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Consider the map $(x, y) \mapsto (x + \epsilon^{-\alpha} \sin (2\pi x) + \epsilon^{-1-\alpha}z, z + \epsilon \sin(2\pi x))$, which is conjugate to the Chirikov standard map with a large parameter. The parameter value $\alpha = 1$ is related…

Dynamical Systems · Mathematics 2020-01-08 Alex Blumenthal , Jacopo De Simoi , Ke Zhang

In a celebrated paper \cite{noe2019boltzmann}, No\'e, Olsson, K\"ohler and Wu introduced an efficient method for sampling high-dimensional Boltzmann distributions arising in molecular dynamics via normalizing flow approximation of transport…

Machine Learning · Computer Science 2026-03-17 Zia Ur Rehman , Gero Friesecke

We consider the problem of recovering a distribution function on the real line from observations additively contaminated with errors following the standard Laplace distribution. Assuming that the latent distribution is completely unknown…

Methodology · Statistics 2017-08-21 Catia Scricciolo

An explicit bound is given for the Kolmogorov distance between a mixture of normal distributions and a normal distribution with properly chosen parameter values. A random variable X has a mixture of normal distributions if its conditional…

Probability · Mathematics 2020-08-07 Krzysztof Bartoszek , Torkel Erhardsson

Laplace's method approximates a target density with a Gaussian distribution at its mode. It is computationally efficient and asymptotically exact for Bayesian inference due to the Bernstein-von Mises theorem, but for complex targets and…

Machine Learning · Computer Science 2026-03-12 Hanlin Yu , Marcelo Hartmann , Bernardo Williams , Mark Girolami , Arto Klami

Divergences that occur in density matrices of decay and scattering processes are shown to be regularized by tracing and unitarity or the optical theorem. These divergences are regularized by the lifetime of the decaying particle or the…

High Energy Physics - Phenomenology · Physics 2024-06-13 Shanmuka Shivashankara , Patti Rizzo , Nicole Cafe

We study the asymptotic distribution of the number of matchings of size $\ell=\ell(n)$ in $G(n,p)$ for a wide range of $p=p(n)\in (0,1)$ and for every $1\le \ell\le \lfloor n/2\rfloor$. We prove that this distribution changes from normal to…

Combinatorics · Mathematics 2015-08-05 Pu Gao , Cristiane M. Sato

We give a new explicitly invertible approximation of the normal cumulative distribution function: $\Phi(x) \simeq 1/2 + 1/2 \sqrt{1-{e}^{-x^2\frac{17+{x}^{2}}{26.694+2x^2}}}$, $\forall x \ge 0$, with absolute error $<4.00\cdot 10^{-5}$,…

Statistics Theory · Mathematics 2012-11-28 Alessandro Soranzo , Emanuela Epure

Circles of a single size can pack together densely in a hexagonal lattice, but adding in size variety disrupts the order of those packings. We conduct simulations which generate dense random packings of circles with specified size…

Computational Physics · Physics 2024-06-18 David J. Meer , Isabela Galoustian , Julio Gabriel de Falco Manuel , Eric R. Weeks

Subject of this letter is the dynamics of a chain obtained performing the continuous limit of a system of links and beads. In particular, the probability distribution of the relative position between two points of the chain averaged over a…

Soft Condensed Matter · Physics 2008-09-15 Franco Ferrari , Jaroslaw Paturej , Thomas A. Vilgis , Tomasz Wydro

We consider a type of nonnormal approximation of infinitely divisible distributions that incorporates compound Poisson, Gamma, and normal distributions. The approximation relies on achieving higher orders of cumulant matching, to obtain…

Probability · Mathematics 2013-04-24 Zhiyi Chi

We derive a simple and precise approximation to probability density functions in sampling distributions based on the Fourier cosine series. After clarifying the required conditions, we illustrate the approximation on two examples: the…

Statistics Theory · Mathematics 2021-04-27 Shigekazu Nakagawa , Hiroki Hashiguchi , Yoko Ono

We prove Wasserstein contraction of simple slice sampling for approximate sampling w.r.t. distributions with log-concave and rotational invariant Lebesgue densities. This yields, in particular, an explicit quantitative lower bound of the…

Probability · Mathematics 2020-09-17 Viacheslav Natarovskii , Daniel Rudolf , Björn Sprungk

Stochastic ordering among distributions has been considered in a variety of scenarios. Economic studies often involve research about the ordering of investment strategies or social welfare. However, as noted in the literature, stochastic…

Stein's method is used to obtain two theorems on multivariate normal approximation. Our main theorem, Theorem 1.2, provides a bound on the distance to normality for any nonnegative random vector. Theorem 1.2 requires multivariate size bias…

Probability · Mathematics 2007-05-23 Larry Goldstein , Yosef Rinott

Asymmetric, non-Gaussian probability distributions are often observed in the analysis of natural and engineering datasets. The lognormal distribution is a standard model for data with skewed frequency histograms and fat tails. However, the…

Methodology · Statistics 2025-05-22 Dionissios T. Hristopulos , Anastassia Baxevani , Giorgio Kaniadakis

The envelope of an elliptical Gaussian complex vector, or equivalently, the amplitude or norm of a bivariate normal random vector has application in many weather and signal processing contexts. We explicitly characterize its distribution in…

Statistics Theory · Mathematics 2026-02-03 Sattwik Ghosal , Ranjan Maitra

We consider the asymmetric random average process (ARAP) with continuous mass variables and parallel discrete time dynamics studied recently by Krug/Garcia and Rajesh/Majumdar [both Jrl. Stat. Phys. 99 (2000)]. The model is defined by an…

Statistical Mechanics · Physics 2007-05-23 Frank Zielen , Andreas Schadschneider

We investigate the random close packing density, $\phi_\textrm{RCP}$, of polydisperse hard sphere systems using a theoretical framework based on the equilibrium model of crowding. We derive a closed-form solution for $\phi_\textrm{RCP}$ in…

Soft Condensed Matter · Physics 2026-05-29 Vinay Vaibhav , Carmine Anzivino , Alessio Zaccone

Flow Matching, a promising approach in generative modeling, has recently gained popularity. Relying on ordinary differential equations, it offers a simple and flexible alternative to diffusion models, which are currently the…

Machine Learning · Statistics 2026-03-13 Lea Kunkel
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