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VBMicroLensing: three algorithms for multiple lensing with contour integration

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arxiv 2410.13660 v1 pith:K67COEJD submitted 2024-10-17 astro-ph.IM

classification astro-ph.IM
keywords algorithmsmultiplelensmicrolensingcomputationalequationlensesnumerical
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Modeling of microlensing events poses computational challenges for the resolution of the lens equation and the high dimensionality of the parameter space. In particular, numerical noise represents a severe limitation to fast and efficient calculations of microlensing by multiple systems, which are of particular interest in exoplanetary searches. We present a new public code built on our previous experience on binary lenses that introduces three new algorithms for the computation of magnification and astrometry in multiple microlensing. Besides the classical polynomial resolution, we introduce a multi-polynomial approach in which each root is calculated in a frame centered on the closest lens. In addition, we propose a new algorithm based on a modified Newton-Raphson method applied to the original lens equation without any numerical manipulation. These new algorithms are more accurate and robust compared to traditional single-polynomial approaches at a modest computational cost, opening the way to massive studies of multiple lenses. The new algorithms can be used in a complementary way to optimize efficiency and robustness.

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Cited by 1 Pith paper

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

  1. Twinkle: A GPU-based binary-lens microlensing code with contour integration method

    astro-ph.IM 2025-01 conditional novelty 7.0 of 10

    A GPU-optimized contour-integration microlensing code with refactored lens-equation coefficients and a new ghost-image detector achieves roughly 100x speedup over a single-threaded CPU reference.

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