Project Description
Parameter estimation of gravitational wave signals observed by LIGO and Virgo is vital for our understanding of the origin of the waves. The signals observed to date have all been from binary neutron stars and black holes, and our parameter estimation tools allow us to make measurements of the masses and spins of the black holes and neutron stars, which is vital information for astrophysics. It also allows us to locate where on the sky the system originated, which allows astronomers to find associated electromagnetic radiation. Such multimessenger observations have been transformative. Various parameter estimation tools are in use by the LIGO/Virgo collaboration. Most commonly used is software that performs Bayesian estimation and model selection using stochastic sampling. RapidPE and RIFT are other software tools that also perform Bayesian estimation, but do not use stochastic sampling to search high dimensional parameter spaces. RIFT is the preferred method to use when a signal is particularly complex. RapidPE is software similar to RIFT but intended to be used in online searches of gravitational wave data (rather than offline on archival data). This work will merge the features of RapidPE and RIFT to obtain a single, more versatile parameter estimation engine.
Tasks and Responsibilites
Assist with the merger of RapidPE and RIFT software tools to perform Bayesian estimation.
Desired Qualifications
None listed.