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lenstronomy II: A gravitational lensing software ecosystem

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arxiv 2106.05976 v1 pith:FRGHCPS4 submitted 2021-06-10 astro-ph.CO astro-ph.GAastro-ph.IM

classification astro-ph.COastro-ph.GAastro-ph.IM
keywords lenstronomylensingsoftwarecommunitygravitationalanalysesbecomebirrer
verification ladder T0 review T1 audit T2 compute T3 formal
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lenstronomy is an Astropy-affiliated Python package for gravitational lensing simulations and analyses. lenstronomy was introduced by Birrer and Amara (2018) and is based on the linear basis set approach by Birrer et a. (2015). The user and developer base of lenstronomy has substantially grown since then, and the software has become an integral part of a wide range of recent analyses, such as measuring the Hubble constant with time-delay strong lensing or constraining the nature of dark matter from resolved and unresolved small scale lensing distortion statistics. The modular design has allowed the community to incorporate innovative new methods, as well as to develop enhanced software and wrappers with more specific aims on top of the lenstronomy API. Through community engagement and involvement, lenstronomy has become a foundation of an ecosystem of affiliated packages extending the original scope of the software and proving its robustness and applicability at the forefront of the strong gravitational lensing community in an open source and reproducible manner.

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Cited by 5 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

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    astro-ph.CO 2025-11 conditional novelty 6.0 of 10

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  4. JWST lensed quasar dark matter survey IV: Stringent warm dark matter constraints from the joint reconstruction of extended lensed arcs and quasar flux ratios

    astro-ph.CO 2025-11 conditional novelty 6.0 of 10

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  5. Analyzing Line-of-sight selection biases in galaxy-scale strong lensing with external convergence and shear

    astro-ph.CO 2025-06 conditional novelty 6.0 of 10

    A hybrid simulation method predicts line-of-sight convergence and shear distributions for strong lenses, showing that neglecting them biases inferred Hubble constant values by up to about one percent.

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