Assegnista di Ricerca presso Università di Pisa
Rome Area, Italy | Research
Esperienza
Assegnista di Ricerca (2018 - Presente)
Università di Pisa
Convegni e Workshop
- 17th International Conference on Mathematical Methods, Comptutational Techniques and Intelligent Systems (MAMECTIS ’15), Tenerife, Canary Islands, Spain – January 10-12, 2015
- Tenuto il talk dal titolo “Interpolant update of preconditioners for sequences of large linear systems“
- 13th EUROPT Workshop on Advances in Continuous Optimization, 8-10 July, 2015: Edinburgh
- Tenuto il talk dal titolo “The update of sequences of some incomplete decompositions matrices for preconditioning“
- Innovation & Growth, a process entangling public and private sectors
September 17-18, 2015: Auditorium Spazio Como – Como IT
- 9th Workshop SDS2016 – Structural Dynamical Systems: Computational Aspects, 14-17 June, 2016: Capitolo, Monopoli, Italy.
- Presentato il poster dal titolo “Solving mixed classical and fractional partial differential equations Short-memory principle and approximate inverses“
- Due Giorni di Algebra Lineare Numerica, 16-17 Febbraio, 2016, Como (CO), Italia
- Tenuto il talk dal titolo “Solving mixed classical and fractional partial differential equations Short-memory principle and approximate inverses“
- Numerical methods for optimal control problems: algorithms, analysis and applications, Roma, June, 19-23, 2017, Istituto Nazionale di Alta Matematica – INdAM
- Tenuto il talk dal titolo “Fractional PDEs Constrained Optimization: An optimize-then-discretize approach with L-BFGS and Approximate Inverse Preconditioning“
-
Structured Matrices in Numerical Linear Algebra: Analysis, Algorithms and Applications, Cortona, Italy, September 4-8, 2017 – INdAM Meeting
- Presentati i poster dal titolo: “Fast Solution of Fractional Differential Equation” e “Fractional PDE Constrained Optimization: An optimize-then-discretize approach with L-BFGS and Approximate Inverse Preconditioning“
- Quantitative Systems: Theory and Applications (QuaSy 2017). Como, Italy. October, 16-17, 2017.
- INdAM Workshop “Design of Reliable, Exact,and Application-oriented technologies for geometric Modeling and numerical Simulation (DREAMS)” INdAM, Rome, Italy, from 22 to 26,January 2018.
-
Due giorni di Algebra Lineare Numerica e Applicazioni. Padua, Italy, from 8 to 9 February 2018.
- Tenuto il talk dal titolo: “Fast Solution of Time-Dependent Fractional PDEs: Sparse and Limited Memory Block Preconditioners”
- Convegno 2018 Del Gruppo Nazionale per Il Calcolo Scientifico Dell’INDAM, Hotel Belvedere, Montecatini Terme, Italy, from 14 to 16 February 2018.
- SIAM conference on Applied Linear Algebra, Hong Kong, 4-8 May 2018.
