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 organizzati con cadenza mensile e 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
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.
Upcoming Colloquia
Past Colloquia
Scaling of brain activity and optimal functionality: from real to artificial neural networks
Abstract: In this work, I review recent advances in data-driven analyses of brain activity, which, when combined with theoretical approaches like renormalization-group techniques and others, provide insights into the dynamical regimes of neural activity across various brain regions. These findings serve as a foundation for designing efficient artificial neural networks with recurrent interactions. Our results demonstrate that both biological and artificial networks achieve optimal performance when tuned to operate near the edge of instability, where scale invariance naturally emerges.
Date: 21st november 2024 - 16.30 (Rome Time)
Complexity, Economics & Statistical Physics
Abstract: In a radically complex world, rational solutions are impossible to determine, not even to learn. One has to turn to satisficing solutions that are generically exponentially numerous. Every agent (even rational) will choose a different one, thereby creating de facto (if not de jure) heterogeneities. Simple models of a complex world necessarily generate a multiplicity of possible emergent properties, often (but not always) separated by “phase transitions”. We will review how all these ideas may come together and be disciplined by tools from statistical physics, in particular concerning disordered, high dimensional models. The overarching idea of phase diagrams and the distinction between stiff and sloppy directions may allow one to build a qualitative, scenario-based approach to macroeconomics, trading the whimsical pursuit of numerically precise predictions with the aim of being “roughly right”.
Date: 6th June 2024 - 15.00 (Italian time)
Recent progress in statistical mechanics for networks of real neurons
Abstract: Perceptions and actions, thoughts and memories result from the coordinated activity of hundreds or even thousands of neurons in the brain. It is an old dream of the physics community to provide a statistical mechanics description for these and other emergent phenomena of life. These theoretical aspirations appear in a new light because of recent developments in our ability to measure the electrical activity of the brain, now sampling thousands of individual neurons simultaneously over hours or days. We review the surprising progress that has been made in bringing theory and experiment together, focusing on maximum entropy methods and a phenomenological renormalization group. These approaches have uncovered new, quantitatively reproducible collective behaviors in networks of real neurons, and provide examples of rich parameter free predictions that agree in detail with experiment.
Date: 19th may 2023 - 12.00 (Rome Time)
Learning and memory in brain networks: Insights from Statistical Physics
Abstract: Memories are thought to be stored in brain networks thanks to modifications of synaptic connectivity. Mathematical models of synaptic plasticity (sometimes called `synaptic plasticity rules' or `learning rules') capture experimental data on plasticity with increasing accuracy, but it is still unclear how realistic synaptic plasticity rules shape network dynamics and information storage. In this talk, I will first review approaches for inferring learning rules from neurophysiological data. I will describe in particular a new approach that infers learning rules from in vivo
electrophysiological data, using experiments that compare the statistics of responses of neurons to sets of novel and familiar stimuli. I will then focus on how the inferred learning rules shape the dynamics of networks, leading to a diversity of attractors, depending on parameters (fixed point attractors, chaotic attractors, or transient sequential activity). Finally, I will show that learning rules inferred from data are close to maximizing information storage in a space of unsupervised learning rules.
Date: 4th May 2023 - 16.30 (Italian time)
Travelling waves and disordered systems
Abstract: The Fisher KPP equation describes the growth of a stable region into an unstable medium. It was introduced in 1937 both by the biologist and statistician Fisher and by the mathematicians Kolmogorov, Petrovsky, Piscounov to model the propagation of a favourable gene in a population. It is one of the classical examples of the problem of velocity selection. It also appears in many other contexts, ranging from the theory of disordered systems to reaction diffusion problems, branching Brownian motion and models of evolution with selection. After a short review, this talk will try to present several results, in particular those related to the theory of directed polymers and of spin glasses.
