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Topological data analysis provides a collection of tools to encapsulate and summarize the shape of data. Currently it is mainly restricted to \emph{mapper algorithm} and \emph{persistent homology}. In this paper we introduce new…

Algebraic Topology · Mathematics 2019-01-23 Paweł Dłotko

In this thesis, the possibility of interpreting the solar and atmospheric neutrino data within the context of theoretical models is being explored. In particular, the implications of the Minimal Supersymmetric Standard Model augmented by a…

High Energy Physics - Phenomenology · Physics 2007-05-23 Psallidas Andreas

This paper is a brief review of recent developments in random matrix theory. Two aspects are emphasized: the underlying role of integrable systems and the occurrence of the distribution functions of random matrix theory in diverse areas of…

Mathematical Physics · Physics 2007-05-23 Craig A. Tracy , Harold Widom

Data augmentation is a cornerstone of the machine learning pipeline, yet its theoretical underpinnings remain unclear. Is it merely a way to artificially augment the data set size? Or is it about encouraging the model to satisfy certain…

Machine Learning · Computer Science 2022-09-22 Ruoqi Shen , Sébastien Bubeck , Suriya Gunasekar

Exploring the shape of point configurations has been a key driver in the evolution of TDA (short for topological data analysis) since its infancy. This survey illustrates the recent efforts to broaden these ideas to model spatial…

Computational Geometry · Computer Science 2024-06-07 Sebastiano Cultrera di Montesano , Ondrej Draganov , Herbert Edelsbrunner , Morteza Saghafian

In this talk we discuss some details of the analysis of neutrino data and our present understanding of neutrino masses and mixing. This talk is based on hep-ph/0306001, hep-ph/0306226 and hep-ph/0404085.

High Energy Physics - Phenomenology · Physics 2016-12-07 M. C. Gonzalez-Garcia , Michele Maltoni

We present a concise review of the recent important experimental developments on neutrino mixing (hints for sterile neutrinos, large $\theta_{13}$, possible non maximal $\theta_{23}$, approaching sensitivity on $\delta_{CP}$) and their…

High Energy Physics - Phenomenology · Physics 2022-03-02 Guido Altarelli

Topological data analysis is an emerging field that applies the study of topological invariants to data. Perhaps the simplest of these invariants is the number of connected components or clusters. In this work, we explore a topological…

Computational Geometry · Computer Science 2023-12-19 Ian Stewart Joyce , Grant Erdmann , Kirk P. Gardner , Ryan Kramer , Kyle Siegrist

We analyze entropic uncertainty relations in a finite dimensional Hilbert space and derive several strong bounds for the sum of two entropies obtained in projective measurements with respect to any two orthogonal bases. We improve the…

Quantum Physics · Physics 2015-06-30 Łukasz Rudnicki , Zbigniew Puchała , Karol Życzkowski

Recently it has been shown that cumulants significantly simplify the analysis of multipartite weak measurements. Here we consider the mathematical structure that underlies this, and find that it can be formulated in terms of what we call…

Quantum Physics · Physics 2009-07-12 Johan Aberg , Graeme Mitchison

The article motivates recent work on saturation of ultrapowers from a general mathematical point of view.

Logic · Mathematics 2018-03-21 M. Malliaris

Networks play a central role in modern data analysis, enabling us to reason about systems by studying the relationships between their parts. Most often in network analysis, the edges are given. However, in many systems it is difficult or…

Machine Learning · Statistics 2014-02-06 Scott W. Linderman , Ryan P. Adams

This work is devoted to elaboration on the idea to use block term decomposition for group data analysis and to raise the possibility of modelling group activity with (Lr, 1) and Tucker blocks. A new generalization of block tensor…

Numerical Analysis · Computer Science 2018-08-08 Pavel Kharyuk , Ivan Oseledets

Large-scale data are often characterized by some degree of inhomogeneity as data are either recorded in different time regimes or taken from multiple sources. We look at regression models and the effect of randomly changing coefficients,…

Methodology · Statistics 2016-08-11 Nicolai Meinshausen , Peter Bühlmann

Battiston et al. (arXiv:2110.06023) provide a comprehensive overview of how investigations of complex systems should take into account interactions between more than two elements, which can be modelled by hypergraphs and studied via…

Data assimilation addresses the general problem of how to combine model-based predictions with partial and noisy observations of the process in an optimal manner. This survey focuses on sequential data assimilation techniques using…

Numerical Analysis · Mathematics 2019-08-15 Sebastian Reich

The existing data appears to provide hints of an underlying high scale theory. These arise from the gauge coupling unification, from the smallness of the neutrino masses, and via a non-vanishing muon anomaly. An overview of high scale…

High Energy Physics - Phenomenology · Physics 2011-01-04 Pran Nath

These notes are a fuller version of four lectures given at the 2015 International Summer Workshop in Reaction Theory held at Indiana University, Bloomington. The aim is to provide a simple introduction to how the tools of "the S-matrix era"…

High Energy Physics - Phenomenology · Physics 2015-07-13 Ian J. R. Aitchison

Various statistical issues relevant to searches for new physics or to parameter determination in analyses of data in neutrino experiments are briefly discussed.

High Energy Physics - Experiment · Physics 2016-07-14 Louis Lyons

We investigate commutator operations on compatible uniformities of an algebra. We present a commutator operation for compatible uniformities of an algebra in a congruence-modular variety which extends the commutator on congruences, and…

Rings and Algebras · Mathematics 2007-05-23 William H. Rowan
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