Hubble Source Catalog Version 4
Frequently Asked Questions



FAQ - General

  1. What is the Hubble Source Catalog (HSC)? What data does it contain?

    The Hubble Source Catalog (HSC) combines more than 64,000 visit-based source lists derived from images from the Hubble Advanced Products (HAP) Single-Visit Mosaics and the Hubble Legacy Archive (HLA) into a single master catalog.

    Version 1 of the HSC contained members of the WFPC2, ACS/WFC, WFC3/UVIS, and WFC3/IR Source Extractor source lists from HLA version DR8 that were public as of June 1, 2014.

    Version 2 contained source lists from the same instruments, but using HLA version DR9.1 images (data public as of June 9, 2015.)

    Version 3 included source lists from the HLA version DR10 images (public as of October 1, 2017.) See the HSCv3 FAQ for more details about this version of the catalog.

    Version 4 uses source lists for ACS/WFC, WFC3/UVIS and WFC3/IR data from HAP that were public as of March 17, 2026. It also incorporates the WFPC2 source lists from HLA DR10.

    See What is new in version 4 below for more details about improvements and enhancements made to Version 4. Version 3 of the HSC will continue to be available and still has some advantages over Version 4 (particularly for WFC3/IR data), but Version 4 is preferred for most purposes because of both the increase in the number of datasets included and the substantial improvements in its photometric and astrometric accuracy.

    This table summarizes some properties of the HSCv4 and HSCv3 catalogs and the input source lists.

    Quantity

    HSCv4

    HSCv3

    Units

    Notes

    number of images

    101,575

    75,443


    number of filter images

    number of visits

    64,840

    48,122


    a visit can have multiple filters

    sky area

    56.2

    40.3

    sq degrees

    unique sky area covered (overlaps count only once)

    image area

    201.7

    147.7

    sq degrees

    total area covered by images (overlaps counted separately)

    number of sources

    540,956,105

    465,175,488


    number of catalog sources (detections in 1 filter at 1 epoch)

    number of matches

    139,162,343

    108,228,655


    number of objects in HSC (each can have multiple filters or epochs)

    maximum sources/match

    512

    497


    maximum number of detections in a single match

    average time range

    597

    493

    days

    mean time range for measurements in a match

    maximum time range

    31.7

    27.7

    years

    maximum time range for measurements in a match


  2. What is new in Version 4 of the Hubble Source Catalog?

    There are many changes in HSC v4 compared with previous versions:

    1. HSC v4 is based on the Hubble Advanced Products rather than on the HLA data products for ACS and WFC3. There are approximately 37% more ACS source lists, 52% more WFC3/IR source lists, and 2.25 times as many WFC3/UVIS source lists compared with HSC v3.  The WFPC2 source lists are unchanged (we are using the same HLA source lists that were included in HSC v3, and there have been no new WFPC2 observations since the instrument was removed from Hubble in 2009).  The table below compares the counts of different filter images and independent target visits for HSCv4 and HSCv3.


      HSCv4

      HSCv3

      HSCv4 / HSCv3 ratio

      camera

      filters

      visits

      filters

      visits

      filters

      visits

      ACS/WFC

      29,215

      19,087

      21,135

      13,891

      1.38

      1.37

      WFC3/IR

      23,147

      14,318

      15,255

      9,644

      1.52

      1.48

      WFC3/UVIS

      20,429

      12,403

      10,203

      5,518

      2.00

      2.25

      WFPC2

      28,784

      19,032

      28,850

      19,069

      1.00

      1.00

      Total

      101,575

      64,840

      75,443

      48,122

      1.35

      1.35


    2. The astrometric calibration is now based on the Gaia DR3 catalog. The result is significantly improved absolute and relative astrometry.  Gaia has allowed the confident identification of much larger errors in the HST pointing (with shifts up to 100 arcsec correctly identified). In this version of the catalog, 96% of the fields have matches to external astrometric reference catalogs.  88% have Gaia DR3 calibration and 8% have calibrations based on the Pan-STARRS1 (PS1) DR2 catalog.  Note that the PS1 astrometry has also been recalibrated using Gaia DR3 (see Lubow et al. 2021 and White et al. 2022), so 96% of the fields have Gaia primary or secondary astrometry. See the HSCv4 Astrometry page for many more details regarding the astrometry in HSCv4 and comparisons with HSCv3.

