Beyond Gaussianity in Gravitational-Wave Data: Deciphering the Symphony of Black Holes and the Early Universe
APA
Çalışkan, M. (2025). Beyond Gaussianity in Gravitational-Wave Data: Deciphering the Symphony of Black Holes and the Early Universe. Perimeter Institute. https://pirsa.org/25110116
MLA
Çalışkan, Mesut. Beyond Gaussianity in Gravitational-Wave Data: Deciphering the Symphony of Black Holes and the Early Universe. Perimeter Institute, Nov. 24, 2025, https://pirsa.org/25110116
BibTex
@misc{ pirsa_PIRSA:25110116,
doi = {10.48660/25110116},
url = {https://pirsa.org/25110116},
author = {{\c C}al{\i}{\c s}kan, Mesut},
keywords = {Cosmology},
language = {en},
title = {Beyond Gaussianity in Gravitational-Wave Data: Deciphering the Symphony of Black Holes and the Early Universe},
publisher = {Perimeter Institute},
year = {2025},
month = {nov},
note = {PIRSA:25110116 see, \url{https://pirsa.org}}
}
Mesut Çalışkan Johns Hopkins University - Department of Physics & Astronomy
Collection
Talk Type
Scientific Series
Subject
Abstract
Upcoming gravitational-wave detectors offer unprecedented potential for probing early-universe physics. They are expected to be sensitive to a wide range of primordial stochastic gravitational-wave backgrounds generated by processes such as inflationary dynamics, phase transitions, and cosmic strings. Extracting these signals requires reliable separation of cosmological backgrounds from the backgrounds produced by unresolved astrophysical sources.
I will review the expected astrophysical diversity of the SGWB and report our latest predictions for the background induced by massive black hole binaries. I will then examine how these astrophysical foregrounds impact sensitivity to early-Universe induced gravitational-wave backgrounds and discuss the central challenge of separating multiple overlapping components.
I will present a new approach to disentangle astrophysical from cosmological contributions by exploiting non-Gaussianities in the gravitational-wave data through wavelet scattering transforms. This method extracts statistical information that is inaccessible to standard analysis techniques.
Finally, I will provide a pedagogical explanation of the mathematical framework underlying wavelet scattering transforms and highlight their physical interpretation using our recent analytical results for Gaussian processes. These results clarify how scattering statistics capture and characterize non-Gaussian signatures in gravitational-wave data.