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Dynamics simulations of constrained particles can greatly aid in understanding the temporal and spatial evolution of biological processes such as lateral transport along membranes and self-assembly of viruses. Most theoretical efforts in…

Computational Physics · Physics 2017-03-03 Stefan Paquay , Remy Kusters

Cross-Correlation random matrices have emerged as a promising indicator of phase transitions in spin systems. The core concept is that the evolution of magnetization encapsulates thermodynamic information [R. da Silva, Int. J. Mod. Phys. C,…

Statistical Mechanics · Physics 2024-08-19 Roberto da Silva , Sandra D. Prado

We present some estimates for the memory kernel function in the generalized Langevin equation, derived using the Mori-Zwanzig formalism from a one-dimensional lattice model, in which the particles interactions are through nearest and second…

Numerical Analysis · Mathematics 2018-01-17 Weiqi Chu , Xiantao Li

We introduce an efficient Langevin method to study bilinear Fermionic Hamiltonians interacting with classical fields. Our method is suitable for very large systems and offers high accuracy. To demonstrate the method, we study complex…

Statistical Mechanics · Physics 2013-12-16 Kipton Barros , Yasuyuki Kato

We propose a scheme for extending the model Hamiltonian method developed originally for studying the equilibrium properties of complex perovskite systems to include Langevin dynamics. The extension is based on Zwanzig's treatment of…

Materials Science · Physics 2015-06-24 Morrel H. Cohen

Bayesian inference in complex generative models is often obstructed by the absence of tractable likelihoods and the infeasibility of computing gradients of high-dimensional simulators. Existing likelihood-free methods for generalized…

Applications · Statistics 2026-01-05 Diksha Bhandari , Sebastian Reich

We propose a method for efficiently incorporating constraints into a stochastic gradient Langevin framework for the training of deep neural networks. Constraints allow direct control of the parameter space of the model. Appropriately…

Machine Learning · Computer Science 2021-06-22 Benedict Leimkuhler , Timothée Pouchon , Tiffany Vlaar , Amos Storkey

We apply well-established concepts of Langevin sampling to derive a new class of algorithms for the efficient computation of free energy differences of fluctuating particles embedded in a 'fast' membrane, i.e., a membrane that…

Numerical Analysis · Mathematics 2020-10-01 Tobias Kies , Carsten Gräser , Luigi Delle Site , Ralf Kornhuber

The problem of effective equations is reviewed and discussed. Starting from the classical Langevin equation, we show how it can be generalized to Hamiltonian systems with non-standard kinetic terms. A numerical method for inferring…

Statistical Mechanics · Physics 2020-01-29 Angelo Vulpiani , Marco Baldovin

We derive a family of correctness conditions for complex Langevin simulations. In particular, we show that if in a given theory the expectation values of all observables within a particular space satisfy the theory's Schwinger-Dyson…

High Energy Physics - Lattice · Physics 2025-12-11 Michael Mandl , Erhard Seiler , Dénes Sexty

We address the problem of constructing accurate mathematical models of the dynamics of molecular systems projected on a collective variable. To this aim we introduce an algorithm optimizing the parameters of a standard or generalized…

Statistical Mechanics · Physics 2018-10-02 Andrea Pérez-Villa , Fabio Pietrucci

Several numerical schemes are proposed for the solution of Nonequilibrium Langevin Dynamics (NELD), and the rate of convergence is analyzed. Due to the special deforming boundary conditions used, care must be taken when using standard…

Numerical Analysis · Mathematics 2017-09-26 Matthew Dobson , Abdel Kader Geraldo

We present lattice simulations of nonequilibrium quantum fields in Minkowskian space-time. Starting from a non-thermal initial state, the real-time quantum ensemble in 3+1 dimensions is constructed by a stochastic process in an additional…

High Energy Physics - Lattice · Physics 2009-11-11 J. Berges , I. -O. Stamatescu

Generalized Langevin dynamics (GLD) arise in the modeling of a number of systems, ranging from structured fluids that exhibit a viscoelastic mechanical response, to biological systems, and other media that exhibit anomalous diffusive…

Computational Physics · Physics 2013-07-25 Andrew D. Baczewski , Stephen D. Bond

We study the design and implementation of numerical methods to solve the generalized Langevin equation (GLE) focusing on canonical sampling properties of numerical integrators. For this purpose, we cast the GLE in an extended phase space…

Numerical Analysis · Mathematics 2020-12-09 Benedict Leimkuhler , Matthias Sachs

We apply complex Langevin dynamics to chiral random matrix theory at nonzero chemical potential. At large quark mass the simulations agree with the analytical results while incorrect convergence is found for small quark masses. The region…

High Energy Physics - Lattice · Physics 2013-12-16 A. Mollgaard , K. Splittorff

The theoretical treatment of Fermi systems consisting of particles with unequal masses is challenging. Even in one spatial dimension analytic solutions are limited to special configurations and numerical progress with Monte Carlo…

Quantum Gases · Physics 2018-07-19 Lukas Rammelmüller , Joaquín E. Drut , Jens Braun

This work presents a systematic methodology for describing the transient dynamics of coarse-grained molecular systems inferred from all-atom simulated data. We suggest Langevin-type dynamics where the coarse-grained interaction potential…

Numerical Analysis · Mathematics 2023-09-22 G. Baxevani , V. Harmandaris , E. Kalligiannaki , I. Tsantili

We present new results of full QCD at nonzero chemical potential. In PRD 92, 094516 (2015) the complex Langevin method was shown to break down when the inverse coupling decreases and enters the transition region from the deconfined to the…

High Energy Physics - Lattice · Physics 2018-04-18 Jacques Bloch , Olaf Schenk

Perceptrons are the building blocks of many theoretical approaches to a wide range of complex systems, ranging from neural networks and deep learning machines, to constraint satisfaction problems, glasses and ecosystems. Despite their…

Disordered Systems and Neural Networks · Physics 2018-11-20 Elisabeth Agoritsas , Giulio Biroli , Pierfrancesco Urbani , Francesco Zamponi
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