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We present a novel infrared spectral energy distribution (SED) modeling methodology that uses likelihood-based weighting of the model fitting results to construct probabilistic Hertzsprung–Russell diagrams (pHRD) for X-ray-identified, intermediate-mass (2–8 M⊙), pre-main-sequence young stellar populations. This methodology is designed specifically for application to young stellar populations suffering strong, differential extinction (ΔAV > 10 mag), typical of Galactic massive star-forming regions. We pilot this technique in the Carina Nebula Complex (CNC) by modeling the 1–8 μm SEDs of 2269 likely stellar members that exhibit no excess emission from circumstellar dust disks at 4.5 μm or shorter wavelengths. A subset of ∼100 intermediate-mass stars in the lightly obscured Trumpler 14 and 16 clusters have available spectroscopic Teff, measured from the Gaia-ESO survey. We correctly identify the stellar temperature in 85% of cases, and the aggregate pHRD for all sources returns the same peak in the stellar age distribution as obtained using the spectroscopic Teff. The SED model parameter distributions of stellar mass and evolutionary age reveal significant variation in the duration of star formation among four large-scale stellar overdensities within the CNC and a large distributed stellar population. Star formation began ∼10 Myr ago and continues to the present day, with the star formation rate peaking ≲3 Myr ago when the massive Trumpler 14 and 16 clusters formed. We make public the set of 100,000 SED models generated from standard pre-main-sequence evolutionary tracks and our custom software package for generating pHRDs and mass–age distributions from the SED fitting results. [ABSTRACT FROM AUTHOR]

We use a large data set of realistic synthetic observations (produced in Paper I of this series) to assess how observational techniques affect the measurement physical properties of star-forming regions. In this part of the series (Paper II), we explore the reliability of the measured total gas mass, dust surface density and dust temperature maps derived from modified blackbody fitting of synthetic Herschel observations. We find from our pixel-by-pixel analysis of the measured dust surface density and dust temperature a worrisome error spread especially close to star formation sites and low-density regions, where for those “contaminated” pixels the surface densities can be under/overestimated by up to three orders of magnitude. In light of this, we recommend to treat the pixel-based results from this technique with caution in regions with active star formation. In regions of high background typical in the inner Galactic plane, we are not able to recover reliable surface density maps of individual synthetic regions, since low-mass regions are lost in the far-infrared background. When measuring the total gas mass of regions in moderate background, we find that modified blackbody fitting works well (absolute error: + 9%; −13%) up to 10 kpc distance (errors increase with distance). Commonly, the initial images are convolved to the largest common beam-size, which smears contaminated pixels over large areas. The resulting information loss makes this commonly used technique less verifiable as now χ2 values cannot be used as a quality indicator of a fitted pixel. Our control measurements of the total gas mass (without the step of convolution to the largest common beam size) produce similar results (absolute error: +20%; −7%) while having much lower median errors especially for the high-mass stellar feedback phase. In upcoming papers (Paper III; Paper IV) of this series we test the reliability of measured star formation rate with direct and indirect techniques. [ABSTRACT FROM AUTHOR]

When modeling astronomical objects throughout the universe, it is important to correctly treat the limitations of the data, for instance finite resolution and sensitivity. In order to simulate these effects, and to make radiative transfer models directly comparable to real observations, we have developed an open-source Python package called the FluxCompensator that enables the post-processing of the output of 3D Monte Carlo radiative transfer codes, such as Hyperion. With the FluxCompensator, realistic synthetic observations can be generated by modeling the effects of convolution with arbitrary point-spread functions, transmission curves, finite pixel resolution, noise, and reddening. Pipelines can be applied to compute synthetic observations that simulate observatories, such as the Spitzer Space Telescope or the Herschel Space Observatory. Additionally, this tool can read in existing observations (e.g., FITS format) and use the same settings for the synthetic observations. In this paper, we describe the package as well as present examples of such synthetic observations. [ABSTRACT FROM AUTHOR]

Through an extensive set of realistic synthetic observations (produced in Paper I), we assess in this part of the paper series (Paper III) how the choice of observational techniques affects the measurement of star formation rates (SFRs) in star-forming regions. We test the accuracy of commonly used techniques and construct new methods to extract the SFR, so that these findings can be applied to measure the SFR in real regions throughout the Milky Way. We investigate diffuse infrared SFR tracers such as those using 24 μm, 70 μm and total infrared emission, which have been previously calibrated for global galaxy scales. We set up a toy model of a galaxy and show that the infrared emission is consistent with the intrinsic SFR using extra-galactic calibrated laws (although the consistency does not prove their reliability). For local scales, we show that these techniques produce completely unreliable results for single star-forming regions, which are governed by different characteristic timescales. We show how calibration of these techniques can be improved for single star-forming regions by adjusting the characteristic timescale and the scaling factor and give suggestions of new calibrations of the diffuse star formation tracers. We show that star-forming regions that are dominated by high-mass stellar feedback experience a rapid drop in infrared emission once high-mass stellar feedback is turned on, which implies different characteristic timescales. Moreover, we explore the measured SFRs calculated directly from the observed young stellar population. We find that the measured point sources follow the evolutionary pace of star formation more directly than diffuse star formation tracers. [ABSTRACT FROM AUTHOR]

We present a catalog of 840 X-ray sources and first results from a 100 ks Chandra X-ray Observatory imaging study of the filamentary infrared (IR) dark cloud G014.225–00.506, which forms the central regions of a larger cloud complex known as the M17 southwest extension (M17 SWex). In addition to the rich population of protostars and young stellar objects with dusty circumstellar disks revealed by archival data from the Spitzer Space Telescope, we discover a population of X-ray-emitting, intermediate-mass pre-main-sequence stars that lack IR excess emission from circumstellar disks. We model the IR spectral energy distributions of this source population to measure its mass function and place new constraints on the destruction timescales for the inner dust disk for 2–8 M☉ stars. We also place a lower limit on the star formation rate (SFR) and find that it is quite high ( M☉ yr−1), equivalent to several Orion Nebula Clusters in G14.225–0.506 alone, and likely accelerating. The cloud complex has not produced a population of massive, O-type stars commensurate with its SFR. This absence of very massive (≳20 M☉) stars suggests that either (1) M17 SWex is an example of a distributed mode of star formation that will produce a large OB association dominated by intermediate-mass stars but relatively few massive clusters, or (2) the massive cores are still in the process of accreting sufficient mass to form massive clusters hosting O stars. [ABSTRACT FROM AUTHOR]