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We prove extension-dimensional versions of finite dimensional selection and approximation theorems. As applications, we obtain several results on extension dimension.

General Topology · Mathematics 2007-05-23 N. Brodsky , A. Chigogidze , A. Karasev

This paper deals with the problem of estimating the covariance matrix of a series of independent multivariate observations, in the case where the dimension of each observation is of the same order as the number of observations. Although…

Information Theory · Computer Science 2015-06-03 Jianfeng Yao , Abla Kammoun , Jamal Najim

The geometric median, a notion of center for multivariate distributions, has gained recent attention in robust statistics and machine learning. Although conceptually distinct from the mean (i.e., expectation), we demonstrate that both are…

Statistics Theory · Mathematics 2026-02-19 Richard Schwank , Mathias Drton

An ultrametric topology formalizes the notion of hierarchical structure. An ultrametric embedding, referred to here as ultrametricity, is implied by a hierarchical embedding. Such hierarchical structure can be global in the data set, or…

Methodology · Statistics 2011-01-11 Fionn Murtagh

We study the entanglement Hamiltonian of two disjoint blocks in the harmonic chain on the line and in its ground state. In the regime of large mass, the non vanishing terms are only the on-site and the nearest-neighbour ones. Analytic…

Statistical Mechanics · Physics 2025-03-26 Francesco Gentile , Andrei Rotaru , Erik Tonni

We examine the physical manifestations of exceptional points and passage times in a two-level system which is subjected to quantum measurements and which admits a non-Hermitian description. Using an effective Hamiltonian acting in the…

Quantum Physics · Physics 2015-06-12 A. Thilagam

Analyzing time series in the frequency domain enables the development of powerful tools for investigating the second-order characteristics of multivariate processes. Parameters like the spectral density matrix and its inverse, the coherence…

Methodology · Statistics 2024-01-19 Jonas Krampe , Efstathios Paparoditis

We continue our efforts to understand, within the framework of the quantum mechanics of the universe as a whole, the quasiclassical realm of familiar experience as a feature emergent from the Hamiltonian of the elementary particles and the…

Quantum Physics · Physics 2019-05-16 Murray Gell-Mann , James Hartle

This paper studies fundamental aspects of modelling data using multivariate Watson distributions. Although these distributions are natural for modelling axially symmetric data (i.e., unit vectors where $\pm \x$ are equivalent), for…

Computation · Statistics 2012-05-28 Suvrit Sra , Dmitrii Karp

Number theorists have studied extensively the connections between the distribution of zeros of the Riemann $\zeta$-function, and of some generalizations, with the statistics of the eigenvalues of large random matrices. It is interesting to…

Mathematical Physics · Physics 2009-10-31 E. Brezin , S. Hikami

The common perception is that strong coupling to the environment will always render the evolution of the system density matrix quasi-classical (in fact, diffusive) in the long time limit. We present here a counter-example, in which a…

Other Condensed Matter · Physics 2007-05-23 Nikolay Prokof'ev , Philip Stamp

In this thesis, we study three physically relevant models of strongly correlated random variables: trapped fermions, random matrices and random walks. In the first part, we show several exact mappings between the ground state of a trapped…

Statistical Mechanics · Physics 2019-06-24 Bertrand Lacroix-A-Chez-Toine

We consider the estimation of large covariance and precision matrices from high-dimensional sub-Gaussian or heavier-tailed observations with slowly decaying temporal dependence. The temporal dependence is allowed to be long-range so with…

Statistics Theory · Mathematics 2019-12-23 Hai Shu , Bin Nan

We characterize monitored quantum dynamics in a solvable model exhibiting a phase transition between a measurement apparatus and a scrambler. We show that approximate decoherent histories emerge in both phases with respect to a…

Quantum Physics · Physics 2026-03-23 Benoît Ferté , Davide Farci , Xiangyu Cao

The dimensionality of entanglement is a core tenet of quantum information processing, especially quantum communication and computation. While it is natural to think of this dimensionality in finite dimensional systems, many of the…

Quantum Physics · Physics 2025-09-04 Shuheng Liu , Jiajie Guo , Matteo Fadel , Qiongyi He , Marcus Huber , Giuseppe Vitagliano

In current research, machine and deep learning solutions for the classification of temporal data are shifting from single-channel datasets (univariate) to problems with multiple channels of information (multivariate). The majority of these…

Machine Learning · Computer Science 2023-04-13 Leonardos Pantiskas , Kees Verstoep , Mark Hoogendoorn , Henri Bal

Dimension theory lies at the heart of fractal geometry and concerns the rigorous quantification of how large a subset of a metric space is. There are many notions of dimension to consider, and part of the richness of the subject is in…

Metric Geometry · Mathematics 2019-09-20 Jonathan M. Fraser

The extreme event statistics plays a very important role in the theory and practice of time series analysis. The reassembly of classical theoretical results is often undermined by non-stationarity and dependence between increments.…

Statistical Finance · Quantitative Finance 2015-05-28 Mauro Politi , Nicolas Millot , Anirban Chakraborti

Interpretations of quantum measurement theory have been plagued by two questions, one concerning the role of observer consciousness and the other the entanglement phenomenon arising from the superposition of quantum states. We emphasize…

Quantum Physics · Physics 2007-05-23 L. E. H. Trainor , Charles J. Lumsden

Extreme value theory provides rigorous theory and statistical tools for extrapolation in machine learning, particularly in settings where traditional methods struggle due to data scarcity in the tails. A broad range of tasks benefit from…

Machine Learning · Statistics 2026-05-05 Sebastian Engelke , Nicola Gnecco , Anne Sabourin