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We present a new method to close the Master Equation representing the continuous time dynamics of Ising interacting spins. The method makes use of the the theory of Random Point Processes to derive a master equation for local conditional…

Disordered Systems and Neural Networks · Physics 2017-05-17 Erik Aurell , Gino Del Ferraro , Eduardo Dominguez , Roberto Mulet

An important challenge in non-Markovian open quantum systems is to understand what information we gain from continuous measurement of an output field. For example, atoms in multimode cavity QED systems provide an exciting platform to study…

Dynamical Ising machines are based on continuous dynamical systems evolving from a generic initial state to a state strongly related to the ground state of the classical Ising model on a graph. Reaching the ground state is equivalent to…

Emerging Technologies · Computer Science 2024-12-06 Mikhail Erementchouk , Aditya Shukla , Pinaki Mazumder

Nonequilibrium dynamics of noninteracting bosons in a one-dimensional ring-shaped lattice is studied by means of the Kinetic Monte Carlo method. The system is approximated by the classical XY model (the kinetic term is neglected) and then…

Quantum Gases · Physics 2017-01-17 Damian Makiela , Maciej M. Maska

Many stochastic continuous-state dynamical systems can be modeled as probabilistic programs with nonlinear non-polynomial updates in non-nested loops. We present two methods, one approximate and one exact, to automatically compute, without…

Applications · Statistics 2025-01-03 Andrey Kofnov , Marcel Moosbrugger , Miroslav Stankovič , Ezio Bartocci , Efstathia Bura

Neural network quantum states are a promising tool to analyze complex quantum systems given their representative power. It can however be difficult to optimize efficiently and effectively the parameters of this type of ansatz. Here we…

Quantum Physics · Physics 2023-05-10 Wenxuan Zhang , Xiansong Xu , Zheyu Wu , Vinitha Balachandran , Dario Poletti

Stochastic and conditional simulation methods have been effective towards producing realistic realizations and simulations of spatial numerical models that share equal probability of occurrence. Application of these methods are valuable…

The dynamical response of an Ising ferromagnet to a plane polarised standing magnetic field wave is modelled and studied here by Monte Carlo simulation in two dimensions. The amplitude of standing magnetic wave is modulated along the…

Statistical Mechanics · Physics 2016-08-08 Ajay Halder , Muktish Acharyya

We propose a hierarchy of multi-level kinetic Monte Carlo methods for sampling high-dimensional, stochastic lattice particle dynamics with complex interactions. The method is based on the efficient coupling of different spatial resolution…

Numerical Analysis · Mathematics 2012-08-06 Evangelia Kalligiannaki , Markos A. Katsoulakis , Petr Plechac

We analyze the quantum jumps of an atom interacting with a cavity field. The strong atom- field interaction makes the cavity transmission depend on the time dependent atomic state, and we present a Hidden Markov Model description of the…

Quantum Physics · Physics 2015-06-18 S. Gammelmark , W. Alt , T. Kampschulte , D. Meschede , K. Molmer

Bistable autonomous systems can be found inmany areas of science. When the intrinsic noise intensity is large, these systems exhibits stochastic transitions from onemetastable steady state to another. In electronic bistable memories, these…

Statistical Mechanics · Physics 2024-05-14 Léopold Van Brandt , Jean-Charles Delvenne

Neuronal ensemble activity, including coordinated and oscillatory patterns, exhibits hallmarks of nonequilibrium systems with time-asymmetric trajectories to maintain their organization. However, assessing time asymmetry from neuronal…

Neurons and Cognition · Quantitative Biology 2025-12-12 Ken Ishihara , Hideaki Shimazaki

Deep learning has shown impressive results in a variety of time series forecasting tasks, where modeling the conditional distribution of the future given the past is the essence. However, when this conditional distribution is…

Machine Learning · Computer Science 2024-02-27 Siqi Liu , Andreas Lehrmann

We propose physical interpretations for stochastic methods which have been developed recently to describe the evolution of a quantum system interacting with a reservoir. As opposed to the usual reduced density operator approach, which…

Quantum Physics · Physics 2015-06-26 Tarso B. L. Kist , M. Orszag , T. A. Brun , L. Davidovich

We investigate the challenge of classical simulation of unitary quantum dynamics with variational Monte Carlo approaches, addressing the instabilities and high computational demands of existing methods. By systematically analyzing the…

Quantum Physics · Physics 2025-07-30 Luca Gravina , Vincenzo Savona , Filippo Vicentini

We study XY spin systems on small world lattices for a variety of graph structures, e.g. Poisson and scale-free, superimposed upon a one dimensional chain. In order to solve this model we extend the cavity method in the one pure-state…

Disordered Systems and Neural Networks · Physics 2016-08-16 Nikos S Skantzos , Isaac Pérez Castillo , Jonathan P L Hatchett

We show how to utilize magnetostriction to synchronize two mechanical vibration modes in a cavity magnomechanical system. The dispersive magnetostrictive interaction provides necessary nonlinearity required for achieving synchronization.…

Quantum Physics · Physics 2023-12-06 Jiong Cheng , Wenlin Li , Jie Li

We present a comprehensive numerical study of dynamic phase transitions in the two-dimensional kinetic Ising model under a non-antisymmetric time-dependent magnetic field including a sinusoidal term and a second harmonic component. We…

We study nonequilibrium dynamical models with two absorbing states: interacting monomer-dimer models, probabilistic cellular automata models, nonequilibrium kinetic Ising models. These models exhibit a continuous phase transition from an…

Statistical Mechanics · Physics 2009-10-30 WonMuk Hwang , Sungchul Kwon , Heungwon Park , Hyunggyu Park

The development of physical simulators, called Ising machines, that sample from low energy states of the Ising Hamiltonian has the potential to drastically transform our ability to understand and control complex systems. However, most of…

Computational Physics · Physics 2021-03-10 Timothee Leleu , Farad Khoyratee , Timothee Levi , Ryan Hamerly , Takashi Kohno , Kazuyuki Aihara
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