- Tenuto il talk dal titolo: “Limited memory block preconditioners for fast solution of time-dependent fractional PDEs”
- Calcolo Scientifico e Modelli Matematici: alla ricerca delle cose nascoste attraverso le cose manifeste 2.0, Como, 16-18 Maggio 2018
- Presentato il poster dal titolo: “Efficient Solution of Time-Fractional Differential Equations with a New Adaptive Multi-Term Discretization of the Generalized Caputo–Dzherbashyan Derivative”
- 10th Workshop SDS2018, Structural Dynamical Systems: Computational Aspects, Porto Giardino Resort, Capitolo (Monopoli) – Bari, Italy, June 12-15, 2018
- Tenuto il talk dal titolo: “Limited memory block preconditioners for fast solution of FPDEs”
- Congresso Nazionale SIMAI 2018, Roma, July 2-6, 2018
- Tenuto il talk dal titolo: “Fast and reliable solution of fractional PDE constrained optimization problems”
-
Rome-Moscow school of Matrix Methods and Applied Linear Algebra 2018, July 28-August 11 (Moscow), September 9-23 (Rome)
- Tenuto il seminario dal titolo: “A Numerical Linear Algebra Perspective on Fractional Differential Equations”
Publication List
Articles and Proceedings
Bertaccini, Daniele; Durastante, Fabio Limited Memory Block Preconditioners for Fast Solution of Fractional Partial Differential Equations Journal Article Journal of Scientific Computing, 2018, ISSN: 1573-7691. Links | BibTeX @article{bertaccini2017BVM,
title = {Limited Memory Block Preconditioners for Fast Solution of Fractional Partial Differential Equations},
author = {Daniele Bertaccini and Fabio Durastante},
url = {https://doi.org/10.1007/s10915-018-0729-3},
doi = {10.1007/s10915-018-0729-3},
issn = {1573-7691},
year = {2018},
date = {2018-05-11},
journal = {Journal of Scientific Computing},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Cipolla, S; Durastante, F Fractional PDE constrained optimization: An optimize-then-discretize approach with L-BFGS and approximate inverse preconditioning Journal Article Applied Numerical Mathematics, 123 , pp. 43-57, 2018. Links | BibTeX @article{Cipolla201843,
title = {Fractional PDE constrained optimization: An optimize-then-discretize approach with L-BFGS and approximate inverse preconditioning},
author = {S Cipolla and F Durastante},
url = {http://communications.elsevier.com/r/?id=h4f2262e6,1e66829c,1e69099b&p1=authors.elsevier.com/a/1VkuTcQDwitj0, Full Text},
doi = {10.1016/j.apnum.2017.09.001},
year = {2018},
date = {2018-01-01},
journal = {Applied Numerical Mathematics},
volume = {123},
pages = {43-57},
publisher = {Elsevier B.V.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Bertaccini, D; Donatelli, M; Durastante, F; Serra-Capizzano, S Optimizing a multigrid Runge–Kutta smoother for variable-coefficient convection–diffusion equations Journal Article Linear Algebra and Its Applications, 533 , pp. 507-535, 2017. Links | BibTeX @article{Bertaccini2017507,
title = {Optimizing a multigrid Runge–Kutta smoother for variable-coefficient convection–diffusion equations},
author = {D Bertaccini and M Donatelli and F Durastante and S Serra-Capizzano},
doi = {10.1016/j.laa.2017.07.036},
year = {2017},
date = {2017-01-01},
journal = {Linear Algebra and Its Applications},
volume = {533},
pages = {507-535},
publisher = {Elsevier Inc.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Bertaccini, D; Durastante, F Solving mixed classical and fractional partial differential equations using short–memory principle and approximate inverses Journal Article Numerical Algorithms, 74 (4), pp. 1061-1082, 2017. Links | BibTeX @article{Bertaccini20171061,
title = {Solving mixed classical and fractional partial differential equations using short–memory principle and approximate inverses},
author = {D Bertaccini and F Durastante},
url = {http://em.rdcu.be/wf/click?upn=KP7O1RED-2BlD0F9LDqGVeSBQMGdh8lhKYmU-2Bp3OALilk-3D_lQ08erATmB1fabwnkhPcgYwcNIcfKhK5Sd2BVmv7GdZz0XqPb8A4ZJ-2BDzaVK7y1PXKKaouZFYqq2RpzpsGArKha0oNPeAkuVI98vr1xSK3hqHdXcyIe8Bn3wNx7bvXSPj13hdszzLI7ZgLP3wDsrNoJ27rsihha44fRqCDGzoKuMD4zlzmlsk1pLkICN80BfqvCas-2BieaO4DZH8XQhSidF50Uownjcb8Yi2rGId9u68fL04EQdv7qJwnc5gfkkjWbQockvGC5TrJXjNg2ErYyQ-3D-3D, Full Text},
doi = {10.1007/s11075-016-0186-8},
year = {2017},
date = {2017-01-01},
journal = {Numerical Algorithms},
volume = {74},
number = {4},
pages = {1061-1082},
