collaborators

7 papers

math.FA2026

Norm of infinite doubly stochastic matrices

Ludovick Bouthat, Javad Mashreghi, Raphaël Vo

In finite dimensions, every doubly stochastic matrix has the -operator norm equal to for all . However, in the infinite-dimensional setting, this pr…

math.PR2026

On the convergence of doubly stochastic Markov chains

Ludovick Bouthat, Nicolas Doyon, Javad Mashreghi +1

We characterize the asymptotic behavior of time-homogeneous doubly stochastic Markov chains. Our investigation revolves around understanding the dynamics of products of doubly stoc…

math.CA2026

Weighted Hardy Inequalities for Nested Averages

Ludovick Bouthat, Pierre-Olivier Parisé

We study a family of Hardy-type inequalities for weighted averages over nested subsets of a measure space. Given a partition of a measure space and a weight function , we consid…

math.MG2026

Sharp Inequalities for Products of Principal Minors of Positive Definite Matrices

Tobias Boege, Ludovick Bouthat

We study sharp inequalities for ratios of products of principal minors of real positive definite matrices. Our main result gives a closed-form solution to a family of nonconvex opt…

math.NA2026

Convergence Analysis of the Random Bisection Method

Ludovick Bouthat, Philippe-André Luneau, Philippe Petitclerc

We propose a generalized version of the bisection method where the cutting point between the two subintervals is chosen at random following an arbitrary distribution. We compute ex…

math.CO2026

A general framework for inequalities on simple graphs

Ludovick Bouthat, Ángel Chávez, Sam Sheng

A general framework is developed for deriving sharp inequalities on simple graphs from majorization and Schur-convexity. After establishing majorization relations between the spect…