453 research outputs found
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 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 are 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 and H\,{\sc i} emission as a function of spatial scale. We find an atomic gas cloud lifetime of 48\,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 emission are present to be very short (\,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
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