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Related papers: Introduction to Langevin Stochastic Processes

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While representation learning has been central to the rise of machine learning and artificial intelligence, a key problem remains in making the learned representations meaningful. For this, the typical approach is to regularize the learned…

Machine Learning · Computer Science 2024-04-11 Dedi Wang , Yihang Wang , Luke Evans , Pratyush Tiwary

It is non-trivial to recognize phase transitions and track dynamics inside a stochastic process because of its intrinsic stochasticity. In this paper, we employ the deep learning method to classify the phase orders and predict the damping…

Nuclear Theory · Physics 2021-06-30 Lijia Jiang , Lingxiao Wang , Kai Zhou

These are lecture notes for a series of lectures given at the Les Houches Summer School on Integrability in Atomic and Condensed Matter Physics, 30 July to 24 August 2018. The same series of lectures has also been given at the Tokyo…

Statistical Mechanics · Physics 2020-09-10 Benjamin Doyon

Minimizing non-convex and high-dimensional objective functions is challenging, especially when training modern deep neural networks. In this paper, a novel approach is proposed which divides the training process into two consecutive phases…

Machine Learning · Computer Science 2017-10-11 Nanyang Ye , Zhanxing Zhu , Rafal K. Mantiuk

Given nonstationary data from molecular dynamics simulations, a Markovian Langevin model is constructed that aims to reproduce the time evolution of the underlying process. While at equilibrium the free energy landscape is sampled,…

Computational Physics · Physics 2021-07-20 Benjamin Lickert , Steffen Wolf , Gerhard Stock

Numerical simulations of fast remagnetization processes using the stochastic dynamics are widely used to study various magnetic systems. In this paper we first address several crucial methodological problems of such simulations: (i) the…

Other Condensed Matter · Physics 2009-11-10 Dmitri V. Berkov , Natalia L. Gorn

We consider simple stochastic climate models, described by slowly time-dependent Langevin equations. We show that when the noise intensity is not too large, these systems can spend substantial amounts of time in metastable equilibrium,…

Atmospheric and Oceanic Physics · Physics 2007-05-23 Nils Berglund , Barbara Gentz

A hidden Markov process is a well known concept in information theory and is used for a vast range of applications such as speech recognition and error correction. We bridge between two disciplines, experimental physics and advanced…

Mesoscale and Nanoscale Physics · Physics 2015-06-24 Ido Kanter , Aviad Frydman , Asaf Ater

This is the list of the full papers accepted for presentation at the 32nd International Conference on Logic Programming, New York City, USA, October 18-21, 2016. In addition to the main conference itself, ICLP hosted four pre-conference…

Programming Languages · Computer Science 2016-08-22 Manuel Carro , Andy King

A new approach for the analysis of Langevin-type stochastic processes in the presence of strong measurement noise is presented. For the case of Gaussian distributed, exponentially correlated, measurement noise it is possible to extract the…

Data Analysis, Statistics and Probability · Physics 2013-05-29 Bernd Lehle

This volume contains the papers presented at CICLOPS'12: 12th International Colloquium on Implementation of Constraint and LOgic Programming Systems held on Tueseday September 4th, 2012 in Budapest. The program included 1 invited talk, 9…

Programming Languages · Computer Science 2013-02-04 Nicos Angelopoulos , Roberto Bagnara

We develop an efficient sampling method by simulating Langevin dynamics with an artificial force rather than a natural force by using the gradient of the potential energy. The standard technique for sampling following the predetermined…

Statistical Mechanics · Physics 2015-09-30 M. Ohzeki , A. Ichiki

These proceedings collate lectures given at the twenty-fifth specialized course organised by the CERN Accelerator School (CAS). The course was held in Bilbao, Spain from 24 May to 2 June 2011, in collaboration with ESS Bilbao. The course…

Accelerator Physics · Physics 2013-08-02 R. Bailey

Quantitative methods and mathematical modeling are playing an increasingly important role across disciplines. As a result, interdisciplinary mathematics courses are increasing in popularity. However, teaching such courses at an advanced…

Other Quantitative Biology · Quantitative Biology 2021-09-10 Mark Jayson Cortez , Alan Eric Akil , Krešimir Josić , Alexander J. Stewart

D. B. Br\"{u}ckner et al. [Phys. Rev. Lett. 125, 058103 (2020)] have described a novel method for inferring the dynamics of systems governed by an underdamped Langevin equation in the presence of measurement noise. While this is a…

Statistical Mechanics · Physics 2026-04-10 Yeeren I. Low

The purpose of this paper is to examine the Lagrangian stochastic modeling of the fluid velocity seen by inertial particles in a nonhomogeneous turbulent flow. A new Langevin-type model, compatible with the transport equation of the drift…

Fluid Dynamics · Physics 2009-07-01 Boris Arcen , Anne Tanière

These proceedings are a summary of four lectures given at the Theoretical Advanced Study Institute in Elementary Particle Physics (TASI) in 2009. These lectures provide a basic introduction to experimental particle physics and the Large…

High Energy Physics - Experiment · Physics 2010-05-03 E. Halkiadakis

We report mainly on the global flagship outreach activity in particle physics: the International Particle Physics Masterclasses. It is illustrated on the example of Slovakia and the Czech Republic. The Masterclasses are described and their…

Physics Education · Physics 2024-01-31 Boris Tomasik , Julia Kekelakova , Ivan Melo , Vojtech Pleskot

These notes are based on the lectures that one of us (HT) gave at the Summer School on the "Theory of Large Deviations and Applications", held in July 2024 at Les Houches in France. They present the basic definitions and mathematical…

Statistical Mechanics · Physics 2025-10-29 Ivan N. Burenev , Daniël W. H. Cloete , Vansh Kharbanda , Hugo Touchette

Response lags are generic to almost any physical system and often play a crucial role in the feedback loops present in artificial nanodevices and biological molecular machines. In this paper, we perform a comprehensive study of small…

Statistical Mechanics · Physics 2015-06-23 M. L. Rosinberg , T. Munakata , G. Tarjus
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