High Level Science Products are observations, catalogs, or models that complement, or are derived from, MAST-supported missions. These include Hubble (HST), James Webb (JWST), TESS, PanSTARRS, Kepler/K2, GALEX, Swift, XMM, and others. HLSPs can include images, spectra, light curves, maps, source catalogs, or simulations. They can include observations from other telescopes, or data that have been processed in a way that differs from what's available in the originating archive. All HLSPs are public immediately with no proprietary periods. Use the filters below to discover HLSP. Search HLSP by coordinates or filenames on MAST Classic. Or, see all HLSPs in a simplified, searchable table.
The 'Measuring Young Stars in Space and Time' (MYSST) project is a large, high spatial resolution, deep Hubble Space Telescope survey of the star forming complex N44 located in the Large Magellanic Cloud (LMC). Observing objects with masses as low as 0.09 M_sun (unreddened 1 Myr pre-main-sequence star), the project aims to draw a comprehensive picture of star formation on the scales of giant molecular clouds by quantifying the star formation history of N44 across space and in time. Observations were taken with the Advanced Camera for Surveys (Wide Field Channel) and the Wide Field Camera 3 (UVIS channel) in the broad band filters F555W and F814W, covering a field of view of approximately 12.2 x 14.7 arcmin^2 or 180 x 215 pc^2 at the distance of the LMC. This archive comprises the primary science output of the survey, i.e. the MYSST photometric catalog and the mosaic images.
The UVESCAPE team has demonstrated a new method for measuring the escape fraction of ionizing photons using HST imaging of resolved stars in NGC 4214, a local analog of high-z starburst galaxies that are thought to be responsible for cosmic reionization. Specifically, they forward model the UV through near-IR spectral energy distributions of ~83,000 resolved stars to infer their individual ionizing flux outputs using the Bayesian Extinction And Stellar Tool (BEAST; Gordon et al. 2016). They constrain the local escape fraction by comparing the number of ionizing photons produced by stars to the number that are either absorbed by dust or consumed by ionizing the surrounding neutral hydrogen in individual star-forming regions. They find substantial spatial variation in the escape fraction (0-40%). Integrating over the entire galaxy yields a global escape fraction of 25% (+16% / -15%). This value is much higher than previous escape fractions of zero reported for this galaxy. They discuss sources of this apparent tension, and demonstrate that the viewing angle and the 3D ISM geometric effects are the cause. If one assumes that NGC 4214 has no internal dust, like many high-z galaxies, they find an escape fraction of 59% (an upper limit for NGC 4214). This is the first non-zero escape fraction measurement for UV-faint (M_FUV) = -15.9 galaxies at any redshift, and supports the idea that starburst UV-faint dwarf galaxies can provide a sufficient amount of ionizing photons to the intergalactic medium. The team has made their catalog of stellar ionizing fluxes available as a High Level Science Product.
The PHANGS program is building the first dataset to enable the multi-phase, multi-scale study of star formation across nearby spiral galaxies, by combining Atacama Large Millimeter/submillimeterArray (ALMA) CO(2-1) mapping, Very Large Telescope/Multi Unit Spectroscopic Explorer (VLT/MUSE) optical spectroscopy, and Hubble Space Telescope (HST) UV-optical imaging. Here, the team provides data products from the PHANGS-HST Treasury survey, which is obtaining five band NUV-U-B-V-I imaging of the disks of 38 spiral galaxies at distances of 4-23 Mpc, and parallel V and I band imaging of their halos, to provide a census of tens of thousands of compact star clusters and associations. The combination of HST, ALMA, and VLT/MUSE observations will yield an unprecedented joint catalog of the observed and physical properties of ~100,000 star clusters, associations, HII regions, and molecular clouds.
TESS images that serve as the input to the MIT Quick Look Pipeline (QLP) are provided here. The team uses a Python package ('tica'), to calibrate the raw pixels and apply astrometric registration in the form of World Coordinate Solutions.
Previous methods of flare detection with both Kepler and TESS data have relied on light curve detrending and using outlier detection heuristics for identifying flare events. stella is a novel way to detect flares in TESS short cadence data using convolutional neural networks (CNNs). Any TESS short cadence light curve can be run through the CNN models provided, without any detrending. The models created by the team return a probability light curve (see example figure), with values between 0-1 if a given light curve event is a flare or not. It takes < 1 minute to predict flares on a single TESS sector light curve using these models. The CNN models were created with Google's machine learning API, Tensorflow. The team has created 100 trained ensembled models to use when predicting flares in other short cadence TESS light curves. Any single model can be used on its own, however the team recommends using at least 10 models and averaging the results. The details of each model can be found in Feinstein et al. 2020. The models can be opened and explored using either Tensorflow, h5py, or any other software that can open HDF5 files.
