English
Related papers

Related papers: Gaussian Distributions and Phase Space Weyl--Heise…

200 papers

We propose a machine learning framework for parameter estimation of single mode Gaussian quantum states. Under a Bayesian framework, our approach estimates parameters of suitable prior distributions from measured data. For phase-space…

Quantum Physics · Physics 2021-08-16 Neel Kanth Kundu , Matthew R. McKay , Ranjan K. Mallik

We address the phase space formulation of a noncommutative extension of quantum mechanics in arbitrary dimension, displaying both spatial and momentum noncommutativity. By resorting to a covariant generalization of the Weyl-Wigner transform…

High Energy Physics - Theory · Physics 2008-11-26 Catarina Bastos , Orfeu Bertolami , Nuno Costa Dias , João Nuno Prata

Mutual space-frequency distribution is proposed and it is shown that Wigner and Weyl distribution functions are only particular cases of these distribution. Mutual distribution for Gaussian signal is analytically obtained. The simple…

Popular Physics · Physics 2008-10-16 Yura Kozlovskii

Gaussian quantum states of bosonic systems are an important class of states. In particular, they play a key role in quantum optics as all processes generated by Hamiltonians up to second order in the field operators (i.e. linear optics and…

Quantum Physics · Physics 2022-03-31 Jonatan Bohr Brask

Phase space quasi-probability functions provide powerful representations of quantum states and operators, as well as criteria for assessing quantum computational resources. In discrete, odd-dimensional systems (qudits), protocols involving…

Quantum Physics · Physics 2025-12-08 Eloi Descamps , Astghik Saharyan , Arne Keller , Pérola Milman

The phase-space description of bosonic quantum systems has numerous applications in such fields as quantum optics, trapped ultracold atoms, and transport phenomena. Extension of this description to the case of fermionic systems leads to…

Quantum Physics · Physics 2016-12-14 Evgeny A. Polyakov

The thesis is devoted to the phase space representation of relativistic quantum mechanics. For a class of observables with matrix-valued Weyl symbols proportional to the identity matrix, the Weyl-Wigner-Moyal formalism is proposed. The…

Quantum Physics · Physics 2007-05-23 A. A. Semenov

We derive a quantum version of the classical-optics Wiener-Khintchine theorem within the framework of detection of phase-space displacements with a suitably designed quantum ruler. A phase-pace based quantum mutual coherence function is…

Quantum Physics · Physics 2022-09-07 Ainara Álvarez-Marcos , Alfredo Luis

Weyl's formulation of quantum mechanics opened the possibility of studying the dynamics of quantum systems both in infinite-dimensional and finite-dimensional systems. Based on Weyl's approach, generalized by Schwinger, a self-consistent…

Mathematical Physics · Physics 2015-06-05 Nicolae Cotfas , Daniela Dragoman

The article explores a new formalism for describing motion in quantum mechanics. The construction is based on generalized coherent states with evolving fiducial vector. Weyl-Heisenberg coherent states are utilised to split quantum systems…

General Relativity and Quantum Cosmology · Physics 2020-09-10 Artur Miroszewski

We introduce matrix quantum phase-space distributions. These extend the idea of a quantum phase-space representation via projections onto a density matrix of global symmetry variables. The method is applied to verification of low-loss…

Quantum Physics · Physics 2025-03-18 Peter D. Drummond , Alexander S. Dellios , Margaret D. Reid

The Moyal--Weyl description of quantum mechanics provides a comprehensive phase space representation of dynamics. The Weyl symbol image of the Heisenberg picture evolution operator is regular in $\hbar$. Its semiclassical expansion…

High Energy Physics - Theory · Physics 2015-06-26 T. A. Osborn , F. H. Molzahn

In this paper we generalize the concept of Wigner function in the case of quantum mechanics with a minimum length scale arising due to the application of a generalized uncertainty principle (GUP). We present the phase space formulation of…

High Energy Physics - Theory · Physics 2021-01-28 Prathamesh Yeole , Vipul Kumar , Kaushik Bhattacharya

In this thesis we focus on Gaussian quantum metrology in the phase-space formalism and its applications in quantum sensing and the estimation of space-time parameters. We derive new formulae for the optimal estimation of multiple parameters…

Quantum Physics · Physics 2016-10-13 Dominik Šafránek

Gaussian quantum mechanics is a powerful tool regularly used in quantum optics to model linear and quadratic Hamiltonians efficiently. Recent interest in qubit-CV hybrid models has revealed a simple, yet important gap in our knowledge,…

Quantum Physics · Physics 2025-06-19 Nicholas Funai

We introduce a quantum phase space representation for the orientation state of extended quantum objects, using the Euler angles and their conjugate momenta as phase space coordinates. It exhibits the same properties as the standard Wigner…

Quantum Physics · Physics 2013-06-11 Timo Fischer , Clemens Gneiting , Klaus Hornberger

A two-step optimization is proposed to represent an arbitrary quantum state to a desired accuracy with the least number of gaussians in phase space. The Husimi distribution of the quantum state provides the information to determine the…

Atomic and Molecular Clusters · Physics 2009-11-10 Anatole Kenfack , Jan M Rost , Alfredo M Ozorio de Almeida

Wigner's quasi-probability distribution function in phase-space is a special (Weyl) representation of the density matrix. It has been useful in describing quantum transport in quantum optics; nuclear physics; decoherence (eg, quantum…

High Energy Physics - Theory · Physics 2008-11-26 Cosmas K Zachos

The density operator for a quantum system in thermal equilibrium with its environment depends on Planck's constant, as well as the temperature. At high temperatures, the Weyl representation, that is, the thermal Wigner function, becomes…

Quantum Physics · Physics 2021-06-30 Alfredo M. Ozorio de Almeida , Gert-Ludwig Ingold , Olivier Brodier

Gaussian processes are probabilistic models that are commonly used as functional priors in machine learning. Due to their probabilistic nature, they can be used to capture the prior information on the statistics of noise, smoothness of the…

Computation · Statistics 2024-02-02 Ahmad Farooq , Cristian A. Galvis-Florez , Simo Särkkä