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The generalized canonical ensemble and its universal equivalence with the microcanonical ensemble
Statistical mechanics model the equivalent subset energy generalized canonical
2014/12/25
This paper shows for a general class of statistical mechanical models that when the microcanonical and canonical ensembles are nonequivalent on a subset of values of the energy, there often exists a g...
Complete analysis of phase transitions and ensemble equivalence for the Curie-Weiss-Potts model
Structure rotating model Potts model porter model
2014/12/25
Using the theory of large deviations, we analyze the phase transition structure of the Curie–Weiss–Potts spin model, which is a mean-field approximation to the nearest-neighbor Potts model. It is equi...
Metastability within the generalized canonical ensemble
The generalized canonical ensemble microcanonical ensemble metastable
2014/12/25
We discuss a property of our recently introduced generalized canonical ensemble [M. Costeniuc, R.S. Ellis, H. Touchette, B. Turkington, The generalized canonical ensemble and its universal equivalence...
Global Optimization, the Gaussian Ensemble, and Universal Ensemble Equivalence
Unconstrained problem global optimization statistical mechanics the equivalent theory of convex function
2014/12/25
Given a constrained minimization problem, under what conditions does there exist a related, unconstrained problem having the same minimum points? This basic question in global optimization motivates t...
Generalized canonical ensembles and ensemble equivalence
Boltzmann continuous function generalized canonical ensemble and physics
2014/12/25
This paper is a companion piece to our previous work [J. Stat. Phys. 119, 1283 (2005)], which introduced a generalized canonical ensemble obtained by multiplying the usual Boltzmann weight factor e...
Covariance inflation in the ensemble Kalman filter: a residual nudging perspective and some implications
Covariance inflation ensemble Kalman filter residual nudging perspective some implications
2013/5/20
This note examines the influence of covariance inflation on the distance between the measured observation and the simulated (or predicted) observation with respect to the state estimate. In order for ...
Ensemble Copula Coupling as a Multivariate Discrete Copula Approach
multivariate discrete copula stochastic array Sklar’s theorem statistical ensemble postprocessing ensemble copula coupling
2013/5/15
In probability and statistics, copulas play important roles theoretically as well as to address a wide range of problems in various application areas. In this paper, we introduce the concept of multiv...
Data Driven Computing by the Morphing Fast Fourier Transform Ensemble Kalman Filter in Epidemic Spread Simulations
Data Driven Computing Morphing Fast Fourier Transform Ensemble Kalman Filter Epidemic Spread Simulations
2010/3/9
The FFT EnKF data assimilation method is proposed and applied to a stochastic
cell simulation of an epidemic, based on the S-I-R spread model. The FFT EnKF
combines spatial statistics and ensemble f...
On the Convergence of the Ensemble Kalman Filter
Exchangeable random variables Monte-Carlo methods dataassimilation theoretical analysis asymptotics EnKF filtering
2009/1/19
Convergence of the ensemble Kalman filter in the limit for large ensembles
to the Kalman filter is proved. In each step of the filter, convergence of
the ensemble sample covariance follows from a we...
Morphing Ensemble Kalman Filters
Ensemble Kalman Filters image processing registration mapping
2007/8/23
A new type of ensemble filter is proposed, which combines an ensemble Kalman filter (EnKF)
with the ideas of morphing and registration from image processing. This results in filters
suitable for non...