Statistical Strong Lensing V. Inference with Microlensed Quasars
Abstract
Microlensing of strongly lensed quasars provides direct information on the stellar component of lens galaxies, and can help break the degeneracy between the stellar initial mass function (IMF) and the dark matter. However, a statistical framework to forward model microlensing data while accounting for strong lensing selection effects is still missing. We incorporated microlensing effects into the hierarchical model of Paper III, and investigated to what extent flux measurements of strongly lensed quasars can break the degeneracy between the stellar IMF and the dark matter distribution. We tested the method on a mock sample of 219 doubly imaged quasars, lensed by circularly symmetric lenses. When microlensing effects are modelled, the inference using image fluxes recovers the input foreground population parameters and provides tighter constraints than the inference without flux constraints. The improvement is clearest in the μα−μ5 plane, where μα describes the mean stellar population synthesis mismatch parameter logαSPS and μ5 describes the mean projected dark matter mass within 5 kpc. The 68% credible interval on μα shrinks from 0.16 dex to 0.09 dex, with the degeneracy between μα and μ5 significantly reduced. By contrast, fitting the image fluxes without accounting for microlensing leads to large biases on the inferred parameters. This work is a first step towards an accurate modelling of microlensing data. Application to real lens samples will require dropping the circular symmetry assumption and adopting more realistic models for the microlensing magnification.
Related
- Late-time distance consistency and model-independent curvature inference with strong lensing, quasars, and galaxy clusters
- Quasars Microlensed by Milky Way Stars: Two Upcoming Events Predicted with Gaia Data Release 3
- Discovering Substellar Dark Matter Halos with Astrometric Weak Lensing of Multiply Imaged Quasars
- Statistical properties of the convergence due to weak gravitational lensing by non-linear structures
- Strong-lensing perturber signatures in self-interacting dark matter simulations
BibTeX
@misc{zhang2026statistical,
title = {{Statistical Strong Lensing V. Inference with Microlensed Quasars}},
author = {Shuo Zhang and Alessandro Sonnenfeld},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.24423},
eprint = {2610.24423},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.24423},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Statistical Strong Lensing V. Inference with Microlensed Quasars
AU - Shuo Zhang
AU - Alessandro Sonnenfeld
PY - 2026
DA - 2026/10/17
PB - arXiv
DO - 10.48550/arxiv.2610.24423
UR - https://arxiv.org/abs/2610.24423
AB - Microlensing of strongly lensed quasars provides direct information on the stellar component of lens galaxies, and can help break the degeneracy between the stellar initial mass function (IMF) and the dark matter. However, a statistical framework to forward model microlensing data while accounting for strong lensing selection effects is still missing. We incorporated microlensing effects into the hierarchical model of Paper III, and investigated to what extent flux measurements of strongly lensed quasars can break the degeneracy between the stellar IMF and the dark matter distribution. We tested the method on a mock sample of 219 doubly imaged quasars, lensed by circularly symmetric lenses. When microlensing effects are modelled, the inference using image fluxes recovers the input foreground population parameters and provides tighter constraints than the inference without flux constraints. The improvement is clearest in the μ_α−μ_5 plane, where μ_α describes the mean stellar population synthesis mismatch parameter logα_SPS and μ_5 describes the mean projected dark matter mass within 5 kpc. The 68% credible interval on μ_α shrinks from 0.16 dex to 0.09 dex, with the degeneracy between μ_α and μ_5 significantly reduced. By contrast, fitting the image fluxes without accounting for microlensing leads to large biases on the inferred parameters. This work is a first step towards an accurate modelling of microlensing data. Application to real lens samples will require dropping the circular symmetry assumption and adopting more realistic models for the microlensing magnification.
ER -