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Related papers: Dynamical overlap simulations using HMC

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We develop a classical Monte Carlo algorithm based on a quasi-classical approximation for a pseudospin S=1 Hamiltonian in real space to construct a phase diagram of a model cuprate with a high Tc. A model description takes into account both…

Strongly Correlated Electrons · Physics 2021-10-25 Yu. D. Panov , A. S. Moskvin , A. A. Chikov , V. A. Ulitko

Hamiltonian Monte Carlo (HMC) samples efficiently from high-dimensional posterior distributions with proposed parameter draws obtained by iterating on a discretized version of the Hamiltonian dynamics. The iterations make HMC…

Computation · Statistics 2019-05-03 Khue-Dung Dang , Matias Quiroz , Robert Kohn , Minh-Ngoc Tran , Mattias Villani

Hamiltonian Monte Carlo (HMC) improves the computational efficiency of the Metropolis algorithm by reducing its random walk behavior. Riemannian Manifold HMC (RMHMC) further improves HMC's performance by exploiting the geometric properties…

Computation · Statistics 2015-06-22 Shiwei Lan , Vassilios Stathopoulos , Babak Shahbaba , Mark Girolami

We propose a new Complex Diffusion Monte Carlo (CDMC) method for the simulation of quantum systems with complex wave function. In CDMC the modulus and phase of wave function are simulated both in contrast to other methods. We successfully…

Condensed Matter · Physics 2007-05-23 B. Abdullaev , M. Musakhanov , A. Nakamura

Hierarchical modeling provides a framework for modeling the complex interactions typical of problems in applied statistics. By capturing these relationships, however, hierarchical models also introduce distinctive pathologies that quickly…

Methodology · Statistics 2013-12-04 M. J. Betancourt , Mark Girolami

We discuss the detailed balance condition for hybrid Monte Carlo method

We address a long standing issue and determine the decorrelation efficiency of the Hybrid Monte Carlo algorithm (HMC), for full QCD with Wilson fermions, with respect to vacuum topology. On the basis of five state-of-the art QCD vacuum…

High Energy Physics - Lattice · Physics 2008-11-26 B. Alles , G. Bali , M. D'Elia , A. Di Giacomo , N. Eicker , S. Guesken , H. Hoeber , Th. Lippert , K. Schilling , A. Spitz , T. Struckmann , P. Ueberholz , J. Viehoff

Traditionally, the field of computational Bayesian statistics has been divided into two main subfields: variational methods and Markov chain Monte Carlo (MCMC). In recent years, however, several methods have been proposed based on combining…

Computation · Statistics 2017-04-19 Cheng Zhang , Babak Shahbaba , Hongkai Zhao

The kinetics of the chiral phase transition is studied within a linear quark-meson-$\sigma$ model, using a Monte-Carlo approach to semiclassical particle-field dynamics. The meson fields are described on the mean-field level and quarks and…

High Energy Physics - Phenomenology · Physics 2015-09-30 Carsten Greiner , Christian Wesp , Hendrik van Hees , Alex Meistrenko

We discuss algorithms for domain wall fermions focussing on accelerating Hybrid Monte Carlo sampling of gauge configurations. Firstly a new multigrid algorithm for domain wall solvers and secondly a domain decomposed hybrid monte carlo…

High Energy Physics - Lattice · Physics 2022-04-01 Peter A Boyle , Dennis Bollweg , Christopher Kelly , Azusa Yamaguchi

We present simulation results for lattice QCD with light pions. For the quark fields we apply chirally symmetric lattice Dirac operators, in particular the overlap hypercube operator, along with the standard overlap operator for comparison.…

High Energy Physics - Lattice · Physics 2007-05-23 W. Bietenholz , S. Shcheredin

A novel family of dynamical Monte Carlo algorithms for lattice polymers is proposed. Our central idea is to simulate an extended ensemble in which the self-avoiding condition is systematically weakened. The degree of the self-overlap is…

Condensed Matter · Physics 2009-10-31 Yukito Iba , George Chikenji , Macoto Kikuchi

Among many types of quantum entanglement properties, the entanglement spectrum provides more abundant information than other observables. Exact diagonalization and density matrix renormalization group method could handle the system in…

Strongly Correlated Electrons · Physics 2025-03-05 Weilun Jiang , Xiaofan Luo , Bin-Bin Mao , Zheng Yan

We develop a GPU-accelerated hybrid quantum Monte Carlo (QMC) algorithm to solve the fundamental yet difficult problem of $U(1)$ gauge field coupled to fermions, which gives rise to a $U(1)$ Dirac spin liquid state under the description of…

Strongly Correlated Electrons · Physics 2026-02-27 Kexin Feng , Chuang Chen , Zi Yang Meng

Hamiltonian Monte Carlo (HMC) is a powerful Markov chain Monte Carlo (MCMC) method for performing approximate inference in complex probabilistic models of continuous variables. In common with many MCMC methods, however, the standard HMC…

Computation · Statistics 2017-04-12 Matthew M. Graham , Amos J. Storkey

We address the calculation of dynamical correlation functions for many fermion systems at zero temperature, using the auxiliary-field quantum Monte Carlo method. The two-dimensional Hubbard hamiltonian is used as a model system. Although…

Strongly Correlated Electrons · Physics 2016-08-24 Ettore Vitali , Hao Shi , Mingpu Qin , Shiwei Zhang

The use of mass preconditioning or Hasenbusch filtering in modern Hybrid Monte Carlo simulations is common. At light quark masses, multiple filters (three or more) are typically used to reduce the cost of generating dynamical gauge fields;…

High Energy Physics - Lattice · Physics 2017-04-07 Taylor Haar , Waseem Kamleh , James Zanotti , Yoshifumi Nakamura

It has become increasingly important to include one or more individual flavours of dynamical fermion in lattice QCD simulations. This is due in part to the advent of QCD+QED calculations, where isospin symmetry breaking means that the up,…

High Energy Physics - Lattice · Physics 2019-03-27 Taylor Haar , Waseem Kamleh , James Zanotti , Yoshifumi Nakamura

We develop the hybrid Monte Carlo method for simulations of single off-lattice polymer chains. We discuss implementation and choice of simulation parameters in some detail. The performance of the algorithm is tested on models for…

High Energy Physics - Lattice · Physics 2009-10-22 A. Irbäck

Hamiltonian Monte Carlo (HMC) has become routinely used for sampling from posterior distributions. Its extension Riemann manifold HMC (RMHMC) modifies the proposal kernel through distortion of local distances by a Riemannian metric. The…

Computation · Statistics 2017-02-21 Akihiko Nishimura , David Dunson