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Register a new userHubble Tarantula Treasury Project: Unraveling Tarantulas Web. I. Observational overview and first results
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The Hubble Tarantula Treasury Project (HTTP) is an ongoing panchromatic imaging survey of stellar populations in the Tarantula Nebula in the Large Magellanic Cloud that reaches into the sub-solar mass regime (< 0.5 Mo). HTTP utilizes the capability of HST to operate the Advanced Camera for Surveys (ACS) and the Wide Field Camera 3 (WFC3) in parallel to study this remarkable region in the near-ultraviolet, optical, and near-infrared spectral regions, including narrow band H$alpha$ images. The combination of all these bands provides a unique multi-band view. The resulting maps of the stellar content of the Tarantula Nebula within its main body provide the basis for investigations of star formation in an environment resembling the extreme conditions found in starburst galaxies and in the early Universe. Access to detailed properties of individual stars allows us to begin to reconstruct the evolution of the stellar skeleton of the Tarantula Nebula over space and time with parcsec-scale resolution. In this first paper we describe the observing strategy, the photometric techniques, and the upcoming data products from this survey and present preliminary results obtained from the analysis of the initial set of near-infrared observations.
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We present a study of the recent star formation of 30 Doradus in the Large Magellanic Cloud (LMC) using the panchromatic imaging survey Hubble Tarantula Treasury Project (HTTP). In this paper we focus on the stars within 20 pc of the center of the massive ionizing cluster of 30 Doradus, NGC 2070. We recovered the star formation history by comparing deep optical and NIR color-magnitude diagrams (CMDs) with state-of-the-art synthetic CMDs generated with the latest PARSEC models, which include all stellar phases from pre-main sequence to post- main sequence. For the first time in this region we are able to measure the star formation using intermediate and low mass stars simultaneously. Our results suggest that NGC2070 experienced a prolonged activity. In particular, we find that the star formation in the region: i) exceeded the average LMC rate ~ 20 Myr ago; ii) accelerated dramatically ~ 7 Myr ago; and iii) reached a peak value 1-3 Myr ago. We did not find significant deviations from a Kroupa initial mass function down to 0.5 Msun. The average internal reddening E(B-V) is found to be between 0.3 and 0.4 mag.
We report on the study of interstellar extinction across the Tarantula nebula (30 Doradus), in the Large Magellanic Cloud, using observations from the Hubble Tarantula Treasury Project in the 0.3 - 1.6 micron range. The considerable and patchy extinction inside the nebula causes about 3500 red clump stars to be scattered along the reddening vector in the colour-magnitude diagrams, thereby allowing an accurate determination of the reddening slope in all bands. The measured slope of the reddening vector is remarkably steeper in all bands than in the the Galactic diffuse interstellar medium. At optical wavelengths, the larger ratio of total-to-selective extinction, namely Rv = 4.5 +/- 0.2, implies the presence of a grey component in the extinction law, due to a larger fraction of large grains. The extra large grains are most likely ices from supernova ejecta and will significantly alter the extinction properties of the region until they sublimate in 50 - 100 Myr. We discuss the implications of this extinction law for the Tarantula nebula and in general for regions of massive star formation in galaxies. Our results suggest that fluxes of strongly star forming regions are likely to be underestimated by a factor of about 2 in the optical.
The VLT-FLAMES Tarantula Survey (VFTS) is an ESO Large Programme that has obtained multi-epoch optical spectroscopy of over 800 massive stars in the 30 Doradus region of the Large Magellanic Cloud (LMC). Here we introduce our scientific motivations and give an overview of the survey targets, including optical and near-infrared photometry and comprehensive details of the data reduction. One of the principal objectives was to detect massive binary systems via variations in their radial velocities, thus shaping the multi-epoch observing strategy. Spectral classifications are given for the massive emission-line stars observed by the survey, including the discovery of a new Wolf-Rayet star (VFTS 682, classified as WN5h), 2 to the northeast of R136. To illustrate the diversity of objects encompassed by the survey, we investigate the spectral properties of sixteen targets identified by Gruendl & Chu from Spitzer photometry as candidate young stellar objects or stars with notable mid-infrared excesses. Detailed spectral classification and quantitative analysis of the O- and B-type stars in the VFTS sample, paying particular attention to the effects of rotational mixing and binarity, will be presented in a series of future articles to address fundamental questions in both stellar and cluster evolution.
We present an overview and first results of the Stratospheric Observatory For Infrared Astronomy Massive (SOMA) Star Formation Survey, which is using the FORCAST instrument to image massive protostars from $sim10$--$40:rm{mu}rm{m}$. These wavelengths trace thermal emission from warm dust, which in Core Accretion models mainly emerges from the inner regions of protostellar outflow cavities. Dust in dense core envelopes also imprints characteristic extinction patterns at these wavelengths, causing intensity peaks to shift along the outflow axis and profiles to become more symmetric at longer wavelengths. We present observational results for the first eight protostars in the survey, i.e., multiwavelength images, including some ancillary ground-based MIR observations and archival {it{Spitzer}} and {it{Herschel}} data. These images generally show extended MIR/FIR emission along directions consistent with those of known outflows and with shorter wavelength peak flux positions displaced from the protostar along the blueshifted, near-facing sides, thus confirming qualitative predictions of Core Accretion models. We then compile spectral energy distributions and use these to derive protostellar properties by fitting theoretical radiative transfer models. Zhang and Tan models, based on the Turbulent Core Model of McKee and Tan, imply the sources have protostellar masses $m_*sim10$--50$:M_odot$ accreting at $sim10^{-4}$--$10^{-3}:M_odot:{rm{yr}}^{-1}$ inside cores of initial masses $M_csim30$--500$:M_odot$ embedded in clumps with mass surface densities $Sigma_{rm{cl}}sim0.1$--3$:{rm{g:cm}^{-2}}$. Fitting Robitaille et al. models typically leads to slightly higher protostellar masses, but with disk accretion rates $sim100times$ smaller. We discuss reasons for these differences and overall implications of these first survey results for massive star formation theories.
The Hubble Tarantula Treasury Project (HTTP) has provided an unprecedented photometric coverage of the entire star-burst region of 30 Doradus down to the half Solar mass limit. We use the deep stellar catalogue of HTTP to identify all the pre--main-sequence (PMS) stars of the region, i.e., stars that have not started their lives on the main-sequence yet. The photometric distinction of these stars from the more evolved populations is not a trivial task due to several factors that alter their colour-magnitude diagram positions. The identification of PMS stars requires, thus, sophisticated statistical methods. We employ Machine Learning Classification techniques on the HTTP survey of more than 800,000 sources to identify the PMS stellar content of the observed field. Our methodology consists of 1) carefully selecting the most probable low-mass PMS stellar population of the star-forming cluster NGC 2070, 2) using this sample to train classification algorithms to build a predictive model for PMS stars, and 3) applying this model in order to identify the most probable PMS content across the entire Tarantula Nebula. We employ Decision Tree, Random Forest and Support Vector Machine classifiers to categorise the stars as PMS and Non-PMS. The Random Forest and Support Vector Machine provided the most accurate models, predicting about 20,000 sources with a candidateship probability higher than 50 percent, and almost 10,000 PMS candidates with a probability higher than 95 percent. This is the richest and most accurate photometric catalogue of extragalactic PMS candidates across the extent of a whole star-forming complex.
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