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We study a stochastic program where the probability distribution of the uncertain problem parameters is unknown and only indirectly observed via finitely many correlated samples generated by an unknown Markov chain with $d$ states. We…

Optimization and Control · Mathematics 2021-06-15 Mengmeng Li , Tobias Sutter , Daniel Kuhn

This is the 13th article in the collection of reviews "Exact results in N=2 supersymmetric gauge theories", ed. J. Teschner. It discusses the relation between the instanton partition functions and the partition function of the topological…

High Energy Physics - Theory · Physics 2014-12-23 Daniel Krefl , Johannes Walcher

We show that the refined Donaldson-Thomas invariants of C3, suitably normalized, have a Gaussian distribution as limit law. Combinatorially these numbers are given by weighted counts of 3D partitions. Our technique is to use the…

Algebraic Geometry · Mathematics 2015-06-15 Andrew Morrison

We continue our study on the partition function for 5D supersymmetric Yang-Mills theory on toric Sasaki-Einstein $Y^{p,q}$ manifolds. Previously, using the localisation technique we have computed the perturbative part of the partition…

High Energy Physics - Theory · Physics 2014-04-28 Jian Qiu , Maxim Zabzine

The so-called Maryland model is a linear version of the quantum kicked rotor; it exhibits Anderson localization in momentum space. By turning the kicks into a Markovian stochastic process, the dynamics becomes a dissipative quantum process…

Quantum Physics · Physics 2016-06-15 Fabio Benatti , Federico Carollo

This work proposes a bootstrapping with positivity methodology to study random $U(N)^{D}$ invariant tensors in the large $N$ limit. As has been done for $U(N)$ invariant random matrices, we combine the Dyson-Schwinger equations and…

High Energy Physics - Theory · Physics 2026-04-22 Nathan Pagliaroli , Carlos I. Pérez-Sánchez , Brayden Smith

We develop a new method for bounding the relative entropy of a random vector in terms of its Stein factors. Our approach is based on a novel representation for the score function of smoothly perturbed random variables, as well as on the de…

Probability · Mathematics 2013-08-20 Ivan Nourdin , Giovanni Peccati , Yvik Swan

Computing partition function is the most important statistical inference task arising in applications of Graphical Models (GM). Since it is computationally intractable, approximate methods have been used to resolve the issue in practice,…

Machine Learning · Statistics 2017-09-13 Sungsoo Ahn , Michael Chertkov , Jinwoo Shin

We consider the Hanany-Witten type brane configuration in a background of RR 4-form field strength and examine the behavior of Euclidean D0-branes propagating between two NS5-branes. We evaluate the partition function of the D0-branes and…

High Energy Physics - Theory · Physics 2011-04-14 So Matsuura

Fix a Calabi-Yau 3-fold $X$ satisfying the Bogomolov-Gieseker conjecture of Bayer-Macr\`i-Toda, such as the quintic 3-fold. By two different wall-crossing arguments we prove two different explicit formulae relating rank 0 Donaldson-Thomas…

Algebraic Geometry · Mathematics 2022-03-22 Soheyla Feyzbakhsh

We prove a conjecture of Haglund which can be seen as an extension of the equidistribution of the inversion number and the major index over permutations to ordered set partitions. Haglund's conjecture implicitly defines two statistics on…

Combinatorics · Mathematics 2014-09-04 Jeffrey B. Remmel , Andrew Timothy Wilson

In this document, we aim to gather various results related to a compositional/categorical approach to rigorous Statistical Mechanics. Rigorous Statistical Mechanics is centered on the mathematical study of statistical systems. Central…

Mathematical Physics · Physics 2024-03-26 Grégoire Sergeant-Perthuis

We compute the Coulomb branch partition function of the 4d $\mathcal{N}=2$ vector multiplet on closed simply-connected quasi-toric manifolds $B$. This includes a large class of theories, localising to either instantons or anti-instantons at…

High Energy Physics - Theory · Physics 2025-06-10 Jim Lundin , Roman Mauch , Lorenzo Ruggeri

We study the statistical mechanics and the dynamical relaxation process of modulationally unstable one-dimensional quantum droplets described by a modified Gross-Pitaevskii equation. To determine the classical partition function thereof, we…

Quantum Gases · Physics 2021-09-22 T. Mithun , S. I. Mistakidis , P. Schmelcher , P. G. Kevrekidis

Probabilistic graphical models have emerged as a powerful modeling tool for several real-world scenarios where one needs to reason under uncertainty. A graphical model's partition function is a central quantity of interest, and its…

Artificial Intelligence · Computer Science 2021-05-25 Durgesh Agrawal , Yash Pote , Kuldeep S Meel

We show that the partition functions which enumerate Donaldson-Thomas invariants of local toric Calabi-Yau threefolds without compact divisors can be expressed in terms of specializations of the Schur measure. We also discuss the relevance…

High Energy Physics - Theory · Physics 2012-09-14 Richard J. Szabo , Miguel Tierz

Plane partitions naturally appear in many problems of statistical physics and quantum field theory, for instance, in the theory of faceted crystals and of topological strings on Calabi-Yau threefolds. In this paper a connection is made…

Statistical Mechanics · Physics 2009-11-11 N. M. Bogoliubov

Max-stable processes are a popular tool for the study of environmental extremes, and the extremal skew-$t$ process is a general model that allows for a flexible extremal dependence structure. For inference on max-stable processes with…

Methodology · Statistics 2020-04-21 B. Beranger , A. G. Stephenson , S. A. Sisson

We consider MAP estimators for structured prediction with exponential family models. In particular, we concentrate on the case that efficient algorithms for uniform sampling from the output space exist. We show that under this assumption…

Machine Learning · Computer Science 2012-05-14 Shankar Vembu , Thomas Gartner , Mario Boley

Max-stable processes provide natural models for the modelling of spatial extreme values observed at a set of spatial sites. Full likelihood inference for max-stable data is, however, complicated by the form of the likelihood function as it…

Methodology · Statistics 2022-12-15 Patrik Andersson , Alexander Engberg
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