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This note gives an explicit description of conditional measures for the determinantal point process with the Bergman kernel.

Probability · Mathematics 2022-01-03 Alexander I. Bufetov

We define multideterminantal probability measures, a family of probability measures on $[k]^n$ where $[k]=\{1,2,\dots,k\}$, generalizing determinantal measures (which correspond to the case $k=2$). We give examples coming from the positive…

Probability · Mathematics 2025-07-16 Richard Kenyon

The Bures metric is a natural choice in measuring the distance of density operators representing states in quantum mechanics. In the past few years a random matrix ensemble and the corresponding joint probability density function of its…

Mathematical Physics · Physics 2017-01-31 Peter J. Forrester , Mario Kieburg

Determinantal point processes are characterized by a special structural property of the correlation functions: they are given by minors of a correlation kernel. However, unlike the correlation functions themselves, this kernel is not…

Probability · Mathematics 2022-06-15 Grigori Olshanski

Basic Parallel Processes (BPPs) are a well-known subclass of Petri Nets. They are the simplest common model of concurrent programs that allows unbounded spawning of processes. In the probabilistic version of BPPs, every process generates…

Logic in Computer Science · Computer Science 2014-01-17 Rémi Bonnet , Stefan Kiefer , Anthony W. Lin

We consider random permutation matrices following a one-parameter family of deformations of the uniform distribution, called Ewens' measures, and modifications of these matrices where the entries equal to one are replaced by i.i.d uniform…

Probability · Mathematics 2018-03-12 Valentin Bahier

We introduce the affine ensemble, a class of determinantal point processes (DPP) in the half-plane C^+ associated with the ax+b (affine) group, depending on an admissible Hardy function {\psi}. We obtain the asymptotic behavior of the…

Probability · Mathematics 2022-10-18 Luis Daniel Abreu , Peter Balazs , Smiljana Jakšić

The birth-death process is a special type of continuous-time Markov chain with index set $\mathbb{N}$. Its resolvent matrix can be fully characterized by a set of parameters $(\gamma, \beta, \nu)$, where $\gamma$ and $\beta$ are…

Probability · Mathematics 2024-09-10 Liping Li

We define a determinantal point process on the complex projective space that reduces to the so-called spherical ensemble for complex dimension 1 under identification of the 2-sphere with the Riemann sphere. Through this determinantal point…

Classical Analysis and ODEs · Mathematics 2017-03-02 Carlos Beltrán , Ujué Etayo

We study the geometry of infinite random Boltzmann planar maps having weight of polynomial decay of order $k^{-2}$ for each vertex of degree $k$. These correspond to the dual of the discrete "stable maps" of Le Gall and Miermont [Scaling…

Probability · Mathematics 2018-11-08 Timothy Budd , Nicolas Curien , Cyril Marzouk

To each finite-dimensional representation of a simple Lie algebra is associated a multiplicative graph in the sense of Kerov and Vershik definedfrom the decomposition of its tensor powers into irreducible components. The conditioning of…

Representation Theory · Mathematics 2017-01-19 Cedric Lecouvey , Pierre Tarrago

A recent approach to the Beck-Fiala conjecture, a fundamental problem in combinatorics, has been to understand when random integer matrices have constant discrepancy. We give a complete answer to this question for two natural models:…

Probability · Mathematics 2021-08-17 Dylan J. Altschuler , Jonathan Niles-Weed

We introduce a random matrix model where the entries are dependent across both rows and columns. More precisely, we investigate matrices of the form $\X=(X_{(i-1)n+t})_{it}\in\R^{p\times n}$ derived from a linear process $X_t=\sum_j c_j…

Probability · Mathematics 2012-02-15 Oliver Pfaffel , Eckhard Schlemm

We show that the symplectic and orthogonal character analogues of Okounkov's Schur measure (on integer partitions) are determinantal, with explicit correlation kernels. We apply this to prove certain Borodin-Okounkov-Gessel-type results…

Probability · Mathematics 2020-01-31 Dan Betea

Determinantal Point Process (DPPs) are statistical models for repulsive point patterns. Both sampling and inference are tractable for DPPs, a rare feature among models with negative dependence that explains their popularity in machine…

Machine Learning · Computer Science 2021-11-30 Michaël Fanuel , Rémi Bardenet

We start by studying a peeling process on finite random planar maps with faces of arbitrary degrees determined by a general weight sequence, which satisfies an admissibility criterion. The corresponding perimeter process is identified as a…

Mathematical Physics · Physics 2016-02-23 Timothy Budd

Macdonald processes are certain probability measures on two-dimensional arrays of interlacing particles introduced by Borodin and Corwin (arXiv:1111.4408 [math.PR]). They are defined in terms of nonnegative specializations of the Macdonald…

Probability · Mathematics 2013-05-24 Alexei Borodin , Leonid Petrov

Linearizing the Heisenberg equations of motion around the ground state of an interacting quantum many-body system, one gets a time-evolution generator in the positive cone of a real symplectic Lie algebra. The presence of disorder in the…

Mesoscale and Nanoscale Physics · Physics 2009-11-11 T. Lueck , H. -J. Sommers , M. R. Zirnbauer

We introduce a general framework to deterministically construct binary measurement matrices for compressed sensing. The proposed matrices are composed of (circulant) permutation submatrix blocks and zero submatrix blocks, thus making their…

Information Theory · Computer Science 2014-09-26 Xin-Ji Liu , Shu-Tao Xia , Tao Dai

Motivated by questions in quantum theory, we study Hilbert space valued Gaussian processes, and operator-valued kernels, i.e., kernels taking values in B(H) (= all bounded linear operators in a fixed Hilbert space H). We begin with a…

Functional Analysis · Mathematics 2024-08-21 Palle E. T. Jorgensen , James Tian
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