Simulating time-varying strong lenses

TL;DR

This paper introduces MOLET, a software tool for simulating time-varying strong lensing systems, addressing the lack of time dimension modeling crucial for accurate time delay and H0 measurements.

Contribution

The paper presents a new, versatile software package that models the time dimension in strong lensing simulations, enabling more accurate analysis of variable lensed sources.

Findings

Observation cadence significantly affects time delay recovery.

Multi-wavelength data improves measurement accuracy.

Simulation demonstrates the importance of physical variability modeling.

Abstract

We present a self-consistent and versatile forward modelling software package that can produce time series and pixel-level simulations of time-varying strongly lensed systems. The time dimension, which needs to take into account different physical mechanisms for variability such as microlensing, has been missing from existing approaches and it is of direct relevance to time delay, and consequently H0, measurements and caustic crossing event predictions. Such experiments are becoming more streamlined, especially with the advent of time domain surveys, and understanding their systematic and statistical uncertainties in a model-aware and physics-driven way can help improve their accuracy and precision. Here we demonstrate the software's capabilities by exploring the effect of measuring time delays from lensed quasars and supernovae in many wavelengths and under different microlensing and intrinsic variability assumptions. In this initial application, we find that the cadence of the observations and combining information from different wavelengths plays an important role in the correct recovery of the time delays. The Mock Lenses in Time (MOLET) software package is available at: \url{https://github.com/gvernard/molet}