    3. The photometry in HSCv4 is also significantly improved compared with HSCv3.  The plot below shows a comparison of the repeated measurements using the WFC3/UVIS F467M field in the globular cluster M4.  The noise in the HSCv4 measurements (bottom) is a factor of two lower than for HSCv3 (top); in this field the median absolute deviation noise is less than 0.01 mag.  These improvements are thought to be mainly the result of better alignment of exposures and filters from the use of Gaia DR3 in the HAP processing. Improved geometric distortion models for the cameras also lead to better source alignment for visits with large dither patterns. See the HSCv4 Photometry page for more information, including analysis of relative photometric accuracy in many fields (and in the entire catalog) and comparisons to external photometric reference catalogs.

      Comparison of noise as a function of magnitude in globular cluster M4 for HSC v3 (top) and HSC v4 (bottom). The plot includes 6,690 objects that have more than 50 repeated measurements in both HSCv3 and HSCv4 in the W3_F467M filter. The horizontal lines show the median noise over the magnitude range from 17 to 18.  The noise in HSC v4 is a factor of two better than HSC v3. (The HSC v3 photometry was already much better than HSC v2, which had a noise level of 0.0245 mag in this field.)

  3. What are five things you should know about the HSC?

    NOTE: Some of the graphics in this section are from older versions, but the qualitative descriptions still apply.

    1. Detailed HSC use cases and videos are available to guide you.
    HSC non-uniformity in M83

    2. Coverage can be very non-uniform (unlike surveys like SDSS), since pointed observations from a wide range of HST instruments, filters, and exposure times have been combined. However, with proper selection of various parameters (e.g., ``NumImages included in a match), this non-uniformity can be minimized in most but not all cases. In the example below, the first image (with NumImages > 10) shows a very nonuniform catalog, while the second image (with NumImages > 3) is better (although it still shows regions of uneven coverage due to different image locations).


    3. WFPC2 source lists are of poorer quality than ACS and WFC3 source lists. As we have gained experience, the HLA and HAP source lists have improved. For example, many of the earlier limitations (e.g., depth, difficulty finding sources in regions of high background, edge effects, photometric bias due to image alignment problems, ...) were fixed in the WFC3 and ACS source lists for version 3. These improved algorithms have not yet been used for WFPC2.

    4. The default in most interfaces and queries is to show all HSC objects in the catalog. This may include a number of artifacts. You can request NumImages > 1 (or more) to filter out many of the artifacts. In the example below we show an F814W WFPC2 image of part of the Hubble Deep Field (HDF). With NumImages > 0 on the left, the image is covered by a haze of thousands of sources, many of which are likely to be artifacts.  That is the hazard of combining more than a hundred separate source lists in this field.  Even the faint sources in this particular field have NumImages in the range 10 - 20, hence a value of NumImages > 20 (right image) is more appropriate.


    5. The default is to use MagAper2 (aperture magnitudes), generated using Source Extractor (Bertin & Arnouts 1996) software. If required for your science needs, you will need to add aperture corrections to estimate total magnitudes. These can be found in the Peak of Concentration Index for Stars and Aperture Correction Table. You can also request MagAuto values if you would like to use the Source Extractor algorithm for estimating the total magnitude. This is especially appropriate for extended sources.

    All HSC magnitudes are in the ABMAG system. Here is a discussion of the ABMAG, VEGAMAG and STMAG systems. A handy, though not exact conversion for ACS is provided in Sirianni et al. (2005). The Synphot package provides a more generic conversion mechanism for all HST instruments. See the HSCv4 Photometry page for an example of converting between different magnitude systems for comparisons to external photometric catalogs.

