A fundamental test for stellar feedback recipes in galaxy simulations

Direct comparisons between galaxy simulations and observations that both reach scales < 100 pc are strong tools to investigate the cloud-scale physics of star formation and feedback in nearby galaxies. Here we carry out such a comparison for hydrodynamical simulations of a Milky Way-like galaxy, including stochastic star formation, HII region and supernova feedback, and chemical post-processing at 8 pc resolution. Our simulation shows excellent agreement with almost all kpc-scale and larger observables, including total star formation rates, radial profiles of CO, HI, and star formation through the galactic disc, mass ratios of the ISM components, both whole-galaxy and resolved Kennicutt-Schmidt relations, and giant molecular cloud properties. However, we find that our simulation does not reproduce the observed de-correlation between tracers of gas and star formation on < 100 pc scales, known as the star formation 'uncertainty principle', which indicates that observed clouds undergo rapid evolutionary lifecycles. We conclude that the discrepancy is driven by insufficiently-strong pre-supernova feedback in our simulation, which does not disperse the surrounding gas completely, leaving star formation tracer emission too strongly associated with molecular gas tracer emission, inconsistent with observations. This result implies that the cloud-scale de-correlation of gas and star formation is a fundamental test for feedback prescriptions in galaxy simulations, one that can fail even in simulations that reproduce all other macroscopic properties of star-forming galaxies.Comment: 13 pages, 10 figures, accepted for publication in MNRA

An uncertainty principle for star formation -- III. The characteristic emission time-scales of star formation rate tracers

We recently presented a new statistical method to constrain the physics of star formation and feedback on the cloud scale by reconstructing the underlying evolutionary timeline. However, by itself this new method only recovers the relative durations of different evolutionary phases. To enable observational applications, it therefore requires knowledge of an absolute 'reference time-scale' to convert relative time-scales into absolute values. The logical choice for this reference time-scale is the duration over which the star formation rate (SFR) tracer is visible because it can be characterised using stellar population synthesis (SPS) models. In this paper, we calibrate this reference time-scale using synthetic emission maps of several SFR tracers, generated by combining the output from a hydrodynamical disc galaxy simulation with the SPS model SLUG2. We apply our statistical method to obtain self-consistent measurements of each tracer's reference time-scale. These include H${\alpha}$ and 12 ultraviolet (UV) filters (from GALEX, Swift, and HST), which cover a wavelength range 150-350 nm. At solar metallicity, the measured reference time-scales of H${\alpha}$ are ${4.32^{+0.09}_{-0.23}}$ Myr with continuum subtraction, and 6-16 Myr without, where the time-scale increases with filter width. For the UV filters we find 17-33 Myr, nearly monotonically increasing with wavelength. The characteristic time-scale decreases towards higher metallicities, as well as to lower star formation rate surface densities, owing to stellar initial mass function sampling effects. We provide fitting functions for the reference time-scale as a function of metallicity, filter width, or wavelength, to enable observational applications of our statistical method across a wide variety of galaxies.Comment: 24 pages, 18 figures, 7 tables (including Appendices); published in MNRA

Towards a multi-tracer timeline of star formation in the LMC -- I.\ Deriving the lifetimes of H\,{\sc i} clouds

The time-scales associated with the various stages of the star formation process remain poorly constrained. This includes the earliest phases of star formation, during which molecular clouds condense out of the atomic interstellar medium. We present the first in a series of papers with the ultimate goal of compiling the first multi-tracer timeline of star formation, through a comprehensive set of evolutionary phases from atomic gas clouds to unembedded young stellar populations. In this paper, we present an empirical determination of the lifetime of atomic clouds using the Uncertainty Principle for Star Formation formalism, based on the de-correlation of H$\alpha$ and H\,{\sc i} emission as a function of spatial scale. We find an atomic gas cloud lifetime of 48$\substack{+13\\-8}$\,Myr. This timescale is consistent with the predicted average atomic cloud lifetime in the LMC (based on galactic dynamics) that is dominated by the gravitational collapse of the mid-plane ISM. We also determine the overlap time-scale for which both H\,{\sc i} and H$\alpha$ emission are present to be very short ($t_{over}<1.7$\,Myr), consistent with zero, indicating that there is a near-to-complete phase change of the gas to a molecular form in an intermediary stage between H\,{\sc i} clouds and H\,{\sc ii} regions. We utilise the time-scales derived in this work to place empirically determined limits on the time-scale of molecular cloud formation. By performing the same analysis with and without the 30 Doradus region included, we find that the most extreme star forming environment in the LMC has little effect on the measured average atomic gas cloud lifetime. By measuring the lifetime of the atomic gas clouds, we place strong constraints on the physics that drives the formation of molecular clouds and establish a solid foundation for the development of a multi-tracer timeline of star formation in the LMC

