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Polynomial dynamical systems are widely used to model and study real phenomena. In biochemistry, they are the preferred choice for modelling the concentration of chemical species in reaction networks with mass-action kinetics. These systems…

Algebraic Geometry · Mathematics 2014-12-30 Elisenda Feliu

The determination of mechanical properties such as the Young's modulus provides an important means to compare classical molecular dynamics simulations with materials. In this respect, ultra-thin materials hold several challenges: their…

Materials Science · Physics 2025-02-06 L. Mihlan , J. Ehrens , J. Schnack

Enhanced sampling techniques such as umbrella sampling and metadynamics are now routinely used to provide information on how the thermodynamic potential, or free energy, depends on a small number of collective variables. The free energy…

Computational Physics · Physics 2018-08-31 Ilaria Gimondi , Gareth A. Tribello , Matteo Salvalaglio

This paper presents a new approach to crowd behaviour anomaly detection that uses a set of efficiently computed, easily interpretable, scene-level holistic features. This low-dimensional descriptor combines two features from the literature:…

Computer Vision and Pattern Recognition · Computer Science 2016-06-17 M. Marsden , K. McGuinness , S. Little , N. E. O'Connor

In molecular dynamics (MD) simulations, transitions between states are often rare events due to energy barriers that exceed the thermal temperature. Because of their infrequent occurrence and the huge number of degrees of freedom in…

Chemical Physics · Physics 2024-12-06 Tuğçe Gökdemir , Jakub Rydzewski

39 detailed mechanisms for combustion of hydrogen, carbon monoxide and methanol are investigated using ReactionKinetics, a Mathematica based package. The obtained results in most cases do not depend on the choice of reaction rate…

Chemical Physics · Physics 2013-08-06 J. Tóth , A. L. Nagy , I. Zsély

Cumulant mapping employs a statistical reconstruction of the whole by sampling its parts. The theory developed in this work formalises and extends ad hoc methods of `multi-fold' or `multi-dimensional' covariance mapping. Explicit formulae…

Data Analysis, Statistics and Probability · Physics 2023-11-06 Leszek J. Frasinski

Modeling an unknown dynamical system is crucial in order to predict the future behavior of the system. A standard approach is training recurrent models on measurement data. While these models typically provide exact short-term predictions,…

Machine Learning · Computer Science 2023-03-02 Katharina Ensinger , Sebastian Ziesche , Barbara Rakitsch , Michael Tiemann , Sebastian Trimpe

An effective Hamiltonian for the Bose subsystem in the mixture of ultracold atomic clouds of bosons and fermions with mutual attractive interaction is used for investigating collective excitation spectrum. The ground state and mode…

Quantum Gases · Physics 2015-05-19 A. M. Belemuk , V. N. Ryzhov

The relevance of equilibrium in a multifragmentation reaction of very central $^{40}Ca+^{40}Ca$ collisions at 35 MeV/nucleon is investigated by using simulations of Antisymmetrized Molecular Dynamics (AMD). Two types of ensembles are…

Nuclear Theory · Physics 2009-01-28 Takuya Furuta , Akira Ono

We present a method which extends Monte Carlo studies to situations that require a large dynamic range in particle number. The underlying idea is that, in order to calculate the collisional evolution of a system, some particle interactions…

Astrophysics · Physics 2009-11-13 C. W. Ormel , M. Spaans

Statistical mechanics provides an effective framework to investigate information processing in biochemical reactions. Within such framework far-reaching analogies are established among (anti-) cooperative collective behaviors in chemical…

Statistical Mechanics · Physics 2021-05-26 Elena Agliari , Adriano Barra , Lorenzo Dello Schiavo , Antonio Moro

Using the collective variables (CV) method the basic relations of statistical field theory of a multicomponent non-homogeneous fluids are reconsidered. The corresponding CV action depends on two sets of scalar fields - fields…

Soft Condensed Matter · Physics 2012-07-02 Oksana Patsahan , Ihor Mryglod , Jean-Michel Caillol

Compared to mean regression and quantile regression, the literature on modal regression is very sparse. A unifying framework for Bayesian modal regression is proposed, based on a family of unimodal distributions indexed by the mode, along…

Methodology · Statistics 2024-07-02 Qingyang Liu , Xianzheng Huang , Rai Bai

The standard equilibrium Green-Kubo and nonequilibrium molecular dynamics (MD) methods for computing thermal transport coefficients in solids typically require relatively long simulation times and large system sizes. To this end, we revisit…

Materials Science · Physics 2019-03-05 Zheyong Fan , Haikuan Dong , Ari Harju , Tapio Ala-Nissila

Nonlinear normal modes (NNMs) are widely used as a tool for developing mathematical models of nonlinear structures and understanding their dynamics. NNMs can be identified experimentally through a phase quadrature condition between the…

Dynamical Systems · Mathematics 2018-07-04 L. Renson , T. L. Hill , D. A. Ehrhardt , D. A. W. Barton , S. A. Neild

We review recent advances in modal regression studies using kernel density estimation. Modal regression is an alternative approach for investigating relationship between a response variable and its covariates. Specifically, modal regression…

Methodology · Statistics 2017-12-08 Yen-Chi Chen

A review of the mechanisms of speciation is performed. The mechanisms of the evolution of species, taking into account the feedback of the state of the environment and mechanisms of the emergence of complexity, are considered. It is shown…

Populations and Evolution · Quantitative Biology 2018-07-18 Alexey V. Melkikh , Alexey V. Melkikh , Andrei Khrennikov

Coupled-mode theory (CMT) is a powerful tool for simulating near-harmonic systems. In telecommunications, variations of the theory have been used extensively to study waveguides, both analytically and through numerical modelling. Analogous…

Instrumentation and Methods for Astrophysics · Physics 2024-12-11 Jonathan Lin

We present and assess a Bayesian method to interpret gravitational wave signals from binary black holes. Our method directly compares gravitational wave data to numerical relativity simulations. This procedure bypasses approximations used…

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