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Related papers: Projection methods in quantum information science

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Most existing results in the analysis of quantum reservoir computing (QRC) systems with classical inputs have been obtained using the density matrix formalism. This paper shows that alternative representations can provide better insights…

Quantum Physics · Physics 2025-05-28 Rodrigo Martínez-Peña , Juan-Pablo Ortega

Any physical process can be represented as a quantum channel mapping an initial state to a final state. Hence it can be characterized from the point of view of communication theory, i.e., in terms of its ability to transfer information.…

Quantum Physics · Physics 2014-12-16 F. Caruso , V. Giovannetti , C. Lupo , S. Mancini

Quantification is well known to be a major obstacle in the construction of a probabilistic network, especially when relying on human experts for this purpose. The construction of a qualitative probabilistic network has been proposed as an…

Artificial Intelligence · Computer Science 2013-01-07 Silja Renooij , Linda C. van der Gaag

We describe the representation of arbitrary density operators in terms of expectation values of simple projection operators. Two representations are presented which yield non--recursive schemes for experimentally determining the density…

Quantum Physics · Physics 2009-10-28 Ole Steuernagel , John A. Vaccaro

We present two projects concerning the main part of my PhD work. In the first one we study quantum channels, which are the most general operations mapping quantum states into quantum states, from the point of view of their divisibility…

Quantum Physics · Physics 2020-09-02 David Davalos

Internet-scale quantum repeater networks will be heterogeneous in physical technology, repeater functionality, and management. The classical control necessary to use the network will therefore face similar issues as Internet data…

Quantum Physics · Physics 2023-04-21 Rodney Van Meter , Joe Touch , Dominic Horsman

Quantum computers can be considered as a natural means for performing machine learning tasks for inherently quantum labeled data. Many quantum machine learning techniques have been developed for solving classification problems, such as…

Quantum Physics · Physics 2025-01-24 Andrey Kardashin , Yerassyl Balkybek , Vladimir V. Palyulin , Konstantin Antipin

This is an exposition of some of the aspects of quantum computation and quantum information that have connections with operator theory. After a brief introduction, we discuss quantum algorithms. We outline basic properties of quantum…

Operator Algebras · Mathematics 2007-05-23 David W. Kribs

The ability to characterise and discern quantum channels is a crucial aspect of noisy quantum technologies. In this work, we explore the problem of distinguishing quantum channels when limited to sub-exponential resources, framed as von…

Quantum Physics · Physics 2025-07-18 Timothy Heightman , Grzegorz Rajchel-Mieldzioć

Simulating quantum physical processes has been one of the major motivations for quantum information science. Quantum channels, which are completely positive and trace preserving processes, are the standard mathematical language to describe…

Quantum Physics · Physics 2024-02-01 Hang Li , Kai Wang , Shijie Wei , Fan Yang , Xinyu Chen , Barry C. Sanders , Dong-Sheng Wang , Gui-Lu Long

Quantum computing is emerging as a new computing resource that could be superior to conventional computing for certain classes of optimization problems. However, in principle, most existing approaches to quantum optimization are intended to…

Optimization and Control · Mathematics 2022-01-21 Chin-Yao Chang , Eric Jones , Yiyun Yao , Peter Graf , Rishabh Jain

The resources needed to conventionally characterize a quantum system are overwhelmingly large for high- dimensional systems. This obstacle may be overcome by abandoning traditional cornerstones of quantum measurement, such as general…

Quantum Physics · Physics 2016-05-17 Gregory A. Howland , Samuel H. Knarr , James Schneeloch , Daniel J. Lum , John C. Howell

We consider the entanglement marginal problem, which consists of deciding whether a number of reduced density matrices are compatible with an overall separable quantum state. To tackle this problem, we propose hierarchies of semidefinite…

Quantum Physics · Physics 2021-11-30 Miguel Navascues , Flavio Baccari , Antonio Acin

If a large Quantum Computer (QC) existed today, what type of physical problems could we efficiently simulate on it that we could not simulate on a classical Turing machine? In this paper we argue that a QC could solve some relevant physical…

Quantum Physics · Physics 2009-11-10 Rolando Somma , Gerardo Ortiz , Emanuel Knill , James Gubernatis

We develop a general method for incentive-based programming of hybrid quantum-classical computing systems using reinforcement learning, and apply this to solve combinatorial optimization problems on both simulated and real gate-based…

Quantum Physics · Physics 2019-08-23 Keri A. McKiernan , Erik Davis , M. Sohaib Alam , Chad Rigetti

We study the problem of programmatic reinforcement learning, in which policies are represented as short programs in a symbolic language. Programmatic policies can be more interpretable, generalizable, and amenable to formal verification…

Machine Learning · Computer Science 2021-01-21 Abhinav Verma , Hoang M. Le , Yisong Yue , Swarat Chaudhuri

In this paper, we study quantitative properties of quantum programs. Properties of interest include (positive) almost-sure termination, expected runtime or expected cost, that is, for example, the expected number of applications of a given…

Logic in Computer Science · Computer Science 2023-12-22 Martin Avanzini , Georg Moser , Romain Péchoux , Simon Perdrix

The Quantum Projection Operator-Based NewtonMethod for Trajectory Optimization (Q-PRONTO) is a numerical method for solving quantum optimal control problems. This paper significantly improves prior versions of the quantum projection…

Quantum Physics · Physics 2024-01-10 Jieqiu Shao , Mantas Naris , John Hauser , Marco M. Nicotra

We present a new method for quantum process tomography. The method enables us to efficiently estimate, with fixed precision, any of the parameters characterizing a quantum channel. It is selective since one can choose to estimate the value…

Quantum Physics · Physics 2008-01-08 Ariel Bendersky , Fernando Pastawski , Juan Pablo Paz

We introduce a general method for the construction of quasiprobability representations for arbitrary notions of quantum coherence. Our technique yields a nonnegative probability distribution for the decomposition of any classical state.…

Quantum Physics · Physics 2018-06-22 J. Sperling , I. A. Walmsley