publisher = {Springer New York LLC},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Durastante, F; Cipolla, S Fractional PDE constrained optimization: box and sparse constrained problems Inproceedings Falcone M. R. Ferretti, Grune L; McEneaney, W (Ed.): Numerical methods for optimal control problems, INdAM Springer, 2017, (In Press). BibTeX @inproceedings{DurastanteCipolla2017,
title = {Fractional PDE constrained optimization: box and sparse constrained problems},
author = {F Durastante and S Cipolla},
editor = {Falcone M., R. Ferretti, L. Grune and W. McEneaney},
year = {2017},
date = {2017-00-00},
booktitle = {Numerical methods for optimal control problems},
publisher = {Springer},
organization = {INdAM},
series = {Springer (INdAM)},
note = {In Press},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Bertaccini, D; Durastante, F Interpolating preconditioners for the solution of sequence of linear systems Journal Article Computers and Mathematics with Applications, 72 (4), pp. 1118-1130, 2016. Links | BibTeX @article{Bertaccini20161118,
title = {Interpolating preconditioners for the solution of sequence of linear systems},
author = {D Bertaccini and F Durastante},
doi = {10.1016/j.camwa.2016.06.023},
year = {2016},
date = {2016-01-01},
journal = {Computers and Mathematics with Applications},
volume = {72},
number = {4},
pages = {1118-1130},
publisher = {Elsevier Ltd},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
|
Durastante, F Interpolant Update of Preconditioners for Sequences of Large Linear Systems Inproceedings Mathematical Methods, Computational Techniques and Intelligent Systems (MAMECTIS '15), pp. 40–47, WSEAS Press 2015. BibTeX @inproceedings{durastante2015interpolant,
title = {Interpolant Update of Preconditioners for Sequences of Large Linear Systems},
author = {F Durastante},
year = {2015},
date = {2015-01-01},
booktitle = {Mathematical Methods, Computational Techniques and Intelligent Systems (MAMECTIS '15)},
volume = {41},
pages = {40--47},
organization = {WSEAS Press},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
|
Lecture Notes
Garoni, C; Durastante, F; Mazza, M; Serra-Capizzano, S Generalized Locally Toeplitz Sequences:A Spectral Analysis Tool for Approximated Differential Equationsand Few Selected Examples Book Chapter XVI BSCG Notes - XVI Brazilian School of Cosmology and Gravitation, Rio de Janeiro, 2017. BibTeX @inbook{garoni2017notes,
title = {Generalized Locally Toeplitz Sequences:A Spectral Analysis Tool for Approximated Differential Equationsand Few Selected Examples},
author = {C Garoni and F Durastante and M Mazza and S Serra-Capizzano},
year = {2017},
date = {2017-06-10},
booktitle = {XVI BSCG Notes - XVI Brazilian School of Cosmology and Gravitation, Rio de Janeiro},
keywords = {},
pubstate = {published},
tppubtype = {inbook}
}
|
Books
Bertaccini, D; Durastante, F Iterative Methods and Preconditioning for Large and Sparse Linear Systems with Applications Book 1, Chapman & Hall/CRC, 2018, ISBN: 978-1498764162. Abstract | Links | BibTeX @book{bertaccini2018book,
title = {Iterative Methods and Preconditioning for Large and Sparse Linear Systems with Applications},
author = {Bertaccini, D. and Durastante, F. },
url = {https://www.amazon.it/dp/1498764169/},
isbn = {978-1498764162},
year = {2018},
date = {2018-02-28},
publisher = {Chapman & Hall/CRC},
edition = {1},
series = {Chapman & Hall/CRC Monographs and Research Notes in Mathematics},
abstract = {This book describes, in a basic way, the most useful and effective iterative solvers and appropriate preconditioning techniques for some of the most important classes of large and sparse linear systems.
The solution of large and sparse linear systems is the most time-consuming part for most of the scientific computing simulations. Indeed, mathematical models become more and more accurate by including a greater volume of data, but this requires the solution of larger and harder algebraic systems. In recent years, research has focused on the efficient solution of large sparse and/or structured systems generated by the discretization of numerical models by using iterative solvers.},
keywords = {},
pubstate = {published},
tppubtype = {book}
}
This book describes, in a basic way, the most useful and effective iterative solvers and appropriate preconditioning techniques for some of the most important classes of large and sparse linear systems.