  4. Where can I find examples of good and bad regions of the HSC?

    NOTE: Some of the images in this section come from older versions of the HSC.

    Good examples:

    Nearby galaxy: ACS, M101 (10918_01) To get the images at right, click on "Advanced HSC controls", select either HSCv4 or HSCv3 from the menu, and click the HSC checkbox to overlay the catalog.  You can greatly speed the download in this crowded region (which is only about 8 arcsec from top to bottom) by checking the "Visible Area" radio button, and then the "Set Region" button.  That downloads only the sources in the visible part of the image.

    In older versions of the HSC, there was sometimes "doubling" of sources that did not get merged together in the HSC.  That problem is rare in HSCv4 and HSCv3 (see the known problems question below for more discussion).  In this field, the HSCv4 catalog has slightly more sources than HSCv3 (particular on the dense star cluster), but we consider both of the catalogs to be of good quality. This is a success story that was once a problem field.


    Star field: ACS, M31 (10265_01), NumImages > 8 version To get the image at right, click on "Advanced HSC controls", select a version of the HSC, check the box for "Require NumImages > 8", then click on the HSC checkbox.

    This is a field with many repeated observations in the ACS F814W filter.  By setting the NumImages  threshold to a relatively high value, we get an outstanding catalog in a crowded field.  Note that the HSCv4 version of the catalog is significantly deeper than the HSCv3 version.  This field is used for testing the absolute photometric accuracy of the HSC on the HSCv4 Photometry page.


    Field of faint galaxies: WFC3/IR (12443_3c), N > 20 version To get the image at right, click on "Advanced HSC controls", then check the box for "Require NumImages > 20", then click on HSC. Note that the higher resolution WFC3/IR image from the HLA is shown here.  This is in the GOODS-N field, which has many overlapping observations, so it is necessary to set the NumImages  threshold to a high value.  This field has doubling issues for both HSCv4 and HSCv3 but is nonetheless a good catalog.

    Gravitational Lens: WFC3/UVIS, (11602_02), N > 1 and N>3 versions. To get the image at right, click on "Advanced HSC controls", then check the box for "Require NumImages > 1", then click on HSC.

    Note the presence of artifacts around the bright star and along the diffraction spikes in this image. It is often possible to remove these by using the appropriate value of the NumImages  criterion. The image to the right increases the NumImages threshold to 3, which produces a clean catalog. When a simple change in the NumImages  threshold produces a good quality, uniform catalog, we consider that a good region.

    Mixed Examples:

    Nearby Galaxy WFC3/UVIS, (12513_05), N > 10 and 3 versions. To get the image at right, click on "Advanced HSC controls", then check the box for "Require NumImages > 10", then click on HSC. Repeat this with "Require NumImages > 3"

    This shows an example where a choice of NumImages > 10 can result in a very nonuniform catalog, while NumImages > 3 results in a more uniform catalog (although it still shows regions of uneven coverage due to different image locations). Because of the strong sensitivity to the choice of NumImages, this is considered a mixed quality region of the catalog.


    Nearby Galaxy WFC3/UVIS, (11360_r1), HSCv3 and HSCv4 versions. To get the image of NGC 2841 at right, click on "Advanced HSC controls", check the box for "Require NumImages > 3", then click on HSC.

    In this field the HSCv1 catalog had many false sources near the nucleus of the galaxy. The results could be improved by increasing the limit to NumImages > 5, but that also results in the loss of many real sources. For this reason we considered this a mixed quality catalog in version 1.

    However, this problem was fixed in version 3, and it remains a good catalog in HSCv4 despite the addition of some sources in the nucleus. So this region has changed from a Mixed to a Good example!