A milestone toward understanding PDR properties in the extreme environment of LMC-30Dor

More complete knowledge of galaxy evolution requires understanding the process of star formation and interaction between the interstellar radiation field and the interstellar medium in galactic environments traversing a wide range of physical parameter space. Here we focus on the impact of massive star formation on the surrounding low metallicity ISM in 30 Doradus in the Large Magellanic Cloud. A low metal abundance, as is the case of some galaxies of the early universe, results in less ultra-violet shielding for the formation of the molecular gas necessary for star formation to proceed. The half-solar metallicity gas in this region is strongly irradiated by the super star cluster R136, making it an ideal laboratory to study the structure of the ISM in an extreme environment. Our spatially resolved study investigates the gas heating and cooling mechanisms, particularly in the photo-dissociation regions where the chemistry and thermal balance are regulated by far-ultraviolet photons (6 eV< h\nu <13.6 eV). We present Herschel observations of far-infrared fine-structure lines obtained with PACS and SPIRE/FTS. We have combined atomic fine-structure lines from Herschel and Spitzer observations with ground-based CO data to provide diagnostics on the properties and the structure of the gas by modeling it with the Meudon PDR code. We derive the spatial distribution of the radiation field, the pressure, the size, and the filling factor of the photodissociated gas and molecular clouds. We find a range of pressure of ~ 10^5 - 1.7x10^6 cm^{-3} K and a range of incident radiation field G_UV ~ 10^2 - 2.5x10^4 through PDR modeling. Assuming a plane-parallel geometry and a uniform medium, we find a total extinction of 1-3 mag , which correspond to a PDR cloud size of 0.2 to 3pc, with small CO depth scale of 0.06 to 0.5pc. We also determine the three dimensional structure of the gas. (Abridged)Comment: 20 pages, 23 figures, accepted in A&

Characterizing and predicting person-specific, day-to-day, fluctuations in walking behavior

Despite the positive health effect of physical activity, one third of the world's population is estimated to be insufficiently active. Prior research has mainly investigated physical activity on an aggregate level over short periods of time, e.g., during 3 to 7 days at baseline and a few months later, post-intervention. To develop effective interventions, we need a better understanding of the temporal dynamics of physical activity. We proposed here an approach to studying walking behavior at "high-resolution" and by capturing the idiographic and day-to-day changes in walking behavior. We analyzed daily step count among 151 young adults with overweight or obesity who had worn an accelerometer for an average of 226 days (~25,000 observations). We then used a recursive partitioning algorithm to characterize patterns of change, here sudden behavioral gains and losses, over the course of the study. These behavioral gains or losses were defined as a 30% increase or reduction in steps relative to each participants' median level of steps lasting at least 7 days. After the identification of gains and losses, fluctuation intensity in steps from each participant's individual time series was computed with a dynamic complexity algorithm to identify potential early warning signals of sudden gains or losses. Results revealed that walking behavior change exhibits discontinuous changes that can be described as sudden gains and losses. On average, participants experienced six sudden gains or losses over the study. We also observed a significant and positive association between critical fluctuations in walking behavior, a form of early warning signals, and the subsequent occurrence of sudden behavioral losses in the next days. Altogether, this study suggests that walking behavior could be well understood under a dynamic paradigm. Results also provide support for the development of "just-in-time adaptive" behavioral interventions based on the detection of early warning signals for sudden behavioral losses