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Markov chain Monte Carlo methods are primarily used for sampling from a given probability distribution and estimating multi-dimensional integrals based on the information contained in the generated samples. Whenever it is possible, more…

Statistical Mechanics · Physics 2017-05-22 Manuel Athènes , Pierre Terrier

Along the line of thoughts of Berry and Robnik\cite{[1]}, we investigated the gap distribution function of systems with infinitely many independent components, and discussed the level-spacing distribution of classically integrable quantum…

Chaotic Dynamics · Physics 2009-11-10 H. Makino , S. Tasaki

We study the statistics of level spacing of geometric resonances in the disordered binary networks. For a definite concentration $p$ within the interval $[0.2,0.7]$, numerical calculations indicate that the unfolded level spacing…

Soft Condensed Matter · Physics 2007-05-23 Y. Gu , K. W. Yu , Z. R. Yang

Spectral properties of random matrices play an important role in statistics, machine learning, communications, and many other areas. Engaging results regarding the convergence of the empirical spectral distribution (ESD) and the…

Statistics Theory · Mathematics 2025-07-08 Zeyan Zhuang , Xin Zhang , Dongfang Xu , Shenghui Song

Typical eigenstates of quantum systems, whose classical limit is chaotic, are well approximated as random states. Corresponding eigenvalue spectra is modeled through appropriate ensemble of random matrix theory. However, a small subset of…

Quantum Physics · Physics 2018-06-21 S. Harshini Tekur , Santosh Kumar , M. S. Santhanam

The mixed spherical models were recently found to violate long-held assumptions about mean-field glassy dynamics. In particular, the threshold energy, where most stationary points are marginal and that in the simpler pure models attracts…

Disordered Systems and Neural Networks · Physics 2024-01-03 Jaron Kent-Dobias

Complete spectroscopy (measurements of a complete sequence of consecutive levels) is often considered as a prerequisite to extract fluctuation properties of spectra. It is shown how this goal can be achieved even if only a fraction of…

Nuclear Theory · Physics 2009-11-10 O. Bohigas , M. P. Pato

We obtain analytic formulae for the spacing between conductance peaks in the Coulomb blockade regime, based on the universal Hamiltonian model of quantum dots. New random matrix theory results are developed in order to treat correlations…

Mesoscale and Nanoscale Physics · Physics 2008-02-04 D. Herman , T. T. Ong , Gonzalo Usaj , H. Mathur , H. U. Baranger

Parameter-dependent statistical properties of spectra of totally connected irregular quantum graphs with Neumann boundary conditions are studied. The autocorrelation functions of level velocities c(x) and c(w,x) as well as the distributions…

Chaotic Dynamics · Physics 2009-07-17 Oleh Hul , Petr Seba , Leszek Sirko

Maximum entropy models are increasingly being used to describe the collective activity of neural populations with measured mean neural activities and pairwise correlations, but the full space of probability distributions consistent with…

Biological Physics · Physics 2017-08-22 Badr F. Albanna , Christopher Hillar , Jascha Sohl-Dickstein , Michael R. DeWeese

Many body localization (MBL) is a phenomena that allows for the preservation of quantum information for long times. We study a variation of the disordered-Heisenberg model, which is known to exhibit an MBL phase [5][6], known as the…

Quantum Physics · Physics 2019-11-27 Nicholas Carrillo

Level statistics of systems that undergo many--body localization transition are studied. An analysis of the gap ratio statistics from the perspective of inter- and intra-sample randomness allows us to pin point differences between…

Disordered Systems and Neural Networks · Physics 2019-03-27 Piotr Sierant , Jakub Zakrzewski

Background: Data preparation, such as missing values imputation and transformation, is the first step in any data analysis and requires crucial attention. Particularly, analysis of metabolites demands more preparation since those small…

Quantitative Methods · Quantitative Biology 2019-05-14 Akram Yazdani , Azam Yazdan

We study mixed models with a single grouping factor, where inference about unknown parameters requires optimizing a marginal likelihood defined by an intractable integral. Low-dimensional numerical integration techniques are regularly used…

Methodology · Statistics 2025-01-22 Alex Stringer , Blair Bilodeau , Yanbo Tang

Mutual Information (MI) is a crucial measure for capturing dependencies between variables, but exact computation is challenging in high dimensions with intractable likelihoods, impacting accuracy and robustness. One idea is to use an…

Machine Learning · Statistics 2025-03-13 Forough Fazeliasl , Michael Minyi Zhang , Bei Jiang , Linglong Kong

Simulations often involve the use of model parameters which are unknown or uncertain. For this reason, simulation experiments are often repeated for multiple combinations of parameter values, often iterating through parameter values lying…

Computation · Statistics 2012-05-22 Jessica W. Leigh , David Bryant

We consider an ensemble of $2\times 2$ normal matrices with complex entries representing operators in the quantum mechanics of 2 - level parity-time reversal (PT) symmetric systems. The randomness of the ensemble is endowed by obtaining…

Mathematical Physics · Physics 2025-01-14 Stalin Abraham , A. Bhagwat , Sudhir Ranjan Jain

We calculate an analytical expression for the terrace-width distribution $P(s)$ for an interacting step system with nearest and next nearest neighbor interactions. Our model is derived by mapping the step system onto a statistically…

Statistical Mechanics · Physics 2013-07-17 Diego Felipe Jaramillo , Gabriel Téllez , Diego Luis González , T. L. Einstein

We calculate the condensate fraction and the condensate and non-condensate spatial and momentum distribution of the Bose-Hubbard model in a trap. From our results, it is evident that using approximate distributions can lead to erroneous…

Quantum Gases · Physics 2013-05-14 Ushnish Ray , David M. Ceperley

We study high-dimensional sample covariance matrices based on independent random vectors with missing coordinates. The presence of missing observations is common in modern applications such as climate studies or gene expression…

Probability · Mathematics 2016-03-01 Kamil Jurczak , Angelika Rohde
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