Date: 23rd March 2023 - 16.30 (Rome Time)
The quantum Mpemba effect
Abstract: The Mpemba effect is the counterintuitive and controversial phenomenon that hot water cools faster than cold one. Here I will introduce an analogous effect recently proposed and observed in extended quantum systems in which a symmetry is explicitly broken by the initial state, but it is restored by the time evolution. To study this phenomenon we introduce a new quantity, dubbed entanglement asymmetry, which is a measure of symmetry breaking inspired by the theory of entanglement in many-body states.
Date: 2nd March 2023 - 16.30 (Italian time)
Dynamics and statistics of swimming microorganisms in turbulence
Abstract: Phytoplankton live in the upper, photic layer of the ocean characterized by turbulent flows which mediate all the ecological processes. Many phytoplankton species are able to swim and this has an important impact of many crucial phenomena, including reproduction and feeding. In this talk I will review some recent results on the interactions between motility and turbulence and their effect on the dynamics and the statistics of the swimming cells.
Date: 23 November 2022 - 16.30 (Italian time)
Departure from equilibrium and signatures of irreversibility in flocking systems
Abstract: Biological groups such as insect swarms and bird flocks are considered as paradigmatic examples of `active' living matter, where self-propelled interacting individuals give rise to collective patterns over large scales. Activity, i.e. the ability of individuals to convert energy into motion, is a crucial feature of these systems. Experiments and theoretical analysis show that - combined with interactions - activity enhances ordering and gives rise to a novel class of dynamic critical behaviour. Activity is primarily related to energy injection and it drives the system out of equilibrium. In this talk, using simple models of collective motion, I will discuss how to quantify the departure from equilibrium in polar active systems, and how to connect it with the emergence of spontaneous order and collective response. I will finally show that signatures of irreversibility can be directly measured from the data and manifest as asymmetries in the two-body distribution.
Date: 26 May 2022 - 16.30 (Italian time)
The Paradigm of Jamming: from Low-Temperature Glasses to Machine Learning and more
Abstract: The jamming transition in packings of hard particles is of fundamental interest in the physics of granular materials and glasses. In recent years the physics of jamming has gained momentum in several interdisciplinary contexts, going from Machine Learning to Inference, Ecology and beyond. I will introduce the Simplest Model of Jamming and show how jammed points share peculiar critical properties, highly universal and deeply related glass physics. After discussing the implications of the vicinity to jamming in a glassy phase, I will consider the problem of Information Storage in Machine Learning. Going from the single neuron to multilayer networks, the capacity limit becomes a jamming point.
Date: 28 April 2022 - 16.30 (Italian time)
Stochastic resetting: how to avoid wandering off in the wrong direction
Abstract: In this talk I will review the idea of stochastic resetting: by returning some dynamical process to its initial condition one can significantly change the behaviour of the process and indeed improve the typical time to complete some complex task. The essence of the idea is that by resetting one cuts off errant trajectories.
I will discuss the simple example of a diffusive particle whose position is reset randomly in time with a constant rate r to some fixed point (e.g. its initial position). This simple system already exhibits the main features of interest induced by resetting:
(i) the system reaches a nontrivial nonequilibrium stationary state
(ii) the mean time for the particle to reach a target is rendered finite and has a minimum, optimal, value as a function of the resetting rate r.
I will discuss generalisations such as non-Markovian resetting, resetting with memory and applications to chemical reactions and search processes.
Evans MR and Majumdar SN Diffusion with stochastic resetting Phys.Rev.Lett. 106 160601 (2011)
Evans MR, Majumdar SN and Schehr G Stochastic resetting and applications J. Phys. A: Math. Theor 53 193001 (2020)
Date: 24 March 2022 - 16.30 (Italian time)
Chaotic destruction of Anderson localization
Abstract: Anderson localization is a universal concept applicable to quantum and classical linear disordered systems. Nonlinearity leads to chaotic dynamical regimes, which break localization. I discuss two basic setups: the spreading of an initially localized wavepacket in a disordered nonlinear medium, and the scattering of incident waves on a disordered nonlinear layer. The question of the asymptotic regime of the spreading is not fully resolved yet, and I discuss several approaches to unravel it. One is based on exploring scaling relations of chaos for disordered weakly nonlinear lattices (close to the KAM regime). Another line of action is to consider strongly nonlinear disordered lattices, where the spreading of a chaotic wavepacket can be at least partially explained with a nonlinear diffusion equation.
