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We present a formalism for studying the behaviour of quantum systems coupled to nonequilibrium environments exhibiting nonGaussian fluctuations. We discuss the role of a qubit as a detector of the statistics of environmental fluctuations,…

Mesoscale and Nanoscale Physics · Physics 2009-11-13 Clive Emary

The algebraic quantification of nonclassicality, which naturally arises from the quantum superposition principle, is related to properties of regular nonclassicality quasiprobabilities. The latter are obtained by non-Gaussian filtering of…

Quantum Physics · Physics 2018-05-21 B. Kühn , W. Vogel

An experimental study of current fluctuations through a tunable transmission barrier, a quantum point contact, are reported. We measure the probability distribution function of transmitted charge with precision sufficient to extract the…

Mesoscale and Nanoscale Physics · Physics 2009-11-13 G. Gershon , Yu. Bomze , E. V. Sukhorukov , M. Reznikov

It has historically been a challenge to perform Bayesian inference in a design-based survey context. The present paper develops a Bayesian model for sampling inference in the presence of inverse-probability weights. We use a hierarchical…

Methodology · Statistics 2020-06-24 Yajuan Si , Natesh S. Pillai , Andrew Gelman

We investigate a stochastic approach to non-equilibrium quantum spin systems based on recent insights linking quantum and classical dynamics. Exploiting a sequence of exact transformations, quantum expectation values can be recast as…

Statistical Mechanics · Physics 2019-01-31 S. De Nicola , B. Doyon , M. J. Bhaseen

We derive a theoretical framework for the experimental certification of non-Gaussian features of quantum states using double homodyne detection. We rank experimental non-Gaussian states according to the recently defined stellar hierarchy…

We study the physics of a magnetic molecule described by a "giant" spin with multiple ($d > 2$) spin states interacting with the quantized cavity field produced by a superconducting resonator. By means of the input-output formalism, we…

Quantum Physics · Physics 2022-06-17 Álvaro Gómez-León , Fernando Luis , David Zueco

Semi- and non-parametric mixture of regressions are a very useful flexible class of mixture of regressions in which some or all of the parameters are non-parametric functions of the covariates. These models are, however, based on the…

Methodology · Statistics 2026-01-21 Peterson Mambondimumwe , Sphiwe B. Skhosana , Najmeh Nakhaei Rad

We analyze the physical meaning of a possible experiment aimed at the simultaneous measurement of two non-commuting spin components. We demonstrate that switching of a strong spin-orbit interaction, e.g., in a solid state or a cold-atom…

Quantum Physics · Physics 2015-05-28 D. Sokolovski , E. Ya. Sherman

Continuous-variable quantum systems are foundational to quantum computation, communication, and sensing. While traditional representations using wave functions or density matrices are often impractical, the tomographic picture of quantum…

Quantum Physics · Physics 2026-03-17 Liubov A. Markovich , Xiaoyu Liu , Jordi Tura

Semi- and non-parametric mixture of regressions are a very useful flexible class of mixture of regressions in which some or all of the parameters are non-parametric functions of the covariates. These models are, however, based on the…

Methodology · Statistics 2026-01-13 Sphiwe B. Skhosana , Weixin Yao

We develop an entanglement criterion with third- and fourth-order cumulants to detect the entanglement of non-Gaussian states. The efficiency of the entanglement criterion is investigated for gravitating mirrors in optomechanical systems.…

Quantum Physics · Physics 2022-01-26 Daisuke Miki , Akira Matsumura , Kazuhiro Yamamoto

We show how to obtain the probability density function for the amplitude of the curvature perturbation, R, produced during an epoch of slow-roll, single-field inflation, working directly from n-point correlation functions of R. These…

Astrophysics · Physics 2007-05-23 David Seery , J. Carlos Hidalgo

We present a straightforward formulation of Stein's method for the semicircular distribution, specifically designed for the analysis of non-commutative random variables. Our approach employs a non-commutative version of Stein's heuristic,…

Probability · Mathematics 2024-12-03 Mario Díaz , Arturo Jaramillo

Gravitational wave detectors will need optimal signal-processing algorithms to extract weak signals from the detector noise. Most algorithms designed to date are based on the unrealistic assumption that the detector noise may be modeled as…

General Relativity and Quantum Cosmology · Physics 2009-11-07 Bruce Allen , Jolien D. E. Creighton , Eanna E. Flanagan , Joseph D. Romano

A stochastic representation of the dynamics of open quantum systems, suitable for non-perturbative system-reservoir interaction, non-Markovian effects and arbitrarily driven systems is presented. It includes the case of driving on…

Statistical Mechanics · Physics 2016-10-05 Jürgen T. Stockburger

We explore the possibility of using "weak measurements" without "weak value" for quantum state estimation. Since for weak measurements the disturbance caused during each measurement is small, we can rescue the state, unlike for the case of…

Quantum Physics · Physics 2019-07-23 Debmalya Das , Arvind

We propose to implement a solid-state rotation sensor by employing a many-body quantum spin system which takes the advantages of the easy controllability of the electron spin and the robustness provided by the collective nuclear spin state.…

Quantum Physics · Physics 2020-09-16 Wenkui Ding , Wenxian Zhang , Xiaoguang Wang

Following on from our recent work, we investigate a stochastic approach to non-equilibrium quantum spin systems. We show how the method can be applied to a variety of physical observables and for different initial conditions. We provide…

Statistical Mechanics · Physics 2020-01-24 S. De Nicola , B. Doyon , M. J. Bhaseen

Gaussian process is a theoretically appealing model for nonparametric analysis, but its computational cumbersomeness hinders its use in large scale and the existing reduced-rank solutions are usually heuristic. In this work, we propose a…

Machine Learning · Statistics 2015-11-25 Leo L. Duan , Xia Wang , Rhonda D. Szczesniak