Estimating Time Delay in Gravitationally Lensed Fluxes

Authors Peter Tino, Juan C. Cuevas-Tello, Somak Raychaudhury



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Author Details

Peter Tino
Juan C. Cuevas-Tello
Somak Raychaudhury

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Peter Tino, Juan C. Cuevas-Tello, and Somak Raychaudhury. Estimating Time Delay in Gravitationally Lensed Fluxes. In Similarity-based learning on structures. Dagstuhl Seminar Proceedings, Volume 9081, pp. 1-3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009) https://doi.org/10.4230/DagSemProc.09081.5

Abstract

We study the problem of estimating the time delay between two signals representing delayed, irregularly sampled and noisy versions of the same underlying pattern. We propose  a kernel-based technique in the context of an astronomical problem, namely estimating the time delay between
two gravitationally lensed signals from a distant quasar.
We test the algorithm on several artificial data sets, and
also on real astronomical observations. By carrying out a statistical analysis of the results we present a detailed comparison of our method with the most popular methods for time delay estimation in astrophysics. Our method yields more accurate and more stable time delay estimates. Our  methodology can be readily applied to current state-of-the-art optical monitoring data in astronomy, but can also be applied in other disciplines involving similar time series data.

Subject Classification

Keywords
  • Time series
  • kernel regression
  • statistical analysis
  • evolutionary algorithms
  • mixed representation

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