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Light from `point sources' such as supernovae is observed with a beam width of order of the sources' size - typically less than 1 AU. Such a beam probes matter and curvature distributions that are very different from coarse-grained…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-30 Chris Clarkson , George Ellis , Andreas Faltenbacher , Roy Maartens , Obinna Umeh , Jean-Philippe Uzan

Using the leading twist approach (LTA) to nuclear shadowing, we calculate the ratios of diffractive and usual parton distributions for a heavy nucleus (Pb) and the proton, $R_{A/p}=(f_{i/A}^{D(3)}/f_{i/A})/(f_{i/p}^{D(3)}/f_{i/p})$, for…

High Energy Physics - Phenomenology · Physics 2024-07-16 V. Guzey , M. Strikman

The problem of probabilistic verification of a neural network investigates the probability of satisfying the safe constraints in the output space when the input is given by a probability distribution. It is significant to answer this…

Artificial Intelligence · Computer Science 2026-04-24 Jingyang Li , Xin Chen , Hongfei Fu , Guoqiang Li

Let $X$ be a compact Hausdorff space, with uniformity $\mathscr{U}$, and let $f \colon X \to X$ be a continuous function. For $D \in \mathscr{U}$, a $D$-pseudo-orbit is a sequence $(x_i)$ for which $(f(x_i),x_{i+1}) \in D$ for all indices…

Dynamical Systems · Mathematics 2020-01-03 Joel Mitchell

In the rest frame of the nucleus, shadowing is due to hadronic fluctuations of the incoming virtual photon, which interact with the nucleons. We expand these fluctuations in a basis of eigenstates of interaction and take only the $q\bar q$…

High Energy Physics - Phenomenology · Physics 2007-05-23 J. Raufeisen , A. V. Tarasov , O. O. Voskresenskaya

We consider the nuclear shadowing in deep-inelastic scattering corresponding to kinematic regions accessible by future experiments at electron-ion colliders. The gluon distribution at small $x$ is obtained using an improved dipole model…

Nuclear Theory · Physics 2024-11-25 G. R. Boroun , B. Rezaei

We consider pure fermionic states with a varying number of quasiparticles and analyze two types of reduced density operators: one is obtained via tracing out modes, the other is obtained via tracing out particles. We demonstrate that…

Quantum Physics · Physics 2016-12-13 Grigori G. Amosov , Sergey N. Filippov

It is well known that under certain conditions on a Banach space $X$, the set of bounded linear operators attaining their numerical radius is a dense subset. We prove in this paper that if $X$ is assumed to be uniformly convex and uniformly…

Functional Analysis · Mathematics 2023-02-28 Mohammed Bachir

The random motion of a Brownian particle confined in some finite domain is considered. Quite generally, the relevant statistical properties involve infinite series, whose coefficients are related to the eigenvalues of the diffusion…

Statistical Mechanics · Physics 2010-04-26 Thomas Bickel

Neural operators aim to approximate the solution operator of a system of differential equations purely from data. They have shown immense success in modeling complex dynamical systems across various domains. However, the occurrence of…

Machine Learning · Computer Science 2025-04-01 Christopher Bülte , Philipp Scholl , Gitta Kutyniok

Let a continuous random process $X$ defined on $[0,1]$ be $(m+\beta)$-smooth, $0\le m, 0<\beta\le 1$, in quadratic mean for all $t>0$ and have an isolated singularity point at $t=0$. In addition, let $X$ be locally like a $m$-fold…

Probability · Mathematics 2010-05-20 Konrad Abramowicz , Oleg Seleznjev

We obtain new inequalities involving Berezin norm and Berezin number of bounded linear operators defined on a reproducing kernel Hilbert space $\mathscr{H}.$ Among many inequalities obtained here, it is shown that if $A$ is a positive…

Functional Analysis · Mathematics 2021-12-21 Pintu Bhunia , Kallol Paul , Anirban Sen

We study the thin-shell conjecture for the Schatten classes. In particular, we establish the conjecture for the operator norm; we also improve on the best known bound for the Schatten classes, due to Barthe and Cordero-Erausquin [F. Barthe…

Functional Analysis · Mathematics 2016-02-23 Jordan Radke , Beatrice-Helen Vritsiou

Recent results in quantization theory show that the mean-squared expected distortion can reach a rate of convergence of $\mathcal{O}(1/n)$, where $n$ is the sample size [see, e.g., IEEE Trans. Inform. Theory 60 (2014) 7279-7292 or Electron.…

Statistics Theory · Mathematics 2015-04-02 Clément Levrard

Based on a recent proof of free choices in linking equations to the experiments they describe, I clarify relations among some purely mathematical entities featured in quantum mechanics (probabilities, density operators, partial traces, and…

Quantum Physics · Physics 2014-09-15 John M. Myers

Phase-space distributions are widely applied in quantum optics to access the nonclassical features of radiations fields. In particular, the inability to interpret the Glauber-Sudarshan distribution in terms of a classical probability…

Quantum Physics · Physics 2016-07-25 J. Sperling

In this paper we revisit the classical method of partitioning classification and study its convergence rate under relaxed conditions, both for observable (non-privatised) and for privatised data. We consider the problem of classification in…

Machine Learning · Statistics 2025-09-09 Balázs Csanád Csáji , László Györfi , Ambrus Tamás , Harro Walk

In this paper, subnormal operators, not necessarily bounded, are discussed as generalized observables. In order to describe not only the information about the probability distribution of the output data of their measurement but also a…

Quantum Physics · Physics 2009-11-06 Masahito Hayashi , Fuminori Sakaguchi

Anyone who has ever worked with a variety~$\boldsymbol{\mathscr{A}}$ of algebras with a reduct in the variety of bounded distributive lattices will know a restricted Priestley duality when they meet one---but until now there has been no…

Category Theory · Mathematics 2016-05-27 Brian A. Davey , Asha Gair

The wrapped normal distribution arises when a the density of a one-dimensional normal distribution is wrapped around the circle infinitely many times. At first look, evaluation of its probability density function appears tedious as an…

Computation · Statistics 2018-01-01 Gerhard Kurz , Igor Gilitschenski , Uwe D. Hanebeck
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