BEGIN:VCALENDAR VERSION:2.0 PRODID:-//linuxsoftware.nz//NONSGML Joyous v1.4//EN BEGIN:VEVENT SUMMARY:Black Hole Spectroscopy Tools for Waveform Modelling DTSTART:20250508T143000Z DTEND:20250508T160000Z DTSTAMP:20260615T033018Z UID:96b5c220-7b82-4b70-96b6-732f384bdb4f SEQUENCE:1 CREATED:20250505T140951Z DESCRIPTION: Next-generation gravitational-wave detectors will have enough sensitivity to resolve multiple ringdown frequencies from binary black ho le mergers. This requires high-fidelity waveform models to extract as much information as possible from these signals and perform tests of general r elativity. In this talk\, I will introduce two public tools for extracting the quasinormal mode amplitudes of binary black hole systems: qnmfits\, w hich uses linear least-squares fitting\, and NRSurr3dq8_RD\, a surrogate m odel that uses machine learning to predict these amplitudes as well as rem nant parameters for areas of parameter space where we lack simulations. Wi th these tools at hand\, one can easily build analytical ringdown waveform s. LAST-MODIFIED:20250505T140951Z LOCATION:DF Seminar Room (2-8.3)\, 2nd floor of Physics Building URL:http://df.vps.tecnico.ulisboa.pt/en/events/black-hole-spectroscopy-too ls-for-waveform-modelling/ X-ALT-DESC;FMTTYPE=text/html:

Next-generation gr avitational-wave detectors will have enough sensitivity to resolve multipl e ringdown frequencies from binary black hole mergers. This requires high- fidelity waveform models to extract as much information as possible from t hese signals and perform tests of general relativity.

In this ta lk\, I will introduce two public tools for extracting the quasinormal mode amplitudes of binary black hole systems: qnmfits\, which uses linear leas t-squares fitting\, and NRSurr3dq8_RD\, a surrogate model that uses machin e learning to predict these amplitudes as well as remnant parameters for a reas of parameter space where we lack simulations. With these tools at han d\, one can easily build analytical ringdown waveforms.

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