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The contribution of this work is twofold. The first part deals with a Hilbert-space version of McCann's celebrated result on the existence and uniqueness of monotone measure-preserving maps: given two probability measures $\rm P$ and $\rm…

Probability · Mathematics 2023-05-23 Alberto González-Sanz , Marc Hallin , Bodhisattva Sen

Given a super-critical branching random walk on $\mathbb{R}$ started from the origin, let $Z\_n(\cdot)$ be the counting measure which counts the number of individuals at the $n$-th generation located in a given set. Under some mild…

Probability · Mathematics 2017-04-19 Xinxin Chen , Hui He

We have examined the success rates of 19 American, Canadian, Australian, and Dutch graduate programs in producing astronomers. A 20-year baseline was considered (1975-1994), incorporating 897 PhD recipients. The major conclusion from our…

A new non-parametric statistic is introduced for the characterization of deviations from power laws. It is tested on the distribution of seismic energies given by the Gutenberg-Richter law. Based on the two first statistical log-moments, it…

Data Analysis, Statistics and Probability · Physics 2007-05-23 V. Pisarenko , D. Sornette , M. Rodkin

In September 2006, Piet Groeneboom officially retired as professor of statistics at Delft University of Technology and the Vrije Universiteit in Amsterdam. He did so by delivering his farewell lecture `Summa Cogitatio' ([42] in Piet's…

Statistics Theory · Mathematics 2007-09-12 Eric A. Cator , Geurt Jongbloed , Cor Kraaikamp , Hendrik P. Lopuhaä , Jon A. Wellner

We report on experimental measurement of the Hilbert-Schmidt distance between two two-qubit states by many-particle interference. We demonstrate that our three-step method for measuring distances in Hilbert space is far less complex than…

Quantum Physics · Physics 2021-12-28 Vojtěch Trávníček , Karol Bartkiewicz , Antonín Černoch , Karel Lemr

Subsampling is an important technique to tackle the computational challenges brought by big data. Many subsampling procedures fall within the framework of importance sampling, which assigns high sampling probabilities to the samples…

Machine Learning · Statistics 2022-03-07 Tieliang Gong , Yuxin Dong , Hong Chen , Bo Dong , Chen Li

Gaussian process regression in its most simplified form assumes normal homoscedastic noise and utilizes analytically tractable mean and covariance functions of predictive posterior distribution using Gaussian conditioning. Its…

Applications · Statistics 2023-01-20 Pooja Algikar , Lamine Mili

These are expanded notes of a seminar held in Columbia university during the Spring and Fall of 2024 about the theory of analytic stacks of Clausen and Scholze, with a focus in the theory of solid mathematics. The seminar is inspired from…

Algebraic Geometry · Mathematics 2026-03-04 Juan Esteban Rodríguez Camargo

Outlier analysis is a critical tool across diverse domains, from clinical decision-making to cybersecurity and talent identification. Traditional statistical outlier detection methods, such as Grubb's test and Dixon's Q, are predicated on…

Methodology · Statistics 2025-08-12 Johan F. Hoorn , Johnny K. W. Ho

Nancy Flournoy was born in Long Beach, California, on May 4, 1947. After graduating from Polytechnic School in Pasadena in 1965, she earned a B.S. (1969) and M.S. (1971) in biostatistics from UCLA. Between her bachelors and masters degrees,…

Other Statistics · Statistics 2015-04-14 William F. Rosenberger

A quantum system can be entirely described by the K\"ahler structure of the projective space P(H) associated to the Hilbert space H of possible states; this is the so-called geometrical formulation of quantum mechanics. In this paper, we…

Differential Geometry · Mathematics 2012-02-07 Mathieu Molitor

We examine how to construct a spatial manifold and its geometry from the entanglement structure of an abstract quantum state in Hilbert space. Given a decomposition of Hilbert space $\mathcal{H}$ into a tensor product of factors, we…

High Energy Physics - Theory · Physics 2017-02-01 ChunJun Cao , Sean M. Carroll , Spyridon Michalakis

The monograph "Invitation to higher local fields" is the result of the conference on higher local fields held in Muenster, August 29 to September 5, 1999. The aim is to provide an introduction to higher local fields (more generally complete…

Number Theory · Mathematics 2009-09-25 Ivan Fesenko , Masato Kurihara

Learning in the presence of outliers is a fundamental problem in statistics. Until recently, all known efficient unsupervised learning algorithms were very sensitive to outliers in high dimensions. In particular, even for the task of robust…

Data Structures and Algorithms · Computer Science 2019-11-15 Ilias Diakonikolas , Daniel M. Kane

We introduce and study a family of random processes on trees we call hipster random walks, special instances of which we heuristically connect to the min-plus binary trees introduced by Robin Pemantle and studied by Auffinger and Cable…

Probability · Mathematics 2019-09-17 Louigi Addario-Berry , Hannah Cairns , Luc Devroye , Celine Kerriou , Rivka Mitchell

Information scrambling, the process by which quantum information spreads and becomes effectively inaccessible, is central to modern quantum statistical physics and quantum chaos. These lecture notes provide an introduction to information…

Quantum Physics · Physics 2025-11-19 Marcin Płodzień

These lecture notes were written for the course 18.657, High Dimensional Statistics at MIT. They build on a set of notes that was prepared at Princeton University in 2013-14 that was modified (and hopefully improved) over the years.

Statistics Theory · Mathematics 2023-10-31 Philippe Rigollet , Jan-Christian Hütter

This is a transcript of a lecture course on Infinite Permutation Groups given by Peter M. Neumann (1940-2020) in Oxford during the academic year 1988-1989. The field of Infinite Permutation Groups only emerged as an independent field of…

Group Theory · Mathematics 2023-07-25 Peter M. Neumann

In this work, we propose a non-parametric and robust change detection algorithm to detect multiple change points in time series data under contamination. The contamination model is sufficiently general, in that, the most common model used…

Methodology · Statistics 2022-06-24 Sujay Bhatt , Guanhua Fang , Ping Li