The solution of large and sparse linear systems is the most time-consuming part for most of the scientific computing simulations. Indeed, mathematical models become more and more accurate by including a greater volume of data, but this requires the solution of larger and harder algebraic systems. In recent years, research has focused on the efficient solution of large sparse and/or structured systems generated by the discretization of numerical models by using iterative solvers. |
Preprints and Submitted
Bertaccini, D; Durastante, F Efficient preconditioner updates for semilinear space-time fractional reaction-diffusion equations Unpublished 2018. Abstract | BibTeX @unpublished{bertaccini2018efficient,
title = {Efficient preconditioner updates for semilinear space-time fractional reaction-diffusion equations},
author = {D Bertaccini and F Durastante},
year = {2018},
date = {2018-00-00},
abstract = {The numerical solution of fractional partial differential equations poses significant computational challenges in regard to efficiency as a result of the nonlocality of the fractional differential operators. In this work we consider the numerical solution of nonlinear space-time fractional reaction-diffusion equations integrated in time by fractional linear multistep formulas. The Newton step needed to advance in (fractional) time requires the solution of sequences of large and dense linear systems because of the fractional operators in space. A preconditioning updating strategy devised recently is adapted and the spectrum of the underlying operators briefly analyzed.1
Because of the quasilinearity of the problem, each Jacobian matrix of the Newton equations can be written as the sum of a multilevel Toeplitz matrix plus a diagonal matrix and produced exactly in the code. Numerical tests with a population dynamics problem show that the proposed approach is fast and reliable with respect to standard direct, unpreconditioned, multilevel circulant/Toeplitz and ILU preconditioned iterative solvers.},
keywords = {},
pubstate = {published},
tppubtype = {unpublished}
}
The numerical solution of fractional partial differential equations poses significant computational challenges in regard to efficiency as a result of the nonlocality of the fractional differential operators. In this work we consider the numerical solution of nonlinear space-time fractional reaction-diffusion equations integrated in time by fractional linear multistep formulas. The Newton step needed to advance in (fractional) time requires the solution of sequences of large and dense linear systems because of the fractional operators in space. A preconditioning updating strategy devised recently is adapted and the spectrum of the underlying operators briefly analyzed.1
Because of the quasilinearity of the problem, each Jacobian matrix of the Newton equations can be written as the sum of a multilevel Toeplitz matrix plus a diagonal matrix and produced exactly in the code. Numerical tests with a population dynamics problem show that the proposed approach is fast and reliable with respect to standard direct, unpreconditioned, multilevel circulant/Toeplitz and ILU preconditioned iterative solvers. |
Bertaccini, D; Popolizio, M; Durastante, F Adaptive updating techniques for the approximation of functions of large matrices Unpublished 2017. Links | BibTeX @unpublished{bertaccini2017adaptive,
title = {Adaptive updating techniques for the approximation of functions of large matrices},
author = {D Bertaccini and M Popolizio and F Durastante},
url = {arXiv:1709.06351},
year = {2017},
date = {2017-09-19},
keywords = {},
pubstate = {Preprint},
tppubtype = {unpublished}
}
|
Mauro, C; Durastante, F A Unifying Framework for Seascape Visibility Analysis Unpublished 2017. BibTeX @unpublished{mauro2017visibility,
title = {A Unifying Framework for Seascape Visibility Analysis},
author = {Mauro, C. and Durastante, F.},
year = {2017},
date = {2017-00-00},
keywords = {},