    Bad Examples:


    Parallel Parallel Starfield: WFPC2 (8013_41), N > 0 and 5 versions. To get the image at right, click on "Advanced HSC controls", then check the box for "Require NumImages > 0", then click on HSC. Repeat this with "Require NumImages > 5".

    This shows a field with a large number of artifacts in a WFPC2 field when using NumImages > 0, both because of the bright stars in the field and various edge effects. While using NumImages > 5 removes many of these artifacts, it is not possible to remove all of them without also removing many of the real sources.

    NOTE: These figures are from version 1. Versions 3 and 4 look fairly similar since the WFPC2 images and source lists that lead to the problems have not changed.

  5. What are the primary "known problems" with HSC Version 4?

    Known Problem # 1 - Artifacts around bright stars and along diffraction spikes

    These often are more prevalent in version 4 than they were in version 3. The examples at right show the HSCv4 and HSCv3 catalogs using NumImages>1  in the vicinity of the gravitational lens (11602_02). The HAP source lists are much less proactive about flagging objects near bright stars than the HLA was.  There are many more artifacts near the center of the bright star and along the diffraction spikes in HSCv4. The new catalog is good away from bright objects, and it is often possible to remove these by using the appropriate value of the NumImages criteria.


    Known Problem # 2 - "Doubling"

    There are occasionally cases where not all the detections of the same source are matched together into a single objects. In these cases, more than one match ID is assigned to the object, and two pink circles are generally seen at the highest magnification in the display, as shown by in the example image of the Pegasus Dwarf Elliptical Galaxy (Peg DIG). This mainly happens in very crowded fields when there are many repeated observations.  The primary cause of the problem lies in the "chainbreaker" step in the processing, which examines large clumps of sources to determine whether they should be broken apart into separate matches.  Sometimes the chainbreaker is too aggressive and breaks apart sources that (by eye) should be joined into a single match. 

    These "double objects" frequently have very different numbers of images associated with the two circles. Hence, this problem can often be handled by using the appropriate value of NumImages to filter out one of the two circles. For example, using Numimages > 4  for this field removes almost all of the doubling artifacts, at the expense of losing the faintest 25% of the objects (see figure on right).

    Approximately 1% of all sources in the catalog have a close neighbor (within 0.1 arcsec).  Not all of these are incorrect however – in many cases the chainbreaker has correctly separated close pairs or groups of objects.      Interestingly, while investigating the doubling artifact we found that some cases are due to the proper motion of the star! These can generally be distinguished from cases where the doubling is due to poor matching by examining the range of dates of the observations for the two circles.

    There are approximately 20 fields like the one shown where the doubling is relatively severe (greater than 20% of the matches in the field have close neighbors).  There are more than 20,000 separate fields in the catalog, so such issues are rare.  Those 20 fields account for 38% of all the close matches in the catalog. We are exploring more robust algorithms for the chainbreaker that may reduce the incidence of this problem.

    Known Problem # 3 - PC and WFC objects are combined for the WFPC2

    Aperture magnitudes for objects on the PC (Planetary Camera) portion of the WFPC2 differ (typically by 0.2 to 0.3 magnitudes) when compared to the same object when it is on the WF (Wide Field) portion of the WFPC2, resulting in additional scatter for the WFPC2 data. This is caused by a variety of reasons including: 1) the pixel scale on the PC is half the size of the WF - while resampling adjusts for this to some degree, it does not fully compensate, 2) Charge Transfer Efficiency loss (CTE) is much higher on the PC due to the lower flux in the smaller pixels. In HSCv3, information about which chip the object is found on is stored in a table named WFPC2PCFrac that is available via CasJobs. That file has not been included in HSCv4 at this time. Moreover, this information was not used when computing the normalized concentration index (CI) or magnitudes of sources, so the accuracy of those quantities is lower (and more variable) for WFPC2.