The Hubble imaging Probe of Extreme Environments and Clusters ('HiPEEC') is a survey investigating star cluster formation in the extreme environments of six merging galaxies. The team provides the reduced, aligned and drizzled HST images (scale of 0.04 arcsec/pixel) for the six galaxies of the survey: NGC34, 1614, 4194, 3256, 3690 and 6052. There are 32 images in total and the filters cover at a minimum UBVI and H-alpha for each galaxy. The team also provides the star cluster catalog for each galaxy. Each catalog includes the position (RA, Dec), measured magnitudes, extinctions, ages and masses from fits to the spectral energy distributions. An explanation of the column contents is given at the start of each file.
The DIAmante project provides raw and systematic-corrected multi-Sector lightcurves extracted from TESS Full Frame Images (FFIs). DIAmante exploits a new pipeline based on difference image analysis which has been specifically developed to analyze FFIs. The main targets are FGKM dwarf and sub-giant stars across the entire sky. The team provides additional supporting material as catalogs and data validation documents for specific targets of interest (e.g. transiting planets). The first data release presents the results (lightcurves and data validation documents) from a search for transiting planets in the Southern ecliptic hemisphere.
The Hubble UV Legacy Library of Young Stars as Essential Standards ('ULLYSES') is a Director's Discretionary program devoting ~1,000 HST orbits to the production of an ultraviolet spectroscopic library of young high- and low-mass stars in the local universe. The ULLYSES program uniformly samples the fundamental astrophysical parameter space for each mass regime -- including spectral type, luminosity class, and metallicity for massive OB stars (in the Magellanic Clouds and two other lower-metallicity nearby galaxies) and the mass, and disk accretion rate for low-mass T Tauri stars (in eight young Galactic star forming regions). The data will be gathered over a three-year period, from Cycle 27 through Cycle 29 (2020-2022). The data products are combined from individual, extracted and calibrated spectra obtained with the COS and STIS instruments on-board HST. Products are made using both archival HST data and new HST observations obtained through the ULLYSES program.
Since the start of the TESS Mission, the TESS Science Processing Operations Center (SPOC) pipeline has been used to calibrate full-frame images (FFI) and to assign world-coordinate system information to the FFI data delivered to the MAST. The SPOC pipeline has generated target pixel files, light curves, and associated products from two-minute cadence target data, but not from FFIs (Jenkins, et al. 2016). Data provided with this release extend the SPOC pipeline processing to include targets selected from the FFIs to create target pixel and light curve files for up to 160,000 targets per sector. Targets are selected from the FFIs using the TESS Input Catalog (TIC; Stassun et al. 2019) with a maximum of 10,000 targets per Sector on each of the sixteen TESS CCDs. Selection criteria include all two-minute cadence targets, targets bright in the near-infrared (H magnitude <=10), targets within 100 parsecs, and targets with TESS magnitude <=13.5. Details of the target selection are given in (Caldwell et al. 2020). The data products for the TESS-SPOC FFI targets are the same as for the two-minute cadence targets: calibrated target pixel files, simple aperture photometry flux time series, presearch data conditioning corrected flux time series, and cotrending basis vectors (CBV) sampled at the FFI cadence. The initial release includes TESS-SPOC FFI data products for the TESS northern hemisphere Sectors 14-26.
The Transiting Exoplanet Survey Satellite (TESS) is the first high-precision full-sky photometry survey in space. The MIT QLP team produced light curves from a magnitude limited (TESS Magnitude smaller than 13.5) set of stars and other stationary luminous objects from the TESS Full Frame Images. The QLP light curves cover the full two-year TESS Primary Mission and include 14,773,977 and 9,602,103 individual light curve segments in the Southern and Northern ecliptic hemispheres, respectively. The photometric precision roughly follows the theoretical predictions pre-launch. The data reduction process is described in the primary reference (Huang et al. 2020). Additional pages in the full QLP data validation report provide additional metrics for decision-making. These plots are useful for diagnosing whether the source of transit-like variability is on target or from a nearby blended source, which is particularly important for FFI data. Some of these data validation pages are available on the MIT TOI Portal. The first data release consists of light curves for targets in Sectors 1-26. Future deliveries of extended mission light curve data with 10 minute cadence are expected to be released in the near future, starting with Sector 27.
PS1-STRM is a neural network source classification and photometric redshift catalog created from the PanSTARRS1 (PS1) DR1. Neural networks have been trained on a compilation of spectroscopic measurements, cross-matched with PS1. Based on PS1 forced mean photometry, a source is classified as galaxy, star, quasar, or unsure. For galaxies, photometric redshift estimation is performed, also yielding an estimate of redshift error via Monte-Carlo sampling. Sources lying outside the parameter coverage of the training set (i.e. extrapolated sources) are identified using self-organizing maps. Classification and photo-z results are provided for every source in the PS1 3Ï€ DR1 ForcedMeanObject table, a total of 2,902,054,648 objects. See the README file and the primary reference paper for a detailed description of the catalog metadata.
