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Diffusion processes are widely used for modelling real-world phenomena. Except for select cases however, analytical expressions do not exist for a diffusion process' transitional probabilities. It is proposed that the cumulant truncation…

Methodology · Statistics 2015-03-13 Melvin M. Varughese

Markov Chain Monte Carlo (MCMC) algorithms are essential tools in computational statistics for sampling from unnormalised probability distributions, but can be fragile when targeting high-dimensional, multimodal, or complex target…

We propose a realization of the two-impurity Anderson model in a double quantum-dot device. When charge transfer between the dots is suppressed the system exhibits a quantum phase transition, controlled by a surface of non-Fermi liquid…

Strongly Correlated Electrons · Physics 2009-11-13 David F. Mross , Henrik Johannesson

Disorder is ubiquitous in solid-state systems, and its crucial influence on transport properties was revealed by the discovery of Anderson localization. Generally speaking, all bulk states will be exponentially localized in the strong…

Disordered Systems and Neural Networks · Physics 2023-11-01 Tong Wang , Zhiming Pan , Keith Slevin , Tomi Ohtsuki

Quantum phase transitions are usually classified into discrete universality classes that typically only depend on symmetries and spatial dimensionalities. In this Letter, we demonstrate an opportunity to continuously vary the critical…

Quantum Physics · Physics 2019-01-24 Fan Yang , Shao-Jian Jiang , Fei Zhou

Model Predictive Control (MPC) is a method to control nonlinear systems with guaranteed stability and constraint satisfaction but suffers from high computation times. Approximate MPC (AMPC) with neural networks (NNs) has emerged to address…

Systems and Control · Electrical Eng. & Systems 2024-09-24 Henrik Hose , Alexander Gräfe , Sebastian Trimpe

We present an accurate numerical determination of the crossover from classical to Ising-like critical behavior upon approach of the critical point in three-dimensional systems. The possibility to vary the Ginzburg number in our simulations…

Statistical Mechanics · Physics 2009-10-31 Erik Luijten , Kurt Binder

Max-stable processes are a popular tool for the study of environmental extremes, and the extremal skew-$t$ process is a general model that allows for a flexible extremal dependence structure. For inference on max-stable processes with…

Methodology · Statistics 2020-04-21 B. Beranger , A. G. Stephenson , S. A. Sisson

In a recent submission to this archive arXiv:cond-mat/0105325, Suslov has claimed that our recent numerical estimate of the critical exponent of the Anderson transition $\nu=1.57\pm.02$ is in error and that the available numerical data are…

Disordered Systems and Neural Networks · Physics 2007-05-23 Keith Slevin , Tomi Ohtsuki

It is well known that conventional simulation algorithms are inefficient for the statistical description of macroscopic systems exactly at the critical point due to the divergence of the corresponding relaxation time (critical slowing…

Computational Physics · Physics 2008-11-26 N. G. Antoniou , F. K. Diakonos , E. N. Saridakis , G. A. Tsolias

Generalized-ensemble Monte Carlo simulations such as the multicanonical method and similar techniques are among the most efficient approaches for simulations of systems undergoing discontinuous phase transitions or with rugged free- energy…

Computational Physics · Physics 2018-02-06 Jonathan Gross , Johannes Zierenberg , Martin Weigel , Wolfhard Janke

Anderson transition in three-dimensional systems is investigated using renormalization group theory. $\beta$-function of a very simple form is derived from a self-consistent consideration, and it gives a value $1+1/\sqrt{3}=1.58$ for the…

Disordered Systems and Neural Networks · Physics 2007-05-23 Arisato Kawabata

Atomistic simulations provide valuable insights into the physical processes governing material behavior. However, their applicability is fundamentally constrained by the limited time scales accessible to brute-force simulations. This…

Computational Physics · Physics 2026-02-16 Michael Kim , Wei Cai

The quantum phase transition of the one-dimensional long-range transverse-field Ising model is explored by combining the quantum Monte Carlo method and stochastic parameter optimization, specifically achieved by tuning correlation ratios so…

Statistical Mechanics · Physics 2024-12-05 Sora Shiratani , Synge Todo

The boundary condition dependence of the critical behavior for the three dimensional Anderson transition is investigated. A strong dependence of the scaling function and the critical conductance distribution on the boundary conditions is…

Disordered Systems and Neural Networks · Physics 2009-10-31 Keith Slevin , Tomi Ohtsuki , Tohru Kawarabayashi

We develop a systematic typical medium dynamical cluster approximation that provides a proper description of the Anderson localization transition in three dimensions (3D). Our method successfully captures the localization phenomenon both in…

Disordered Systems and Neural Networks · Physics 2014-02-19 C. E. Ekuma , H. Terletska , K. -M. Tam , Z. -Y. Meng , J. Moreno , M. Jarrell

An interplay between non-Hermiticity and disorder plays an important role in condensed matter physics. Here, we report the universal critical behaviors of the Anderson transitions driven by non-Hermitian disorders for three dimensional (3D)…

Disordered Systems and Neural Networks · Physics 2021-03-09 Xunlong Luo , Tomi Ohtsuki , Ryuichi Shindou

We provide rigorous theoretical bounds for Anderson acceleration (AA) that allow for approximate calculations when applied to solve linear problems. We show that, when the approximate calculations satisfy the provided error bounds, the…

Numerical Analysis · Mathematics 2024-04-30 Massimiliano Lupo Pasini , M. Paul Laiu

The parametric motion of energy levels for non-interacting electrons at the Anderson localization critical point is studied by computing the energy level-curvatures for a quasiperiodic ring with twisted boundary conditions. We find a…

Disordered Systems and Neural Networks · Physics 2009-11-10 S. N. Evangelou

Autocorrelations in MCMC chains increase the variance of the estimators they produce. We propose the occlusion process to mitigate this problem. It is a process that sits upon an existing MCMC sampler, and occasionally replaces its samples…

Computation · Statistics 2024-11-20 Max Hird , Florian Maire
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