    Known Problem # 4     - Poor photometry for WFC3/IR observations

    The WFC3/IR measurements in HSCv4 are of poorer quality than in HSCv3.  This is likely the result of drizzling the WFC3/IR data with a larger pixel size in the HAP products.  See the photometry FAQ and the HSCv4 Photometry page for more discussion of this issue.


FAQ - About Images and Matches

  1. How are HLA images and source lists constructed?

    The Hubble Source Catalog (HSC) is based on HAP segment source lists (for ACS and WFC3) and HLA Source Extractor (Bertin & Arnouts 1996) source lists (for WFPC2).  The HAP segment catalogs are generated using the photutils package, with parameters tuned to approximately reproduce the HLA Source Extractor catalogs. To build these source lists, the HAP and HLA pipelines first construct a "white light" or "detection" image by combining the different filter observations within each visit for each detector. This filter-combined drizzled image provides added depth. Source Extractor is run on the white light detection image to identify each source and determine its position.

    Next, the combined drizzled image for each filter used in the detection image is checked for sources at the positions indicated by the finding algorithm in Source Extractor. If a valid source (flags less than or equal to 5) is detected at a given position then its properties are entered into the HLA source list appropriate for the visit, detector, and filter. (See HLA Source List FAQ for a definition of the flagging system for HLA source lists, which generally has been carried over to the HAP source lists.) These are defined as level 0 detections, and are reported in the HSC Detailed Table to have a value of Det = Y.

    Sources that are found in the white light detection image, but not in a particular filter used to make the white light image, are regarded as "filter-based non-detections". These have Det = N in the Detailed Table.

    NOTE: Currently the HSC search form does not show non-detections for direct cone searches of the Detailed Table but does include them in the lists of measurements for a specific MatchID. Searches in the database are more flexible and can be applied to the non-detections.

    More details about how HLA images are constructed can be found at the HLA Images FAQ. More details about how HLA source lists are constructed can be found at the HLA Source List FAQ. The generation of the HAP products is description in the Drizzlepac documentation, and the source code used for the HAP products is available online in Github.

    A general outline of the entire process of making the HSC is available in section 3.1 of Whitmore et al. 2016.

  2. How are "matches" defined in the HSC? What is the algorithm that combines the sources?

    The source detections (and non-detections) that correspond to the same physical object (as determined by the algorithms defined in Budavari & Lubow 2012) are given a unique MatchID number and an associated match position (MatchRA, MatchDec). Each member of the match, including non-detections, also has an assigned MemID value and a source position (SourceRA, SourceDec). As part of the matching process, astrometric corrections are made to overlapping images. Each source detection and non-detection has a separation distance, D (small d in the plots below), from the match position.

    Distribution of relative astrometric errors in HSCv4 and HSCv3. Left panel: Scatter in source positions for matched sources before (orange) and after (blue) HSCv4 processing. Right panel: Same distribution but showing much larger offsets and using a logarithmic y axis. The green line shows the results for HSCv3.

    The two plots show (in blue) the distribution of the relative astrometric errors in version 4 of the HSC corrected astrometry, as measured by the positional offsets of the sources contributing to multi-visit matches from their match positions. Plotted in orange are the corresponding distributions of astrometric errors based on the original HST image astrometry. The areas under the blue and orange curves in the left plot are the same, but the original distribution (orange curve) has a long tail that extends far beyond the limits of the plot.  Note that the HAP astrometry has already been calibrated using Gaia DR3 and other external catalogs, but the HSCv4 astrometry is nonetheless still significantly improved compared with the original positions.

    The right plot is on a much larger distance scale than the left plot. Furthermore, the right plot has a logarithmic vertical scale.  Large astrometric errors up to 5 arcsec occur for both the HAP catalogs (orange) and the HSCv3 catalog (green). Such large errors are rare, but even larger errors occur in the worst cases. HSCv4 (blue) has completely eliminated the long tail of sources with large errors. In version 4, the peak (mode) of the HSC corrected astrometric error distribution is 3.4 mas, while the median offset is 6.9 mas. For comparison, the values for HSCv3 were 3.0 mas (mode/peak) and 7.6 mas (median).  The increase in the mode for HSCv4 is due to degradation in the WFC3/IR astrometry.  See the astrometry discussion and the HSCv4 Astrometry page for more details.

