English
Related papers

Related papers: The Kernel Quantum Probabilities (KQP) Library

200 papers

Quantum computing's transition from theory to reality has spurred the need for novel software tools to manage the increasing complexity, sophistication, toil, and fallibility of quantum algorithm development. We present Qualtran, an…

The present survey results from the will to reconcile two approaches to quantum probabilities: one rather physical and coming directly from quantum mechanics, the other more algebraic. The second leading idea is to provide a unified picture…

Mathematical Physics · Physics 2022-10-18 Raphael Chetrite , Frederic Patras

In recent times, quantum reservoir computing has emerged as a potential resource for time series prediction. Hence, there is a need for a flexible framework to test quantum circuits as nonlinear dynamical systems. We have developed a…

Quantum Physics · Physics 2024-01-22 Stanley Miao , Ola Tangen Kulseng , Alexander Stasik , Franz G. Fuchs

The use of kernel functions is a common technique to extract important features from data sets. A quantum computer can be used to estimate kernel entries as transition amplitudes of unitary circuits. Quantum kernels exist that, subject to…

Bounds on quantum probabilities and expectation values are derived for experimental setups associated with Bell-type inequalities. In analogy to the classical bounds, the quantum limits are experimentally testable and therefore serve as…

Quantum Physics · Physics 2007-05-23 Stefan Filipp , Karl Svozil

We develop a quantum version of the probability estimation framework [arXiv:1709.06159] for randomness generation with quantum side information. We show that most of the properties of probability estimation hold for quantum probability…

Quantum Physics · Physics 2023-02-06 Emanuel Knill , Yanbao Zhang , Honghao Fu

The Hilbert space formalism of quantum mechanics is reviewed with emphasis on applications to quantum computing. Standard interferomeric techniques are used to construct a physical device capable of universal quantum computation. Some…

High Energy Physics - Theory · Physics 2007-05-23 K. Svozil

Quantum Monte Carlo (QMC) methods deliver highly accurate electronic structure calculations but are computationally intensive. The quantum Monte Carlo kernel library (QMCkl) provides a modular, portable collection of high-performance…

The quantum mechanical probability densities are compared with the probability densities treated by the theory of random variables. The relevance of their difference for the interpretation of quantum mechanics is commented.

Quantum Physics · Physics 2008-04-28 Alberto C. de la Torre

Our aim is to experimentally study the possibility of distinguishing between quantum sources of randomness--recently proved to be theoretically incomputable--and some well-known computable sources of pseudo-randomness. Incomputability is a…

Quantum Physics · Physics 2009-12-23 Cristian S. Calude , Michael J. Dinneen , Monica Dumitrescu , Karl Svozil

Signal processing techniques will lean on blind methods in the near future, where no redundant, resource allocating information will be transmitted through the channel. To achieve a proper decision, however, it is essential to know at least…

Quantum Physics · Physics 2007-05-23 Ferenc Balázs , Sándor Imre

Comparing probability distributions is a core challenge across the natural, social, and computational sciences. Existing methods, such as Maximum Mean Discrepancy (MMD), struggle in high-dimensional and non-compact domains. Here we…

Machine Learning · Statistics 2025-09-09 Logan S. McCarty

This is the documentation for generating random samples from the quantum state space in accordance with a specified distribution, associated with this webpage: http://tinyurl.com/QSampling . Ready-made samples (each with at least a million…

Quantum probabilities are defined for several important physical cases characterizing measurements with multimode quantum systems. These are the probabilities for operationally testable measurements, for operationally uncertain…

Quantum Physics · Physics 2015-06-19 V. I. Yukalov , E. P. Yukalova , D. Sornette

Quantum kernel methods offer significant theoretical benefits by rendering classically inseparable features separable in quantum space. Yet, the practical application of Quantum Machine Learning (QML), currently constrained by the…

Machine Learning · Computer Science 2026-02-03 Philipp Altmann , Maximilian Mansky , Maximilian Zorn , Jonas Stein , Claudia Linnhoff-Popien

The subject of this work is quantum predicative programming -- the study of developing of programs intended for execution on a quantum computer. We look at programming in the context of formal methods of program development, or programming…

Quantum Physics · Physics 2008-02-19 Anya Tafliovich , E. C. R. Hehner

In the paper is discussed complete probabilistic description of quantum systems with application to multiqubit quantum computations. In simplest case it is a set of probabilities of transitions to some fixed set of states. The probabilities…

Quantum Physics · Physics 2007-05-23 Alexander Yu. Vlasov

We discuss some issues about probability in quantum mechanics, with particular emphasis on the GHZ theorem. We propose the usage of nonmonotonic upper probabilities as a tool to derive consistent joint upper probabilities for systems where…

Quantum Physics · Physics 2007-05-23 J. Acacio de Barros , Patrick Suppes

Quantum computing (QC) is an emerging computing paradigm with potential to revolutionize the field of computing. QC is a field that is quickly developing globally and has high barriers of entry. In this paper we explore both successful…

Software Engineering · Computer Science 2022-06-16 Ruslan Shaydulin , Caleb Thomas , Paige Rodeghero

Developing intuition about quantum information theory problems is difficult, as is verifying or ruling-out of hypothesis. We present a Matlab package intended to provide the QIT community with a new and powerful tool-set for quantum…

Quantum Physics · Physics 2007-08-06 Shai Machnes