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We demonstrate that a new tool, a model independent numerical Eliashberg inversion of the optical self-energy, based on maximum entropy considerations can be used to extract the magnetic excitation spectra of high-transition-temperature…

Superconductivity · Physics 2007-07-24 J. Hwang , T. Timusk , E. SChachinger , J. P. Carbotte

We introduce a new numerical technique -- bosonic auxiliary-field Monte Carlo (bAFMC) -- which allows to calculate the thermal properties of large lattice-boson systems within a systematically improvable semiclassical approach, and which is…

Strongly Correlated Electrons · Physics 2017-08-02 Daniele Malpetti , Tommaso Roscilde

Elastic systems that are spatially heterogeneous in their mechanical response pose special challenges for molecular simulations. Standard methods for sampling thermal fluctuations of a system's size and shape proceed through a series of…

Materials Science · Physics 2015-05-13 Sander Pronk , Phillip L. Geissler

Dynamic bonding is an essential feature of many soft materials. Molecular simulations have proven to be a powerful tool for modeling bonding kinetics and thermodynamics in these materials, providing insights into their properties that…

Soft Condensed Matter · Physics 2026-05-26 Tyla R. Holoman , B. P. Prajwal , Glen M. Hocky , Thomas M. Truskett

We present results of large scale simulations of the spin-1 Heisenberg antiferromagnet on a tetragonal lattice. The stochastic series expansion quantum Monte Carlo method is used to calculate equilibrium thermodynamic variables in the…

Strongly Correlated Electrons · Physics 2013-01-01 Keola Wierschem , Pinaki Sengupta

We propose a non-collinear spin-constrained method that generates training data for deep-learning-based magnetic model, which provides a powerful tool for studying complex magnetic phenomena that requires large-scale simulations at the…

Sampling the stationary points of a complicated potential energy landscape is a challenging problem. Here we introduce a sampling method based on relaxation from stationary points of the highest index of the Hessian matrix. We illustrate…

Statistical Mechanics · Physics 2014-07-25 Ciaran Hughes , Dhagash Mehta , David J Wales

A recent reformulation [1] of the problem of Coulomb gases in the presence of a dynamical dielectric medium showed that finite temperature simulations of such systems can be accomplished on the basis of completely local Hamiltonians on a…

Soft Condensed Matter · Physics 2009-11-11 A. Duncan , R. D. Sedgewick

The results of numerical simulation using a modified Monte Carlo method with a thermostat algorithm for a pseudospin model of orthonickelates are presented. Temperature phase diagrams are constructed for various degrees of filling and for…

Statistical Mechanics · Physics 2025-11-18 V. S. Ryumshin , Yu. D. Panov , V. A. Ulitko , A. S. Moskvin

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

We study the application of a new method for simulating nonlinear dynamics of many-body spin systems using quantum measurement and feedback [Mu\~noz-Arias et al., Phys. Rev. Lett. 124, 110503 (2020)] to a broad class of many-body models…

Quantum Physics · Physics 2020-08-19 Manuel H. Muñoz-Arias , Ivan H. Deutsch , Poul S. Jessen , Pablo M. Poggi

Thermalization of heavy quarks in the quark-gluon plasma (QGP) is one of the most promising phenomena for understanding the strong interaction. The energy loss and momentum broadening at low momentum can be well described by a stochastic…

High Energy Physics - Phenomenology · Physics 2024-05-01 Xiaojian Du , Wenyang Qian

We present dynamical properties of spin crossover compounds with photomagnetization, proposing a new model in which the spin-crossover phenomena and magnetic ordering are incorporated in a unified way. By using this model, the novel…

Materials Science · Physics 2009-11-11 Masamichi Nishino , Kamel Boukheddaden , Seiji Miyashita , Francois Varret

We establish efficient algorithms for weakly-interacting quantum spin systems at arbitrary temperature. In particular, we obtain a fully polynomial-time approximation scheme for the partition function and an efficient approximate sampling…

Quantum Physics · Physics 2026-01-30 Ryan L. Mann , Gabriel Waite

We consider a class of non-standard, two-dimensional (2D) Hamiltonian models that may show features of active particle dynamics, and therefore, we refer to these models as active Hamiltonian (AH) systems. The idea is to consider a spin…

Statistical Mechanics · Physics 2024-09-24 Antik Bhattacharya , Jürgen Horbach , Smarajit Karmakar

Simulations of quantum chemistry and quantum materials are believed to be among the most important potential applications of quantum information processors, but realizing practical quantum advantage for such problems is challenging. Here,…

We study the planar antiferromagnetic Heisenberg model on a decorated hexagonal lattice, involving both classical spins (occupying the vertices) and quantum spins (occupying the middle of the links). This study is motivated by the…

Condensed Matter · Physics 2009-10-28 J. Leandri , Y. Leroyer , S. V. Meshkov , Y. Meurdesoif , O. Kahn , B. Mombelli , D. Price

We put forward a Monte Carlo algorithm that samples the Euclidean time operator growth dynamics at infinite temperature. Crucially, our approach is free from the numerical sign problem for a broad family of quantum many-body spin systems,…

Strongly Correlated Electrons · Physics 2024-11-26 Ayush De , Umberto Borla , Xiangyu Cao , Snir Gazit

Simulating the transient effects occurring in superconducting accelerator magnet circuits requires including the mutual electro-thermo-dynamic interaction among the circuit elements, such as power converters, magnets, and protection…

The paper proposes a Riemannian Manifold Hamiltonian Monte Carlo sampler to resolve the shortcomings of existing Monte Carlo algorithms when sampling from target densities that may be high dimensional and exhibit strong correlations. The…

Computation · Statistics 2019-12-18 Mark Girolami , Ben Calderhead , Siu A. Chin
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