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A Monte Carlo method is presented to evaluate quantum states with many particles moving in the continuum. The scattering state is generated at each time by a Monte Carlo random sampling algorithm. The same calculation are repeated until the…

Nuclear Theory · Physics 2013-06-06 Zhen-Xiang Xu , Chong Qi

The Monte Carlo Hamiltonian method developed recently allows to investigate ground state and low-lying excited states of a quantum system, using Monte Carlo algorithm with importance sampling. However, conventional MC algorithm has some…

High Energy Physics - Lattice · Physics 2018-01-17 Xiang-Qian Luo , Xiao-Ni Cheng , Helmut Kroger

We study a classical fully-frustrated honeycomb lattice Ising model using Markov chain Monte Carlo methods and exact calculations . The Hamiltonian realizes a degenerate ground state manifold of equal-energy states, where each hexagonal…

Statistical Mechanics · Physics 2009-06-02 Shawn Andrews , Hans De Sterck , Stephen Inglis , Roger G. Melko

We apply the event-chain Monte Carlo algorithm to classical continuum spin models on a lattice and clarify the condition for its validity. In the two-dimensional XY model, it outperforms the local Monte Carlo algorithm by two orders of…

Statistical Mechanics · Physics 2018-09-13 Manon Michel , Johannes Mayer , Werner Krauth

Interacting spin systems are of fundamental relevance in different areas of physics, as well as in quantum information science, and biology. These spin models represent the simplest, yet not fully understood, manifestation of quantum…

Quantum Physics · Physics 2015-02-27 Johannes Schachenmayer , Alexander Pikovski , Ana Maria Rey

Quantum spin systems with strong geometric restrictions give rise to rich quantum phases such as valence bond solids and spin liquid states. However, the geometric restrictions often hamper the application of sophisticated numerical…

Statistical Mechanics · Physics 2019-05-01 Zheng Yan , Yongzheng Wu , Chenrong Liu , Olav F. Syljuåsen , Jie Lou , Yan Chen

The hour-glass-like dispersion of spin excitations is a common feature of underdoped cuprates. It was qualitatively explained by the random phase approximation based on various ordered states with some phenomenological parameters; however,…

Strongly Correlated Electrons · Physics 2017-12-06 Zuo-Dong Yu , Yuan Zhou , Chang-De Gong

We present a new, biased Monte Carlo scheme for simulating complex, cyclic peptides. Backbone atoms are equilibrated with a biased rebridging scheme, and side-chain atoms are equilibrated with a look-ahead configurational bias Monte Carlo.…

Biological Physics · Physics 2009-10-31 Minghong G. Wu , Michael W. Deem

Antiferromagnetic Heisenberg spin chains with various spin values ($S=1/2,1,3/2,2,5/2$) are studied numerically with the quantum Monte Carlo method. Effective spin $S$ chains are realized by ferromagnetically coupling $n=2S$…

Strongly Correlated Electrons · Physics 2009-10-30 Y. J. Kim , M. Greven , U. -J. Wiese , R. J. Birgeneau

We introduce a minimal model for 2D cuprates with the on-site Hilbert space reduced to only three effective valence centers CuO$_4^{7-,6-,5-}$ (nominally Cu$^{1+,2+,3+}$) and make use of the S=1 pseudospin formalism. Despite its seeming…

Superconductivity · Physics 2015-06-22 A. S. Moskvin

In 1986, Swendsen and Wang proposed a replica Monte Carlo algorithm for spin glasses [Phys. Rev. Lett. 57 (1986) 2607]. Two important ingredients are present, (1) the use of a collection of systems (replicas) at different of temperatures,…

Statistical Mechanics · Physics 2009-11-10 Jian-Sheng Wang , Robert H. Swendsen

We provide an extension to lattice systems of the reptation quantum Monte Carlo algorithm, originally devised for continuous Hamiltonians. For systems affected by the sign problem, a method to systematically improve upon the so-called…

Other Condensed Matter · Physics 2010-10-26 Giuseppe Carleo , Federico Becca , Saverio Moroni , Stefano Baroni

We present a new Subset Simulation approach using Hamiltonian neural network-based Monte Carlo sampling for reliability analysis. The proposed strategy combines the superior sampling of the Hamiltonian Monte Carlo method with…

Machine Learning · Statistics 2024-01-11 Denny Thaler , Somayajulu L. N. Dhulipala , Franz Bamer , Bernd Markert , Michael D. Shields

Sampling from complicated probability distributions is a hard computational problem arising in many fields, including statistical physics, optimization, and machine learning. Quantum computers have recently been used to sample from…

The principle and the efficiency of the Monte Carlo transfer-matrix algorithm are discussed. Enhancements of this algorithm are illustrated by applications to several phase transitions in lattice spin models. We demonstrate how the…

Condensed Matter · Physics 2009-10-28 M. P. Nightingale , H. W. J. Bloete

We propose a quantum Monte Carlo algorithm capable of simulating the Bose-Hubbard model on arbitrary graphs, obviating the need for devising lattice-specific updates for different input graphs. We show that with our method, which is based…

Statistical Mechanics · Physics 2024-04-29 Itay Hen , Emre Akaturk

We propose a simple procedure by which the interaction parameters of the classical spin Hamiltonian can be determined from the knowledge of four-point correlation functions and specific heat. The proposal is demonstrated by using the…

Statistical Mechanics · Physics 2018-07-16 Vinit Kumar Singh , Jung Hoon Han

A vector bosonic field coupled to the electronic spin is treated by means of the continuous-time quantum Monte Carlo method. In the Bose Kondo model with a sub-Ohmic density of states $\rho_{B}(\omega) \propto \omega^{s}$ with s=0.2, two…

Strongly Correlated Electrons · Physics 2013-03-11 Junya Otsuki

We establish a deterministic and stochastic spherical quasi-interpolation framework featuring scaled zonal kernels derived from radial basis functions on the ambient Euclidean space. The method incorporates both quasi-Monte Carlo and Monte…

Numerical Analysis · Mathematics 2025-10-15 Zhengjie Sun , Mengyuan Lv , Xingping Sun

A first-order phase transition separating the smooth phase from the crumpled one is found in a fixed connectivity surface model defined on a disk. The Hamiltonian contains the Gaussian term and an intrinsic curvature term.

Soft Condensed Matter · Physics 2009-11-11 M. Igawa , H. Koibuchi , M. Yamada