Lenstool

Lenstool
Name	Lenstool
Developer	Institut de Recherche en Astrophysique et Planétologie
Initial release	1993
Latest release	(varies)
Programming language	C, Fortran, Python
Operating system	Unix-like, Linux, macOS
Genre	Astrophysical modelling, Gravitational lensing

Lenstool

Lenstool is a software package for modelling strong gravitational lensing by galaxy clusters, galaxies, and compact mass distributions. It is used by researchers working with observational facilities and surveys to infer mass distributions and cosmological parameters from lensing observables. The code integrates with data from telescopes and collaborations, enabling comparisons between models and images produced by instruments.

Overview

Lenstool is employed by teams associated with observatories and institutions such as European Southern Observatory, Hubble Space Telescope, James Webb Space Telescope, Subaru Telescope, Canada–France–Hawaii Telescope, Atacama Large Millimeter/submillimeter Array, Very Large Telescope, Keck Observatory, Gemini Observatory, ALMA Regional Centre, Space Telescope Science Institute, Max Planck Society, Centre National de la Recherche Scientifique, National Aeronautics and Space Administration, European Space Agency, National Science Foundation, National Research Council (Canada), Institute for Advanced Study, Harvard-Smithsonian Center for Astrophysics, California Institute of Technology, Princeton University, Massachusetts Institute of Technology, University of Cambridge, University of Oxford, University of Zurich, University of Tokyo, Kavli Institute for the Physics and Mathematics of the Universe, Jet Propulsion Laboratory, Stanford University, Yale University, Columbia University, University of California, Berkeley, University of Chicago, Leiden University, University of Edinburgh, University of Toronto, Utrecht University, University of California, Santa Cruz, Australian National University, Research School of Astronomy and Astrophysics.

The package has been cited in publications by groups working on lens modelling alongside survey projects such as Sloan Digital Sky Survey, Dark Energy Survey, COSMOS, CANDELS, CLASH, Frontier Fields, Euclid, LSST, Pan-STARRS, KiDS.

Features and Capabilities

Lenstool provides parametric lens modelling, optimization, and Bayesian inference used by teams analysing data from Hubble Space Telescope programs and ground-based campaigns. It supports mass components tied to luminous tracers such as models informed by Sérsic profile fits from imaging analyzed in pipelines from GALFIT and catalogues from SExtractor. The code includes support for cluster-scale halos, galaxy-scale halos, external shear, and multi-plane configurations employed in joint analyses with spectroscopic data from Keck Observatory and Very Large Telescope instruments like DEIMOS and VIMOS.

For statistical inference, Lenstool integrates Markov Chain Monte Carlo samplers and optimization strategies comparable to those used in studies at Planck Collaboration, WMAP, BOSS, and eBOSS. It produces critical curves, caustics, magnification maps, and time-delay predictions relevant for programmes such as H0LiCOW and transient follow-up by Zwicky Transient Facility, Pan-STARRS and LSST Science Collaboration.

Methodology and Algorithms

Lenstool implements parametric mass models including dual Pseudo-Isothermal Elliptical Mass Distributions inspired by analyses performed by groups at University of Montreal and others, and analytic profiles like Navarro–Frenk–White used by researchers associated with Princeton University and Kavli Institute. Optimization uses Bayesian likelihoods and priors following frameworks adopted in work by Bradac et al., Jullo et al., and teams collaborating with CosmoMC and other inference packages. The MCMC sampling and error estimation methods are analogous to techniques used in cosmological parameter estimation by Planck Collaboration and model comparison methods from Akaike Information Criterion and Bayesian Information Criterion studies.

Lenstool supports ray-tracing algorithms and source-plane reconstruction methods akin to approaches used in lensing analyses by groups at Max Planck Institute for Astrophysics, Institute for Computational Cosmology, and CEA Saclay. Multi-plane ray-tracing and perturbative corrections align with theoretical formalisms from researchers at Institute for Advanced Study and Perimeter Institute.

Applications and Usage

Researchers apply Lenstool to reconstruct mass distributions in galaxy clusters such as Abell 1689, MACS J1149.5+2223, Abell 2744, CL0024+17, RX J1347.5-1145, Bullet Cluster, MACS J0717.5+3745, and to model galaxy-scale lenses used in studies involving COSMOS field galaxies and quasar lens systems like SDSS J1029+2623 and lenses from the CASTLES database. Its outputs inform dark matter studies linking to theories advanced by Vera Rubin, Fritz Zwicky, and numerical simulations conducted by teams using codes such as GADGET, AREPO, and RAMSES at institutions including Lawrence Berkeley National Laboratory and Los Alamos National Laboratory.

Lenstool is used in the analysis pipeline for time-delay cosmography projects associated with H0LiCOW and TDCOSMO, supporting constraints on the Hubble constant alongside datasets from Planck Collaboration, SH0ES programme, Riess et al., and gravitational-wave standard-siren measurements by LIGO Scientific Collaboration and Virgo Collaboration.

Development and History

Originally developed in the 1990s by groups connected to Institut de Recherche en Astrophysique et Planétologie and collaborators at institutions like Observatoire de Paris, the code evolved through contributions from teams affiliated with Laboratoire d'Astrophysique de Marseille, Université Grenoble Alpes, CEA, CNRS, and international partners at University of California, Santa Barbara and University of Hawaii. The project has been advanced through collaborations with survey consortia including HST Frontier Fields teams and cluster lensing working groups at European Southern Observatory.

Over successive versions, Lenstool incorporated modules for interoperability with analysis tools and languages used at NASA Goddard Space Flight Center, Space Telescope Science Institute, Astropy Project, and simulation toolchains from NumPy and SciPy ecosystems. The software development has paralleled methodological advances documented in conference proceedings from meetings of the American Astronomical Society, International Astronomical Union, European Astronomical Society, and summer schools hosted at Kavli Summer Program and Les Houches.

Category:Astronomical software