Date: 24 February 2022 - 16.30 (Italian time)
Biomimetic navigation of complex natural environments
Abstract: Living systems face the challenge of navigating natural environments shaped by non-trivial physical mechanisms. Notable examples are provided by long-distance orientation using airborne olfactory cues transported by turbulent flow, the tracking of surface-bound trails of odor cues, and flight in the lowest layers of the atmosphere. Terrestrial animals, insects, and birds have evolved navigation strategies that accomplish the above tasks with an efficiency that is often surprising and yet unmatched by human technology. Indeed, robotic applications for olfactory sniffers and unmanned aerial vehicles face similar challenges for the automated location of explosives, chemical, and toxic leaks, as well as the monitoring of biodiversity, surveillance, disaster relief, cargo transport, and agriculture. The interdisciplinary interplay between biology, physics, and robotics is key to jointly advancing fundamental understanding and technology. I shall review the above natural phenomena, then discuss the physics that constrains and shapes the navigation tasks, how machine-learning methods are brought to bear on those tasks, and conclude with the relevant strategies of behavior and open issues.
Date: 27 January 2022 - 16.30 (Italian time)
2021 Plenary Colloquia
Many body localization, between integrability and glassiness
Abstract: Many-Body Localization (MBL) is a peculiar form of ergodicity breaking and out-of-equilibrium dynamics which occurs in certain interacting quantum systems subject to quenched disorder. In the first part of this talk, I will briefly discuss the connection between localization, integrability and glassiness, in order to motivate the claim that Many-Body Localized systems are both integrable and glassy, albeit in their own special way. In the second part of the talk, I will discuss a toy model aimed at capturing the interplay between the quenched disorder and some slow, thermally induced fluctuations affecting the effective local disorder of the system. I will summarise the rich phenomenology brought about by these additional fluctuations, stressing in particular the connections to the unfreezing transition and configurational chaos in the simplest models of glassy systems.
Date: 23 December 2021 - 16.30 (Italian time)
Quantum bound to chaos and Fluctuation-Dissipation relation
Abstract: Chaos may be defined for quantum systems on the basis of an analogue of the Lyapunov exponent.
It turns out that the value of the Lyapunov exponent can take a maximal value $=2\pi \hbar /T$, the 'bound to chaos'.
It has now become clear that this bound may be derived from the quantum fluctuation-dissipation relation, the KMS relation, revealing it as a bona-fide thermodynamic concept.
Date: 25 November 2021 - 16.30 (Italian time)
When do economies converge to a static equilibrium, and when do they have endogenous dynamics?
J. Doyne Farmer, Institute for New Economic Thinking at the Oxford Martin School & Mathematical Institute at University of Oxford
Abstract: Equilibrium is one of the core concepts in economics. I will explain the difference between equilibrium in physics and equilibrium in economics, and discuss the question of when it is appropriate to assume that an economy will converge to equilibrium and when it is not. To get a more quantitative and systematic answer, I will present a body of work in game theory, where we exhaustively study normal form games and show that convergence to equilibrium becomes unlikely when games are complicated and competitive (this uses a nice statistical mechanics model). I will also present a toy model of the macroeconomy and a toy model of the financial system that have chaotic oscillations.
Date: September 23, 2021 - 16.00 (Italian time)
Microscopic theory of the fluctuating hydrodynamics in nonlinear lattices
Abstract: The theory of fluctuating hydrodynamics has been an important tool for analyzing macroscopic behavior in nonlinear lattices. However, despite its practical success, its microscopic derivation is still incomplete. In this work, we provide the microscopic derivation of fluctuating hydrodynamics, using the coarse-graining and projection technique; the equivalence of ensembles turns out to be critical. The Green-Kubo (GK) like formula for the bare transport coefficients is presented in a numerically computable form. Our numerical simulations show that the bare transport coefficients exist for a sufficiently large but finite coarse-graining length in the infinite lattice within the framework of the GK like formula. This demonstrates that the bare transport coefficients uniquely exist for each physical system.
