LPTMC Seminars

Guy Bunin (Technion Haïfa)
27.05.2024 10:45  11:45SéminairesManyspecies dynamics in space
Natural ecosystems often harbor individuals of many species, spread out in space. We describe two very different dynamical behaviors (‘phases’) that can be found in such systems, depending on the interactions between the species. In one phase, population sizes undergone huge fluctuations, spanning many orders of magnitude, that persist indefinitely in time. In the other phase, every location in space assumes one of many stable states, where each state is characterized by the combination of species present in that location. These different states may then expand in space, resulting in a selfreplication mechanism that competes over space. This leads to selection over ecosystem states, in analogy with Darwinian selection.

Weitao Chen (National University of Singapore)
16.05.2024 14:00  15:00SéminairesMultifractality and dynamics at the Anderson transition: From finite dimension to infinite dimension
Multifractality is an exotic property that emerges at the Anderson transition. Meanwhile, the dynamics are highly influenced by the multifractality of the eigenstates. This presentation will focus on the emergence of multifractality and its dynamic signatures in randommatrix ensembles amenable to analytical treatment. Firstly, I will revisit randommatrix ensembles that capture multifractal properties in finite dimensions, emphasizing the scaleinvariant properties of dynamics as a consequence of multifractality. Secondly, I will introduce new randommatrix ensembles featuring critical properties in infinite dimension, the upper critical dimension of the Anderson transition. Through analytical arguments, these models reveal two scenarios of critical properties: logarithmic multifractality and critical localization. These results will help to clarify some elusive problems of Anderson transitions in random graphs.
References: Physical Review E 108(5) , 054127 (2023); arXiv:2312.17481 (2023).

Denis Ullmo (LPTMS)
13.05.2024 10:45  11:45SéminairesPedestrians in static crowds are not grains, but game players.
The shortterm (‘operational’) dynamics of pedestrian crowds are generally thought to involve no anticipation, except perhaps the avoidance of the most imminent
collisions. I will show that current models rooted in this belief fail to reproduce essential features observed experimentally by Nicolas et al. [Sci. Rep. 9, 105 (2019).] when a static crowd is crossed by an intruder.The missing ingredient can be identified as the pedestrians’ ability to plan ahead far enough beyond the next interaction. On this basis, I will introduce a minimal model based on meanfield game theory which proves remarkably successful in capturing the experimental observations associated with this setting, but also other dailylife situations such as partial metro boarding. These findings are clear evidence that a long term game theoretical approach is key to capturing essential elements of the dynamics of crowds.
[refs : Phys. Rev. E 107, 024612 (2023), SciPost Phys. 16, 104 (2024)]