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20172026
most citedQuantitative Boltzmann Gibbs principles via orthogonal polynomial duality

11 citations · 11 across the 4 of their papers we have counts for

collaborators

6 papers

q-fin.MF2026

Consumption-investment under alternative stochastic-integral conventions

Mario Ayala, Benjamin Vallejo Jiménez

We study the Merton consumption-investment problem when risky asset dynamics are written under stochastic-integral conventions indexed by , interpolating between the Itô ()…

math.AP2024

Group Dispersal Modelling Revisited

Mario Ayala, Jérôme Coville, Samuel Soubeyrand

In this paper we revisit the notion of grouped dispersal that have been introduced by Soubeyrand and co-authors \cite{soubeyrand2011patchy} to model the simultaneous (and hence dep…

math.PR2022

A measure-valued stochastic model for vector-borne viruses

Mario Ayala, Jerome Coville, Raphael Forien

In this work we propose a measure-valued stochastic process representing the dynamics of a virus population, structured by phenotypic traits and geographical space, and where virus…

math.PR2020

Higher order fluctuation fields and orthogonal duality polynomials

Mario Ayala, Gioia Carinci, Frank Redig

Inspired by the works in [1] and [8] we introduce what we call -th-order fluctuation fields and study their scaling limits. This construction is done in the context of particle…

math.PR2019

Condensation of SIP particles and sticky Brownian motion

Mario Ayala, Gioia Carinci, Frank Redig

We study the symmetric inclusion process (SIP) in the condensation regime. We obtain an explicit scaling for the variance of the density field in this regime, when initially starte…

math.PR2017★ 11 cited

Quantitative Boltzmann Gibbs principles via orthogonal polynomial duality

Mario Ayala, Gioia Carinci, Frank Redig

We study fluctuation fields of orthogonal polynomials in the context of particle systems with duality. We thereby obtain a systematic orthogonal decomposition of the fluctuation fi…