LensAgent is a training-free LLM agent framework that reconstructs mass distributions in SLACS strong lensing systems to extract sub-galactic substructures.
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Hierarchical Bayesian lensing+dynamics on 121 galaxies yields γ_PPN=1.027^{+0.099}_{-0.095} (GR-consistent) and 2σ evidence for increasing radial stellar anisotropy toward low redshift.
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LensAgent: A Self Evolving Agent for Autonomous Physical Inference of Sub-galactic Structure
LensAgent is a training-free LLM agent framework that reconstructs mass distributions in SLACS strong lensing systems to extract sub-galactic substructures.
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Joint constraints on gravity and stellar orbital anisotropy in massive galaxies
Hierarchical Bayesian lensing+dynamics on 121 galaxies yields γ_PPN=1.027^{+0.099}_{-0.095} (GR-consistent) and 2σ evidence for increasing radial stellar anisotropy toward low redshift.