Paper 14145-260
Paper 14145-260
Determining PSF stability requirements for low-mass dark matter subhalo detection with the Habitable Worlds Observatory
8 July 2026 • 17:30 - 19:00 CEST | Room B4-M3
Abstract
Dark matter dominates the universe's mass, yet its fundamental nature remains unknown. Competing theories predict different populations of low-mass subhalos (~10^6-10^7 M_sun), below current detection limits (~10^8 M_sun). The upcoming Habitable Worlds Observatory (HWO) could reach this regime, but only if its point spread function (PSF) quality and stability are tightly controlled. We present HWO-SLAPS, a strong-lensing simulation and analysis pipeline that simulates galaxy-galaxy lenses with embedded subhalos, convolves them with a segmented-mirror PSF containing controlled aberrations and temporal drifts, and adds realistic detector noise. Using Fisher-matrix forecasts, we compute detection significance as a function of subhalo mass and PSF stability. We then map minimum detectable subhalo mass versus PSF wavefront error and drift, deriving quantitative PSF stability and engineering requirements for HWO and a general framework linking optics stability to dark-matter science yield.
Presenter
Georgios N. Vassilakis
Univ. of Cambridge (United Kingdom), Jet Propulsion Lab. (United States)
Georgios (George) Vassilakis is a PhD student in astrophysics and machine learning at the University of Cambridge, jointly based in DAMTP and the Institute of Astronomy, working on applications of machine learning for astronomical imaging. Before starting the PhD, George completed a BS in applied physics at Northeastern University and worked on weak-lensing data reduction for the Superpressure Balloon-borne Imaging Telescope (SuperBIT) and dark matter mass mapping. During a recent internship at NASA's Jet Propulsion Laboratory, he developed HWO-SLAPS, an end-to-end strong lensing analysis pipeline to connect Habitable Worlds Observatory PSF stability and segmented-mirror aberrations to low-mass dark matter subhalo detectability, providing quantitative engineering requirements for this key science case.