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Using a dual representation of lattice fermion models that is based on spin-charge transformation and fermionisation of the original description, I derive an algorithm for diagrammatic Monte Carlo simulation of strongly correlated systems.…

Strongly Correlated Electrons · Physics 2018-02-21 Johan Carlström

We present a new method for conducting Monte Carlo inference in graphical models which combines explicit search with generalized importance sampling. The idea is to reduce the variance of importance sampling by searching for significant…

Machine Learning · Computer Science 2013-01-18 Dale Schuurmans , Finnegan Southey

Within the framework of the renormalization group approach to the models of critical dynamics, we propose a method for a considerable reduction of the number of integrals needed to calculate the critical exponents. With this method we…

Statistical Mechanics · Physics 2018-04-18 L. Ts. Adzhemyan , E. V. Ivanova , M. V. Kompaniets , S. Ye. Vorobyeva

The Diffusion Monte Carlo method is devoted to the computation of electronic ground-state energies of molecules. In this paper, we focus on implementations of this method which consist in exploring the configuration space with a {\bf fixed}…

Numerical Analysis · Mathematics 2007-05-23 Tony Lelievre , Mohamed El Makrini , Benjamin Jourdain

We introduce and compare three different Monte Carlo determinantal algorithms that allow one to compute dynamical quantities, such as the self-energy, of fermionic systems in their thermodynamic limit. We show that the most efficient…

Strongly Correlated Electrons · Physics 2018-02-14 Alice Moutenet , Wei Wu , Michel Ferrero

Structural and topological information play a key role in modeling flow and transport through fractured rock in the subsurface. Discrete fracture network (DFN) computational suites such as dfnWorks are designed to simulate flow and…

We study the properties of the two-dimensional Fermi polaron model in which an impurity attractively interacts with a Fermi sea of particles in the zero-range limit. We use a diagrammatic Monte Carlo (DiagMC) method which allows us to…

Quantum Gases · Physics 2015-06-18 Jonas Vlietinck , Jan Ryckebusch , Kris Van Houcke

In this report we give an overview on recent results obtained from extensive Monte Carlo (MC) computer simulations of the 3D 2-state (Ising) and 4-state Potts models with bond-dilution. The motivation to study the 4-state Potts model…

Statistical Mechanics · Physics 2010-07-13 P. -E. Berche , C. Chatelain , B. Berche , W. Janke

Monte Carlo techniques are used to investigate the equilibrium threshold concentration, xe, in the dilute anisotropic antiferromagnet Fe(x)Zn(1-x)F2 in an applied magnetic field, considered to be an ideal random-field Ising model system.…

Disordered Systems and Neural Networks · Physics 2009-10-31 W. C. Barber , D. P. Belanger

We calculate the electronic structure and magnetic properties of hydrogenated graphite surfaces using van der Waals density functional theory (DFT) and model Hamiltonians. We find, as previously reported, that the interaction between…

Mesoscale and Nanoscale Physics · Physics 2015-03-06 M. Moaied , J. V. Alvarez , J. J. Palacios

We consider the behavior of an Ising ferromagnet obeying the Glauber dynamics under the influence of a fast switching, random external field. In Part I, we introduced a general formalism for describing such systems and presented the mean…

Statistical Mechanics · Physics 2009-10-31 J. Hausmann , P. Rujan

We study the mean field dilute model of a ferromagnet. We find and prove an expression for the free energy density at high temperature, and at temperature zero. We find the critical line of the model, separating the phase with zero…

Statistical Mechanics · Physics 2009-11-13 Luca De Sanctis , Francesco Guerra

A Monte-Carlo algorithm for discrete statistical models that combines the full power of the Belief Propagation algorithm with the advantages of a detailed-balanced heat bath approach is presented. A sub-tree inside the factor graph is first…

Statistical Mechanics · Physics 2014-07-02 Aurélien Decelle , Florent Krzakala

We demonstrate, by considering the triangular lattice spin-1/2 Heisenberg model, that Monte Carlo sampling of skeleton Feynman diagrams within the fermionization framework offers a universal first-principles tool for strongly correlated…

Strongly Correlated Electrons · Physics 2013-04-09 S. A. Kulagin , N. Prokof'ev , O. A. Starykh , B. Svistunov , C. N. Varney

The one dimensional Kondo lattice model is investigated using Quantum Monte Carlo and transfer matrix techniques. In the strong coupling region ferromagnetic ordering is found even at large band fillings. In the weak coupling region the…

Condensed Matter · Physics 2007-05-23 Matthias Troyer , Diethelm Würtz

Fermionic cold atoms in optical traps provide viable quantum simulators of correlation effects in electronic systems. For dressed Rydberg atoms in two-dimensional traps with out-of-plane dipole moments, a realistic model of the pairwise…

Quantum Gases · Physics 2026-01-13 Clio Johnson , Neil D. Drummond , James P. Hague , Calum MacCormick

Solving partial differential equations in high dimensions by deep neural network has brought significant attentions in recent years. In many scenarios, the loss function is defined as an integral over a high-dimensional domain. Monte-Carlo…

Numerical Analysis · Mathematics 2019-11-06 Jingrun Chen , Rui Du , Panchi Li , Liyao Lyu

The wavelength of a periodic spatial structure of Turing type is an intrinsic property of the considered reaction-diffusion dynamics and we address the question of its control at the microscopic scale for given dynamical parameters. The…

Pattern Formation and Solitons · Physics 2018-09-26 Gabriel Morgado , Bogdan Nowakowski , Annie Lemarchand

The electronic and magnetic properties of concentrated and diluted ferromagnetic semiconductors are investigated by using the Kondo lattice model, which describes an interband exchange coupling between itinerant conduction electrons and…

Disordered Systems and Neural Networks · Physics 2009-11-11 Guixin Tang , Wolfgang Nolting

Gradient networks can be used to model the dominant structure of complex networks. Previous works have focused on random gradient networks. Here we study gradient networks that minimize jamming on substrate networks with scale-free and…

Statistical Mechanics · Physics 2009-11-13 Natali Gulbahce