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Register a new userDeriving star formation histories from integrated light: Colors and indices
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We present results of a detailed study aiming at understanding to what precision star formation histories (SFHs) can be determined for distant galaxies observable in integrated light only. Using our evolutionary synthesis code, we have performed a set of simulations of galaxies with a wide range of different SFHs. By analysing the resulting colors, spectra and Lick indices, we investigate to which extent different SF scenarios can be discriminated on the basis of their photometric and spectral properties, respectively. We find the robust result that no later than 4 Gyrs after the latest episode of enhanced star formation all scenarios exhibit very similar colors and indices; in practice, it is not possible to distinguish different scenarios of star formation which have evolved for more than 1, at the utmost 3-4 Gyrs since the last star forming event, even when using spectral indices. For how long different SF scenarios can be disentangled highly depends on the range of colors available and absorption lines considered, as well as on the details of the SFHs to be compared.
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We examine the star formation histories (SFHs) of galaxies in smoothed particle hydrodynamics (SPH) simulations, compare them to parametric models that are commonly used in fitting observed galaxy spectral energy distributions, and examine the efficacy of these parametric models as practical tools for recovering the physical parameters of galaxies. The commonly used tau-model, with SFR ~ exp(-t/tau), provides a poor match to the SFH of our SPH galaxies, with a mismatch between early and late star formation that leads to systematic errors in predicting colours and stellar mass-to-light ratios. A one-parameter lin-exp model, with SFR ~ t*exp(-t/tau), is much more successful on average, but it fails to match the late-time behavior of the bluest, most actively star-forming galaxies and the passive, red and dead galaxies. We introduce a 4-parameter model, which transitions from lin-exp to a linear ramp after a transition time, which describes our simulated galaxies very well. We test the ability of these parametrised models to recover (at z=0, 0.5, and 1) the stellar mass-to-light ratios, specific star formation rates, and stellar population ages from the galaxy colours, computed from the full SPH star formation histories using the FSPS code of Conroy et al. (2009). Fits with tau-models systematically overestimate M/L by ~ 0.2 dex, overestimate population ages by ~ 1-2 Gyr, and underestimate sSFR by ~ 0.05 dex. Fits with lin-exp are less biased on average, but the 4-parameter model yields the best results for the full range of galaxies. Marginalizing over the free parameters of the 4-parameter model leads to slightly larger statistical errors than 1-parameter fits but essentially removes all systematic biases, so this is our recommended procedure for fitting real galaxies.
We combine new data from the main sequence (M_* versus SFR) of star-forming galaxies and galaxy colors (from GALEX to Spitzer) with a flexible stellar population scheme to deduce the mass-to-light ratio (Upsilon_*) of star-forming galaxies from the SPARC and S^4G samples. We find that the main sequence for galaxies, particular the low-mass end, combined with the locus of galaxy colors, constrains the possible star formation histories of disk and dwarf galaxies to a similar shape found by Speagle et al. (2014). Combining the deduced star formation history with stellar population models in the literature produces reliable Upsilon_* values as a function of galaxy color with an uncertainty of only 0.05 dex. We provide prescriptions to deduce Upsilon_* for optical and near-IR bandpasses, with near-IR bandpasses having the least uncertainty (Upsilon_* from 0.40 to 0.55). We also provide the community with a webtool, with flexible stellar population parameters, to generate their own Upsilon_* values over the wavelength range for most galaxy surveys.
A key uncertainty in galaxy evolution is the physics regulating star formation, ranging from small-scale processes related to the life-cycle of molecular clouds within galaxies to large-scale processes such as gas accretion onto galaxies. We study the imprint of such processes on the time-variability of star formation with an analytical approach tracking the gas mass of galaxies (regulator model). Specifically, we quantify the strength of the fluctuation in the star-formation rate (SFR) on different timescales, i.e. the power spectral density (PSD) of the star-formation history, and connect it to gas inflow and the life-cycle of molecular clouds. We show that in the general case the PSD of the SFR has three breaks, corresponding to the correlation time of the inflow rate, the equilibrium timescale of the gas reservoir of the galaxy, and the average lifetime of individual molecular clouds. On long and intermediate timescales (relative to the dynamical timescale of the galaxy), the PSD is typically set by the variability of the inflow rate and the interplay between outflows and gas depletion. On short timescales, the PSD shows an additional component related to the life-cycle of molecular clouds, which can be described by a damped random walk with a power-law slope of $betaapprox2$ at high frequencies with a break near the average cloud lifetime. We discuss star-formation burstiness in a wide range of galaxy regimes, study the evolution of galaxies about the main sequence ridgeline, and explore the applicability of our method for understanding the star-formation process on cloud-scale from galaxy-integrated measurements.
The impact of HST photometry and European astronomy in studies concerning the star formation histories of resolved galaxies is described. Our current knowledge of the star formation history of systems within 10-20 Mpc, as derived from the colour-magnitude diagrams of their resolved stellar populations, is reviewed, as well as the impact of these results on our understanding of galaxy evolution.
A new method of determining galaxy star-formation histories (SFHs) is presented. Using the method, the feasibility of recovering SFHs with multi-band photometry is investigated. The method divides a galaxys history into discrete time intervals and reconstructs the average rate of star formation in each interval. This directly gives the total stellar mass. A simple linear inversion solves the problem of finding the most likely discretised SFH for a given set of galaxy parameters. It is shown how formulating the method within a Bayesian framework lets the data simultaneously select the optimal regularisation strength and the most appropriate number of discrete time intervals for the reconstructed SFH. The method is demonstrated by applying it to mono-metallic synthetic photometric catalogues created with different input SFHs, assessing how the accuracy of the recovered SFHs and stellar masses depend on the photometric passband set, signal-to-noise and redshift. The results show that reconstruction of SFHs using multi-band photometry is possible, being able to distinguish an early burst of star formation from a late one, provided an appropriate passband set is used. Although the resolution of the recovered SFHs is on average inferior compared to what can be achieved with spectroscopic data, the multi-band approach can process a significantly larger number of galaxies per unit exposure time.
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