Speaker
Description
Primordial black holes (PBHs) may have formed from the collapse of large density fluctuations in the early Universe and provide a powerful probe of the primordial power spectrum on otherwise inaccessible scales. However, translating PBH abundances into constraints on primordial physics remains limited by theoretical uncertainties. A key source of this uncertainty is the choice of window function, which describes how fluctuations on different scales contribute to collapse. Despite its central role, this ingredient is often treated in a simplified or inconsistent way.
In this talk, I will highlight the impact of the window function on PBH predictions and present recent work aimed at improving its modelling, including exploratory machine learning approaches. These results represent a step toward a more robust connection between early-Universe physics and PBH observables.
| Other topic / keywords: | Primordial black holes |
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