Gravitational wave (GW) observations from binary black hole (BBH) mergers have provided new insights into strong-field gravity. A growing area of research focuses on environmental effects, where dark matter or other surrounding matter can influence the BBH dynamics and leave detectable imprints on GW signals. Dark matter, in particular, could form dense regions around black holes, potentially seeded by primordial black holes or amplified through processes like adiabatic growth or superradiance, modifying the resulting GW emission.
This workshop will examine the impact of such environments on BBH waveforms, with a focus on detecting and constraining these effects using GW observations. We will explore novel data analysis techniques, including machine learning and simulation-based inference (SBI), to enhance parameter inference and disentangle environmental signatures. The workshop aims to foster interdisciplinary collaboration in this emerging field by bringing together experts from gravitational wave astronomy, dark matter theory, and machine learning.
Organizers
Enrico Barausse (local contact, SISSA)
Gianfranco Bertone (University of Amsterdam, GRAPPA)
Andrea Maselli (GSSI)
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