Plenary Colloquia SIFS

La SIFS organizza dei Plenary Colloquia online su temi vari connessi alla Fisica Statistica, come attività culturale e momento di condivisione per tutti i soci.

I seminari sono poi resi disponibili online tramite il canale Youtube ufficiale della SIFS, per chi fosse interessato e non riuscisse a seguirli in diretta.

I colloquia sono tenuti online sulla piattaforma Microsoft Teams.

Istruzioni per partecipare ai Colloquia

  • prima dell'orario stabilito per il colloquium verrà pubblicato nella Home del sito web della SIFS e su questa pagina, il link per poter accedere al meeting su Teams;

  • chiunque può accedere al meeting semplicemente cliccando sul link, anche in assenza di un account Teams o Microsoft. Consigliamo fortemente l'uso di Google Chrome che è completamente supportato da Teams, mentre altri browsers potrebbero dare problemi;

  • una volta cliccato sul link è sufficiente seguire le indicazioni, inserendo un nome per essere individuabili nella riunione. Vi chiediamo di accedere alla riunione spegnendo videocamera e microfono prima di entrare o immediatamente, in modo da alleggerire la piattaforma;

  • il colloquium verrà registrato, per essere reso accessibile successivamente tramite il canale Youtube SIFS: partecipando alla riunione date il consenso per la registrazione;

  • il colloquium durerà circa 1 ora, divisa in circa 50 minuti di seminario e 10 minuti di domande. Le domande possono essere formulate tramite la chat della riunione e verranno poste allo speaker solo al termine della presentazione.

A perspective view on fully developed turbulence

Roberto Benzi, Università Roma "Tor Vergata"

Abstract: In this talk I discuss some basic physical properties of three dimensional fully developed turbulence. In particular, I will focus on the case of homogeneous and isotropic turbulence (H.I.T). This is a relatively narrow view of turbulence when compared to the enormous number of problems where turbulence plays a significant role. In fact, there exist many different turbulent "problems". Nevertheless, in the case of H.I.T there has been a remarkable scientific effort over the last few decades which, probably for the first time, provided a well defined theoretical framework with a significant agreement against laboratory and/or numerical data. The aim of this talk is to review this effort and to illustrate our present knowledge on the problem.

Date: May 22, 2020 - 16.30

The thermodynamic uncertainty relation

Udo Seifert, Institute for Theoretical Physics, University of Stuttgart

Abstract: The thermodynamic uncertainty relation discovered in 2015 is arguably one of the most promising insights arising from stochastic thermodynamics. It relates the mean and fluctuations of any current to the overall entropy production in a non-equilibrium steady state. It provides a lower bound on the inevitable cost of temporal precision of processes, leading, e.g. to the minimal cost for measuring time in a finite temperature environment. As a tool for thermodynamic inference, it gives a model-free universal upper bound on the efficiency of molecular motors in terms of experimentally accessible observables. Current challenges to the theory include the still missing proof for underdamped dynamics and extensions to periodically and time-dependently driven systems.

Date: June 25, 2020 - 16.30

Simplicial complexes and dynamics

Ginestra Bianconi, School of Mathematical Sciences, Queen Mary University of London

Abstract: Networks are everywhere and they describe a large variety of complex systems such as social networks and the brain. In the last few decades, unveiling the underlying architecture of complex systems using the network approach has been key to reveal how the statistical properties of network structure affect dynamics, including most notably epidemic spreading and network robustness. Recently is has been realized that many complex systems such as brain networks and social networks include interactions among two or more nodes. These complex systems cannot be captured by networks including exclusively pairwise interactions, rather these systems should be represented by higher-order networks such as simplicial complexes.

In this talk I will show that taking into account higher-order interactions and combining network theory with topology can greatly enhance the ability to predict the function of complex systems starting from their structure.

I will overview recent results on the interplay between network topology and dynamics focusing on percolation and on synchronization phenomena.

A new topological approach [1] to synchronization on simplicial complexes will be presented. Here the theory of synchronization is combined with topology (specifically Hodge theory) for formulating the higher-order Kuramoto model that uses the higher-order Laplacians and provides the main synchronization route for topological signals. I will show that the dynamics defined on links can be projected to a dynamics defined on nodes and triangles that undergo a synchronization transition.

This model can be applied to study synchronization of topological signals in the brain and in biological transport networks as it proposes a new set of topological transformations that can reveal collective synchronization phenomena that could go unnoticed otherwise.

[1] Millán AP, Torres JJ, Bianconi G. Explosive higher-order Kuramoto dynamics on simplicial complexes. Physical Review Letters. 2020 May 27;124(21):218301

Date: July 16, 2020 - 16.30

High-dimensional cost landscape and gradient descent in Tensor PCA and its generalisations

Chiara Cammarota, King's College London

Abstract: Tensor PCA is a prototypical, particularly hard, high-dimensional estimation problem. In this talk I will discuss how it can be used to reveal, by means of statistical mechanics approaches, the details of the intimate connection between the geometry of the high dimensional cost landscape and the performances of gradient descent based algorithms. I will also show how the added knowledge about the cost landscape allows to devise both specific and potentially general strategies to substantially increase the performances of gradient descent based algorithms.

Date: fall 2020 (confirmation will be given upon later verification of the boundary conditions imposed by the pandemia)

Statistical Mechanics and Large-Deviation Methods: Highlights and News

Satya Majumdar, Laboratoire de Physique Theorique et Modeles Statistique (LPTMS), Université de Paris-Sud (Orsay)

Abstract: TBA

Date: fall 2020 (confirmation will be given upon later verification of the boundary conditions imposed by the pandemia)


Leticia F. Cugliandolo, Sorbonne Université, Laboratoire de Physique Théorique et Hautes Energies

Abstract: TBA

Date: September 2020


David Mukamel, Weizmann Institute of Science

Abstract: TBA

Date: TBA


Giulio Biroli, Ecole Normale Supérieure

Abstract: TBA

Date: TBA