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

Which feedback mechanisms dominate in the high-pressure environment of the Central Molecular Zone?

This article has been accepted for publication in Monthly Notices of the Royal Astronomical Society ©: 2020 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society. All rights reserved. Final published version available at https://doi.org/10.1093/mnras/staa2719.Supernovae (SNe) dominate the energy and momentum budget of stellar feedback, but the efficiency with which they couple to the interstellar medium (ISM) depends strongly on how effectively early, pre-SN feedback clears dense gas from star-forming regions. There are observational constraints on the magnitudes and timescales of early stellar feedback in low ISM pressure environments, yet no such constraints exist for more cosmologically typical high ISM pressure environments. In this paper, we determine the mechanisms dominating the expansion of H ii regions as a function of size-scale and evolutionary time within the high-pressure (P/kB ∼ 107 − 8 K cm−3) environment in the inner 100 pc of the Milky Way. We calculate the thermal pressure from the warm ionised (PHII; 104 K) gas, direct radiation pressure (Pdir), and dust processed radiation pressure (PIR). We find that (1) Pdir dominates the expansion on small scales and at early times (0.01-0.1 pc; 0.1 pc; >1 Myr); (3) during the first ≲ 1 Myr of growth, but not thereafter, either PIR or stellar wind pressure likely make a comparable contribution. Despite the high confining pressure of the environment, natal star-forming gas is efficiently cleared to radii of several pc within ∼ 2 Myr, i.e. before the first SNe explode. This ‘pre-processing’ means that subsequent SNe will explode into low density gas, so their energy and momentum will efficiently couple to the ISM. We find the H ii regions expand to a radius of ∼ 3pc, at which point they have internal pressures equal with the surrounding external pressure. A comparison with H ii regions in lower pressure environments shows that the maximum size of all H ii regions is set by pressure equilibrium with the ambient ISM.Peer reviewe

Understanding External Influences on Target Detection and Classification Using Camera Trap Images and Machine Learning

Using machine learning (ML) to automate camera trap (CT) image processing is advantageous for time-sensitive applications. However, little is currently known about the factors influencing such processing. Here, we evaluate the influence of occlusion, distance, vegetation type, size class, height, subject orientation towards the CT, species, time-of-day, colour, and analyst performance on wildlife/human detection and classification in CT images from western Tanzania. Additionally, we compared the detection and classification performance of analyst and ML approaches. We obtained wildlife data through pre-existing CT images and human data using voluntary participants for CT experiments. We evaluated the analyst and ML approaches at the detection and classification level. Factors such as distance and occlusion, coupled with increased vegetation density, present the most significant effect on DP and CC. Overall, the results indicate a significantly higher detection probability (DP), 81.1%, and correct classification (CC) of 76.6% for the analyst approach when compared to ML which detected 41.1% and classified 47.5% of wildlife within CT images. However, both methods presented similar probabilities for daylight CT images, 69.4% (ML) and 71.8% (analysts), and dusk CT images, 17.6% (ML) and 16.2% (analysts), when detecting humans. Given that users carefully follow provided recommendations, we expect DP and CC to increase. In turn, the ML approach to CT image processing would be an excellent provision to support time-sensitive threat monitoring for biodiversity conservation

Comparing molecular gas across cosmic time-scales: the Milky Way as both a typical spiral galaxy and a high-redshift galaxy analogue

Detailed observations of the nearest star-forming regions in the Milky Way (MW) provide the ultimate benchmark for studying star formation. The extent to which the results of these Galaxy-based studies can be extrapolated to extragalactic systems depends on the overlap of the environmental conditions probed. In this paper, we compare the properties of clouds and star-forming regions in the MW with those in nearby galaxies and in the high-redshift Universe. We find that in terms of their baryonic composition, kinematics and densities, the clouds in the solar neighbourhood are similar to those in nearby galaxies. The clouds and regions in the Central Molecular Zone (CMZ, i.e. the inner 250 pc) of the MW are indistinguishable from high-redshift clouds and galaxies. The presently low star formation rate in the CMZ therefore implies that either (1) its gas represents the initial conditions for high-redshift starbursts or (2) some yet unidentified process consistently suppresses star formation over ≳ 108 yr time-scales. We conclude that the MW contains large reservoirs of gas with properties directly comparable to most of the known range of star formation environments and is therefore an excellent template for studying star formation across cosmological time-scales