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We present in this article the use of probabilistic background constraints in astronomical image deconvolution to approach to a solution as an interval estimate. We elaborate our objective -- the interval estimate of the unknown object from…

Instrumentation and Methods for Astrophysics · Physics 2015-06-12 Zhuo-xi Huo , Jian-feng Zhou

We consider the problem of estimating a nested structure of two expectations taking the form $U_0 = E[\max\{U_1(Y), \pi(Y)\}]$, where $U_1(Y) = E[X\ |\ Y]$. Terms of this form arise in financial risk estimation and option pricing. When…

Computational Finance · Quantitative Finance 2023-08-16 Abdul-Lateef Haji-Ali , Jonathan Spence

We performed a detailed analysis and the Monte Carlo simulation of the neutron lifetime experiment [S. Arzumanov et al., Phys. Lett. B 483 (2000) 15] because of the strong disagreement by 5.6 standard deviations between the results of this…

Nuclear Experiment · Physics 2014-11-21 A. K. Fomin , A. P. Serebrov

In the present paper we study quasi-Monte Carlo rules for approximating integrals over the $d$-dimensional unit cube for functions from weighted Sobolev spaces of regularity one. While the properties of these rules are well understood for…

Numerical Analysis · Mathematics 2020-01-17 Peter Kritzer , Friedrich Pillichshammer , G. W. Wasilkowski

The work addresses the analogy between trivial knotting and excluded volume in looped polymer chains of moderate length, $N<N_0$, where the effects of knotting are small. A simple expression for the swelling seen in trivially knotted loops…

Soft Condensed Matter · Physics 2007-05-23 N. T. Moore , A. Y. Grosberg

We present results of a high precision Monte Carlo simulation of dynamically triangulated random surfaces (up to $\approx$ 34,000 triangles) coupled to one scalar field ($c=1$). The mean square extent has been measured for different actions…

High Energy Physics - Theory · Physics 2009-10-22 T. Filk , M. Marcu , B. Scheffold

We observe a realization of a stationary generalized weighted Voronoi tessellation of the d-dimensional Euclidean space within a bounded observation window. Given a geometric characteristic of the typical cell, we use the minus-sampling…

Probability · Mathematics 2019-06-10 Daniela Flimmel , Zbyněk Pawlas , Joseph E. Yukich

As a test of quenched lattice twisted mass QCD, we compute the non-perturbatively O($a$) improved pseudoscalar and vector meson masses and the pseudoscalar decay constant down to $M_{\rm PS}/M_{\rm V} = 0.467(13)$ at $\beta=6$ in large…

High Energy Physics - Lattice · Physics 2015-06-25 M. Della Morte , R. Frezzotti , J. Heitger

We develop Monte Carlo methods for sampling random states and corresponding bit strings in qubit systems. To this end, we derive exact probability density functions that yield the Porter-Thomas distribution in the limit of large systems. We…

Quantum Physics · Physics 2025-09-05 Andreas Raab

We carry out a combined analysis of elliptic and triangular flow data using viscous relativistic hydrodynamics. We show that these data allow to put tight constraints on models of the early dynamics of a nucleus-nucleus collision.…

Nuclear Theory · Physics 2014-01-10 Ekaterina Retinskaya , Matthew Luzum , Jean-Yves Ollitrault

The core of every orbit determination process is the comparison between the measured observables and their predicted values, computed using the adopted mathematical models, and the minimization, in a least square sense, of their…

Instrumentation and Methods for Astrophysics · Physics 2019-08-22 Marco Zannoni , Paolo Tortora

Uncertainty assessment has gained rapid interest in medical image analysis. A popular technique to compute epistemic uncertainty is the Monte-Carlo (MC) dropout technique. From a network with MC dropout and a single input, multiple outputs…

Computer Vision and Pattern Recognition · Computer Science 2023-08-08 Robin Camarasa , Daniel Bos , Jeroen Hendrikse , Paul Nederkoorn , M. Eline Kooi , Aad van der Lugt , Marleen de Bruijne

Investing efficiently in future research to improve policy decisions is an important goal. Expected Value of Sample Information (EVSI) can be used to select the specific design and sample size of a proposed study by assessing the benefit of…

We discuss possible sources of systematic errors in the computation of critical exponents by renormalization-group methods, extrapolations from exact enumerations and Monte Carlo simulations. A careful Monte Carlo determination of the…

High Energy Physics - Lattice · Physics 2009-10-30 Sergio Caracciolo , Maria Serena Causo , Andrea Pelissetto

Multivariate normal (MVN) probabilities arise in myriad applications, but they are analytically intractable and need to be evaluated via Monte-Carlo-based numerical integration. For the state-of-the-art minimax exponential tilting (MET)…

Computation · Statistics 2026-01-28 Jian Cao , Matthias Katzfuss

A method for calculating the pressure tensor in constant-volume Monte Carlo simulations of convex bodies is presented. In contrast to other approaches, the method requires only an isotropic scaling of the simulation box, and the counting of…

Statistical Mechanics · Physics 2009-11-11 Michael P. Allen

Direct numerical simulations are performed for the steady flow normal to a circular disk at the Reynolds number of 1000. Numerical simulations are conducted with different levels of simplification procedure by reducing the azimuthal…

Fluid Dynamics · Physics 2019-06-26 Xinliang Tian

We study the expected volume of random polytopes generated by taking the convex hull of independent identically distributed points from a given distribution. We show that for log-concave distributions supported on convex bodies, we need at…

Metric Geometry · Mathematics 2021-11-16 Debsoumya Chakraborti , Tomasz Tkocz , Beatrice-Helen Vritsiou

We present an analytical derivation of the volume fractions for random close packing (RCP) in both $d=3$ and $d=2$, based on the same methodology. Using suitably modified nearest neigbhour statistics for hard spheres, we obtain…

Soft Condensed Matter · Physics 2022-01-13 Alessio Zaccone

We study structured nonsmooth convex finite-sum optimization that appears widely in machine learning applications, including support vector machines and least absolute deviation. For the primal-dual formulation of this problem, we propose a…

Optimization and Control · Mathematics 2021-04-08 Chaobing Song , Stephen J. Wright , Jelena Diakonikolas
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