Integrating shear and flexion into cluster reconstruction pipelines

Jacob Shpiece

doi:10.17918/00011539

Galaxy clusters are the most massive gravitationally bound systems in the Universe and serve as uniquely sensitive laboratories for the nature of dark matter and the history of structure formation. Their mass distributions encode the cumulative imprint of hierarchical assembly, while their substructure populations test predictions of the [lambda]CDM model on the subgalactic scales where alternative dark matter physics may leave observable signatures. Weak gravitational lensing offers a uniquely direct route to mapping cluster mass distributions independent of the dynamical or baryonic state of the system, but conventional shear-only reconstructions are limited in their ability to resolve the small-scale features that are most diagnostic of the underlying cosmology. This thesis develops and applies a new framework for cluster mass reconstruction that integrates weak-lensing shear with first (F) and second (G) flexion within a unified statistical pipeline. I first establish the theoretical foundation of [lambda]CDM cosmology, dark matter halos, and the gravitational lensing formalism, including the higher-order flexion observables that probe the gradient and curvature of the convergence field. I then present a taxonomic review of existing multi-signal cluster reconstruction methods, organizing them by mass representation and inference strategy and identifying the underpopulated region of design space that motivates the work that follows. I introduce ARCH (Adaptive Reconstruction of Cluster Halos), a staged optimization pipeline combining candidate seeding, local optimization, physical filtering, forward selection, and global strength refinement, with signal contributions weighted by per-source uncertainties. Applied to JWST imaging of Abell 2744 and El Gordo, ARCH recovers convergence maps and subcluster masses consistent with published weak- and strong-lensing analyses: the Abell 2744 core mass within 300 h⁻¹ kpc is recovered at 2.1 x 10¹⁴ M_[Sun]h⁻¹, and the El Gordo NW and SE clumps at 2.6 x 10¹⁴ and 2.3 x 10¹⁴ M_[Sun]h⁻¹ respectively, with jackknife uncertainties at the 10¹²-10¹³ M_[Sun]h⁻¹ level. The all-signal and shear+F configurations consistently produce the most stable reconstructions, demonstrating that flexion enhances sensitivity to cluster substructure when anchored by shear, while flexion-only combinations remain unstable in cluster fields. I further extend ARCH to incorporate strong-lensing constraints alongside the existing weak-lensing signals, enabling tighter recovery of cluster cores, and discuss prospective applications including improved constraints on the subhalo mass function, lensing-based tests of dark matter properties, and the systematic exploitation of high-density JWST cluster fields. Together, these results demonstrate that flexion-inclusive, multi-signal reconstruction is a practical and powerful tool for cluster-scale lensing in the JWST era, extending the reach of weak-lensing dark matter mapping into the substructure regime.

Integrating shear and flexion into cluster reconstruction pipelines

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Integrating shear and flexion into cluster reconstruction pipelines

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