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In this paper, we study the two natural polarizations, namely the standard polarization and the box polarization, of the d-th power of the maximal ideal in a polynomial ring. We show that these polarizations correspond to smooth points in…

Commutative Algebra · Mathematics 2013-03-27 Henning Lohne

One of the difficulties with performing polarization analysis is that the mean polarization fraction of sub-divided data sets is larger than the polarization fraction for the integrated measurement. The resulting bias is one of the…

Instrumentation and Methods for Astrophysics · Physics 2018-07-18 Victor Mikhalev

For a track based polarimeter, such as the Imaging X-ray Polarimetry Explorer (IXPE), the sensitivity to polarization depends on the modulation factor, which is a strong function of energy. In previous work, a likelihood method was…

Instrumentation and Methods for Astrophysics · Physics 2021-09-29 Herman L. Marshall

We model voting behaviour in the multi-group setting of a two-tier voting system using sequences of de Finetti measures. Our model is defined by using the de Finetti representation of a probability measure (i.e. as a mixture of…

Probability · Mathematics 2026-01-14 Gabor Toth

Radio sources are often polarized. Accurate measurement of simply the flux density of a radio source requires a basic understanding of polarization and its measurement techniques. We provide an introductory, heuristic discussion of these…

Astrophysics · Physics 2007-05-23 Carl Heiles

We review possible measures of complexity which might in particular be applicable to situations where the complexity seems to arise spontaneously. We point out that not all of them correspond to the intuitive (or "naive") notion, and that…

Data Analysis, Statistics and Probability · Physics 2012-08-20 Peter Grassberger

Recent work shows that path gradient estimators for normalizing flows have lower variance compared to standard estimators for variational inference, resulting in improved training. However, they are often prohibitively more expensive from a…

Machine Learning · Computer Science 2024-03-26 Lorenz Vaitl , Ludwig Winkler , Lorenz Richter , Pan Kessel

TRIUMF experiment E497 is a study of parity violation in pp scattering at an energy where the leading term in the analyzing power is expected to vanish, thus measuring a unique combination of weak-interaction flavour conserving terms. It is…

Instrumentation and Detectors · Physics 2009-11-06 A. R. Berdoz

The prospects for accomplishing X-ray polarization measurements appear to have grown in recent years after a more than 35-year hiatus. Unfortunately, this long hiatus has brought with it some confusion over the statistical uncertainties…

Instrumentation and Methods for Astrophysics · Physics 2015-05-19 Martin C. Weisskopf , Ronald F. Elsner , Stephen L. O'Dell

The polarization of a coherent depolarized incident light beam passing through a disordered medium is investigated. The local polarization of the scattered far field and the probability density function are calculated and show an excellent…

Optics · Physics 2011-06-06 Jacques Sorrentini , Myriam Zerrad , Gabriel Soriano , Claude Amra

Sequential Monte Carlo Samplers are a class of stochastic algorithms for Monte Carlo integral estimation w.r.t. probability distributions, which combine elements of Markov chain Monte Carlo methods and importance sampling/resampling…

Probability · Mathematics 2007-05-23 Andreas Eberle , Carlo Marinelli

We determine the order of magnitude of the $n$th $\ell_p$-polarization constant of the unit sphere $S^{d-1}$ for every $n,d \geq 1$ and $p>0$. For $p=2$, we prove that extremizers are isotropic vector sets, whereas for $p=1$, we show that…

Metric Geometry · Mathematics 2020-10-21 Gergely Ambrus , Sloan Nietert

A common way to discretize a probability measure is to use an empirical measure as a discrete approximation. But how far from being optimal is this approximation in the p-Wasserstein distance? In this paper, we study this question in two…

Probability · Mathematics 2025-08-05 March T. Boedihardjo

The paper has two main goals. The first is to take a new approach to rearrangements on certain classes of measurable real-valued functions on $\mathbb{R}^n$. Rearrangements are maps that are monotonic (up to sets of measure zero) and…

Metric Geometry · Mathematics 2022-02-15 Gabriele Bianchi , Richard J. Gardner , Paolo Gronchi , Markus Kiderlen

A simple model to handle the flow of people in emergency evacuation situations is considered: at every point x, the velocity U(x) that individuals at x would like to realize is given. Yet, the incompressibility constraint prevents this…

Analysis of PDEs · Mathematics 2010-02-04 Bertrand Maury , Aude Roudneff-Chupin , Filippo Santambrogio

When studying convergence of measures, an important issue is the choice of probability metric. In this review, we provide a summary and some new results concerning bounds among ten important probability metrics/distances that are used by…

Probability · Mathematics 2007-05-23 Alison L. Gibbs , Francis Edward Su

We present a model of polarization swings in blazars from axially symmetric blobs propagating on curved trajectories. If the minimum inclination of the velocity vector to the line of sight is smaller than Gamma^{-1}, the polarization angle…

High Energy Astrophysical Phenomena · Physics 2012-08-28 Krzysztof Nalewajko

The detection of polarized sources in the WMAP 5-year data is a very difficult task. The maps are dominated by instrumental noise and only a handful of sources show up as clear peaks in the Q and U maps. Optimal linear filters applied at…

Cosmology and Nongalactic Astrophysics · Physics 2014-11-20 M. Lopez-Caniego , M. Massardi , J. Gonzalez-Nuevo , L. Lanz , D. Herranz , G. De Zotti , J. L. Sanz , F. Argueso

In this paper we introduce the intuitive notion of trivergence of probability distributions (TPD). This notion allow us to calculate the similarity among triplets of objects. For this computation, we can use the well known measures of…

Information Theory · Computer Science 2015-06-23 Juan-Manuel Torres-Moreno

Normalizing flows are an established approach for modelling complex probability densities through invertible transformations from a base distribution. However, the accuracy with which the target distribution can be captured by the…

Machine Learning · Statistics 2024-02-02 Harry Bevins , Will Handley , Thomas Gessey-Jones