Date: July 22, 2021 - 12.00 (Italian time)
The physics of cement cohesion
Emanuela Del Gado, Department of Physics, Institute for Soft Matter Synthesis and Metrology, Georgetown University, Washington DC
Abstract: Cement is the main binding agent in concrete, literally gluing together rocks and sand into the most-used synthetic material on Earth. However, cement production is responsible for significant amounts of man-made greenhouse gases—in fact if the cement industry were a country, it would be the third largest emitter in the world. It has become clear that even a slight reduction of cement carbon footprint will dramatically reduce the global anthropogenic CO2 emissions of the whole construction sector, and that meeting emission-reduction targets for new constructions calls for deeper scientific understanding of cement properties and performance. Cement cohesion originates from the accumulation and confinement of ions in solution between the surfaces of cement hydrates, surprisingly similar to a range of colloidal and biological matter, but surface charge densities and ionic compositions set cement outside the validity range of established mean field theories for electrostatics in solution. The progress made through experiments, simulations and theory over the years has left a knowledge gap in the fundamental understanding of how nanoscale cohesive forces emerge during cement hydration. I will discuss how, about one century after the early studies of cement hydration, we have quantitatively solved this notoriously hard problem and filled this gap, discovering how cement cohesion originates from water-ion interlocking when confined between the charged surfaces of calcium-silicate-hydrates. Starting from these new insights, I will analyze how statistical mechanics approaches and 3D numerical simulations studies open a new path to understand cement performance, durability and sustainability, and to scientifically grounded strategies of material design for greener cements.
Date: June 24, 2021 - 14.30 (Italian time) - during the work for the I SIFS Conference
Quantum Simulation & Measurement of Entanglement
Peter Zoller, Center for Quantum Physics, University of Innsbruck, and Institute for Quantum Optics and Quantum Information, Innsbruck, Austrian Academy of Sciences
Abstract: Cold atoms and ions constitute not only a platform to build highly controlled quantum many-body systems, but also provide us with a unique toolbox to develop and implement novel measurement protocols for many-body observables. Here we discuss a 'randomized measurement toolbox', where we apply random unitaries to many-body quantum states in the quantum simulator, and statistical correlations between measured probabilities provides access to quantities characterizing entanglement. This includes (Renyi) entanglement entropies, or even a complete `learning' of the entanglement Hamiltonian and entanglement spectrum. We illustrate our theoretical concepts with experimental data showing build-up of entanglement in quench dynamics, which were taken on a programmable trapped-ion simulator realizing a long-range transverse Ising model.
Date: May 27, 2021 - 16.30 (Italian time)
Optimal Transport in Plants and Forests
Abstract: Forests represent one of the most complex systems with a high degree of structural and functional diversity.
Water transport through plants is a key driver of the carbon and other biogeochemical cycles and is a crucial link in plant adaptation to climate and vegetation response to climate change.
First, we discuss the shape of the xylems, the conduits responsible for transporting water to the leaves: wider conduits transport more water but are more vulnerable to conduction-blocking gas embolisms, and cost more for a plant to build, a tension necessarily shaping xylem conduit diameters along plant stems. A solution based on Pareto multi-optimization leads to the prediction of a universal shape of xylems which will be compared with data spanning terrestrial plant orders, life forms, habitats, and sizes.
In the second part we will present an optimization principle leading to the prediction of the total evapotranspiration of water in single plants and its consequences in the tree size distribution in natural plant communities, an issue of great importance for carbon storage. Predictions are tested in forests at various latitudes and deviations from the predictions are used to quantify degrees of disturbances.
