TD-CARMA: Painless, Accurate, and Scalable Estimates of Gravitational Lens Time Delays with Flexible CARMA Processes

نویسندگان

چکیده

Cosmological parameters encoding our understanding of the expansion history Universe can be constrained by accurate estimation time delays arising in gravitationally lensed systems. We propose TD-CARMA, a Bayesian method to estimate cosmological modelling observed and irregularly sampled light curves as realizations Continuous Auto-Regressive Moving Average (CARMA) process. Our model accounts for heteroskedastic measurement errors microlensing, an additional source independent extrinsic long-term variability brightness. The semi-separable structure CARMA covariance matrix allows fast scalable likelihood computation using Gaussian Process modeling. obtain sample from joint posterior distribution nested sampling approach. This ``painless'' Computation, dealing with expected multi-modality straightforward manner not requiring specification starting values or initial guess delay, unlike existing methods. In addition, proposed procedure automatically evaluates evidence, allowing us perform principled selection. TD-CARMA is parsimonious, typically includes no more than dozen unknown parameters. apply six doubly quasars HS 2209+1914, SDSS J1001+5027, J1206+4332, J1515+1511, J1455+1447, J1349+1227, estimating their $-21.96 \pm 1.448$, $120.93 1.015$, $111.51 1.452$, $210.80 2.18$, $45.36 1.93$ $432.05 1.950$ respectively. These estimates are consistent those derived relevant literature, but two four times precise.

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ژورنال

عنوان ژورنال: The Astrophysical Journal

سال: 2023

ISSN: ['2041-8213', '2041-8205']

DOI: https://doi.org/10.3847/1538-4357/acbea1