FUNCOMP

Numerical Computation with Functions Instead of Numbers

Coordinatore	THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD    more Spiacenti, non ci sono informazioni su questo coordinatore. Contattare Fabio per maggiori infomrazioni, grazie.
Nazionalità Coordinatore	United Kingdom [UK]
Totale costo	1˙668˙157 €
EC contributo	1˙668˙157 €
Programma	FP7-IDEAS-ERC Specific programme: "Ideas" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
Code Call	ERC-2011-ADG_20110209
Funding Scheme	ERC-AG
Anno di inizio	2012
Periodo (anno-mese-giorno)	2012-03-01   -   2017-02-28

 Partecipanti

#	participant	country	role	EC contrib. [€]
1	THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD  Organization address address: University Offices, Wellington Square city: OXFORD postcode: OX1 2JD contact info Titolo: Ms. Nome: Gill Cognome: Wells Email: send email Telefono: +44 1865 289800 Fax: +44 1865 289801	UK (OXFORD)	hostInstitution	1˙668˙157.00
2	THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD  Organization address address: University Offices, Wellington Square city: OXFORD postcode: OX1 2JD contact info Titolo: Prof. Nome: Lloyd Nicholas Cognome: Trefethen Email: send email Telefono: +44 1865 615317 Fax: +44 1865 615101	UK (OXFORD)	hostInstitution	1˙668˙157.00

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 Obiettivo del progetto (Objective)

'Numerical analysis, scientific computing, and computational science are built on technologies of discretization such as splines, finite differences, and finite elements. Yet for most applications it is ultimately continuous functions that are of scientific interest, and the discretizations are a means to the end of working with them. This project will advance mathematics and algorithms to enable scientists and engineers to compute with functions rather than their discretizations. Such computations will be numerical as opposed to symbolic, for speed and wide applicability, yet will achieve some of the “feel” of symbolic computing. The goal is to do for computing with functions what floating-point arithmetic has done for computing with numbers: to hide away details of discretization from most users, most of the time.'