Speaker
Description
This work uses Lick indices to derive an independent, cosmology-free measurement of the Hubble parameter H(z), focusing on massive, passive galaxies at low redshift (z<0.4) from SDSS Legacy data. Unlike prior studies based on Full Spectral Fitting (FSF) or the D4000 spectral feature, we adopt a novel combined Lick index approach. Two Stellar Population Synthesis models are employed: Thomas, Maraston & Johansson (2011) and the updated model from Knowles et al. (2021). A critical analysis of systematic effects is presented, highlighting the importance of index selection and the superiority of stacked spectra (from galaxies grouped by velocity dispersion and redshift) over single-galaxy spectra. We introduce a new method to model velocity dispersion effects in the Knowles framework.
We observe oscillatory redshift trends for certain Balmer and iron indices, affecting the inferred t(z). Relations for the evolution of galaxy age, metallicity, and $\alpha$/Fe with mass are obtained and compared with literature results. Central to this study are H(z) estimates derived using a cosmographic H(z;H$_0$,q$_0$,j$_0$...) approach, covering the redshift range up to $0.4$. Besides the H(z) estimation we recover posterior probabilities for the cosmographic parameters, among which we have H$_0$. Without the introduction of Gaussian priors or refining the data selection by removing bad quality sets of data, we find H$_0 = 76.7^{+8.7} _{-6.2}$ km s$^{-1}$ Mpc$^{-1}$. When some outliers are cut out and Gaussian priors on q$_0$ and j$_0$ introduced, the posterior of H$_0$ contracts down to $70.95^{+3.45} _{-3.40}$ km s$^{-1}$ Mpc$^{-1}$.
These findings highlight the utility of Lick indices in providing H(z) measurements while emphasizing the need to mitigate systematic uncertainties, and pave the way for an extension of our work at higher redshift, fully exploiting the BOSS and eBOSS data and future spectra at z>1.0.
