Enabling Multi Messenger Astronomy with a low-latency LISA data pipeline

Informazioni relative al progetto

EMILIA

ID dell’accordo di sovvenzione: 101065596

DOI

10.3030/101065596

Progetto chiuso

Data della firma CE 4 Luglio 2022

Data di avvio 1 Gennaio 2023

Data di completamento 31 Dicembre 2024

Finanziato da

• Marie Skłodowska-Curie Actions (MSCA)

Costo totale

Nessun dato

Contributo UE

€ 169 326,72

Coordinato da

ARISTOTELIO PANEPISTIMIO THESSALONIKIS
Greece

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Documents, reports (1)

Communication, Dissemination & Outreach Plan

The plan describes the planned measures to maximize the impact of the project, including the dissemination and exploitation measures that are planned, and the target group(s) addressed. Regarding communication measures and public engagement strategy, the aim is to inform and reach out to society and show the activities performed, and the use and the benefits the project will have for citizens.

Data Management Plan (1)

Data Management Plan

The Data Management Plan describes the data management life cycle for all data sets that will be collected, processed or generated by the action. It is a document describing what data will be collected, processed or generated and following what methodology and standards, whether and how this data will be shared and/or made open, and how it will be curated and preserved.

Pubblicazioni

Peer reviewed articles (6)

Neural density estimation for Galactic binaries in the LISA data analysis

Autori: Natalia Korsakova, Stanislav Babak, Michael L. Katz, Nikolaos Karnesis, Sviatoslav Khukhlaev, Jonathan R. Gair
Pubblicato in: Physical Review D, Numero 110, 2024, ISSN 2470-0010
Editore: American Physical Society (APS)
DOI: 10.1103/PhysRevD.110.104069

Heavy-tailed likelihoods for robustness against data outliers: Applications to the analysis of gravitational wave data

Autori: Argyro Sasli, Nikolaos Karnesis, Nikolaos Stergioulas
Pubblicato in: Physical Review D, Numero 108, 2023, ISSN 2470-0010
Editore: American Physical Society (APS)
DOI: 10.1103/PhysRevD.108.103005

The interacting double white dwarf population with LISA: Stochastic foreground and resolved sources

Autori: A. Toubiana, N. Karnesis, A. Lamberts, M. C. Miller
Pubblicato in: Astronomy & Astrophysics, Numero 692, 2024, ISSN 0004-6361
Editore: EDP Sciences
DOI: 10.1051/0004-6361/202450174

Efficient GPU-accelerated multisource global fit pipeline for LISA data analysis

Autori: Michael L. Katz, Nikolaos Karnesis, Natalia Korsakova, Jonathan R. Gair, Nikolaos Stergioulas
Pubblicato in: Physical Review D, Numero 111, 2025, ISSN 2470-0010
Editore: American Physical Society (APS)
DOI: 10.1103/PHYSREVD.111.024060

Extracting gravitational wave signals from LISA data in the presence of artifacts

Autori: Eleonora Castelli, Quentin Baghi, John Baker, jacob Slutsky, Jrme Bobin, Nikolaos Karnesis, Antoine Petiteau, Orion Sauter, Peter J Wass, William J. Weber
Pubblicato in: Classical and Quantum Gravity, 2025, ISSN 0264-9381
Editore: IOP Publishing
DOI: 10.1088/1361-6382/adb931

Characterization of non-Gaussian stochastic signals with heavier-tailed likelihoods

Autori: N. Karnesis, A. Sasli, R. Buscicchio, N. Stergioulas
Pubblicato in: Physical Review D, Numero 111, 2025, ISSN 2470-0010
Editore: American Physical Society (APS)
DOI: 10.1103/PhysRevD.111.022005