The team provides a list of 937 candidate asymptotic giant branch (AGB) stars in M31 star clusters from the Panchromatic Hubble Andromeda Treasury survey, together with their finding charts. The photometric criteria selects stars brighter than the tip of the red giant branch, which includes the bulk of the thermally pulsing AGB stars as well as early-AGB stars and other luminous cool giants expected in young stellar populations (e.g., massive red supergiants, and intermediate-mass red helium-burning stars). The AGB stars can be differentiated using the ages estimated for the clusters. Cross-matching with additional databases reveals two carbon stars and 10 secure variables among them.
NLTE calculations of hot white dwarf (WD) model atmospheres are the cornerstone of modern flux calibrations for the Hubble Space Telescope (HST) and for the CALSPEC database. These theoretical spectral energy distributions (SEDs) provide the relative flux vs. wavelength, and only the absolute flux level remains to be set by reconciling the measured absolute flux of Vega in the visible with the Midcourse Space Experiment (MSX) values for Sirius in the mid-IR. The most recent SEDs calculated by the tlusty and tmap NLTE model atmosphere codes for the primary WDs G191B2B, GD153, and GD71 show improved agreement to 1% from 1500 Angstroms to 30 microns, in comparison to the previous 1% consistency only from 2000 Angstroms to 5 microns. These new NLTE models of hot WDs now provide consistent flux standards from the FUV to the mid-IR. Model grids from both the TLUSTY207 and TMAP2019 NLTE software codes are presented across a range of stellar parameters. Both grids contain 132 models with effective temperature (T_eff) in the range 20,000 - 95,000 K and gravity (logg) between 7.0 and 9.5, with six steps of 0.5. The steps in T_eff are 2,000 K between 20,000 and 40,000 K and 5,000 K between 40,000 and 95,000 K. The wavelengths are presented in Angstroms, measured in vaccuum. The fluxes are Eddington fluxes, with different conversions for the two model sets to needed to convert to physical fluxes. See the Bohlin et al. 2020 paper for important information on how to use and convert the fluxes from these models.
The Kepler/K2 mission offered to the science community the opportunity of obtaining high-precision light curves for a large variety of stellar fields, including stellar clusters. However, most Kepler/K2 data analyses reported in the literature are based on aperture photometry. Aperture photometry is perfectly suitable to investigating stars in sparse fields but it suffers from severe limitations in crowded environments like the central regions of stellar clusters. Thus, the wealth of information included in stellar clusters analyzed with the Kepler/K2 mission is often unexplored. The team has made use of their experience with undersampled Hubble Space Telescope images and developed a new method to analyze crowded regions with the Kepler/K2 data. The combination of a high-angular-resolution catalog and accurate point-spread-function (PSF) models allows them to pinpoint a star in a Kepler/K2 exposure and measure its flux after all detectable nearby stars are PSF-subtracted from the image. This PSF-based technique: (i) increases the number of analyzable objects in the field, (ii) provides an unbiased flux measurement for each source, (iii) extracts stellar light curves in a crowded environment and (iv) improves the reachable photometric precision for faint stars. This technique is designed to exploit the huge potential offered by the 'super-stamps', but it is also perfectly suitable to analyze single, isolated stamps. The team releases the light curves for stars in the open clusters M35 and NGC2158 observed during Campaign 0, and M44 and M67 in Campaign 5. They also provide the high-angular-resolution input catalogs used in their works, the lists of the variable stars identified (only for M 44 and M67 clusters) and the Kepler/K2 stacked images for each cluster.
GALEX UV Unique Source Catalogs ("GUVcat") and Cross-Matches With Gaia and SDSS ("GUVmatch") (GUVCAT)
The GALEX database contains almost 600 million source measurements in far-UV and near-UV. Some sources have repeated measurements (useful to search for variability, for example), due to repeated observations of the same field or overlap between fields. Bianchi, Shiao, and Thilker 2017 constructed catalogs of clean, unique (i.e. only one entry for each object) UV sources, useful to estimate density of sources across the sky or the number of sources with given magnitude or color ranges, or to match UV sources with other catalogs (revised version 2020). Flags are included to check for artifacts, as well as for existing multiple observations, and flags indicating whether a source is within the footprint of a large galaxy or stellar cluster where source identification and photometry may be unreliable or inconsistent across the bands. GUVcat is composed using tiles from the AIS (All-Sky Imaging Survey), with a depth of about 19.9/20.8 in FUV/NUV ABmag. Bianchi & Shiao 2020 matched the GUVcat_AIS with SDSS DR14 and Gaia DR2 databases (GUVMatch). Tags are included to identify and track multiple optical matches to UV sources.