English

FEADME: Fast Elliptical Accretion Disk Modeling Engine

High Energy Astrophysical Phenomena 2025-12-12 v1

Abstract

We present FEADME (Fast Elliptical Accretion Disk Modeling Engine), a GPU-accelerated Python framework for modeling broad Balmer-line emission using a relativistic elliptical accretion-disk formalism. Leveraging Jax and NumPyro for differentiable forward modeling and efficient Bayesian inference, FEADME enables large-sample, reproducible analyses of disk-dominated emission-line profiles. We apply the framework to 237 double-peaked emitters (DPEs) from the literature and to five tidal disruption events (TDEs) with disk-like Hα\alpha emission, fitting three physically motivated model families per spectrum and selecting the preferred model using approximate leave-one-out (LOO) cross-validation. We find that AGN exhibit a broad, continuous distribution of disk geometries and kinematics, with significant diversity in disk parameters. Most TDE disk parameter distributions are statistically indistinguishable from those of the AGN, with the sole robust difference being that TDE disks are significantly more circular, consistent with rapid debris circularization in tidal disruption events. The majority of both AGN and TDEs favor models that include both a disk and an additional broad-line component, suggesting that disk emission commonly coexists with more isotropic or wind-driven gas. These results indicate that once a line-emitting disk forms, its spectroscopic appearance is governed by similar physical processes in both persistent AGN and transient TDE accretion flows, and they demonstrate the utility of FEADME for population-level studies of disk structure in galactic nuclei.

Keywords

Cite

@article{arxiv.2512.10228,
  title  = {FEADME: Fast Elliptical Accretion Disk Modeling Engine},
  author = {Nicholas Earl and K. Decker French and Jason T. Hinkle and Yashasvi Moon and Margaret Shepherd and Margaret E. Verrico},
  journal= {arXiv preprint arXiv:2512.10228},
  year   = {2025}
}

Comments

20 pages, 7 figures, pending submission to ApJ

R2 v1 2026-07-01T08:19:50.768Z