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Related papers: Conditional Density Matrix in the Context of Nonco…

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A new quantum mechanical notion -- Conditional Density Matrix -- is discussed and is applied to describe some physical processes. This notion is a natural generalization of von Neumann density matrix for such processes as divisions of…

Quantum Physics · Physics 2007-05-23 V. V. Belokurov , O. A. Khrustalev , V. A. Sadovnichy , O. D. Timofeevskaya

It is well known that density matrices can be used in quantum mechanics to represent the information available to an observer about either a system with a random wave function (``statistical mixture'') or a system that is entangled with…

Quantum Physics · Physics 2007-05-23 Detlef Duerr , Sheldon Goldstein , Roderich Tumulka , Nino Zanghi

In this paper we develop the conditional density matrix formalism for adequate description of division and unificationof quantum systems. Applications of this approach to the descriptions of parapositronium, quantum teleportation and others…

Quantum Physics · Physics 2007-05-23 V. V. Belokurov , O. A. Khrustalev , V. A. Sadovnichy , O. D. Timofeevskaya

The quantum density matrix generalises the classical concept of probability distribution to quantum theory. It gives the complete description of a quantum state as well as the observable quantities that can be extracted from it. Its…

Quantum Physics · Physics 2023-08-31 Apoorva D. Patel

A quantum system's state is identified with a density matrix. Though their probabilistic interpretation is rooted in ensemble theory, density matrices embody a known shortcoming. They do not completely express an ensemble's physical…

Quantum Physics · Physics 2021-06-30 Fabio Anza , James P. Crutchfield

We point out that density matrices can only be used to describe quantum states, so the entanglement contained in a density matrix is just quantum entanglement. This means a bipartite state described by a density matrix contains quantum…

Quantum Physics · Physics 2010-12-27 Yong Zhou

The density matrix formalism which is widely used in the theory of measurements, quantum computing, quantum description of chemical and biological systems always imply the averaging over the states of the environment. In practice this is…

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

We clarify different definitions of the density matrix by proposing the use of different names, the full density matrix for a single-closed quantum system, the compressed density matrix for the averaged single molecule state from an…

Quantum Physics · Physics 2007-05-23 Gui Lu Long , Yi-Fan Zhou , Jia-Qi Jin , Yang Sun , Hai-Woong Lee

In these notes I explain how to describe one-dimensional quantum systems that are simultaneously near to, but not exactly at, a critical point, and in a far-from-equilibrium steady state. This description uses a density matrix on scattering…

Statistical Mechanics · Physics 2012-12-06 Benjamin Doyon

We develop a theoretical approach to compute the conditioned spectral density of $N \times N$ non-invariant random matrices in the limit $N \rightarrow \infty$. This large deviation observable, defined as the eigenvalue distribution…

Disordered Systems and Neural Networks · Physics 2018-08-15 Isaac Pérez Castillo , Fernando L. Metz

In this note I will present a subtle interplay between density matrices and the knowledge about their preparation, and I will argue that there is a need to consider a new type of quantum state, in between pure states and density matrices.

Quantum Physics · Physics 2018-11-15 Sandu Popescu

We give necessary and sufficient conditions under which a density matrix acting on a two-fold tensor product space is separable. Our conditions are given in terms of quantum conditional information transmission.

Quantum Physics · Physics 2016-09-08 Robert R. Tucci

A density matrix describes the statistical state of a quantum system. It is a powerful formalism to represent both the quantum and classical uncertainty of quantum systems and to express different statistical operations such as measurement,…

Machine Learning · Computer Science 2024-05-01 Fabio A. González , Alejandro Gallego , Santiago Toledo-Cortés , Vladimir Vargas-Calderón

In ordinary, non-relativistic, quantum physics, time enters only as a parameter and not as an observable: a state of a physical system is specified at a given time and then evolved according to the prescribed dynamics. While the state can,…

Quantum Physics · Physics 2013-02-13 Joseph Fitzsimons , Jonathan Jones , Vlatko Vedral

Subsystems of composite quantum systems are described by reduced density matrices, or quantum marginals. Important physical properties often do not depend on the whole wave function but rather only on the marginals. Not every collection of…

Quantum Physics · Physics 2014-10-31 Michael Walter

The dynamical equation satisfied by the density matrix, when a quantum system is subjected to one or more constraints arising from conserved quantities, is derived. The resulting nonlinear motion of the density matrix has the property that…

Quantum Physics · Physics 2015-02-23 Dorje C. Brody , Anna C. T. Gustavsson , Lane P. Hughston

The physical regions (domains or basins) within the molecular structure are open systems that exchange charge between them and consequently house a fractional number of electrons (net charge). The natural framework describing the quantum…

Quantum Physics · Physics 2023-10-23 Roberto Bochicchio , Boris Maulén

In a paper of us, it is showed that Density Matrices do not provide a complete description of ensembles of states in quantum mechanics, since they lack measurable information concerning the preparation of the ensembles. Bodor and Di\'osi…

Quantum Physics · Physics 2012-04-06 F. Fratini , A. G. Hayrapetyan

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

This paper introduces a novel approach to probabilistic deep learning, kernel density matrices, which provide a simpler yet effective mechanism for representing joint probability distributions of both continuous and discrete random…

Machine Learning · Computer Science 2024-05-01 Fabio A. González , Raúl Ramos-Pollán , Joseph A. Gallego-Mejia
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