Title: Stochastic probing methods for estimating the trace of functions of sparse symmetric matrices,
Speaker(s): Michele Rinelli, Scuola Normale Superiore,
Date and time: 30 May 2023, 16:00 (Europe/Rome),
Lecture series: Seminar on Numerical Analysis,
Venue: Dipartimento di Matematica (Aula Riunioni).
You can access the full event here: https://events.dm.unipi.it/e/198
Abstract
--------
We consider the combination of two approaches for the trace estimation of a symmetric matrix function f(A) when the only feasible operations are matrix-vector products and quadratic forms with f(A): stochastic estimators, such as the Hutchinson estimator and its refined variants Hutch++ and the recent XTrace, and probing methods based on graph colorings. Particularly effective is the case where we replace the indicator vectors for the coloring used in probing by random vectors whose non-zero entries have Rademacher distribution. A theoretical analysis exposes conditions under which using just one Rademacher probing vector per color is provably better than the classical probing approach. Numerical experiments show that existing methods are also outperformed under suitable conditions on the sparsity pattern of A and on the spectrum of f(A). This talk is based on a joint work with Andreas Frommer and Marcel Schweitzer.
--
Indico :: Email Notifier
https://events.dm.unipi.it/e/198
Title: Stochastic probing methods for estimating the trace of functions of sparse symmetric matrices,
Speaker(s): Michele Rinelli, Scuola Normale Superiore,
Date and time: 30 May 2023, 16:00 (Europe/Rome),
Lecture series: Seminar on Numerical Analysis,
Venue: Dipartimento di Matematica (Aula Riunioni).
You can access the full event here: https://events.dm.unipi.it/e/198
Abstract
--------
We consider the combination of two approaches for the trace estimation of a symmetric matrix function f(A) when the only feasible operations are matrix-vector products and quadratic forms with f(A): stochastic estimators, such as the Hutchinson estimator and its refined variants Hutch++ and the recent XTrace, and probing methods based on graph colorings. Particularly effective is the case where we replace the indicator vectors for the coloring used in probing by random vectors whose non-zero entries have Rademacher distribution. A theoretical analysis exposes conditions under which using just one Rademacher probing vector per color is provably better than the classical probing approach. Numerical experiments show that existing methods are also outperformed under suitable conditions on the sparsity pattern of A and on the spectrum of f(A). This talk is based on a joint work with Andreas Frommer and Marcel Schweitzer.
--
Indico :: Email Notifier
https://events.dm.unipi.it/e/198
Dear all,
I am forwarding this announcement in case anyone is interested.
All the best,
Paola
-------- Forwarded Message --------
Subject: [DKIM Failed - Firma mittente non verificata][gdrmoa] POSTDOC
at AROMATH, Inria of Université Côte d'Azur.
Date: Tue, 23 May 2023 10:16:57 +0200
From: Bernard Mourrain <Bernard.Mourrain(a)inria.fr>
Reply-To: Bernard Mourrain <Bernard.Mourrain(a)inria.fr>
To: gdrmoa(a)listes.math.cnrs.fr
Dear Colleagues,
A POSTDOC position is available in Aromath
<https://es.sonicurlprotection-fra.com/click?PV=2&MSGID=20230523083043027614…>
team at Inria of Université Côte d'Azur
<https://es.sonicurlprotection-fra.com/click?PV=2&MSGID=20230523083043027614…>.
The duration of the contract is _1+1 years (one year renewable one
additional year)_.
The starting date is flexible, ideally in fall 2023.
Here is the link to the official announcement and to apply
<https://es.sonicurlprotection-fra.com/click?PV=2&MSGID=20230523083043027614…>
to the position.
Please feel free to contact me for any questions you may have.
Please also forward this message to any potential interested candidates
you may know.
Best regards,
Bernard Mourrain
Carissimi,
vi inoltro il seguente annuncio di seminario, nell'ambito delle
manifestazioni d'interesse del Progetto di Eccellenza.
Saluti, Beatrice
-------- Forwarded Message --------
Subject: [Personale.docente.dm] Prossimi seminari Dipartimento di
Eccellenza
Date: Mon, 22 May 2023 07:54:42 +0000
From: Maria Stella Gelli <maria.stella.gelli(a)unipi.it>
To: personale.docente(a)dm.unipi.it <personale.docente(a)dm.unipi.it>
Cari tutti,
vi segnalo che venerdì alle ore 11.00 in Aula Magna si terrà il quarto
dei seminari collegati alla manifestazione di interesse
del Progetto di Eccellenza.
Lo speaker è Luca Heltai (Sissa)
https://www.dm.unipi.it/eventi/an-overview-on-non-matching-approximation-me…
<https://www.dm.unipi.it/eventi/an-overview-on-non-matching-approximation-me…>
I seminari proseguiranno nelle prossime settimane, potete seguire il
calendario (in continua evoluzione) al seguente link
https://www.dm.unipi.it/seminari-di-dipartimento/
<https://www.dm.unipi.it/seminari-di-dipartimento/>
Vi segnaliamo sul canale Colloquia del Team Dipartimento di Matematica
trovate la registrazione dei seminari passati, inoltre, a meno di
problematiche dell'ultimo minuto, i seminari sono trasmessi in
streaming sullo stesso canale.
