activity
19992023
most citedFree-energy distribution of the directed polymer at high temperature

330 citations · 4.7k across the 114 of their papers we have counts for

collaborators

115 papers

cond-mat.soft2023

Transition from viscous fingers to foam during drainage in heterogeneous porous media

Federico Lanza, Santanu Sinha, Alex Hansen +2

We investigate the behavior of drainage displacements in heterogeneous porous media finding a transition from viscous fingering to foam-like region. A pore network model incorporat…

cond-mat.dis-nn2023★ 4 cited

Localization induced by spatially uncorrelated subohmic baths in one dimension

Saptarshi Majumdar, Laura Foini, Thierry Giamarchi +1

We study an incommensurate XXZ spin chain coupled to a collection of local harmonic baths. At zero temperature, by varying the strength of the coupling to the bath the chain underg…

cond-mat.stat-mech2023★ 15 cited

Generalized disorder averages and current fluctuations in run and tumble particles

Stephy Jose, Alberto Rosso, Kabir Ramola

We present exact results for the fluctuations in the number of particles crossing the origin up to time in a collection of non-interacting run and tumble particles in one dimen…

cond-mat.stat-mech2023★ 11 cited

Local time of a system of Brownian particles on the line with steplike initial condition

Ivan N. Burenev, Satya N. Majumdar, Alberto Rosso

We consider a system of non-interacting Brownian particles on a line with a step-like initial condition, and we investigate the behavior of the local time at the origin at large ti…

cond-mat.dis-nn2023★ 2 cited

Depinning free of the elastic approximation

Alejandro B. Kolton, Ezequiel E. Ferrero, Alberto Rosso

We model the isotropic depinning transition of a domain-wall using a two dimensional Ginzburg-Landau scalar field instead of a directed elastic string in a random media. An exact a…

physics.geo-ph2023

Assessing the predicting power of GPS data for aftershocks forecasting

Vincenzo Maria Schimmenti, Giuseppe Petrillo, Alberto Rosso +1

We present a machine learning approach for the aftershock forecasting of Japanese earthquake catalogue from 2015 to 2019. Our method takes as sole input the ground surface deformat…