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Register a new userStochastic modelling of star-formation histories II: star-formation variability from molecular clouds and gas inflow
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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.
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Giant molecular clouds (GMCs) are the primary reservoirs of cold, star-forming molecular gas in the Milky Way and similar galaxies, and thus any understanding of star formation must encompass a model for GMC formation, evolution, and destruction. These models are necessarily constrained by measurements of interstellar molecular and atomic gas, and the emergent, newborn stars. Both observations and theory have undergone great advances in recent years, the latter driven largely by improved numerical simulations, and the former by the advent of large-scale surveys with new telescopes and instruments. This chapter offers a thorough review of the current state of the field.
Galaxy evolution is generally affected by tidal interactions. Firstly, in this series, we reported several effects which suggest that tidal interactions contribute to regulating star formation (SF). To confirm that so, we now compare stellar mass assembly histories and SF look-back time annular profiles between CALIFA survey tidally and non-tidally perturbed galaxies. We pair their respective star-forming regions at the closest stellar mass surface densities to reduce the influence of stellar mass. The assembly histories and annular profiles show statistically significant differences so that higher star formation rates characterize regions in tidally perturbed galaxies. These regions underwent a more intense (re)activation of SF in the last 1 Gyr. Varying shapes of the annular profiles also reflect fluctuations between suppression and (re)activation of SF. Since gas-phase abundances use to be lower in more actively than in less actively star-forming galaxies, we further explore the plausible presence of metal-poor gas inflows able to dilute such abundances. The resolved relations of oxygen (O) abundance, with stellar mass density and with total gas fraction, show slightly lower O abundances for regions in tidally perturbed galaxies. The single distributions of O abundances statistically validate that so. Moreover, from a metallicity model based on stellar feedback, the mass rate differentials (inflows$-$outflows) show statistically valid higher values for regions in tidally perturbed galaxies. These differentials, and the metal fractions from the population synthesis, suggest dominant gas inflows in these galaxies. This dominance, and the differences in SF through time, confirm the previously reported effects of tidal interactions on SF.
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 investigate Schmidts conjecture (i.e., that the star formation rate scales in a power-law fashion with the gas density) for four well-studied local molecular clouds (GMCs). Using the Bayesian methodology we show that a local Schmidt scaling relation of the form Sigma*(A_K) = kappa x (A_K)^{beta} (protostars pc^{-2}) exists within (but not between) GMCs. Further we find that the Schmidt scaling law, by itself, does not provide an adequate description of star formation activity in GMCs. Because the total number of protostars produced by a cloud is given by the product of Sigma*(A_K) and S(> A_K), the differential surface area distribution function, integrated over the entire cloud, the clouds structure plays a fundamental role in setting the level of its star formation activity. For clouds with similar functional forms of Sigma*(A_K), observed differences in their total SFRs are primarily due to the differences in S(> A_K) between the clouds. The coupling of Sigma*(A_K) with the measured S(> A_K) in these clouds also produces a steep jump in the SFR and protostellar production above A_K ~ 0.8 magnitudes. Finally, we show that there is no global Schmidt law that relates the star formation rate and gas mass surface densities between GMCs. Consequently, the observed Kennicutt-Schmidt scaling relation for disk galaxies is likely an artifact of unresolved measurements of GMCs and not a result of any underlying physical law of star formation characterizing the molecular gas.
We test some ideas for star formation relations against data on local molecular clouds. On a cloud by cloud basis, the relation between the surface density of star formation rate and surface density of gas divided by a free-fall time, calculated from the mean cloud density, shows no significant correlation. If a crossing time is substituted for the free-fall time, there is even less correlation. Within a cloud, the star formation rate volume and surface densities increase rapidly with the corresponding gas densities, faster than predicted by models using the free-fall time defined from the local density. A model in which the star formation rate depends linearly on the mass of gas above a visual extinction of 8 mag describes the data on these clouds, with very low dispersion. The data on regions of very massive star formation, with improved star formation rates based on free-free emission from ionized gas, also agree with this linear relation.
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