Fast and Reliable Time Delay Estimation of Strong Lens Systems Using Method of Smoothing and Cross-Correlation

TL;DR

This paper presents a new statistical approach combining smoothing and cross-correlation techniques to accurately estimate time delays in strong lensing systems, even with complex observational data.

Contribution

The paper introduces a novel method for time delay estimation that effectively handles data complexities, validated through recent lensing challenges.

Findings

Demonstrated reliable and precise time delay estimates

Effective handling of seasonal gaps and noise

Proven success in lensing challenges

Abstract

The observable time delays between the multiple images of strong lensing systems with time variable sources can provide us with some valuable information to probe the expansion history of the Universe. Estimation of these time delays can be very challenging due to complexities of the observed data where there are seasonal gaps, various noises and systematics such as unknown microlensing effects. In this paper we introduce a novel approach to estimate the time delays for strong lensing systems implementing various statistical methods of data analysis including the method of smoothing and cross-correlation. The method we introduce in this paper has been recently used in TDC0 and TDC1 Strong Lens Time Delay Challenges and has shown its power in reliable and precise estimation of time delays dealing with data with different complexities.