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Using Landau's theory of two-fluid hydrodynamics, we investigate first and second sound propagating in a two-dimensional Bose gas. We study the temperature and interaction dependence of both sound modes and show that their behaviour…

Quantum Gases · Physics 2018-03-09 Miki Ota , Sandro Stringari

The evaluation of the path-integral representation for stochastic processes in the weak-noise limit shows that these systems are governed by a set of equations which are those of a classical dynamics. We show that, even when the noise is…

Condensed Matter · Physics 2009-10-22 S. J. B. Einchcomb , A. J. McKane

The stochastic dynamics of micron and nanoscale cantilevers immersed in a viscous fluid are quantified. Analytical results are presented for long slender cantilevers driven by Brownian noise. The spectral density of the noise force is not…

Mesoscale and Nanoscale Physics · Physics 2009-11-11 M. R. Paul , M. T. Clark , M. C. Cross

Stochastic averaging allows for the reduction of the dimension and complexity of stochastic dynamical systems with multiple time scales, replacing fast variables with statistically equivalent stochastic processes in order to analyze…

Probability · Mathematics 2015-02-25 William F. Thompson , Rachel A. Kuske , Adam H. Monahan

Anomalous Sound Detection (ASD) aims at identifying anomalous sounds from machines and has gained extensive research interests from both academia and industry. However, the uncertainty of anomaly location and much redundant information such…

Sound · Computer Science 2025-08-22 Guirui Zhong , Qing Wang , Jun Du , Lei Wang , Mingqi Cai , Xin Fang

We investigate the resonance type behaviour of an overdamped Brownian particle in a bistable potential driven by external periodic signal. It has been shown previously that the input energy pumped into the system by the external drive shows…

Statistical Mechanics · Physics 2007-05-23 Debasis Dan , A. M. Jayannavar

Estimating parameters of a diffusion process given continuous-time observations of the process via maximum likelihood approaches or, online, via stochastic gradient descent or Kalman filter formulations constitutes a well-established…

Methodology · Statistics 2025-03-17 Jan Albrecht , Sebastian Reich

We develop a general framework for state estimation in systems modeled with noise-polluted continuous time dynamics and discrete time noisy measurements. Our approach is based on maximum likelihood estimation and employs the calculus of…

Optimization and Control · Mathematics 2026-01-16 Griffin M. Kearney , Makan Fardad

Quantum enhanced sensing is a powerful technique in which nonclassical states are used to improve the sensitivity of a measurement. For enhanced mechanical displacement sensing, squeezed states of light have been shown to reduce the photon…

Quantum Physics · Physics 2016-07-05 Jeremy B. Clark , Florent Lecocq , Raymond W. Simmonds , José Aumentado , John D. Teufel

An analytic solution to a stationary heat conduction problem in 2D unbounded doubly periodic composite materials with temperature dependent conductivities of their components is given. Corresponding nonlinear boundary value problem is…

Analysis of PDEs · Mathematics 2014-04-01 David Kapanadze , Gennady Mishuris , Ekaterina Pesetskaya

Starting from our previous work where we have obtained a system of coupled integro-differential equations for acoustic sound waves and phonon density fluctuations in 2D crystals, we derive here the corresponding hydrodynamic equations and…

Statistical Mechanics · Physics 2019-04-15 Pablo Scuracchio , Karl H. Michel , Francois M. Peeters

Stochastic resonance is a non-linear phenomenon, in which the sensitivity of signal detectors can be enhanced by adding random noise to the detector input. Here, we demonstrate that noise can also improve the information flux in recurrent…

Neurons and Cognition · Quantitative Biology 2018-11-30 Patrick Krauss , Karin Prebeck , Achim Schilling , Claus Metzner

We study derivative-free methods for policy optimization over the class of linear policies. We focus on characterizing the convergence rate of these methods when applied to linear-quadratic systems, and study various settings of driving…

Machine Learning · Computer Science 2020-05-19 Dhruv Malik , Ashwin Pananjady , Kush Bhatia , Koulik Khamaru , Peter L. Bartlett , Martin J. Wainwright

We develop a machine learning algorithm to infer the emergent stochastic equation governing the evolution of an order parameter of a many-body system. We train our neural network to independently learn the directed force acting on the order…

Disordered Systems and Neural Networks · Physics 2024-12-10 Francesco Carnazza , Federico Carollo , Sabine Andergassen , Georg Martius , Miriam Klopotek , Igor Lesanovsky

Diffusion probabilistic models have achieved remarkable success in generative tasks across diverse data types. While recent studies have explored alternative degradation processes beyond Gaussian noise, this paper bridges two key diffusion…

Computer Vision and Pattern Recognition · Computer Science 2025-11-24 Hao-Chien Hsueh , Chi-En Yen , Wen-Hsiao Peng , Ching-Chun Huang

In this paper, we consider a quasi-linear stochastic heat equation on $[0,1]$, with Dirichlet boundary conditions and controlled by the space-time white noise. We formally replace the random perturbation by a family of noisy inputs…

Probability · Mathematics 2009-07-16 Xavier Bardina , Maria Jolis , Lluis Quer-Sardanyons

We provide examples of initial data which saturate the enhanced diffusion rates proved for general shear flows which are H\"{o}lder regular or Lipschitz continuous with critical points, and for regular circular flows, establishing the…

Analysis of PDEs · Mathematics 2019-11-25 Michele Coti Zelati , Theodore D. Drivas

How predictable are turbulent flows? Here we use theoretical estimates and shell model simulations to argue that Eulerian spontaneous stochasticity, a manifestation of the non-uniqueness of the solutions to the Euler equation that is…

Fluid Dynamics · Physics 2024-02-20 Dmytro Bandak , Alexei Mailybaev , Gregory L. Eyink , Nigel Goldenfeld

Higher order fluctuation expansions for stochastic heat equations (SHE) with nonlinear, non-conservative and conservative noise are obtained. These Edgeworth-type expansions describe the asymptotic behavior of solutions in suitable joint…

Probability · Mathematics 2024-06-27 Benjamin Gess , Zhengyan Wu , Rangrang Zhang

We present here a formulation for the calculation of the configuration averaged lattice thermal conductivity in random alloys. Our formulation is based on the augmented-space theorem, introduced by one of us, combined with a generalized…

Materials Science · Physics 2013-12-25 Aftab Alam , Abhijit Mookerjee