Date: April 29, 2021 - 16.30 (Italian time)
Manipulating molecules one at a time: from energy to information
Felix Ritort, Small Biosystems Lab, Departament de Física de la Matèria Condensada, Facultat de Física, Universitat de Barcelona
Abstract: “Take a single DNA molecule and pull from its extremities while recording the force-extension curve until it gets fully straightened.” This thought experiment, which was just a dream a few decades ago, has become standard in many research labs worldwide. Force spectroscopy techniques (such as laser optical tweezers) are a fabulous tool for manipulating and monitoring biological molecules' direct action at the individual level. By measuring forces in the piconewton range and energies roughly equivalent to 1kT, we have the experimental accuracy in resolving the thermal energy unit. Recent advances in such technologies combined with theoretical developments in nonequilibrium physics offer the exciting prospect of experimentally testing fundamental physical principles and concepts in single-molecule experiments [1].
This talk will illustrate laser optical tweezers for single-molecule manipulation and some of the main applications in physics and biology. In particular, I will also present results on a Maxwell demon's experimental realization using single DNA molecules pulled under feedback protocols as a pioneering example of the thermodynamics of data processing and information [2].
1. F. Ritort, The noisy and marvelous molecular world of biology, Inventions, 4(2) (2019) 24
2. M. Ribezzi-Crivellari and F. Ritort, Large work extraction and the Landauer limit in the Continuous Maxwell Demon, Nature Physics 15 (2019) 660–664
Date: March 25, 2021 - 16.30 (Italian time)
Anomalous transport in classical one-dimensional systems
Abstract: Transport properties of one-dimensional systems are reviewed, starting from the definition of heat flux, recently revisited to make it correct also over microscopic scales.
Various theoretical and numerical approaches are discussed in paradigmatic models to illustrate the conditions for the emergence of an anomalous (diverging) heat conductivity and to reconstruct the general scenario. Some finite-size effects are also reviewed, including the seemingly normal conductivity observed in nearly integrable systems.
In the second part of the colloquium, I turn the attention towards coupled transport processes in systems characterized by two conservation laws (such as energy and mass). The reference model will be the discrete nonlinear Schroedinger equation, often used in the study of DNA dynamics, cold atoms, and optical arrays. I mostly focus on anti-intuitive phenomena such non-monotonous temperature profiles, which can be accounted for by linear-response theory and the emergence of "negative" temperatures, associated with an intermittent transport of mass and energy.
Date: February 25, 2021 - 16.30 (Italian time)
Spontaneous vs. stimulated brain activity: A statistical physics approach
Abstract: The understanding of the fundamental relation between brain resting activity and the response to stimuli is a long-standing fascinating question. Recent experiments have shown that the spontaneous brain activity is characterized by avalanches showing absence of characteristic size, result successfully interpreted in the context of criticality. However, in order to support the idea that the brain acts close to a critical point it is crucial to evidence the existence of long-range correlations. The temporal organization of neuronal avalanches in the rat cortex in vitro is characterized by a complex organization, leading to the characteristic brain oscillations and a dynamic balance between excitation and inhibition. The question concerning the relation between spontaneous and evoked activity is addressed by means of the coarse-grained Wilson Cowan model. An approach inspired in non-equilibrium statistical physics allows to derive a fluctuation-dissipation relation, suggesting that measurements of the correlations in spontaneous fluctuations in the brain activity alone could provide a prediction for the system response to a stimulus. Theoretical predictions are in good agreement with MEG data for healthy patients performing visual tasks.
Date: February 4, 2021 - 16.30 (Italian time)
2020 Plenary Colloquia
Extreme Values Statistics: An overview and perspectives
Satya Majumdar, Laboratoire de Physique Theorique et Modeles Statistique (LPTMS), Université de Paris-Sud (Orsay)
Abstract: Extreme value statistics (EVS) concerns the study of the statistics of the maximum or the minimum of a set of random variables. This is an important problem for any time-series and has applications in climate, finance, sports, all the way to physics of disordered systems where one is interested in the statistics of the ground state energy. While the EVS of 'uncorrelated' variables is well understood, little is known for strongly correlated random variables. Only recently this subject has gained much importance both in statistical physics and in probability theory. In this talk, I will give an overview and perspectives on this interdisciplinary and rapidly evolving area of research.
