GDR Ondes Gravitationnelles : Rencontre du groupe de travail "méthodes d'analyse des données"

Session

Session 3

7 oct. 2026, 14:00

Dirac/RdC-Amphithéâtre (IP2I)

4. Accurate and efficient simulation-based inference for massive black-hole binaries with LISA

Alice Spadaro (L2I Toulouse, CNRS/IN2P3, Université de Toulouse)

07/10/2026 14:00

We develop an accurate simulation-based inference framework for high-mass (≳ 10⁷M⊙) black-hole binaries observable by LISA. The method is implemented within the Dingo gravitational-wave parameter-estimation code, extending its application from ground-based detectors to the LISA band. We train a normalizing-flow model using aligned-spin higher-mode waveform models and a low-frequency...

8. A simulation-based inference pipeline for fast parameter estimation of massive black hole binaries with LISA data

Louis Le Saulnier (CEA/IRFU/DEDIP)

07/10/2026 14:20

This work focuses on data analysis for LISA, with a particular focus on fast parameter inference of massive black hole binaries (MBHBs). Fast parameter estimation will be essential for LISA’s Low-Latency Alert Pipeline (LLAP), which will enable electromagnetic and multi-messenger follow-up of detected sources. This requires working with pre-merger signals, allowing other observatories to see...

9. Low-latency detection and parameter estimation of massive black hole binaries for LISA

Malvina Bellotti (Observatoire de la Côte d'Azur, Nice)

07/10/2026 14:40

LISA will observe massive black hole binaries (MBHBs) hours to weeks before they merge. If these systems are in gas-rich environments, they might produce an electromagnetic (EM) counterpart: this motivates the development of pipelines able to localize and characterize the source fast enough to trigger a follow-up search. The main data analysis pipeline, the Global Fit, will model all LISA...

1. Diffusing the assumptions: realistic LISA stochastic component separation with physics-aware simulation-based inference

Iuliu Cuceu (Observatoire de la Côte d'Azur)

07/10/2026 15:00

The numerous sources that LISA will observe pose a unique data analysis challenge, with the most promising current avenue being a Global Fit, a simultaneous inference of all sources. Within the LISA Global fit, stochastic sources, from instrumental noise, to the galactic foreground and astrophysical or cosmological backgrounds, are particularly relevant due to their effect on the quality of...

5. Plug-and-Play methods for reconstructing polarizations of gravitational wave signals

Thomas Sainrat (CentraleSupélec)

07/10/2026 15:20

Reconstructing gravitational wave polarizations from detector data is a challenging problem due to the low SNR and the ill-posed nature of the the problem. We leverage the so-called "Plug-and-Play" methods, commonly used in inverse problem literature to achieve state-of-the-art image reconstruction. They explicitely separate the differentiable likelihood and the regularization, which is...