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

Solar spicules are ubiquitous and strongly overlapping 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 construct a stochastic three-dimensional spicule-population model and synthesize Mg II k spectra with radiative transfer, including instrumental degradation and photon noise. We then constrain the hyperparameters that describe the underlying spicule population with likelihood-free Bayesian inference based on 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.