Date: December 3, 2020 - 16.30 (Italian time)
Absolute Negative Mobility: can it take place in thermal equilibrium?
Abstract: Absolute Negative Mobility (ANM) is a phenomenon whereby current in a stationary system is in a direction opposite to the driving field. Naïve argument suggests that ANM cannot take place in systems in thermal equilibrium as this could lead to a violation of the second law of thermodynamics. Thus numerous previous theoretical and experimental studies of ANM have dealt with the response to a driving field in nonequilibrium steady states. In this talk a simple lattice model of a driven tracer is introduced and demonstrated to exhibit ANM in equilibrium, with no violation of the basic laws of thermodynamics. The limits of validity of the naïve argument are elucidated and the entropy production which accompany the motion of the tracer is calculated.
Date: November 19, 2020 - 16.30 (Italian time)
How amorphous materials yield under stress: a new kind of out of equilibrium phase transition
Abstract: I will show that a new kind of out of equilibrium phase transition is at the core of how amorphous solids yield in response to external deformations—a phenomenon that is crucial both for practical applications and for theoretical reasons. Such phase transition has strong connections with phenomena studied in the theory of disordered systems such as the zero-temperature spinodal of the Random Field Ising Model, the Depinning transition, and rare events.
Our results unveil that despite large differences in the materials’ microscopic interactions and typical scales (from colloids to molecular glasses) a large degree of universality emerges as there are only two ways in which amorphous solids respond to a deformation: One, typical of well-annealed materials, is characterized by an abrupt failure with a macroscopic stress drop and the sudden emergence of sharp shear bands; the other, typical of poorly annealed materials, shows merely a smooth crossover. By varying the preparation protocol, one can change the response of a given material from one to the other, and this change is controlled by a random critical point, akin to the one of the zero temperature Random Field Ising Model.
Date: October 29, 2020 - 16.30 (Italia time)
Rough landscapes and glass dynamics: from inference to machine learning
Abstract: The realm of statistical mechanics has been enlarged to describe systems, such as glass forming materials, where structural disorder plays the predominant role. Interestingly the spectrum of applications of this new physics goes much beyond the scope of condensed matter and extends to the currently booming field of data science. In this colloquium I will focus on the challenge of signal-reconstruction from noisy collections of data, omnipresent in machine learning applications and in classical inference problems. By leveraging tools and ideas from glass physics, I will show how we can describe, predict, and enhance the performances of algorithms introduced to tackle these reconstruction problems.
Date: October 15, 2020 - 16.30 (Italian time)
(Non equilibrium) thermodynamics of classical Integrable models
Leticia F. Cugliandolo, Sorbonne Université, Laboratoire de Physique Théorique et Hautes Energies, Institut Universitaire de France
Abstract: Motivated by recent experimental developments in atomic physics, a large theoretical effort has been devoted to the analysis of the quench dynamics of quantum isolated systems. In this talk I will describe the evolution of a family of classical many-body integrable models after instantaneous quenches of the same kind. My aim will be to distinguish the effects of the quantum/classical nature of the systems from those of the interactions, be them external and due to the environment, or internal (integrability vs. non-integrability). I will also show that the asymptotic dynamics of these models can be fully elucidated, and the stationary properties compared to the ones obtained using a Generalised Gibbs Ensemble. The latter can not only be built but also used to evaluate analytically all relevant observables, a quite remarkable fact for an interacting integrable system.
Date: October 1, 2020 - 16.30 (Italian time)
Simplicial complexes and dynamics
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 (Italian time)
The thermodynamic uncertainty relation
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 (Italian time)
A perspective view on fully developed turbulence
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 (Italian time)