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We study Poisson's equation in the context of general state space Markov chains. For chains satisfying a contraction assumption w.r.t. a Wasserstein distance, we show that a solution exists for Lipschitz functions and investigate its…

Probability · Mathematics 2026-02-24 Julian Hofstadler

What can one say on convergence to stationarity of a finite state Markov chain that behaves "locally" like a nearest neighbor random walk on ${\mathbb Z}$ ? The model we consider is a version of nearest neighbor lazy random walk on the…

Probability · Mathematics 2014-10-31 Iddo Ben-Ari , Hugo Panzo , Elizabeth Tripp

We develop a new probabilistic method for deriving deviation estimates in directed planar polymer and percolation models. The key estimates are for exit points of geodesics as they cross transversal down-right boundaries. These bounds are…

Probability · Mathematics 2023-08-30 Elnur Emrah , Christopher Janjigian , Timo Seppäläinen

We study the quadratically regularized optimal transport (QOT) problem for quadratic cost and compactly supported marginals $\mu$ and $\nu$. It has been empirically observed that the optimal coupling $\pi_\epsilon$ for the QOT problem has…

Optimization and Control · Mathematics 2024-10-07 Johannes Wiesel , Xingyu Xu

We exactly rewrite the Z(2) lattice gauge theory with standard plaquette action as a random surface model equivalent to the untruncated set of its strong coupling graphs. By extending the worm approach applied to spin models we simulate…

High Energy Physics - Lattice · Physics 2015-06-12 Tomasz Korzec , Ulli Wolff

We consider the approximation of a convolution of possibly different probability measures by (compound) Poisson distributions and also by related signed measures of higher order. We present new total variation bounds having a better…

Probability · Mathematics 2017-03-08 Bero Roos

We introduce new coupling conditions for isentropic flow on networks based on an artificial density at the junction. The new coupling conditions can be derived from a kinetic model by imposing a condition on energy dissipation. Existence…

Analysis of PDEs · Mathematics 2020-06-17 Yannick Holle , Michael Herty , Michael Westdickenberg

We study incremental stability and convergence of switched (bimodal) Filippov systems via contraction analysis. In particular, by using results on regularization of switched dynamical systems, we derive sufficient conditions for convergence…

Systems and Control · Computer Science 2020-03-18 Mario di Bernardo , Davide Fiore , S. John Hogan

We present a general duality result for Wasserstein distributionally robust optimization that holds for any Kantorovich transport cost, measurable loss function, and nominal probability distribution. Assuming an interchangeability principle…

Optimization and Control · Mathematics 2024-11-26 Luhao Zhang , Jincheng Yang , Rui Gao

Recent studies on stability and contractivity have highlighted the importance of semi-inner products, which we refer to as pairings, associated with general norms. A pairing is a binary operation that relates the derivative of a curve's…

Optimization and Control · Mathematics 2026-04-03 Anton V. Proskurnikov , Francesco Bullo

In this article we show how ideas, methods and results from optimal transportation can be used to study various aspects of the stationary measuresof Iterated Function Systems equipped with a probability distribution. We recover a classical…

Classical Analysis and ODEs · Mathematics 2021-06-02 Benoît Kloeckner

Doeblin coefficients are a classical tool for analyzing the ergodicity and exponential convergence rates of Markov chains. Propelled by recent works on contraction coefficients of strong data processing inequalities, we investigate whether…

Information Theory · Computer Science 2024-07-03 Anuran Makur , Japneet Singh

We present a new formulation based on the classical Dirichlet-Neumann formulation for interface coupling problems in linearized elasticity. By using Taylor series expansions, we derive a new set of interface conditions that allow our…

Numerical Analysis · Mathematics 2017-10-06 Pavel Bochev , James Cheung , Max Gunzburger , Mauro Perego

We study and extend the duality web unifying different decoupling limits of type II superstring theories and M-theory. We systematically build connections to different corners, such as Matrix theories, nonrelativistic string and M-theory,…

High Energy Physics - Theory · Physics 2024-10-18 Chris D. A. Blair , Johannes Lahnsteiner , Niels A. Obers , Ziqi Yan

A long-standing expectation is that two repulsively coupled oscillators tend to oscillate in opposite directions. It has been difficult to achieve complete synchrony in coupled identical oscillators with purely repulsive coupling. Here, we…

Chaotic Dynamics · Physics 2023-01-18 Simin Mirzaei , Md Sayeed Anwar , Fatemeh Parastesh , Sajad Jafari , Dibakar Ghosh

Mixtures of high dimensional Gaussian distributions have been studied extensively in statistics and learning theory. While the total variation distance appears naturally in the sample complexity of distribution learning, it is analytically…

Probability · Mathematics 2022-03-11 Sami Davies , Arya Mazumdar , Soumyabrata Pal , Cyrus Rashtchian

A cornerstone of geometric reconstruction, rotation averaging seeks the set of absolute rotations that optimally explains a set of measured relative orientations between them. In addition to being an integral part of bundle adjustment and…

Computer Vision and Pattern Recognition · Computer Science 2024-06-28 Gabriel Moreira , Manuel Marques , João Paulo Costeira

In this short note we provide a quantitative version of the classical Runge approximation property for second order elliptic operators. This relies on quantitative unique continuation results and duality arguments. We show that these…

Analysis of PDEs · Mathematics 2017-08-22 Angkana Rüland , Mikko Salo

In this paper, we prove a structure theorem for discrete optimal transportation plans. We show that, given any pair of discrete probability measures and a cost function, there exists an optimal transportation plan that can be expressed as…

Optimization and Control · Mathematics 2021-04-28 Gennaro Auricchio , Marco Veneroni

This monograph develops a comprehensive statistical learning framework that is robust to (distributional) perturbations in the data using Distributionally Robust Optimization (DRO) under the Wasserstein metric. Beginning with fundamental…

Machine Learning · Statistics 2021-08-23 Ruidi Chen , Ioannis Ch. Paschalidis