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One of the most important statistics in studying the zeros of L-functions is the 1-level density, which measures the concentration of zeros near the central point. Fouvry and Iwaniec [FI] proved that the 1-level density for L-functions…

Number Theory · Mathematics 2010-03-30 Steven J. Miller , Ryan Peckner

Membrane-fluctuation-induced attraction between ligand--receptor sites binding neighboring membranes is studied using meshless membrane simulations and the Weil--Farago two-dimensional lattice model. For the adhesion sites binding two…

Soft Condensed Matter · Physics 2013-06-25 Hiroshi Noguchi

This is the first paper of a series of three, reporting on numerical simulation studies of geometric and mechanical properties of static assemblies of spherical beads under an isotropic pressure. Frictionless systems assemble in the unique…

Disordered Systems and Neural Networks · Physics 2008-02-01 Ivana Agnolin , Jean-Noël Roux

Anisotropic functional deconvolution model is investigated in the bivariate case under long-memory errors when the design points $t_i$, $i=1, 2, \cdots, N$, and $x_l$, $l=1, 2, \cdots, M$, are irregular and follow known densities $h_1$,…

Statistics Theory · Mathematics 2020-01-07 Rida Benhaddou

This paper describes how realistic neuromorphic networks can have their connectivity fully characterized in analytical fashion. By assuming that all neurons have the same shape and are regularly distributed along the two-dimensional…

Disordered Systems and Neural Networks · Physics 2007-05-23 Luciano da Fontoura Costa , Marconi Soares Barbosa

We investigate the application of efficient recursive numerical integration strategies to models in lattice gauge theory from quantum field theory. Given the coupling structure of the physics problems and the group structure within lattice…

High Energy Physics - Lattice · Physics 2021-12-10 Tobias Hartung , Karl Jansen , Frances Y. Kuo , Hernan Leövey , Dirk Nuyens , Ian H. Sloan

We discuss joint temporal and contemporaneous aggregation of $N$ independent copies of strictly stationary AR(1) and INteger-valued AutoRegressive processes of order 1 (INAR(1)) with random coefficient $\alpha \in (0, 1)$ and idiosyncratic…

Probability · Mathematics 2016-01-19 Fanni Nedényi , Gyula Pap

Various theoretical obstacles are associated with a homogeneous and isotropic distribution of ``charge'' which is subject to a repulsive, long-range force. We show how these can be overcome, for all practical purposes, by the simple device…

General Relativity and Quantum Cosmology · Physics 2009-11-07 M. Brisudova , R. P. Woodard , W. H. Kinney

We explore the macroscopic consequences of lattice anisotropy for Diffusion Limited Aggregation (DLA) in three dimensions. Simple cubic and BCC lattice growths are shown to approach universal asymptotic states in a coherent fashion, and the…

Statistical Mechanics · Physics 2007-05-23 Nicholas R. Goold , Ellak Somfai , Robin C. Ball

We consider a linear model where the coefficients - intercept and slopes - are random with a law in a nonparametric class and independent from the regressors. Identification often requires the regressors to have a support which is the whole…

Statistics Theory · Mathematics 2020-06-22 Christophe Gaillac , Eric Gautier

Random graph alignment refers to recovering the underlying vertex correspondence between two random graphs with correlated edges. This can be viewed as an average-case and noisy version of the well-known graph isomorphism problem. For the…

Machine Learning · Statistics 2021-08-18 Luca Ganassali , Laurent Massoulié , Marc Lelarge

Using real-space renormalisation techniques we analyse the Ising model on a Sierpi\'nski gasket with anisotropic microscopic couplings, and observe a restoration of isotropy on macroscopic scales. In particular, via use of a decimation…

Condensed Matter · Physics 2009-10-30 D. C. Brody , A. Ritz

We study how sampling geometry contributes to uncertainty in modeling spatial geophysical observations as sampled random fields characterized by stationary, isotropic, parametric covariance functions. We incorporate the signature of…

Methodology · Statistics 2026-04-03 Olivia L. Walbert , Frederik J. Simons , Arthur P. Guillaumin , Sofia C. Olhede

Introduction. Neural network models of autoassociative, distributed memory allow storage and retrieval of many items (vectors) where the number of stored items can exceed the vector dimension (the number of neurons in the network). This…

Neural and Evolutionary Computing · Computer Science 2017-09-05 V. I. Gritsenko , D. A. Rachkovskij , A. A. Frolov , R. Gayler , D. Kleyko , E. Osipov

This doctoral thesis undertakes an in-depth exploration of limiting shape theorems across diverse mathematical structures, with a specific focus on subadditive processes within finitely generated groups exhibiting polynomial growth rates,…

Probability · Mathematics 2024-08-22 Lucas R. de Lima

In $M$-estimation under standard asymptotics, the weak convergence combined with the polynomial type large deviation estimate of the associated statistical random field Yoshida (2011) provides us with not only the asymptotic distribution of…

Statistics Theory · Mathematics 2017-04-18 Hiroki Masuda , Yusuke Shimizu

Topography and gravity are geophysical fields whose joint statistical structure derives from interface-loading processes modulated by the underlying mechanics of isostatic and flexural compensation in the shallow lithosphere. Under this…

Geophysics · Physics 2013-02-25 Frederik J. Simons , Sofia C. Olhede

We have studied the anisotropic three-dimensional nearest-neighbor Ising model with competitive interactions in an uniform longitudinal magnetic field $H$. The model consists of ferromagnetic interaction $J_{x}(J_{z})$ in the $x(z)$…

Statistical Mechanics · Physics 2012-06-29 Octavio D. R. Salmon , Minos A. Neto , J. Roberto Viana , Igor T. Padilha , J. R. de Sousa

We extend the latent position random graph model to the line graph of a random graph, which is formed by creating a vertex for each edge in the original random graph, and connecting each pair of edges incident to a common vertex in the…

Social and Information Networks · Computer Science 2024-02-27 Zachary Lubberts , Avanti Athreya , Youngser Park , Carey E. Priebe

Isotonic regression is a nonparametric approach for fitting monotonic models to data that has been widely studied from both theoretical and practical perspectives. However, this approach encounters computational and statistical overfitting…

Methodology · Statistics 2012-03-21 Ronny Luss , Saharon Rosset , Moni Shahar
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