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Multimodal distributions of some physics based model parameters are often encountered in engineering due to different situations such as a change in some environmental conditions, and the presence of some types of damage and nonlinearity.…

Computation · Statistics 2022-10-19 Felipe Igea , Alice Cicirello

Mesoscopic $N-$atom systems derive their structural and dynamical properties from processes coupled across multiple scales in space and time. An efficient method for understanding these systems in the friction dominated regime from the…

Chemical Physics · Physics 2014-01-28 Andrew Abi Mansour , Peter J. Ortoleva

Recent measurements of durations of non-equilibrium processes provide valuable information on microscopic mechanisms and energetics. Comprehensive theory for corresponding experiments so far is well developed for single-particle systems…

Statistical Mechanics · Physics 2020-09-04 David Voráč , Philipp Maass , Artem Ryabov

The separation of substances into different phases is ubiquitous in nature and important scientifically and technologically. This phenomenon may become drastically different if the species involved, whether molecules or supramolecular…

We adapt Vertex models to understand the physical origin of the formation of long-range ordered structures in repulsive soft particles. The model incorporates contributions from the volume and surface area of each particle. Sampling using…

Soft Condensed Matter · Physics 2022-06-28 Toluwanimi O. Bello , Sangwoo Lee , Patrick T. Underhill

Demand for high-performance, robust, and safe autonomous systems has grown substantially in recent years. These objectives motivate the desire for efficient safety-theoretic reasoning that can be embedded in core decision-making tasks such…

Robotics · Computer Science 2022-12-27 Kristoffer M. Frey , Ted J. Steiner , Jonathan P. How

An efficient Path Integral Monte Carlo procedure is proposed to simulate the behavior of quantum many-body dissipative systems described within the framework of the influence functional. Thermodynamic observables are obtained by Monte Carlo…

Statistical Mechanics · Physics 2009-11-07 Luca Capriotti , Alessandro Cuccoli , Andrea Fubini , Valerio Tognetti , Ruggero Vaia

First of all, this paper presents some improvements of DSMC method in the form of new schemes and approaches, that, for a wide class of problems, increase performance and reduce the demands on computer resources. The most important…

Fluid Dynamics · Physics 2012-01-16 Roman V. Maltsev

Spatial fields in the Earth and environmental sciences are often available at multiple scales or resolutions. While coarse-scale data (e.g., from global circulation models) are often abundant, they lack the local detail provided by…

Methodology · Statistics 2026-04-01 Alejandro Calle-Saldarriaga , Paul F. V. Wiemann , Matthias Katzfuss

We introduce methods and theory for fractionally cointegrated curve time series. We develop a variance-ratio test to determine the dimensions associated with the nonstationary and stationary subspaces. For each subspace, we apply a local…

Statistics Theory · Mathematics 2024-09-10 Won-Ki Seo , Han Lin Shang

While existing mathematical descriptions can accurately account for phenomena at microscopic scales (e.g. molecular dynamics), these are often high-dimensional, stochastic and their applicability over macroscopic time scales of physical…

Machine Learning · Statistics 2016-09-08 P. S. Koutsourelakis , Elias Bilionis

Time-dependent data often exhibit characteristics, such as non-stationarity and heavy-tailed errors, that would be inappropriate to model with the typical assumptions used in popular models. Thus, more flexible approaches are required to be…

Machine Learning · Statistics 2023-11-02 Taole Sha , Michael Minyi Zhang

Non-reciprocal systems have been shown to sustain time-dependent patterns, most prominently travelling waves. The transition into these time-dependent states generally breaks time-translational invariance, representing a clear deviation…

Statistical Mechanics · Physics 2026-05-13 Emir Sezik , Gunnar Pruessner

A numerical technique is introduced that reduces exponentially the time required for Monte Carlo simulations of non-equilibrium systems. Results for the quasi-stationary probability distribution in two model systems are compared with the…

Adaptation and Self-Organizing Systems · Physics 2009-11-07 A. Bandrivskyy , S. Beri , D. G. Luchinsky , R. Mannella , P. V. E. McClintock

In dynamic Monte Carlo simulations, using for example the Metropolis dynamic, it is often required to simulate for long times and to simulate large systems. We present an overview of advanced algorithms to simulate for larger times and to…

Statistical Mechanics · Physics 2007-05-23 M. A. Novotny , Alice K. Kolakowska , G. Korniss

This paper is concerned with mathematical modeling of intelligent systems, such as human crowds and animal groups. In particular, the focus is on the emergence of different self-organized patterns from non-locality and anisotropy of the…

Mathematical Physics · Physics 2010-09-07 Emiliano Cristiani , Benedetto Piccoli , Andrea Tosin

Many real-world systems studied are governed by complex, nonlinear dynamics. By modeling these dynamics, we can gain insight into how these systems work, make predictions about how they will behave, and develop strategies for controlling…

Machine Learning · Statistics 2019-06-05 Josue Nassar , Scott W. Linderman , Monica Bugallo , Il Memming Park

Anisotropy at the level of the inter-particle interaction provides the particles with specific instructions for the self-assembly of target structures. The ability to synthesize non-spherical colloids, together with the possibility of…

Soft Condensed Matter · Physics 2020-01-03 Carina Karner , Christoph Dellago , Emanuela Bianchi

Gaussian processes (GPs) are commonplace in spatial statistics. Although many non-stationary models have been developed, there is arguably a lack of flexibility compared to equipping each location with its own parameters. However, the…

Machine Learning · Statistics 2018-07-19 Leo L. Duan , Xia Wang , Rhonda D. Szczesniak

This paper introduces a new behavioral system model with distinct external and internal signals possibly evolving on different time scales. This allows to capture abstraction processes or signal aggregation in the context of control and…

Systems and Control · Computer Science 2014-02-17 Anne-Kathrin Schmuck , Jörg Raisch