About
The Laser Interferometer Space Antenna (LISA) will deliver an unprecedented view of the gravitational-wave universe, but unlocking its scientific potential hinges on a monumental data science challenge: the "global fit". Extracting thousands of overlapping, time-varying signals from complex instrumental noise is a high-dimensional inference problem that pushes the limits of traditional stochastic sampling methods. In this talk, I will explore how Simulation-Based Inference (SBI) is emerging as a promising framework to break this computational bottleneck. I will overview the current landscape of SBI applied to LISA data, highlighting how it has been used across the various source classes. Finally, I will outline what I see as the significant hurdles that remain as we scale these algorithms toward a full analysis pipeline.
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The talk
Credits and licence
- Institution
- CERN
- Speaker
- James Alvey
- Year
- 2026
- Language
- English
- Source
- CERN
- Licence
- CERN, as CERN states it. CERN's terms
- Attribution
- © CERN. CERN provides its audiovisual media free of charge for educational and informational use, credited to CERN; this lecture is shown in CERN's own player.
- Who can watch
- CERN gives no rating. Invisible Network shows it to Teens profiles and older, judged from what the source says about it. How courses are placed