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Related papers: Code Swendsen-Wang Dynamics

200 papers

Measurement-induced phases exhibit unconventional dynamics as emergent collective phenomena, yet their behavior in tailored interacting systems -- crucial for quantum technologies -- remains less understood. We develop a systematic toolbox…

Quantum Physics · Physics 2025-06-24 Zejian Li , Anna Delmonte , Xhek Turkeshi , Rosario Fazio

Lindblad dynamics and other open-system dynamics provide a promising path towards efficient Gibbs sampling on quantum computers. In these proposals, the Lindbladian is obtained via an algorithmic construction akin to designing an artificial…

Quantum Physics · Physics 2025-03-07 Zhiyan Ding , Bowen Li , Lin Lin

In many dynamical systems in nature, the law of the dynamics changes along with the temporal evolution of the system. These changes are often associated with the occurrence of certain events. The timing of occurrence of these events…

Probability · Mathematics 2021-07-12 S. Gallo , G. Iacobelli , G. Ost , D. Y. Takahashi

Strongly-coupled gauge theories far from equilibrium may exhibit unique features that could illuminate the physics of the early universe and of hadron and ion colliders. Studying real-time phenomena has proven challenging with…

The density of states of continuous models is known to span many orders of magnitudes at different energies due to the small volume of phase space near the ground state. Consequently, the traditional Wang-Landau sampling which uses the same…

Statistical Mechanics · Physics 2013-11-20 Yang Wei Koh , Hwee Kuan Lee , Yutaka Okabe

Many physical phenomena, including thermalization in open quantum systems and quantum Gibbs sampling, are modeled by Lindbladians approximating a system weakly coupled to a bath. Understanding the convergence speed of these Lindbladians to…

Lattice spin models in statistical physics are used to understand magnetism. Their Hamiltonians are a discrete form of a version of a Dirichlet energy, signifying a relationship to the Harmonic map heat flow equation. The Gibbs…

Probability · Mathematics 2020-04-10 Yuan Gao , Kay Kirkpatrick , Jeremy Marzuola , Jonathan Mattingly , Katherine Newhall

Preparing thermal (Gibbs) states is a common task in physics and computer science. Recent algorithms mimic cooling via system-bath coupling, where the cost is determined by mixing time, akin to classical Metropolis-like algorithms. However,…

Quantum Physics · Physics 2024-12-13 David Gamarnik , Bobak T. Kiani , Alexander Zlokapa

This note introduces the double flip move for accelerating the Swendsen-Wang algorithm for Ising models with mixed boundary conditions below the critical temperature. The double flip move consists of a geometric flip of the spin lattice…

Numerical Analysis · Mathematics 2022-05-17 Lexing Ying

We study the stability of topological order against local perturbations by considering the effect of a magnetic field on a spin model -- the toric code -- which is in a topological phase. The model can be mapped onto a quantum loop gas…

Statistical Mechanics · Physics 2008-12-02 Simon Trebst , Philipp Werner , Matthias Troyer , Kirill Shtengel , Chetan Nayak

Szegedy's quantum walk gives a generic quadratic speedup for reversible classical Markov chains, but extending this mechanism to quantum Gibbs sampling has remained challenging beyond special cases. We present a walk-free quantum algorithm…

Quantum Physics · Physics 2026-04-28 Jiaqi Leng , Jiaqing Jiang , Lin Lin

We study the phase diagrams of a family of 3D "Walker-Wang" type lattice models, which are not topologically ordered but have deconfined anyonic excitations confined to their surfaces. We add a perturbation (analogous to that which drives…

Strongly Correlated Electrons · Physics 2013-12-25 F. J. Burnell , C. W. von Keyserlingk , S. H. Simon

Employing the Schwinger-Keldysh formalism, we formulate an effective field theory for s-wave superconducting phase transition, where the dynamical variables consist of electromagnetic gauge field and complex scalar order parameter.…

High Energy Physics - Theory · Physics 2026-05-11 Yanyan Bu , Zexin Yang

We propose a semiclassical framework for solving open quantum dynamics in driven-dissipative spin systems. Our method consists of generalized spin-wave approximations tailored to describing quantum trajectories unravelled from the master…

Quantum Physics · Physics 2026-04-24 Zejian Li , Anna Delmonte , Rosario Fazio

We propose a variational quantum algorithm to study the real time dynamics of quantum systems as a ground-state problem. The method is based on the original proposal of Feynman and Kitaev to encode time into a register of auxiliary qubits.…

Quantum Physics · Physics 2023-02-16 Stefano Barison , Filippo Vicentini , Ignacio Cirac , Giuseppe Carleo

In this paper, we introduce a novel and general framework for the variational quantum simulation of Lindblad equations. Building on the close relationship between the unraveled Lindblad dynamics, stochastic Magnus integrators, and…

Quantum Physics · Physics 2025-09-22 Jia-Cheng Huang , Hao-En Li , Yi-Cheng Wang , Guang-Ze Zhang , Jun Li , Han-Shi Hu

We prove that the spectral gap of the Swendsen-Wang dynamics for the random-cluster model is larger than the spectral gap of a single-bond dynamics, that updates only a single edge per step. For this we give a representation of the…

Probability · Mathematics 2014-01-21 Mario Ullrich

Switching dynamical systems provide a powerful, interpretable modeling framework for inference in time-series data in, e.g., the natural sciences or engineering applications. Since many areas, such as biology or discrete-event systems, are…

Machine Learning · Computer Science 2021-09-30 Lukas Köhs , Bastian Alt , Heinz Koeppl

Swendsen-Wang dynamics for the Potts model was proposed in the late 1980's as an alternative to single-site heat-bath dynamics, in which global updates allow this MCMC sampler to switch between metastable states and ideally mix faster. Gore…

Probability · Mathematics 2017-05-03 Reza Gheissari , Eyal Lubetzky , Yuval Peres

The Metropolis-within-Gibbs (MwG) algorithm is a widely used Markov Chain Monte Carlo method for sampling from high-dimensional distributions when exact conditional sampling is intractable. We study MwG with Random Walk Metropolis (RWM)…

Machine Learning · Statistics 2025-10-01 Cecilia Secchi , Giacomo Zanella