pubstate = {published},
tppubtype = {unpublished}
}
|
Durastante, F Efficient Solution of Time-Fractional Differential Equations with a New Adaptive Multi-Term Discretization of the Generalized Caputo--Dzherbashyan Derivative Unpublished 0000. BibTeX @unpublished{durastante2018adaptive,
title = {Efficient Solution of Time-Fractional Differential Equations with a New Adaptive Multi-Term Discretization of the Generalized Caputo--Dzherbashyan Derivative},
author = {F Durastante},
keywords = {},
pubstate = {textbfSubmitted},
tppubtype = {unpublished}
}
|
Cipolla, S; Fiore, Di C; Durastante, F; Zellini, P Regularizing properties of a class of matrices including the optimal and the superoptimal preconditioners Unpublished 0000. BibTeX @unpublished{cipolladifioredurastantezellini,
title = {Regularizing properties of a class of matrices including the optimal and the superoptimal preconditioners},
author = {S Cipolla and C Di Fiore and F Durastante and P Zellini},
keywords = {},
pubstate = {textbfIn Preparation},
tppubtype = {unpublished}
}
|
[table width=”800″ colwidth=”20|280|190|100|90|120″ colalign=”left|left|left|left|left|center”]
,Certificazione,Ente,Da, A,
1,First Certificate in English, University of Cambridge (ESOL Examinations),Giugno 2008, presente, 
2,Game Theory,Stanford University & The University of British Columbia,Febbraio 2013,presente,
3,Linear and Discrete Optimization,École Polytechnique Fédérale de Lausanne,Aprile 2013,presente,
4,Computing for data analysis,Johns Hopkins University,Ottobre 2013,presente,
5,Gamification, University of Pennsylvania, Marzo 2015, presente,
6,University Teaching 101,Johns Hopkins University,Maggio 2015,presente,
7,Getting Started With Python,University of Michigan,Novembre 2015,presente,
8,Quantitative Biology Workshop, MITx, Maggio 2016, presente, 
[/table]
[table caption=”Laurea Magistrale in Matematica” width=”800″ colwidth=”380|70|350|70″ colalign=”left|center|left|center” ]
Esame, Voto, Esame, Voto
Complementi di Analisi Matematica 1 (Teoria della Misura), 27, Complementi di Analisi Numerica 1 (Metodi Numerici per l’Approssimazione), 30
Teoria delle Rappresentazioni 1,30,Laboratorio di Calcolo, 30
Metodi Numerici per le PDE, 30L, Lingua Inglese E3, Idoneo
Complementi di Analisi Numerica 2, 30, Codifica e Compressione di Segnali e Immagini, 29
Complementi di Probabilità, 27, Meccanica Analitica e Celeste, 30
Complementi di Analisi Matematica 2 (Analisi Funzionale), 30, Metodi Numerici per l’Ottimizzazione, 30L
Storia della Scienza, 28
[/table]
Dottorato in Informatica e Matematica del Calcolo
- Deterministic/probabilistic Dynamical systems with applications to extreme events theory, Prof. Vaienti
- Joint spectral radius and optimization for subdivision, Prof. M. Charina
- Introduction to Multigrid, Prof. M. Donatelli
- Krylov subspace methods for discrete ill-posed problem, Prof. P. Novati
- Macroscopic and Kinetic Models of Vehicular Traffic Flows, Prof. A. Tosin
- Exploiting Hidden Structure in Matrix Computations. Algorithms and Applications
CIME-EMS Summer School in applied mathematics
June 22 – June 26, 2015 – Cetraro (CS)
(Scuola seguita con borsa Full Board del CIME)
- Computational Finance, Prof.dr. Cornelis W. Oosterlee
- Toeplitz e Localmente Toeplitz come strumenti di indagine spettrale per EDP approssimate, Prof. S. Serra-Capizzano
- Introduction to Isogeometric Analysis, Prof. C. Manni, Dr. F. Pelosi, Dr. H. Speleers
- Network analysis, orthogonal polynomials, and Gauss quadrature – L. Reichel
- Frontiers in Partial Differential Equations Analysis and Solvers
Summer school supported by the Department of Mathematics F. Casorati (Pavia) and by Fondazione Alma Mater Ticinenis.
May 22 – 25, 2017
-
Splines and PDEs: Recent Advances from Approximation Theory to Structured Numerical Linear Algebra
CIME-EMS Summer School in applied mathematics
July 3 – Jult 7, 2017 – Cetraro (CS)
(Scuola seguita con borsa Partial Grant del CIME, estesa a Full Board)