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This study is about the properties of the sets of objects associated in a structure resulting from multiple-processes involving chance as are materials whose texture is unordered and random. Being a paper scientist the author refers to the…

Materials Science · Physics 2015-12-29 Jacques Silvy

The probability distribution function (PDF) of the mass surface density is an essential characteristic of the structure of molecular clouds or the interstellar medium in general. Observations of the PDF of molecular clouds indicate a…

Astrophysics of Galaxies · Physics 2015-06-18 Joerg Fischera

Independently trained transformers compute the same function in residual-stream bases that differ by a uniform random rotation on $\mathrm{SO}(d_{\mathrm{model}})$. We call this phenomenon polymorphism: same function, mutually…

Machine Learning · Computer Science 2026-05-26 Jordan F. McCann

The intrinsic volumes are measures of the content of a convex body. This paper uses probabilistic and information-theoretic methods to study the sequence of intrinsic volumes of a convex body. The main result states that the intrinsic…

Metric Geometry · Mathematics 2019-03-21 Martin Lotz , Michael B. McCoy , Ivan Nourdin , Giovanni Peccati , Joel A. Tropp

Emerging coherent X-ray scattering patterns of single-particles have shown dominant morphological signatures in agreement with predictions of the scattering model used for conventional protein crystallography. The key question is if and to…

Biomolecules · Quantitative Biology 2014-07-28 Aliakbar Jafarpour

The non-linear transformations incurred by the rays in an optical system can be suitably described by matrices to any desired order of approximation. In systems composed of uniform refractive index elements, each individual ray refraction…

Optics · Physics 2009-11-10 Jose B. Almeida

Statisticians increasingly face the problem to reconsider the adaptability of classical inference techniques. In particular, divers types of high-dimensional data structures are observed in various research areas; disclosing the boundaries…

Statistics Theory · Mathematics 2017-06-09 Paavo Sattler , Markus Pauly

In this paper we give a new and simplified proof of the variational Hodge conjecture for complete intersection cycles on a hypersurface in projective space.

Algebraic Geometry · Mathematics 2023-10-10 Remke Kloosterman

Sampling from the posterior is a key technical problem in Bayesian statistics. Rigorous guarantees are difficult to obtain for Markov Chain Monte Carlo algorithms of common use. In this paper, we study an alternative class of algorithms…

Statistics Theory · Mathematics 2024-08-26 Andrea Montanari , Yuchen Wu

A high-order quadrature scheme is constructed for the evaluation of Laplace single and double layer potentials and their normal derivatives on smooth surfaces in three dimensions. The construction begins with a harmonic approximation of the…

Numerical Analysis · Mathematics 2024-11-20 Shidong Jiang , Hai Zhu

We propose two new conformity scores for conformal prediction, in a general multivariate regression framework. The underlying score functions are based on a covariance analysis of the residuals and the input points. We give theoretical…

Statistics Theory · Mathematics 2025-06-30 Iain Henderson , Adrien Mazoyer , Fabrice Gamboa

An extension of the Method of Regularized Stokeslets (MRS) in three dimensions is developed for triangulated surfaces with a piecewise linear force distribution. The method extends the regularized Stokeslet segment methodology used for…

Numerical Analysis · Mathematics 2024-11-05 Dana Ferranti , Ricardo Cortez

A statistical framework is presented for the study of the orthogonally polarized modes of radio pulsar emission via the covariances between the Stokes parameters. To accommodate the typically heavy-tailed distributions of single-pulse radio…

Instrumentation and Methods for Astrophysics · Physics 2017-02-07 Willem van Straten , Caterina Tiburzi

We observe stationary random tessellations $X=\{\Xi_n\}_{n\ge1}$ in $\mathbb{R}^d$ through a convex sampling window $W$ that expands unboundedly and we determine the total $(k-1)$-volume of those $(k-1)$-dimensional manifold processes which…

Probability · Mathematics 2007-09-14 Lothar Heinrich , Hendrik Schmidt , Volker Schmidt

We consider a one-dimensional diffusion process with coefficients that are periodic outside of a finite 'interface region'. The question investigated in this article is the limiting long time / large scale behaviour of such a process under…

Probability · Mathematics 2010-05-14 Martin Hairer , Charles Manson

We proposed a novel approach to coherent imaging of dynamic samples. The inter-frame similarity of the sample's local structures is found to be a powerful constraint in phasing a sequence of diffraction patterns. We devised a new image…

Optics · Physics 2024-07-11 Pengju Sheng , Fucai Zhang

Global and local regularities of functions are analyzed in anisotropic function spaces, under a common framework, that of hyperbolic wavelet bases. Local and directional regularity features are characterized by means of global quantities…

Functional Analysis · Mathematics 2012-10-09 Patrice Abry , Marianne Clausel , Stéphane Jaffard , Stéphane Roux , Béatrice Vedel

In a circle (an S^1) with circumference 1 assume m objects distributed pseudo-randomly. In the universal covering R^1 assume the objects replicated accordingly, and take an interval L>1. In this interval, make the normalized histogram of…

General Relativity and Quantum Cosmology · Physics 2007-05-23 A. F. F. Teixeira

Using high-fidelity numerical simulations based on a lattice Boltzmann framework, the advection-enhanced transport of a passive scalar from a prolate spheroid in simple shear flow has been thoroughly investigated across various parameters,…

Fluid Dynamics · Physics 2025-10-15 Yanxing Wang , Hui Wan , Tie Wei , Fangjun Shu

Inferring physical fields from sparse observations while strictly satisfying partial differential equations (PDEs) is a fundamental challenge in computational physics. Recently, deep generative models offer powerful data-driven priors for…

Machine Learning · Computer Science 2026-01-29 Zichao Yu , Ming Li , Wenyi Zhang , Difan Zou , Weiguo Gao