NumPI May 2025

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2 discussions

Nello Cristianini a Pisa
by Gianna M. Del Corso 20 May '25

20 May '25

Cari colleghi, Giovedì 22/5 alle 11:00 nell’aula magna dell’ex facoltà di Scienze, Nello Cristianini, professore di intelligenza artificiale all’ Università di Bath terrà una presentazione del suo libro "Machina Sapiens <https://www.mulino.it/isbn/9788815384461>” discutendo dei rischi e delle implicazioni dell'AI generativa. Sarà un'ottima occasione per approfondire temi di grande attualità nel nostro campo con uno dei principali esperti dell'argomento, che li presenterà in modo accessibile. Vi incoraggio a partecipare e a contribuire alla discussione, invitando anche gli studenti del nostro corso di laurea. Cordiali saluti, Gianna @@@@@@@@@@@@@@@@@ Gianna M. Del Corso, PhD Dipartimento di Informatica, Università di Pisa Largo Pontecorvo, 3 56127 Pisa, Italy ph. +39-050-2213118 @@@@@@@@@@@@@@@@@

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[Indico] Federica Mugnaioni, Optimal and Scalable Augmented Lagrangian preconditioners for Fictitious Domain problems, 13/05/2025, 11:00 Europe/Rome
by fabio.durastante＠unipi.it 12 May '25

12 May '25

Title: Optimal and Scalable Augmented Lagrangian preconditioners for Fictitious Domain problems, Speaker(s): Federica Mugnaioni, Scuola Normale Superiore, Date and time: 13 May 2025, 11:00 (Europe/Rome), Lecture series: Seminar on Numerical Analysis, Venue: Dipartimento di Matematica (Saletta Riunioni). You can access the full event here: https://events.dm.unipi.it/e/321 Abstract -------- One of the major drawbacks of using Fictitious Domain methods is the computational demands of solving the associated large-scale linear systems, both in terms of time and memory. To address this issue, we propose two augmented Lagrangian-based preconditioners for efficiently solving linear systems of equations with a block two-by-two and three-by-three structure arising from fictitious domain problems and from finite element discretizations of immersed boundary methods. We consider two relevant examples to illustrate the performance of these preconditioners when used in conjunction with flexible GMRES: the Poisson and the Stokes fictitious domain problems. We provide a detailed spectral analysis, deriving lower and upper bounds for the eigenvalues of the preconditioned matrix and showing their independence with respect to discretization parameters. Furthermore, we discuss the eigenvalue distribution when inexact versions of the preconditioners are employed. We show the effectiveness of the proposed approach and the robustness of our preconditioning strategies through extensive numerical tests in both two and three dimensions, using different immersed geometries.M. Benzi, M. Feder, L. Heltai and F. Mugnaioni. Optimal and Scalable Augmented Lagrangian preconditioners for Fictitious Domain problems. arXiv:2504.11339, 2025 Note ---- A reminder of tomorrow's seminar. -- Indico :: Email Notifier https://events.dm.unipi.it/e/321

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NumPI May 2025