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Related papers: Phase Transition and Strong Predictability

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This paper discusses the thermodynamic irreversibility realized in high-dimensional Hamiltonian systems with a time-dependent parameter. A new quantity, the irreversible information loss, is defined from the Lyapunov analysis so as to…

Statistical Mechanics · Physics 2009-10-31 Shin-ichi Sasa , Teruhisa S. Komatsu

A hallmark of a thermodynamic phase transition is the qualitative change of system thermodynamic properties such as energy and heat capacity. On the other hand, no phase transition is thought to operate in the supercritical state of matter…

Statistical Mechanics · Physics 2020-04-13 L. Wang , C. Yang , M. T. Dove , V. V. Brazhkin , K. Trachenko

C. Shannon introduced the notion of entropy for random sequences. What about their temperature? After discussing some methods for introducing information temperature (IT) for binary random stationary ergodic sequence, we suggest using IT as…

Statistical Mechanics · Physics 2022-03-15 Oleg Usatenko

We consider continuous and discrete (1+1)-dimensional wetting models which undergo a localization/delocalization phase transition. Using a simple approach based on Renewal Theory we determine the precise asymptotic behavior of the partition…

Probability · Mathematics 2007-05-23 Francesco Caravenna , Giambattista Giacomin , Lorenzo Zambotti

Phase transitions are a fundamental concept in science describing diverse phenomena ranging from, e.g., the freezing of water to Bose-Einstein condensation. While the concept is well-established in equilibrium, similarly fundamental…

The grand canonical formalism is employed to study the thermodynamic structure of a model displaying a quantum phase transition when studied with respect to the canonical formalism. A numerical survey shows that the grand partition function…

Quantum Physics · Physics 2016-07-05 Kevin Jimenez , Jose Reslen

We propose an iterative proposal to estimate critical points for statistical models based on configurations by combing machine-learning tools. Firstly, phase scenarios and preliminary boundaries of phases are obtained by…

Disordered Systems and Neural Networks · Physics 2019-10-23 X. L. Zhao , L. B. Fu

We study the distribution of the Schmidt coefficients of the reduced density matrix of a quantum system in a pure state. By applying general methods of statistical mechanics, we introduce a fictitious temperature and a partition function…

Quantum Physics · Physics 2010-07-05 A. De Pasquale , P. Facchi , G. Parisi , S. Pascazio , A. Scardicchio

Transition path theory (TPT) offers a powerful formalism for extracting the rate and mechanism of rare dynamical transitions between metastable states. Most applications of TPT either focus on systems with modestly sized state spaces or use…

Statistical Mechanics · Physics 2026-01-14 Nils E. Strand , Schuyler B. Nicholson , Hadrien Vroylandt , Todd R. Gingrich

An information-theoretic framework known as integrated information theory (IIT) has been introduced recently for the study of the emergence of consciousness in the brain [D. Balduzzi and G. Tononi, PLoS Comput. Biol. 4, e1000091 (2008)].…

Neurons and Cognition · Quantitative Biology 2011-07-11 Andre Nathan , Valmir C. Barbosa

Phase transition in the two-dimensional $q$-state Potts model with random ferromagnetic couplings in the large-q limit is conjectured to be described by the isotropic version of the infinite randomness fixed point of the random…

Statistical Mechanics · Physics 2007-05-23 J-Ch. Angles d'Auriac , F. Igloi

A systematic method for the computation of finite temperature ($T$) crossover functions near quantum critical points close to, or above, their upper-critical dimension is devised. We describe the physics of the various regions in the $T$…

Condensed Matter · Physics 2008-12-18 Subir Sachdev

We develop a finite temperature field theory formalism in any dimension that has the filling fractions as the basic dynamical variables. The formalism efficiently decouples zero temperature dynamics from the quantum statistical sums. The…

High Energy Physics - Theory · Physics 2008-11-26 André LeClair

Predicting and characterizing phase transitions is crucial for understanding generic physical phenomena such as crystallization, protein folding and others. However, directly observing phase transitions is not always easy, and often one has…

Statistical Mechanics · Physics 2025-03-20 Suemin Lee , Ruiyu Wang , Lukas Herron , Pratyush Tiwary

In the Information Bottleneck (IB), when tuning the relative strength between compression and prediction terms, how do the two terms behave, and what's their relationship with the dataset and the learned representation? In this paper, we…

Machine Learning · Computer Science 2020-01-08 Tailin Wu , Ian Fischer

How can one perform Bayesian inference on stochastic simulators with intractable likelihoods? A recent approach is to learn the posterior from adaptively proposed simulations using neural network-based conditional density estimators.…

Machine Learning · Computer Science 2019-05-21 David S. Greenberg , Marcel Nonnenmacher , Jakob H. Macke

We show that the usefulness of the thermal state of a specific spin-lattice model for measurement-based quantum computing exhibits a transition between two distinct "phases" - one in which every state is a universal resource for quantum…

Quantum Physics · Physics 2009-12-18 Sean D. Barrett , Stephen D. Bartlett , Andrew C. Doherty , David Jennings , Terry Rudolph

The minimal set of thermodynamic control parameters consists of a statistical (thermal) and a mechanical one. These suffice to introduce all the pertinent thermodynamic variables; thermodynamic processes can then be defined as paths on this…

Statistical Mechanics · Physics 2009-11-13 Jan Birjukov , Thomas Jahnke , Günter Mahler

We estimate the expected behavior of a quantum model of heat engine when we have incomplete information about external macroscopic parameters, like magnetic field controlling the intrinsic energy scales of the working medium. We explicitly…

Quantum Physics · Physics 2015-05-28 George Thomas , Ramandeep S. Johal

We investigate the dynamical and structural properties of absorbing phase transitions (APTs) within granular systems. Specifically, we examine a model for vibrofluidized systems of spherical grains, which undergo a transition from a state…

Soft Condensed Matter · Physics 2025-12-24 Raphael Maire , Andrea Plati , Frank Smallenburg , Giuseppe Foffi