TD-CARMA: Painless, accurate, and scalable estimates of gravitational-lens time delays with flexible CARMA processes

Antoine Meyer Speaker
Imperial College London
Wednesday, Aug 9: 11:55 AM - 12:15 PM
Topic-Contributed Paper Session 
Metro Toronto Convention Centre 
Cosmological parameters encoding our understanding of the expansion history of the Universe can be constrained by the accurate estimation of time delays arising in gravitationally lensed systems. We propose TD-CARMA, a Bayesian method to estimate cosmological time delays by modelling the observed and irregularly sampled light curves as realizations of a CARMA process. Our model accounts for heteroskedastic measurement errors and microlensing, an additional source of independent extrinsic long-term variability in source brightness. The semi-separable structure of the CARMA covariance matrix allows for fast and scalable likelihood computation using Gaussian Process modeling. We obtain a sample from the joint posterior distribution of the model parameters using a nested sampling approach. This allows for ``painless'' Bayesian Computation, dealing with the expected multi-modality of the posterior distribution and not requiring the specification of starting values or an initial guess for the time delay, unlike existing methods. Our time delay estimates for six doubly lensed quasars are consistent with those derived in the literature, but are typically two to four times more precise.