Solar spicule population properties inferred from IRIS Mg II k off-limb spectra using likelihood-free Bayesian inference

Abstract

Solar spicules are ubiquitous and strongly overlap in off-limb observations, which complicates the interpretation of individual events. We aim to infer population-level properties of spicules from IRIS Mg II k off-limb spectra using a forward model that explicitly accounts for line-of-sight superposition and instrumental effects. We constructed a stochastic 3D spicule-population model and synthesized Mg II k spectra with radiative transfer, including instrumental degradation and photon noise. We then constrained the hyperparameters that describe the underlying spicule population with likelihood-free Bayesian inference. This approach combines approximate Bayesian computation and an adaptive population Monte Carlo sampler, comparing observed and simulated datasets through principal-component summary statistics at five heights above the limb. The inferred posterior constrains effective population-level properties of the spicules that dominate the observed Mg II k variability and height dependence. These constraints provide a route to connect off-limb spectroscopy with forthcoming spectropolarimetric diagnostics of the chromosphere--corona interface.

arXiv comment12 pages, 10 figures, accepted for publication in Astronomy & Astrophysics