Tra il XVI e il XVIII secolo è avvenuta, in Europa, una rivoluzione cosmologica. Si tratta di molto più di un semplice cambiamento “geometrico” (il Sole al centro invece della Terra al centro); si tratta della sostituzione di tutto un insieme di conoscenze e di concezioni. Le nuove concezioni sono state sviluppate in modo non sincrono, talvolta secondo le osservazioni empiriche ma talvolta anche contro le osservazioni empiriche, e hanno preso il sopravvento quando sono arrivate a costituire un insieme sufficientemente completo e coerente.
Vengono percorsi i passaggi principali, attraverso i protagonisti chiave (Copernico, Tycho Brahe, Keplero, Galileo, Newton), sia astronomi osservatori sia puramente speculativi, le loro scoperte e i loro tentativi di interpretazione, cercando di mettere in luce alcuni snodi che sono particolarmente interessanti dal punto di vista epistemologico.
The Material Point Method for the simulation of water-related hazards and their interaction with critical structures
Antonia Larese, Universita degli studi di Padova & Technical University of Munich
In recent years, natural hazards involving large mass movements such as landslides, debris flows, and mud flows have been increasing their frequency and intensity as a consequence of climate change and other related factors. These phenomena often carry huge rocks and heavy materials that may, directly or indirectly, cause damage to our structures resulting in a relevant socio-economic impact.
The numerical simulation of the above events still represents a big challenge mainly for two reasons: the need to deal with large strain regimes and the intrinsic multiphysics nature of such events.
While the Finite Element Method (FEM) represents a recognized, well established and widely used technique in many engineering fields, unfortunately it shows some limitation when dealing with problems where large deformation occurs. In the last decades many possible alternatives have been proposed and developed to overcome this drawback, such as the use of the so called particle-based methods. Among these, the Material Point Method (MPM) blends the advantages of both mesh-based and mesh-less methods. MPM avoids the problems of mesh tangling while preserving the accuracy of Lagrangian FEM and it is especially suited for non linear problems in solid mechanics and fluid dynamics.
The talk will show some recent advances in MPM formulations , presenting both an irreducible and mixed formulation stabilized using variational multiscale techniques, as well as the partitioned strategies to couple MPM with other techniques such as FEM or DEM [2, 3]. All algorithms are implemented within the Kratos-Multiphysics open-source framework and available under the BSD license.
 Iaconeta, I., Larese, A., Rossi, R. and Guo, Z., Comparison of a Material Point Method and
a Meshfree Galerkin Method for the simulation of cohesive-frictional materials, Materials, 10 , 1150, (2017).
 Chandra, B., Singer, V., Teschemacher, T., Wuechner, R. and Larese, A., Nonconforming
Dirichlet boundary conditions in Implicit Material Point Method by means of penalty augmentation,
Acta Geotechnica, 16(8), 2315-2335 (2021).
 Singer, V., Sautter, K.B., Larese, A., Wuchner, R. and Bletzinger, K.U.,, A Partitioned
Material Point Method and Discrete Element Method Coupling Scheme , Under revision in Advanced Modeling and Simulation in Engineering Sciences (2022).
Long-time behavior for local and nonlocal porous medium equations with small initial energy
Bruno Volzone, Università degli Studi di Napoli 'Parthenope'
In the first part of the talk, we will describe some aspects of a study developed in a joint paper with L. Brasco concerning the long-time behavior for the solution of the Porous Medium Equation in an open bounded connected set, with smooth boundary and sign-changing initial datum. Homogeneous Dirichlet boundary conditions are considered. We prove that if the initial datum has sufficiently small energy, then the solution converges to a nontrivial constant-sign solution of a sublinear Lane-Emden equation, once suitably rescaled.
We also give a sufficient energetic criterion on the initial datum, which permits to decide whether convergence takes place towards the positive solution or to the negative one. The second part of the talk will be devoted to some new advances obtained in collaboration with G. Franzina, in the spirit of the ones explained above, for the study of the asymptotics of signed solutions for the Fractional Porous Medium Equation.
Optimal design of planar shapes with active materials
Active materials (e.g., polymer gels, liquid crystal elastomers) have emerged as suitable candidates for shape morphing applications, where the configuration of a body is varied in a controlled fashion upon triggering the active response. Given the large variety of these materials, a natural question is to compare different morphing mechanisms for a desired functional shape change and select the most effective one with respect to a certain optimality criterion. To address such a question, we set an optimal control problem that allows to determine the active strains suitable to attain a desired equilibrium transformation, while minimizing the complexity of the activation. Specifically, we discuss the planar morphing of active, hyperelastic bodies in the plain-strain regime, in the absence of external forces.