Cari saluti
Maria Stella Gelli & Francesco Sala per il Direttore
Title: Grassmann extrapolation of density matrices as a tool to accelerate Born-Oppenheimer molecular dynamics,
Speaker(s): Federica Pes, Università di Pisa,
Date and time: 19 May 2023, 15:00 (Europe/Rome),
Lecture series: Seminar on Numerical Analysis,
Venue: Dipartimento di Matematica (Aula Riunioni).
You can access the full event here: https://events.dm.unipi.it/e/192
Abstract
--------
Born-Oppenheimer molecular dynamics (BOMD) is a powerful but expensive technique. The main bottleneck in a density functional theory (DFT) BOMD calculation is the solution to the DFT nonlinear equations that requires an iterative procedure that starts from a guess for the density matrix. To speed up such calculations, various extrapolation strategies have been developed to use densities available at previous simulation steps as a guess for the iterative procedure. However, density matrices belong in a Grassmann manifold, which is not a vector space. Therefore the linear extrapolation is performed in a tangent space of the manifold, thanks to a locally bijective map between the manifold and its tangent space.In this contribution, we introduce an approximately time reversible approach to extrapolate density matrices. Some numerical experiments show optimal performance, compared to the state of the art.
--
Indico :: Email Notifier
https://events.dm.unipi.it/e/192
Buongiorno,
inoltro questo annuncio per una posizione a KU Leuven. La posizione è
nel gruppo di analisi numerica ed è orientata al quantum computing.
A presto,
Paola
-------- Forwarded Message --------
Subject: Faculty position Numerical Methods for Quantum Computing at KU
Leuven
Date: Tue, 9 May 2023 13:15:26 +0200
From: Nick Vannieuwenhoven <nick.vannieuwenhoven(a)kuleuven.be>
To: paola.boito(a)unipi.it
Dear Prof. Paola Boito,
We would like to draw your attention to the job offer for the full-time
faculty position in /Numerical Methods for Quantum Computing/ at KU
Leuven, with application deadline September 14, 2023. A short
description is included below. A detailed description is available at
https://www.kuleuven.be/personeel/jobsite/jobs/60205789
Since we believe that the position could be of interest to some of your
group members, colleagues or collaborators, we would kindly ask you to
forward the message, in particular to excellent post-docs and junior
group leaders.
Best regards,
Nick Vannieuwenhoven
----
Prof. dr. Nick Vannieuwenhoven,
Member of the search committee.
KU Leuven,
Department of Computer Science,
Celestijnenlaan 200A, bus 2402,
3001 Heverlee,
Belgium.
*Faculty Position, Numerical Methods for Quantum Computing, KU Leuven *
The Science, Engineering, and Technology Group of KU Leuven invites
applications for a full time research professorship in the research unit
Numerical Analysis and Applied Mathematics (NUMA). The research in NUMA
covers many aspects of computational mathematics, including
approximation theory, numerical integration, numerical (multi-) linear
algebra, numerical partial differential equations, uncertainty
quantification, optimization and control, discrete optimization and
scheduling, and high-performance computing. The research unit also
performs research in collaboration with industry. The new position aims
to strengthen the experience in the domain of quantum computing.
Quantum computing is a novel computing paradigm relying on fundamental
properties of quantum physics. It features new core building blocks that
can lead to exponential speedups relative to traditional computing. This
requires a fundamental shift in the design of numerical algorithms and
their optimized mapping to available quantum circuits. Candidates are
expected to have already obtained excellent research results within the
research field of design, analysis, development, and implementation of
new quantum algorithms for numerical computing.
The successful candidate is expected to develop a research program on
quantum computing, ensure high-quality education within the area of
mathematical engineering, and be prepared to provide scientific and
administrative services.
For further details, contact information and the application procedure
(deadline September 14, 2023), follow the link:
https://www.kuleuven.be/personeel/jobsite/jobs/60205789
The vacancy fits within the KU Leuven Quantum initiative:
https://set.kuleuven.be/en/about-us/vacancies/quantum
Title: Grassmann extrapolation of density matrices as a tool to accelerate Born-Oppenheimer molecular dynamics,
Speaker(s): Federica Pes, Università di Pisa,
Date and time: 19 May 2023, 15:00 (Europe/Rome),
Lecture series: Seminar on Numerical Analysis,
Venue: Dipartimento di Matematica (Aula Riunioni).
You can access the full event here: https://events.dm.unipi.it/e/192
Abstract
--------
Born-Oppenheimer molecular dynamics (BOMD) is a powerful but expensive technique. The main bottleneck in a density functional theory (DFT) BOMD calculation is the solution to the DFT nonlinear equations that requires an iterative procedure that starts from a guess for the density matrix. To speed up such calculations, various extrapolation strategies have been developed to use densities available at previous simulation steps as a guess for the iterative procedure. However, density matrices belong in a Grassmann manifold, which is not a vector space. Therefore the linear extrapolation is performed in a tangent space of the manifold, thanks to a locally bijective map between the manifold and its tangent space.In this contribution, we introduce an approximately time reversible approach to extrapolate density matrices. Some numerical experiments show optimal performance, compared to the state of the art.
--
Indico :: Email Notifier
https://events.dm.unipi.it/e/192