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Observations or measurements taken of a quantum system (a small number of fundamental particles) are inherently random. If the state of the system depends on unknown parameters, then the distribution of the outcome depends on these…

Statistics Theory · Mathematics 2007-06-13 Richard D. Gill

The paper develops new methods of non-parametric estimation a compound Poisson distribution. Such a problem arise, in particular, in the inference of a Levy process recorded at equidistant time intervals. Our key estimator is based on…

Statistics Theory · Mathematics 2015-10-19 Alexey Lindo , Sergei Zuyev , Serik Sagitov

We study non-gaussianity effects, using the $\delta N$ formalism, in a multi-field inflationary model consisting of K\"ahler moduli derived from type IIB string compactification in the large volume limit. The analytical work in this paper…

High Energy Physics - Theory · Physics 2010-10-19 Per Berglund , Guoqin Ren

Heterogeneity in dynamics in the form of non-Gaussian molecular displacement distributions appears ubiquitously in soft matter. We address the quantification of such heterogeneity using an information-theoretic measure of the distance…

Soft Condensed Matter · Physics 2020-08-04 Rahul Dandekar , Soumyakanti Bose , Suman Dutta

The telecloning protocol distributes quantum states from a single sender to multiple receivers via a shared entangled state by exploiting the notions of teleportation and approximate cloning. We investigate the optimal telecloning…

Quantum Physics · Physics 2024-07-03 Sudipta Das , Rivu Gupta , Himadri Shekhar Dhar , Aditi Sen De

We present a quantifier of non-classical correlations for bipartite, multi-mode Gaussian states. It is derived from the Discriminating Strength measure, introduced for finite dimensional systems in A. Farace et al., New. J. Phys. 16, 073010…

Quantum Physics · Physics 2015-11-03 Luca Rigovacca , Alessandro Farace , Antonella De Pasquale , Vittorio Giovannetti

We address the dual challenge of estimating deviations from Gaussianity arising in models of the Early Universe, whilst retaining information necessary to assess whether a detection of non-Gaussianity is primordial. We do this by…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-13 Dipak Munshi , Alan Heavens

Anomalous diffusion and non-Gaussian statistics are detected experimentally in a two-dimensional driven-dissipative system. A single-layer dusty plasma suspension with a Yukawa interaction and frictional dissipation is heated with laser…

Soft Condensed Matter · Physics 2009-11-13 Bin Liu , J. Goree

We propose a critical dissipaive quantum metrology schemes for single parameter estimation which are based on a quantum probe consisting of coherently driven ensemble of $N$ spin-1/2 particles under the effect of squeezed, collective spin…

Quantum Physics · Physics 2023-08-16 Venelin P. Pavlov , Diego Porras , Peter A. Ivanov

Cubic phase states provide the essential non-Gaussian resource for continuous-variable quantum computing. We show that they also offer significant potential for quantum metrology, surpassing the phase-sensing sensitivity of all Gaussian…

Quantum Physics · Physics 2025-12-04 Jiajie Guo , Shuheng Liu , Boxuan Jing , Qiongyi He , Manuel Gessner

We investigate and compare the fundamental performance of several distributed learning methods that have been proposed recently. We do this in the context of a distributed version of the classical signal-in-Gaussian-white-noise model, which…

Statistics Theory · Mathematics 2017-11-10 Botond Szabo , Harry van Zanten

Since the appearance of the classical paper of Lifshitz almost half a century ago, linear stability analysis of cosmological models is textbook knowledge. Until recently, however, little was known about the behavior of higher than linear…

Astrophysics · Physics 2007-05-23 R. Juszkiewicz , F. R. Bouchet

We study the long-range effective drift and diffusivity of a particle in a random medium moving subject to a given molecular diffusivity and a local drift. The local drift models the effect of a random electrostatic field on a neutral but…

Disordered Systems and Neural Networks · Physics 2009-10-30 I. T. Drummond , R. R. Horgan , C. A. da Silva Santos

Quantum probes are atomic-sized devices mapping information of their environment to quantum mechanical states. By improving measurements and at the same time minimizing perturbation of the environment, they form a central asset for quantum…

We introduce a simple and efficient technique to verify quantum discord in unknown Gaussian states and a certain class of non-Gaussian states. We show that any separation in the peaks of the marginal distributions of one subsystem…

We measure the sensitivity of a broadband atomic magnetometer using quantum non-demolition spin measurements. A cold, dipole-trapped sample of rubidium atoms provides a long-lived spin system in a non-magnetic environment, and is probed…

Quantum Physics · Physics 2009-11-25 M. Koschorreck , M. Napolitano , B. Dubost , M. W. Mitchell

We investigate the estimation of dephasing-induced decoherence in continuous-variable quantum systems using non-Gaussian probe states. By purifying the open system, we identify optimal probes, specifically squeezed cat and symmetric…

Quantum Physics · Physics 2026-01-27 Arman , Prasanta K. Panigrahi

Quantum non-demolition (QND) measurements improve sensitivity by evading measurement back-action. The technique was first proposed to detect mechanical oscillations in gravity wave detectors,and demonstrated in the measurement of optical…

Quantum Physics · Physics 2014-09-25 R. J. Sewell , M. Napolitano , N. Behbood , G. Colangelo , M. W. Mitchell

Non-Gaussian states, described by Wigner quasi-probability distribution taking negative values, are of great interest for various applications of quantum physics. It is known however that they are highly vulnerable to dissipation. In this…

Quantum Physics · Physics 2025-09-26 Boulat Nougmanov

Many problems in navigation and tracking require increasingly accurate characterizations of the evolution of uncertainty in nonlinear systems. Nonlinear uncertainty propagation approaches based on Gaussian mixture density approximations…

Machine Learning · Statistics 2025-12-30 Jackson Kulik , Keith A. LeGrand