Gravity.jl: Fast and accurate gravitational lens modeling in Julia

We present Gravity.jl , a new proprietary software for the modeling of gravitational lens systems. Gravity.jl is written in the Julia programming language, and is designed to be fast, accurate, and flexible. It can be used to model gravitational lens systems composed of multiple lensing planes, and to perform Bayesian inference on the lens model parameters. In this paper we present the theoretical and statistical ideas behind the code, and we describe its main features. In this first paper of the series, we focus on the modeling of point-like and small extended sources, for which we can linearize the lens equation. We show a practical use of Gravity.jl on a galaxy-scale lens, and we compare the results with those obtained with other codes. We also show how Gravity.jl can be used to perform Bayesian inference on cosmological parameters.

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Publication Details

Journal
Astronomy and Astrophysics
Published
2024-09-14
DOI
https://doi.org/10.1051/0004-6361/202451214
Citations
5
Primary Topic
Geophysics and Gravity Measurements
Type
article
Field-Weighted Citation Impact
2.40
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article

Gravity.jl: Fast and accurate gravitational lens modeling in Julia

Marco Lombardi
5 citations
Astronomy and Astrophysics
Geophysics and Gravity Measurements
2.40
article

Gravity.jl: Fast and accurate gravitational lens modeling in Julia

Marco Lombardi
article en
5 citations

Abstract

We present Gravity.jl , a new proprietary software for the modeling of gravitational lens systems. Gravity.jl is written in the Julia programming language, and is designed to be fast, accurate, and flexible. It can be used to model gravitational lens systems composed of multiple lensing planes, and to perform Bayesian inference on the lens model parameters. In this paper we present the theoretical and statistical ideas behind the code, and we describe its main features. In this first paper of the series, we focus on the modeling of point-like and small extended sources, for which we can linearize the lens equation. We show a practical use of Gravity.jl on a galaxy-scale lens, and we compare the results with those obtained with other codes. We also show how Gravity.jl can be used to perform Bayesian inference on cosmological parameters.

Astronomy and AstrophysicsVol. 690
University of Milan (IT)
Openalex Percentile: Top 12%
Geophysics and Gravity Measurements
2.40
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