[Paper Review] Microlensing of strongly lensed quasars

G. Vernardos, Dominique Sluse+10 more|arXiv (Cornell University)|Dec 1, 2023

Galaxies: Formation, Evolution, Phenomena4 citations

TL;DR

This review synthesizes the theoretical foundations, current methods, and key scientific insights from quasar microlensing, a technique that maps quasar structures at sub-microarcsecond scales using gravitational lensing by compact objects in lensing galaxies. It highlights advances in probing accretion disk and broad-line region sizes, mass functions, and cosmological parameters, while identifying challenges in systematic biases and future potential from next-generation surveys and machine learning.

ABSTRACT

Strong gravitational lensing of quasars has the potential to unlock the poorly understood physics of these fascinating objects, as well as serve as a probe of the lensing mass distribution and of cosmological parameters. In particular, gravitational microlensing by compact bodies in the lensing galaxy can enable mapping of quasar structure to $\lt 10^{-6}$ arcsec scales. Some of this potential has been realized over the past few decades, however the upcoming era of large sky surveys promises to bring this to full fruition. Here we review the theoretical framework of this field, describe the prominent current methods for parameter inference from quasar microlensing data across different observing modalities, and discuss the constraints so far derived on the geometry and physics of quasar inner structure. We also review the application of strong lensing and microlensing to constraining the granularity of the lens potential, i.e. the contribution of the baryonic and dark matter components, and the local mass distribution in the lens, i.e. the stellar mass function. Finally, we discuss the future of the field, including the new possibilities that will be opened by the next generation of large surveys and by new analysis methods now being developed.

Motivation & Objective

• To synthesize the theoretical and observational state of quasar microlensing for probing quasar inner structure at <10−6 arcsec scales.
• To review current methods for parameter inference from microlensing light curves across different observing modalities.
• To assess constraints on quasar accretion disk and broad-line region geometry and physics derived from microlensing.
• To examine the role of microlensing in probing the granularity of lens potential and local mass distributions, including stellar mass functions.
• To outline future directions, including the impact of large-scale surveys and emerging analysis techniques like machine learning.

Proposed method

• Theoretical modeling of microlensing magnification patterns using ray-shooting simulations and ray-tracing techniques to simulate light deflection by compact masses.
• Bayesian inference with Markov Chain Monte Carlo (MCMC) sampling to estimate source size, structure, and lens parameters from observed light curves.
• Use of high-resolution microlensing maps to model the response of accretion disks and broad-line regions to microlensing magnification.
• Application of machine learning for fast generation of magnification maps and direct parameter inference, reducing reliance on computationally expensive likelihood evaluations.
• Integration of multi-epoch photometric and spectroscopic data to constrain time delays and reverberation signals in microlensed quasars.
• Development of robust triggers and predictors for high-magnification events (HMEs) to optimize data collection from upcoming surveys like LSST.

Figure 1: Illustration of the effect of microlensing on a source, in this case, the coat-of-arms of Bern, Switzerland, the seat of the International Space Science Institute, where the “Strong Gravitational Lensing” workshop was held between 18-22 of July 2022 that lead to the writing of this review.

Experimental results

Research questions

• RQ1 How can microlensing be used to map the structure of quasar accretion disks and broad-line regions at sub-microarcsecond resolution?
• RQ2 What constraints do microlensing observations place on the size and geometry of the quasar emission regions?
• RQ3 To what extent can microlensing probe the stellar mass function and dark matter distribution in lensing galaxies?
• RQ4 How do systematic biases in modeling (e.g., in BLR vs. disk fitting) affect the accuracy of inferred source sizes?
• RQ5 What role can machine learning and new data analysis techniques play in overcoming computational and modeling challenges in microlensing?

Key findings

• Microlensing enables mapping of quasar structures at scales below 10−6 arcsec, revealing substructure in accretion disks and broad-line regions.
• Current modeling of the broad-line region (BLR) and accretion disk together limits the range of viable models, with only a small fraction of realizations successfully reproducing observed light curves.
• Systematic uncertainties in BLR modeling are significant, particularly due to the need for high-resolution, large-scale microlensing maps and the blending of BLR and disk emission in broad-band fluxes.
• Despite high computational costs, only a small number of model realizations (tens out of millions) successfully reproduce the data, suggesting potential need for more complex models or improved noise modeling.
• Machine learning shows promise for accelerating magnification map generation and direct parameter inference, potentially reducing reliance on slow Bayesian sampling.
• The advent of large surveys like LSST will demand new, scalable analysis methods and robust HME triggers to fully exploit microlensing's potential for cosmological and astrophysical discovery.

Figure 2: Multiply imaged quasar Q 2237+0305. Left: the lensed quasar seen through the central regions of a foreground spiral galaxy-lens (credits: J. Rhoads, S. Malhotra, I. Dell’Antonio, NOAO/WIYN/NSF). Right: zoom on the bulge of the galaxy-lens seen in the centre, surrounded by multiple images o