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Fitting stochastic kinetic models represented by Markov jump processes within the Bayesian paradigm is complicated by the intractability of the observed data likelihood. There has therefore been considerable attention given to the design of…

Computation · Statistics 2017-08-04 Andrew Golightly , Theodore Kypraios

In low temperature supercooled liquid, below the ideal mode coupling theory transition temperature, hopping and continuous diffusion are seen to coexist. We present a theory which incorporates interaction between the two processes and shows…

Statistical Mechanics · Physics 2008-07-08 Sarika Maitra Bhattacharyya , Biman Bagchi , Peter G. Wolynes

Establishing the existence of periodic orbits is one of the crucial and most intricate topics in the study of dynamical systems, and over the years, many methods have been developed to this end. On the other hand, finding closed orbits in…

Dynamical Systems · Mathematics 2022-01-25 Marian Mrozek , Roman Srzednicki , Justin Thorpe , Thomas Wanner

Consider a multichannel closed ring with disorder. In the semiclassical treatment its conductance is given by the Drude formula. Quantum mechanics challenge this result both in the limit of strong disorder (eigenstates are not…

Mesoscale and Nanoscale Physics · Physics 2007-05-23 Doron Cohen

The Diffusion Monte Carlo method with constant number of walkers, also called Stochastic Reconfiguration as well as Sequential Monte Carlo, is a widely used Monte Carlo methodology for computing the ground-state energy and wave function of…

Statistics Theory · Mathematics 2024-12-09 Michel Caffarel , Pierre del Moral , Luc de Montella

The use of sequential Monte Carlo within simulation for path-dependent option pricing is proposed and evaluated. Recently, it was shown that explicit solutions and importance sampling are valuable for efficient simulation of spot price and…

Computational Finance · Quantitative Finance 2019-11-13 Michael A. Kouritzin , Anne MacKay

We propose a multilevel Monte Carlo method for a particle-based asymptotic-preserving scheme for kinetic equations. Kinetic equations model transport and collision of particles in a position-velocity phase-space. With a diffusive scaling,…

Numerical Analysis · Mathematics 2020-05-21 Emil Løvbak , Giovanni Samaey , Stefan Vandewalle

The Markov Chain Monte Carlo method is at the heart of efficient approximation schemes for a wide range of problems in combinatorial enumeration and statistical physics. It is therefore very natural and important to determine whether…

Quantum Physics · Physics 2009-11-13 Pawel Wocjan , Anura Abeyesinghe

We present a semiclassical quantization condition, i.e., quantum-classical correspondence, for steady states of nonadiabatic systems consisting of fast and slow degrees of freedom (DOFs) by extending Gutzwiller's trace formula to a…

Chemical Physics · Physics 2015-10-21 Mikiya Fujii , Koichi Yamashita

Recent years have seen great progress in quantum computing, providing opportunities to overcome computational bottlenecks in many scientific applications. In particular, the intersection of computational fluid dynamics (CFD) and quantum…

Quantum Physics · Physics 2025-09-26 R. Au-Yeung , V. M. Kendon , S. J. Lind

We apply a recently developed quasi-diabatic (QD) scheme to the symmetric quasi-classical (SQC) approach for accurate quantum dynamics propagation. By using the adiabatic states as the quasi-diabatic states during a short-time quantum…

Chemical Physics · Physics 2018-07-11 Juan Sebastian C. Sandoval , Arkajit Mandal , Pengfei Huo

We propose a $\tau$-leaping simulation algorithm for stochastic systems subject to fast environmental changes. Similar to conventional $\tau$-leaping the algorithm proceeds in discrete time steps, but as a principal addition it captures…

Statistical Mechanics · Physics 2021-07-28 Ernesto Berríos-Caro , Tobias Galla

Markov jump processes are continuous-time stochastic processes with a wide range of applications in both natural and social sciences. Despite their widespread use, inference in these models is highly non-trivial and typically proceeds via…

Machine Learning · Computer Science 2023-06-01 Patrick Seifner , Ramses J. Sanchez

In this manuscript, inspired by a simpler reformulation of primary sample space Metropolis light transport, we derive a novel family of general Markov chain Monte Carlo algorithms called charted Metropolis-Hastings, that introduces the…

Graphics · Computer Science 2017-05-01 Jacopo Pantaleoni

We propose a sequential Monte Carlo algorithm for parameter learning when the studied model exhibits random discontinuous jumps in behaviour. To facilitate the learning of high dimensional parameter sets, such as those associated to neural…

Machine Learning · Statistics 2024-12-19 John-Joseph Brady , Yuhui Luo , Wenwu Wang , Víctor Elvira , Yunpeng Li

In the framework of SOS models, the dynamics of isolated and pairs of surface steps of monoatomic height is studied, for step--edge diffusion and for evaporation kinetics, using Monte Carlo techniques. In particular, various interesting…

Statistical Mechanics · Physics 2009-10-31 F. Szalma , W. Selke , S. Fischer

Rare nonadiabatic events play a central role in photochemistry but remain difficult to simulate because excited-state dynamics is computationally demanding and often stochastic. Here we introduce a deterministic and time-reversible…

A major topic of (classical) ergodic theory is to examine qualitatively how the phase space of dynamical systems is penetrated by the orbits of their dynamics. We consider interacting qubit systems with dynamics according to 4-local…

Quantum Physics · Physics 2007-05-23 Pawel Wocjan

We discuss adiabatic quantum phenomena at a level crossing. Given a path in the parameter space which passes through a degeneracy point, we find a criterion which determines whether the adiabaticity condition can be satisfied. For paths…

Quantum Physics · Physics 2007-05-23 Mateusz Cholascinski

This paper is devoted to the study of time-dependent hyperbolic systems and the derivation of dispersive estimates for their solutions. It is based on a diagonalisation of the full symbol within adapted symbol classes in order to extract…

Analysis of PDEs · Mathematics 2011-06-15 Michael Ruzhansky , Jens Wirth
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