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The paper proposes a new Monte-Carlo simulator combining the advantages of Sequential Monte Carlo simulators and Hamiltonian Monte Carlo simulators. The result is a method that is robust to multimodality and complex shapes to use for…

Computation · Statistics 2018-12-20 Remi Daviet

We analyze the line radiative transfer in protoplanetary disks using several approximate methods and a well-tested Accelerated Monte Carlo code. A low-mass flaring disk model with uniform as well as stratified molecular abundances is…

Astrophysics · Physics 2009-11-13 Ya. Pavlyuchenkov , D. Semenov , Th. Henning , St. Guilloteau , V. Pietu , R. Launhardt , A. Dutrey

The reduced density matrix of excitons coupled to a phonon bath at a finite temperature is studied using the path integral Monte Carlo method. Appropriate choices of estimators and importance sampling schemes are crucial to the performance…

Quantum Physics · Physics 2015-06-04 Sangwoo Shim , Alán Aspuru-Guzik

Multirate integration uses different time step sizes for different components of the solution based on the respective transient behavior. For inter/extrapolation-based multirate schemes, we construct a new subclass of schemes by using…

Numerical Analysis · Mathematics 2023-12-15 Kevin Schäfers , Andreas Bartel , Michael Günther , Christoph Hachtel

We are developing a framework for multiscale computation which enables models at a ``microscopic'' level of description, for example Lattice Boltzmann, Monte Carlo or Molecular Dynamics simulators, to perform modelling tasks at the…

Dynamical Systems · Mathematics 2007-05-23 A. J. Roberts , I. G. Kevrekidis

Determinantal points processes are a promising but relatively under-developed tool in machine learning and statistical modelling, being the canonical statistical example of distributions with repulsion. While their mathematical formulation…

Machine Learning · Computer Science 2022-03-31 Nicholas P Baskerville

Biasing or importance sampling is a powerful technique in Monte Carlo radiative transfer, and can be applied in different forms to increase the accuracy and efficiency of simulations. One of the drawbacks of the use of biasing is the…

Instrumentation and Methods for Astrophysics · Physics 2016-05-11 Maarten Baes , Karl D. Gordon , Tuomas Lunttila , Simone Bianchi , Peter Camps , Mika Juvela , Rolf Kuiper

We present an elementary and self-contained account of the analogies existing between classical diffusion and the imaginary-time evolution of quantum systems. These analogies are used to develop a new quantum simulation method which allows…

Condensed Matter · Physics 2007-05-23 S. Baroni , S. Moroni

The propagator in the instanton background in the $(- \lambda \phi^{4})$ scalar model in four dimensions is studied.Leading and sub-leading terms of its asymptotics for large momenta and its on-shell double residue are calculated…

High Energy Physics - Phenomenology · Physics 2014-11-17 Yu. A. Kubyshin , P. G. Tinyakov

Path-integral techniques are a powerful tool used in open quantum systems to provide an exact solution for the non-Markovian dynamics. However, the exponential scaling of the tensor size with quantum memory length of these techniques limits…

Quantum Physics · Physics 2025-08-25 L. M. J. Hall , A. Gisdakis , E. A. Muljarov

We report on a Monte Carlo method that generates one-dimensional trajectories for Bohm's formulation of quantum mechanics that doesn't involve differentiation or integration of any equations of motion. At each time, t=n\delta t…

Quantum Physics · Physics 2009-11-13 T. M. Coffey , R. E. Wyatt , W. C. Schieve

Monte Carlo statistical ray-tracing methods are commonly employed to simulate carrier transport in nanostructured materials. In the case of a large degree of nanostructuring and under linear response (small driving fields), these…

Mesoscale and Nanoscale Physics · Physics 2023-02-09 Pankaj Priyadarshi , Neophytos Neophytou

Most numerical methods for time integration use real time steps. Complex time steps provide an additional degree of freedom, as we can select the magnitude of the step in both the real and imaginary directions. By time stepping along…

Numerical Analysis · Mathematics 2022-12-06 Jithin D. George , Samuel Y. Jung , Niall M. Mangan

Monte-Carlo simulations are routinely used for estimating the scaling exponents of complex systems. However, due to finite-size effects, determining the exponent values is often difficult and not reliable. Here we present a novel technique…

Computational Physics · Physics 2013-03-05 Indrek Mandre , Jaan Kalda

We generalize a recently developed method for accelerated Monte Carlo calculation of path integrals to the physically relevant case of generic many-body systems. This is done by developing an analytic procedure for constructing a hierarchy…

Statistical Mechanics · Physics 2011-08-08 Aleksandar Bogojevic , Ivana Vidanovic , Antun Balaz , Aleksandar Belic

We present powerful new analysis techniques to constrain effective field theories at the LHC. By leveraging the structure of particle physics processes, we extract extra information from Monte-Carlo simulations, which can be used to train…

High Energy Physics - Phenomenology · Physics 2018-09-19 Johann Brehmer , Kyle Cranmer , Gilles Louppe , Juan Pavez

The semiclassical approximation to the coherent state propagator requires complex classical trajectories in order to satisfy the associated boundary conditions, but finding these trajectories in practice is a difficult task that may…

Quantum Physics · Physics 2007-12-04 Marcel Novaes

We present a family of modified Hermite integrators of arbitrary order possessing superior behaviour for the integration of Keplerian and near-Keplerian orbits. After recounting the derivation of Hermite N-body integrators of arbitrary…

Earth and Planetary Astrophysics · Physics 2020-06-23 Alexander J. Dittmann

The importance-sampling Monte Carlo algorithm appears to be the universally optimal solution to the problem of sampling the state space of statistical mechanical systems according to the relative importance of configurations for the…

Statistical Mechanics · Physics 2010-06-22 Martin Weigel

The advances in materials and biological sciences have necessitated the use of molecular simulations to study polymers. The Markov chain Monte Carlo simulations enable the sampling of relevant microstates of polymeric systems by traversing…

Soft Condensed Matter · Physics 2023-07-24 Monika Angwani , Tushar Mahendrakar , Kaustubh Rane