foster an increase of performance in…

High Energy Physics - Phenomenology · Physics 2021-03-17 Andrew Blance , Michael Spannowsky

We offer a fresh perspective on the relational interpretation of quantum mechanics as a way of thinking about the world described by quantum theory based on quantifiable notions of information. This allows us to provide a definition of a…

Quantum Physics · Physics 2026-02-10 Andrea Di Biagio , Carlo Rovelli

Artificial intelligence and machine learning paves the way to achieve greater technical feats. In this endeavor to hone these techniques, quantum machine learning is budding to serve as an important tool. Using the techniques of deep…

Quantum mechanics is usually presented starting from a series of postulates about the mathematical framework. In this work we show that those same postulates can be derived by assuming that measurements are discrete interactions: that is,…

Quantum Physics · Physics 2008-01-08 Gabriele Carcassi

An attempt is made to formulate quantum mechanics (QM) in physical rather than in mathematical terms. It is argued that the appropriate conceptual framework for QM is "contextual objectivity", which includes an objective definition of the…

Quantum Physics · Physics 2016-09-08 Philippe Grangier

Improved measurement techniques are central to technological development and foundational scientific exploration. Quantum optics relies upon detectors sensitive to non-classical features of light, enabling precise tests of physical laws and…

Quantum Physics · Physics 2014-07-18 Merlin Cooper , Michal Karpinski , Brian J. Smith
‹ Prev 1 2 3 10 Next ›