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VERSION:2.0
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SUMMARY:GWDALI: Derivative approximation for gravitational wave likelihood
 s
DTSTART:20241113T110000Z
DTEND:20241113T130000Z
DTSTAMP:20260703T064826Z
UID:433e9e2e-34c6-4cd6-9888-3c0d9e30ce86
SEQUENCE:2
CREATED:20241112T154711Z
DESCRIPTION:In the next decade\, third-generation gravitational wave (GW) 
 observatories\, such as the Einstein Telescope and Cosmic Explorer\, will 
 begin operation\, enabling the detection of compact object coalescences at
  unprecedented distances (up to z &lt\; 100). Analyzing these sources cosm
 ologically necessitates GW parameter inference\, which typically involves 
 around 15 parameters for each detection—a process that is computationall
 y intensive. To address this challenge\, we discuss the application of Der
 ivative Approximation for Likelihoods (DALI) in gravitational wave and cos
 mological data analysis. DALI is a more time-efficient approach that incor
 porates higher-order terms in the Taylor expansion of likelihoods\, which 
 is particularly advantageous when the expected posterior distributions dev
 iate from Gaussianity\, rendering the Fisher Matrix approximation unreliab
 le. Such deviations often occur in the context of GW signals from compact 
 binary coalescences\, especially in cases of parameter degeneracies\, such
  as the distance-inclination degeneracy. In this presentation\, we explore
  the behavior of gravitational wave DALI-posteriors under various paramete
 rizations of GW signals and demonstrate how their accuracy can be enhanced
  using automatic differentiation (autodiff).
LAST-MODIFIED:20241112T154730Z
LOCATION:Sala de Seminários do DF\,  Pavilhão de Física\, 2º piso
URL:http://df.vps.tecnico.ulisboa.pt/pt/eventos/gwdali-derivative-approxim
 ation-for-gravitational-wave-likelihoods/
X-ALT-DESC;FMTTYPE=text/html:<p data-block-key="z4h4o">In the next decade\
 , third-generation gravitational wave (GW) observatories\, such as the Ein
 stein Telescope and Cosmic Explorer\, will begin operation\, enabling the 
 detection of compact object coalescences at unprecedented distances (up to
  z &lt\; 100). Analyzing these sources cosmologically necessitates GW para
 meter inference\, which typically involves around 15 parameters for each d
 etection—a process that is computationally intensive.<br/><br/> To addre
 ss this challenge\, we discuss the application of Derivative Approximation
  for Likelihoods (DALI) in gravitational wave and cosmological data analys
 is. DALI is a more time-efficient approach that incorporates higher-order 
 terms in the Taylor expansion of likelihoods\, which is particularly advan
 tageous when the expected posterior distributions deviate from Gaussianity
 \, rendering the Fisher Matrix approximation unreliable.<br/><br/> Such de
 viations often occur in the context of GW signals from compact binary coal
 escences\, especially in cases of parameter degeneracies\, such as the dis
 tance-inclination degeneracy. In this presentation\, we explore the behavi
 or of gravitational wave DALI-posteriors under various parameterizations o
 f GW signals and demonstrate how their accuracy can be enhanced using auto
 matic differentiation (autodiff).</p>
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