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Geometrically decorated two-dimensional (2D) discrete surfaces can be more effective than conventional smooth reflectors in managing wave radiation. Constructive non-specular wave scattering permits the scattering angle to be other than…

The phenomenon of half-spectral unidirectional invisibility is introduced for one-dimensional periodic optical structures with tailored real and imaginary refractive index distributions in a non-$\mathcal{PT}$-symmetric configuration. The…

Optics · Physics 2016-01-15 Stefano Longhi

Network theory and inverse modeling are two standard tools of applied physics, whose combination is needed when studying the dynamical organization of spatially distributed systems from indirect measurements. However, the associated…

Data Analysis, Statistics and Probability · Physics 2015-01-30 Vincent Wens

Calculus and geometry are ubiquitous in the theoretical modelling of scientific phenomena, but have historically been very challenging to apply directly to real data as statistics. Diffusion geometry is a new theory that reformulates…

Differential Geometry · Mathematics 2026-02-09 Iolo Jones , David Lanners

We study the collinear splitting functions needed for next-to-next-to-leading order calculations of jet production in the vacuum and in dense QCD matter. These splitting functions describe the probability of a parton to evolve into…

High Energy Physics - Phenomenology · Physics 2013-04-15 Michael Fickinger , Grigory Ovanesyan , Ivan Vitev

Two related issues are discussed, which might be easily explored by present and future COMPASS experiments. The first one deals with the new world of transversity, the fundamental polarized parton distribution so far totally unknown. The…

High Energy Physics - Phenomenology · Physics 2007-05-23 Mauro Anselmino

The goal of decentralized optimization over a network is to optimize a global objective formed by a sum of local (possibly nonsmooth) convex functions using only local computation and communication. It arises in various application domains,…

Optimization and Control · Mathematics 2015-03-17 John Duchi , Alekh Agarwal , Martin Wainwright

A point spread function of hexagonally segmented telescopes is derived by a new symmetrical formulation. By introducing three variables on a pupil plane, the Fourier transform of pupil functions is derived by a three-dimensional Fourier…

Instrumentation and Methods for Astrophysics · Physics 2018-11-28 Satoshi Itoh , Taro Matsuo , Shibai Hiroshi , Takahiro Sumi

The double-direction orthogonalization algorithm is applied to construct sequences of polynomials, which are orthogonal over the interval [0,1]with the weighting function 1. Functional and recurrent relations are derived for the sequences…

Numerical Analysis · Mathematics 2025-10-20 Vladimir Chelyshkov

In this paper, we show that the halfspace depth random variable for samples from a univariate distribution with a notion of center is distributed as a uniform distribution on the interval [0,1/2]. The simplicial depth random variable has a…

Methodology · Statistics 2023-04-27 Rui Ding

Diffusion models have become a popular approach for image generation and reconstruction due to their numerous advantages. However, most diffusion-based inverse problem-solving methods only deal with 2D images, and even recently published 3D…

Image and Video Processing · Electrical Eng. & Systems 2023-09-04 Suhyeon Lee , Hyungjin Chung , Minyoung Park , Jonghyuk Park , Wi-Sun Ryu , Jong Chul Ye

This paper studies the asymptotic behaviors of the pairwise angles among n randomly and uniformly distributed unit vectors in R^p as the number of points n -> infinity, while the dimension p is either fixed or growing with n. For both…

Statistics Theory · Mathematics 2013-06-04 Tony Cai , Jianqing Fan , Tiefeng Jiang

A distribution shift can have fundamental consequences such as signaling a change in the operating environment or significantly reducing the accuracy of downstream models. Thus, understanding distribution shifts is critical for examining…

Machine Learning · Computer Science 2023-06-21 Sean Kulinski , David I. Inouye

Angular observations, or observations lying on the unit circle, arise in many disciplines and require special care in their description, analysis, interpretation and visualization. We provide methods to construct concentric circular boxplot…

Methodology · Statistics 2026-02-06 Joshua D. Berlinski , Fan Dai , Ranjan Maitra

We propose data thinning, an approach for splitting an observation into two or more independent parts that sum to the original observation, and that follow the same distribution as the original observation, up to a (known) scaling of a…

Methodology · Statistics 2023-11-22 Anna Neufeld , Ameer Dharamshi , Lucy L. Gao , Daniela Witten

The Gumbel trick is a method to sample from a discrete probability distribution, or to estimate its normalizing partition function. The method relies on repeatedly applying a random perturbation to the distribution in a particular way, each…

Machine Learning · Statistics 2017-06-14 Matej Balog , Nilesh Tripuraneni , Zoubin Ghahramani , Adrian Weller

Integer-order differential operators were originally used to describe local and isotropic effects, in both space and time. However, in fields like biology, the modelling of complex phenomena with spatial heterogeneity necessitates more…

Dynamical Systems · Mathematics 2025-03-18 Cypres Verbeeck , Nikolaos Sfakianakis

The maximum achievable rate or mutual informa- tion of multidimensional rotationally invariant distributions in the presence of additive white Gaussian noise is analyzed. A simple expression for the special case of multisphere distributions…

Information Theory · Computer Science 2016-04-15 Johnny Karout , Rene'-Jean Essiambre , Erik Agrell , Antonia Tulino

Spectral discretizations of fractional derivative operators are examined, where the approximation basis is related to the set of Jacobi polynomials. The pseudo-spectral method is implemented by assuming that the grid, used to represent the…

Numerical Analysis · Mathematics 2018-03-29 Lorella Fatone , Daniele Funaro

To investigate neural network parameters, it is easier to study the distribution of parameters than to study the parameters in each neuron. The ridgelet transform is a pseudo-inverse operator that maps a given function $f$ to the parameter…

Machine Learning · Computer Science 2024-04-22 Sho Sonoda , Isao Ishikawa , Masahiro Ikeda