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We present a multidimensional extension of Kellerer's theorem on the existence of mimicking Markov martingales for peacocks, a term derived from the French for stochastic processes increasing in convex order. For a continuous-time peacock…

Probability · Mathematics 2025-06-03 Gudmund Pammer , Benjamin A. Robinson , Walter Schachermayer

Let $\mu$ = ($\mu$t)t$\in$R be any 1-parameter family of probability measures on R. Its quantile process (Gt)t$\in$R : ]0, 1[ $\rightarrow$ RR, given by Gt($\alpha$) = inf{x $\in$ R : $\mu$t(]--$\infty$, x]) > $\alpha$}, is not Markov in…

Probability · Mathematics 2018-04-30 Charles Boubel , Nicolas Juillet

A classical result of Strassen asserts that given probabilities $\mu, \nu$ on the real line which are in convex order, there exists a \emph{martingale coupling} with these marginals, i.e.\ a random vector $(X_1,X_2)$ such that $X_1\sim \mu,…

Probability · Mathematics 2016-09-13 Mathias Beiglboeck , Nicolas Juillet

Strassen's classical martingale coupling theorem states that two real-valued random variables are ordered in the convex (resp.\ increasing convex) stochastic order if and only if they admit a martingale (resp.\ submartingale) coupling. By…

Probability · Mathematics 2017-05-11 Lasse Leskelä , Matti Vihola

We develop a probabilistic approach to the celebrated Jacobian conjecture, which states that any Keller map (i.e. any polynomial mapping $F\colon \mathbb{C}^n \to \mathbb{C}^n$ whose Jacobian determinant is a nonzero constant) has a…

Combinatorics · Mathematics 2026-01-26 Elia Bisi , Piotr Dyszewski , Nina Gantert , Samuel G. G. Johnston , Joscha Prochno , Dominik Schmid

In this paper, we exhibit a new family of martingale couplings between two one-dimensional probability measures $\mu$ and $\nu$ in the convex order. This family is parametrised by two dimensional probability measures on the unit square with…

Probability · Mathematics 2019-03-08 Benjamin Jourdain , William Margheriti

We consider the problem of finding a real valued martingale fitting specified marginal distributions. For this to be possible, the marginals must be increasing in the convex order and have constant mean. We show that, under the extra…

Probability · Mathematics 2008-08-19 George Lowther

We show that the sequential closure of a family of probability measures on the canonical space of c{\`a}dl{\`a}g paths satisfying Stricker's uniform tightness condition is a weak${}^*$ compact set of semimartingale measures in the pairing…

Probability · Mathematics 2020-04-21 Matti Kiiski

Given a family $(\mu_\lambda,\lambda\geq0)$ of integrable mean-zero probability measures such that, for every $\lambda\geq0$, $\mu_\lambda$ is the image of $\mu_1$ under the homothety $y\longmapsto\sqrt{\lambda}y$, we provide a necessary…

Probability · Mathematics 2019-06-20 Antoine-Marie Bogso , Mbehou Mohamed

We prove a generalization of the Shapiro-Shapiro conjecture on Wronskians of polynomials, allowing the Wronskian to have complex conjugate roots. We decompose the real Schubert cell according to the number of real roots of the Wronski map,…

Algebraic Geometry · Mathematics 2021-07-12 Jake Levinson , Kevin Purbhoo

One tuple of probability vectors is more informative than another tuple when there exists a single stochastic matrix transforming the probability vectors of the first tuple into the probability vectors of the other. This is called matrix…

Statistics Theory · Mathematics 2024-04-26 Muhammad Usman Farooq , Tobias Fritz , Erkka Haapasalo , Marco Tomamichel

We develop a new approach to prove multiplier theorems in various geometric settings. The main idea is to use martingale transforms and a Gundy-Varopoulos representation for multipliers defined via a suitable extension procedure. Along the…

Probability · Mathematics 2021-07-13 Rodrigo Bañuelos , Fabrice Baudoin , Li Chen , Yannick Sire

It was shown by the authors that two one-dimensional probability measures in the convex order admit a martingale coupling with respect to which the integral of $\vert x-y\vert$ is smaller than twice their $\mathcal W_1$-distance…

Probability · Mathematics 2021-05-06 Benjamin Jourdain , William Margheriti

We are interested in the local limits of families of random trees that satisfy the Markov branching property, which is fulfilled by a wide range of models. Loosely, this property entails that given the sizes of the sub-trees above the root,…

Probability · Mathematics 2016-08-26 Camille Pagnard

Let $s(n)$ denote the number of ones in the binary expansion of a natural number $n\in\mathbb{N}$. For any $t\in\mathbb{N}$ and $d\in\mathbb{Z}$, let $\mu_t(d)$ denote the asymptotic density of the set of those natural numbers $n$ for which…

Probability · Mathematics 2026-05-22 Dawid Tarłowski

We make two observations regarding the invertibility of Keller maps. i.e., polynomial maps for which the determinant of their Jacobian matrix is identically equal to 1. In our first result, we show that if P is a n-dimensional Keller map,…

Algebraic Geometry · Mathematics 2007-05-23 Richard J. Lipton , Evangelos Markakis

Two proofs of the Koml\'os-Major-Tusn\'ady embedding theorems, one for the uniform empirical process and one for the simple symmetric random walk, are given. More precisely, what are proved are the univariate coupling results needed in the…

Probability · Mathematics 2020-08-10 Manjunath Krishnapur

We consider a tuple $\Phi = (\phi_1,\ldots,\phi_m)$ of commuting maps on a finitary matroid $X$. We show that if $\Phi$ satisfies certain conditions, then for any finite set $A\subseteq X$, the rank of $\{\phi_1^{r_1}\cdots\phi_m^{r_m}(a):a…

Combinatorics · Mathematics 2025-02-06 Antongiulio Fornasiero , Elliot Kaplan

Consider a compact metric space $S$ and a pair $(j,k)$ with $k \ge 2$ and $1 \le j \le k$. For any probability distribution $\theta \in P(S)$, define a Markov chain on $S$ by: from state $s$, take $k$ i.i.d. ($\theta$) samples, and jump to…

Probability · Mathematics 2024-03-28 David J. Aldous , Madelyn Cruz , Shi Feng

Multimarginal optimal transport (MOT) has gained increasing attention in recent years, notably due to its relevance in machine learning and statistics, where one seeks to jointly compare and align multiple probability distributions. This…

Optimization and Control · Mathematics 2026-01-27 Yehya Cheryala , Mokhtar Z. Alaya , Salim Bouzebda
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