Our approach aims to be general enough to account for a broad set of active materials through the notion of target metric. For the case of affine shape changes, we derive explicit conditions on the geometry of the reference configuration for the optimality of homogeneous target metrics.
More complex shape changes are then analyzed via numerical simulations. We explore the impact on optimal solutions of different objective functionals, some of them inspired by features of existing active materials. Further, we show how stresses arising from incompatibilities contribute to reduce the complexity of the controls. We believe that our approach may be exploited for the accurate design of active systems and may also contribute to gather insight into the morphing strategies adopted by biological systems, as a result of natural selection.
“A cosa serve la matematica?” Qual è quel docente che non si è mai sentito rivolgere questa domanda? Spesso è una domanda provocatoria, posta dallo studente più "simpatico" della classe. Ma a volte è una domanda sincera, posta da uno sconosciuto in treno. Solitamente siamo troppo stanchi o demoralizzati per rispondere a questa domanda. Ovviamente la matematica è utilissima, nel mondo di oggi, pieno di dati e in cui ogni aspetto della vita è intrecciato ad applicazioni, banali o profonde della matematica. Forse però vale la pena di soffermarsi un attimo in più su tale domanda e cercare di sviscerarla meglio...
Cosa vuol dire "a cosa serve la matematica?"?
La matematica pura è utile?
Perché i politici devono sapere la matematica?
A cosa serve a me la matematica?
L'utilità della matematica è interessante per chi la studia?
Nel seminario più che fornire le mie personali risposte proverò a dare un po' di materiale per pensarci su. Spero possa essere utile per avere qualche idea in più la prossima volta che sentirete queste o altre domande...
Nick Trefethen is Professor of Numerical Analysis and head of the Numerical Analysis Group at Oxford University. He was educated at Harvard and Stanford and held positions at NYU, MIT, and Cornell before moving to Oxford in 1997. He is a Fellow of the Royal Society and a member of the US National Academy of Engineering, and served during 2011-2012 as President of SIAM. He has won many prizes including the Gold Medal of the Institute for Mathematics and its Applications, the Naylor Prize of the London Mathematical Society, and the Polya and von Neumann Prizes from SIAM. He holds honorary doctorates from the University of Fribourg and Stellenbosch University.
As an author Trefethen is known for his books including Numerical Linear Algebra (1997), Spectral Methods in MATLAB (2000), Spectra and Pseudospectra (2005), Approximation Theory and Approximation Practice (2013/2019), Exploring ODEs (2018), and An Applied Mathematician's Apology (2022). He organized the SIAM 100-Dollar, 100-Digit Challenge in 2002 and is the inventor of Chebfun.
Applications of AAA rational approximation
Nick Trefethen, University of Oxford
giovedì 23 febbraio 2023 alle ore 14:00
Aula Consiglio VII piano - Dipartimento di Matematica
For the first time, a method has recently become available for fast computation of near-best rational approximations on arbitrary sets in the real line or complex plane: the AAA algorithm (Nakatsukasa-Sete-T. 2018). We will present the algorithm and then demonstrate a number of applications, including
* detection of singularities
* model order reduction
* analytic continuation
* functions of matrices
* nonlinear eigenvalue problems
* interpolation of equispaced data
* smooth extension of multivariate real functions
* extrapolation of ODE and PDE solutions into the complex plane
* solution of Laplace problems
* conformal mapping
* Wiener-Hopf factorization
The talk investigates the relation between normalized critical points of the nonlinear Schrödinger energy functional and critical points of the corresponding action functional on the associated Nehari manifold. First, we show that the ground state levels are strongly related by the following duality result: the (negative) energy ground state level is the Legendre–Fenchel transform of the action ground state level. Furthermore, whenever an energy ground state exists at a certain frequency, then all action ground states with that frequency have the same mass and are energy ground states too. We see that the converse is in general false and that the action ground state level may fail to be convex. Next we analyze the differentiability of the ground state action level and we provide an explicit expression involving the mass of action ground states. Finally we show that similar results hold also for local minimizers, and we exhibit examples of domains where our results apply.
This is a joint work with Enrico Serra and Paolo Tilli.
Recent results for the Navier-Stokes-Cahn-Hilliard model with unmatched densities
We consider the initial-boundary value problem for the incompressible Navier-Stokes-Cahn-Hilliard system with non-constant density proposed by Abels, Garcke and Grün in 2012. This model arises in the diffuse interface theory for binary mixtures of viscous incompressible fluids. In particular, this system is a generalization of the well-known Model H in the case of fluids with unmatched densities. In this talk, I will present some recent results concerning the propagation of regularity of global weak solutions (for which uniqueness is not known) and their longtime convergence towards an equilibrium state in three dimensional bounded domains.
