Cake Talk by Kartheik Iyer
The star formation histories (SFHs) of galaxies contain a wealth of information about the physical processes responsible for regulating star formation over time. Studying the SFHs of galaxies at different epochs therefore charts the growth of individual galaxies over cosmic time, and provides a fuller picture of how galaxy populations at different epochs are connected. In this talk, we'll cover (i) the state of the art in Bayesian techniques that recover non-parametric SFHs from spectrophotometric data, (ii) how they are applied to current and upcoming surveys using HST & JWST, (iii) what we can learn from these SFHs in terms of robust masses, star formation rates and timescales, (iv) how SFHs in cosmological simulations agree (and disagree) amongst themselves and with the observations, (v) how this ties to the input physics and numerical prescriptions and (vi) how we can push the envelope using physically motivated models for the auto-covariance function of galaxy SFHs.