The Variability of Star Formation Rate in Galaxies: II. Power Spectrum Distribution on the Main Sequence

Abstract

We constrain the temporal power spectrum of the sSFR(t) of star-forming galaxies, using a welldefined sample of Main Sequence galaxies from MaNGA and our earlier measurements of the ratio of the SFR averaged within the last 5 Myr to that averaged over the last 800 Myr. We explore the assumptions of stationarity and ergodicity that are implicit in this approach. We assume a single power-law form of the PSD but introduce an additional free parameter, the "intrinsic scatter", to try to account for any non-ergodicity introduced from various sources. We analyze both an "integrated" sample consisting of global measurements of all of the galaxies, and also 25 sub-samples obtained by considering five radial regions and five bins of integrated stellar mass. Assuming that any intrinsic scatter is not the dominant contribution to the Main Sequence dispersion of galaxies, we find that the PSDs have slopes between 1.0 and 2.0, indicating that the power (per log interval of frequency) is mostly contributed by longer timescale variations. We find a correlation between the returned PSDs and the inferred gas depletion times (τ dep,eff ) obtained from application of the extended Schmidt Law, in that regions with shorter gas depletion times show larger integrated power and flatter PSD. Intriguingly, it is found that shifting the PSDs by the inferred τ dep,eff causes all of the 25 PSDs to closely overlap, at least in that region where the PSD is best constrained and least affected by uncertainties about any intrinsic scatter. A possible explanation of these results is the dynamical response of the gas regulator system of Lilly et al. (2013) to a uniform time-varying inflow, as previously proposed in .

The Diversity and Variability of Star Formation Histories in Models of Galaxy Evolution

“…With degeneracies due to current observational uncertainties, they find that they cannot constrain both a slope and break timescale, but find a break timescale of ∼ 200 Myr assuming a slope of β = 2. Wang & Lilly (2020a) extend this analysis in a spatially resolved direction and find PSD slopes of β ∼ 1 − 2 in the timescale range ∼ 5 Myr to ∼ 800 Myr, assuming no break in the PSD (which implies that SFHs are correlated over the the age of the universe). They also find that the slopes generally decrease with stellar mass for M * > 10 9 M , and are correlated with estimated gas depletion timescales in galaxies.…”

“…Processes like hierarchical structure formation and correlated stochastic star formation additionally link short timescales to longer ones, creating an overall spectral slope to the PSD, shown in the bottom panel of Figure 3. Physical processes can additionally drive features at certain characteristic timescales, for e.g., the regulator model (Lilly et al 2013, see also Bouché et al 2010Davé et al 2012;Forbes et al 2014b) predicts SFHs correlated below an equilibrium timescale of a galaxy's gas reservoir, with the slope at timescales below the break steeper by 2 than the slope above it (Wang & Lilly 2020a;Tacchella et al 2020). Such features can be seen as breaks in the PSD (Caplar & Tacchella 2019).…”

“…Iyer et al (2019) analysed a sample of CANDELS galaxies at 0.5 < z < 3.0 and found that ∼ 15 − 20% of galaxies showed evidence for multiple strong episodes of star formation, with the median timescale separating multiple peaks to be ∼ 0.4τ H , which matches the predictions using cosmoto the PSDs of individual galaxy SFHs over time. This assumption is explored in detail in Wang & Lilly (2020a). logical simulations by Tacchella et al (2016).…”

Stochastic modelling of star-formation histories II: star-formation variability from molecular clouds and gas inflow

“…A similar conclusion was reached by Hahn et al (2019), who studied the scatter of the stellar-to-halo mass relation. Wang & Lilly (2020) used MaNGA data to constrain the PSD of star formation in local galaxies, finding slopes between 1.0 and 2.0, which indicates that the power of the star-formation variability is mostly contributed by longer timescale variations.…”