Paradossi dei sistemi elettorali
Orazio Puglisi , Dipartimento di Matematica e Informatica "U. Dini", Università di Firenze
L’idea di “democrazia” che è ormai ben radicata dentro ciascuno di noi, spesso ci porta a considerare la questione dei sistemi elettorali (ovvero metodi per ottenere, a partire dalle preferenze degli individui di una certa popolazione, una lista di preferenze unica) con una certa leggerezza. Invece, appena si approfondisce la teoria dei sistemi di voto, ci si imbatte immediatamente in situazioni paradossali e problemi imprevisti, quasi sempre di difficile soluzione. Inizieremo questa conferenza discutendo alcuni dei principali problemi e paradossi che si presentano nella progettazione di un sistema elettorale. Nella parte finale ci occuperemo di un problema di diversa natura, ma di notevole importanza, ovvero quello della definizione “imparziale” dei collegi elettorali.
Spectral analysis of Kohn Laplacian on spherical manifolds
In this talk, we discuss the spectral analysis of Kohn Laplacian on spheres and the quotients of spheres. In particular, we obtain an analog of Weyl’s law for the Kohn Laplacian on lens spaces. We also show that two 3-dimensional lens spaces with fundamental groups of equal prime order are isospectral with respect to the Kohn Laplacian if and only if they are CR isometric.
The Grassmannian is a smooth moduli space with very rich geometry that parameterizes simple varieties, namely, linear spaces. One can study a natural generalization, the component of a Hilbert scheme that parameterizes a pair of linear spaces in P^n. In this talk, I will describe the geometry of this component and show that they are smooth Mori dream spaces. Along the way, we will obtain a complete classification of the degenerations of a pair of linear spaces.
Uncertainty Quantification for spatially-extended neurobiological networks
This talk presents a framework for forward uncertainty quantification problems in spatially-extended neurobiological networks. We will consider networks in which the cortex is represented as a continuum domain, and local neuronal activity evolves according to an integro-differential equation, collecting inputs nonlocally, from the whole cortex. These models are sometimes referred to as neural field equations.
Large-scale brain simulations of such models are currently performed heuristically, and the numerical analysis of these problems is largely unexplored. In the first part of the talk I will summarise recent developments for the rigorous numerical analysis of projection schemes  for deterministic neural fields, which sets the foundation for developing Finite-Element and Spectral schemes for large-scale problems.
The second part of the talk will discuss the case of systems in the presence of uncertainties modelled with random data, in particular: random synaptic connections, external stimuli, neuronal firing rates, and initial conditions (and any combination thereof). Such problems give rise to random solutions, whose mean, variance, or other quantities of interest have to be estimated using numerical simulations. This so-called forward uncertainty quantification problem is challenging because it couples spatially nonlocal, nonlinear problems to large-dimensional random data.
I will present a family of schemes that couple a spatial projector for the spatial discretisation, to stochastic collocation for the random data. We will analyse the time-dependent problem with random data and the schemes from a functional analytic viewpoint, and show that the proposed methods can achieve spectral accuracy, provided the random data is sufficiently regular.
Acknowledgements. This talk presents joint work with Francesca Cavallini (VU Amsterdam), Svetlana Dubinkina (VU Amsterdam), and Gabriel Lord (Radboud University).
 Avitabile D, Projection methods for Neural Field Equations arXiv e-prints,
This paper applies a recently developed sentiment proxy to the construction of a new risk factor and provides a comprehensive understanding of its role in sentiment-augmented asset pricing models. We find that news and social media search-based indicators are significantly related to excess returns of international equity indices. Adding sentiment factors to both classical and more recent linear factor pricing models leads to a significant increase in their performance. When it is estimated using the Fama-MacBeth procedure, our sentiment-adjusted pricing model implies positive (negative) estimates of the risk premium for positive (negative) sentiment factors. We further differentiate between developed and emerging markets and uncover different patterns of return reversals / persistence in the long-term. Our results contribute to the explanation of global cross-sectional average excess returns and are robust to augmenting the model with fundamental factors, momentum, idiosyncratic volatility, skewness, kurtosis, and the returns on international currencies. When compared to competing definitions of sentiment factors popular in the literature, our novel sentiment risk variable turns out to be superior in terms of predictive power.