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Journal club dei sistemi Complessi

Ciclo di seminari si propone di presentare agli studenti della Magistrale in Fisica alcuni temi 
rilevanti nell'ambito dei sistemi complessi. 

Questo ciclo di seminari si propone di presentare agli studenti della Magistrale in Fisica alcuni temi rilevanti nell'ambito dei sistemi complessi. A questi incontri sono dedicate due ore, vi sara' quindi ampio spazio per contestualizzare gli argomenti, per fare domande e discutere con l'oratore. Per ulteriori informazioni o proposte di seminario contattare: Giuseppe Luca Celardo, giuseppeluca.celardo@unifi.it
ANNULLATO
Martedi' 19 Novembre alle ore 15:00 in Aula Magna del Dipartimento di Fisica e Astronomia. 
Author:Stefano
 Ruffo
ISC-CNR and SISSA

Title: Ensemble inequivalence in quantum  mechanics
Abstract
Ensemble inequivalence, i.e., the possibility of observing different thermodynamic properties depending on the statistical ensemble, is one of the hallmarks of long-range physics, which has been demonstrated in numerous classical systems. I will present an example of ensemble inequivalence for a long-range quantum ferromagnet. While the zero temperature microcanonical quantum phase-diagram coincides with that of the canonical ensemble, the phase diagrams of the two ensembles are different at finite temperature. This is in contrast with the common lore of statistical mechanics of systems with short-range interactions where thermodynamic properties are bound to coincide for macroscopic systems described by different ensembles. I will also
take the opportunity of this talk to highlight the Journal of Statistical Mechanics: Theory and Experiment who is 20 year old this year.

N. Defenu, D. Mukamel and S. Ruffo, Phys. Rev. Lett., 133, 050403 (2024).
SEMINARIO 1: 
Giovedi' 23 Maggio alle 16:30: Torcini Aula 281 prenotata 16:15--17:30
Alessandro Torcini
CY Cergy Paris University, Cergy-Pontoise (France)
ISC-CNR, Sesto Fiorentino (Italy)
Title :  A robust balancing mechanism for spiking neural networks

Abstract :

Neurons in the brain cortex fire irregularly and with a low firing
rate despite being subject to a
continuous stimulation (bombardment) from thousands of connected
neurons. This seemingly counter-intuitive
evolution has been explained in terms of the theory of dynamical
balance of excitation and inhibition [1] considered
as one of the major contributions of theoretical physics to
neuroscience. However, this theory has been recently criticized,
because it requires unphysically large external currents,
experimentally unjustified. We propose a balancing
mechanism based on a biologically plausible form of synaptic
plasticity, which works also with weak external currents.
Biologically, the mechanism exploits the plasticity of
excitatory–excitatory synapses induced by short-term
depression [2]. Mathematically, the nonlinear response of the synaptic
activity is the key ingredient responsible
for the emergence of a stable balanced regime. Our claim is supported
by a simple self-consistent analysis accompanied
by extensive simulations performed for increasing network sizes. The
dynamical regime is characterized by highly irregular
spiking dynamics of all neurons as usually observed in the brain cortex [3].

[1] C. van Vreeswijk and H. Sompolinsky, Science 274, 1724 (1996).

[2] M. V. Tsodyks and H. Markram, Proceedings of the national academy
of sciences 94, 719 (1997).

[3] A. Politi and A. Torcini, Chaos 34, 041102 (2024).
   
SEMINARIO 2: 
Mercoledì 29 Maggio: 3:30pm-4:30pm, AULA QUERZOLI, LENS

Hsing-Ta (Theta) Chen, Ph.D. (he/him)
Assistant Professor
Department of Chemistry and Biochemistry
University of Notre Dame

Title:
Collective optical effects and local electron dynamics: Superradiance, Rabi splitting, and Marcus ratesAbstract:Utilizing


strong light-matter interactions between quantum excitations and confined electromagnetic fields opens up new possibilities to impact chemical reactivity and charge transport. As electronic or vibrational excitations of a molecular ensemble are strongly coupled with photonic modes (for example near a plasmonic nanoparticle or in a microcavity), collective excitations among molecules lead to intriguing phenomena that are fundamentally distinct from conventional photoexcitation. Despite recent developments, understanding collective excitations remains challenging from theory and simulation perspectives. In this talk, I will present our recent efforts in modeling superradiance and cavity effects in a disordered system and our future endeavors to develop a theoretical toolbox for simulating collective excitation in materials.
SEMINARIO 3:
Giovedì 30 Maggio 
Relatore:Dr
Michele Monti
IIT Genova

Data: 30/05/2024
Ora: 16:30, AULA 281


Titolo
Role of noise in biochemical networks

Abstract
In this lecture, I will provide an overview of the stochastic
processes that influence the behavior of biochemical networks, with a special focus on the role of noise. I will also discuss biological
examples that illustrate how biochemical networks can control noise
through specific structures, and explore the importance of noise in
enabling cells to compute time.
Il seminario sara' trasmesso anche online al seguente link:  
Venerdì 14 Giugno: 14:30 - 16:30, AULA 281, Dipartimento di Fisica e Astronomia

Andrea Orlandi

 

Consorzio LaMMA
  Laboratorio di Monitoraggio e Modellistica Ambientale
  per lo Sviluppo Sostenibile
  Environmental Modelling and Monitoring Laboratory
  for Sustainable Development

 

 

 

 

 Titolo: 

Introduzione alla modellistica per la previsione meteo 

 

Caratterizzazione degli obiettivi: 

Seminario di complemento al corso di Fisica dell’Atmosfera. Aperto alla fruizione anche da parte di studenti di altri corsi e ricercatori del Dipartimento. 

 

Abstract: 

Brevi cenni introduttivi sulla dinamica dell’atmosfera planetaria e sull’evoluzione storica dei vari approcci sviluppati per la sua comprensione, descrizione e previsione numerica. Sintesi schematica delle moderne tecniche di previsione numerica delle condizioni meteorologiche (Numerical Weather Prediction, NWP) e climatiche, con riferimenti alla predicibilità ed alle tecniche di Ensemble Prediction. 

 

 

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