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The development of superresolution techniques, i.e., allowing for efficient resolution below the Rayleigh limit, became one of the important branches in contemporary optics and metrology. Recent findings show that perfect spatial mode…

Quantum Physics · Physics 2025-04-01 Konrad Schlichtholz

This paper is devoted to the study of couplings of the Lebesgue measure and the Poisson point process. We prove existence and uniqueness of an optimal coupling whenever the asymptotic mean transportation cost is finite. Moreover, we give…

Probability · Mathematics 2013-08-14 Martin Huesmann , Karl-Theodor Sturm

The maximum a posteriori (MAP) configuration of binary variable models with submodular graph-structured energy functions can be found efficiently and exactly by graph cuts. Max-product belief propagation (MP) has been shown to be suboptimal…

Machine Learning · Computer Science 2012-02-19 Daniel Tarlow , Inmar E. Givoni , Richard S. Zemel , Brendan J. Frey

The recent discovery of superconductivity under high pressure in the ladder compound BaFe$_2$S$_3$ has opened a new field of research in iron-based superconductors with focus on quasi one-dimensional geometries. In this publication, using…

Strongly Correlated Electrons · Physics 2017-08-09 N. D. Patel , A. Nocera , G. Alvarez , A. Moreo , E. Dagotto

Given a stochastic state process $(X_t)_t$ and a real-valued submartingale cost process $(S_t)_t$, we characterize optimal stopping times $\tau$ that minimize the expectation of $S_\tau$ while realizing given initial and target…

Probability · Mathematics 2020-12-24 Nassif Ghoussoub , Young-Heon Kim , Aaron Zeff Palmer

Two random processes X and Y on a metric space are said to be $\varepsilon$-shy coupled if there is positive probability of them staying at least a positive distance $\varepsilon$ apart from each other forever. Interest in the literature…

Probability · Mathematics 2013-03-18 Maury Bramson , Krzysztof Burdzy , Wilfrid Kendall

This paper is concerned with determining the shortest path for a pursuer aiming to intercept a moving target travelling at a constant speed. To address this challenge, we introduce an efficient mathematical model outlined as an optimal…

Optimization and Control · Mathematics 2025-01-28 M. Akter , M. M. Rizvi , M. Forkan

The reduction of couplings idea consists in the search for renormalization group invariant relations between seemingly independent parameters of a theory that hold to all orders of perturbation theory. This concept can be applied to $N=1$…

High Energy Physics - Phenomenology · Physics 2021-02-17 Gregory Patellis

We study lattice superconductors coupled to gauge fields, such as an attractive Hubbard model in electromagnetic fields, with a standard gauge fixing. We prove upper bounds for a two-point Cooper pair correlation at finite temperatures in…

Mathematical Physics · Physics 2018-05-23 Yasuhiro Tada , Tohru Koma

Classical (maximal) superintegrable systems in $n$ dimensions are Hamiltonian systems with $2n-1$ independent constants of the motion, globally defined, the maximum number possible. They are very special because they can be solved…

Mathematical Physics · Physics 2015-11-04 Yuxuan Chen , Ernie G. Kalnins , Qiushi Li , Willard Miller

Consider a multiperiod optimal transport problem where distributions $\mu_{0},\dots,\mu_{n}$ are prescribed and a transport corresponds to a scalar martingale $X$ with marginals $X_{t}\sim\mu_{t}$. We introduce particular couplings called…

Probability · Mathematics 2019-05-21 Marcel Nutz , Florian Stebegg , Xiaowei Tan

In this paper, we want to establish some general results in the Lorentzian optimal transport theory that have well-known Riemannian counterparts. As a first result, we will provide non-trivial assumptions on the measures to ensure strong…

Optimization and Control · Mathematics 2026-01-15 Alec Metsch

The martingale part in the semimartingale decomposition of a Brownian motion with respect to an enlargement of its filtration, is an anticipative mapping of the given Brownian motion. In analogy to optimal transport theory, we define causal…

Probability · Mathematics 2017-12-13 Beatrice Acciaio , Julio Backhoff Veraguas , Anastasiia Zalashko

In this work, we develop a collection of novel methods for the entropic-regularised optimal transport problem, which are inspired by existing mirror descent interpretations of the Sinkhorn algorithm used for solving this problem. These are…

Optimization and Control · Mathematics 2025-07-17 Vishwak Srinivasan , Qijia Jiang

We consider (stochastic) subgradient methods for strongly convex but potentially nonsmooth non-Lipschitz optimization. We provide new equivalent dual descriptions (in the style of dual averaging) for the classic subgradient method, the…

Optimization and Control · Mathematics 2024-12-31 Benjamin Grimmer , Danlin Li

In this paper, we study the stability of the shadow, a projection of a measure onto the set of couplings with respect to the Wasserstein distance. The shadow was introduced by \citet{Eckstein_Nutz_2022} to analyze the stability of the…

Statistics Theory · Mathematics 2026-04-21 Jakwang Kim

Compactness is one of the most versatile tools in the analysis of nonlinear PDEs and systems. Usually, compactness is established by means of some embedding theorem between functional spaces. Such theorems, in turn, rely on appropriate…

Analysis of PDEs · Mathematics 2017-06-30 Anna Zhigun

In this paper, we study linearly constrained policy optimization over the manifold of Schur stabilizing controllers, equipped with a Riemannian metric that emerges naturally in the context of optimal control problems. We provide extrinsic…

Optimization and Control · Mathematics 2023-10-27 Shahriar Talebi , Mehran Mesbahi

We construct a three dimensional deconfinement method which enables us to find new three-dimensional dualities and we apply various techniques developed in four dimensional supersymmetric gauge theories, such as the product gauge groups and…

High Energy Physics - Theory · Physics 2016-09-21 Keita Nii

This paper introduces a coordinate descent version of the V\~u-Condat algorithm. By coordinate descent, we mean that only a subset of the coordinates of the primal and dual iterates is updated at each iteration, the other coordinates being…

Optimization and Control · Mathematics 2019-01-17 Olivier Fercoq , Pascal Bianchi