BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//CERN//INDICO//EN
BEGIN:VEVENT
SUMMARY:Characterizing Background Signals in Red Giant Power Spectra
DTSTART:20260811T103000Z
DTEND:20260811T113000Z
DTSTAMP:20260803T014400Z
UID:indico-event-9403@scitalks.tifr.res.in
DESCRIPTION:Speakers: Anohita Mallick (DAA\, TIFR)\n\nThe background compo
 nent of red giant power spectra\, comprising granulation and mesogranulati
 on signals\, is commonly modeled using scaling relations that assume these
  signals behave self-similarly. Using ∼9\,300 Kepler red giants with ste
 llar parameters from a crossmatch with APOGEE\, we model the background co
 mponents and infer empirical scaling relations for the characteristic freq
 uencies and amplitudes of both signals as functions of surface gravity\, e
 ffective temperature\, and metallicity within a Bayesian framework\, testi
 ng for deviations from simple scaling behavior using flexible\, data-drive
 n models.\nWe extend this characterization of the background signal to tes
 t whether it also carries diagnostic information on stellar multiplicity\,
  as a complement to traditional  detection methods. We construct syntheti
 c asteroseismic power spectra reproducing Kepler observations\, with binar
 ies modeled as flux-weighted combinations of two stellar power spectra spa
 nning merged\, overlapping\, and widely separated oscillation components. 
 A gradient-boosted tree classifier is trained on 40\,000 such spectra to i
 dentify binaries via global power spectrum morphology and is validated aga
 inst known classifications in literature.\nTogether\, these two analyses u
 se detailed modeling of the background signal in red giant power spectra t
 o place new constraints on convective processes and to develop an extendab
 le framework for identifying unresolved binaries\, with applicability to l
 arger Kepler samples and future PLATO data.\n\nhttps://scitalks.tifr.res.i
 n/event/9403/
LOCATION:AG-66
URL:https://scitalks.tifr.res.in/event/9403/
END:VEVENT
END:VCALENDAR