    To summarize, the relative astrometric error distribution in the original HST images has a long tail that has been greatly reduced by the HSC corrections, and the tail for HSCv4 is improved further compared with HSCv3.  Many more details are available on the HSCv4 Astrometry page, which has more information on both the algorithms used, on the measured accuracy of absolute and relative astrometry in HSCv4, and careful comparisons between HSCv3 and HSCv4 astrometry.

  3. What are the HSC Summary Search Form and the HSC Detailed Search Form?

    Older versions of the HSC were accessed via custom web forms, including the Summary Search Form (which searched the list of objects in the HSC) and the Detailed Search Form (which accessed individual measurements of those objects taken in different filters. Those forms are no longer available, and new access modes for MAST catalogs are currently under active development.  The primary current access to the HSC is via the CasJobs and TAP database interfaces.  This section will be updated with additional information when the new MAST Catalogs interface is released.

    Properties of some of the main HSC tables that were accessed by the Summary Search Form and the Detailed Search Form are described below.  If you need information about the older form interfaces themselves, refer to the documentation for HSCv3.

  4. What information is available in the HSC summary tables?

    The HSC summary tables include results for all detections for a given match on a single row. The magnitudes from repeated visits using the same filter and camera are averaged together.  The positions for all detections (from any camera or filter) are combined into a single match position.  A variety of other summary information for each match is included. 

    Below are details on some of the main tables.  Note that the structure of the tables is almost identical to the tables for HSCv3.  Most of the changes affect only the ancillary tables (e.g., the hlascience table from HSCv3 is simply called the Science table in HSCv4).

    The SumPropMagAper2Cat  table contains information for each match that is independent of the particular camera and filters that observed the source.
    Table SumPropMagAper2Cat
    Description: This table summarizes properties of each match based on sources with valid Source Extractor aper2 magnitudes. The companion table SumMagAper2Cat contains the aper2 magnitude information for the match.
    nameunitsdatatypedescription
    MatchIDnonebigintidentifier for the match
    MatchRAdegreesfloatright ascension coordinate of the match position
    MatchDecdegreesfloatdeclination coordinate of the match position
    DSigmamilliarcsecondsfloatstandard deviation of source positions in match
    AbsCorrnonecharindicator of whether the match contains sources that are aligned to a standard catalog
    NumFiltersnoneintnumber of filters in match with sources detected in the aper2 aperture
    NumVisitsnoneintnumber of visits in match with sources detected in the aper2 aperture
    NumImagesnoneintnumber of HAP or HLA single filter, visit-combined (level 2) images in match with sources detected in the aper2 aperture
    StartTimetimedatetimeearliest start time of exposures in match with sources detected in the aper2 aperture
    StopTimetimedatetimelatest stop time of exposures in match with sources detected in the aper2 aperture
    StartMJDtimefloatmodified Julian date (MJD) for earliest start time of exposures in match with sources detected in the aper2 aperture
    StopMJDtimefloatmodified Julian date (MJD) for latest stop time of exposures in match with sources detected in the aper2 aperture
    TargetNamenonestringname of a target for an exposure in match
    CInonefloataverage normalized concentration index for sources detected in the aper2 aperture within the match
    CI_Sigmanonefloatstandard deviation of normalized concentration index values for sources detected in the aper2 aperture within the match
    KronRadiusarcsecondsfloataverage Kron radius for sources detected in the aper2 aperture within the match
    KronRadius_Sigmaarcsecondsfloatstandard deviation of Kron radius values for sources detected in the aper2 aperture within the match
    Extinctionmagnitudesfloatextinction, obtained from the NASA/IPAC Extragalactic Database (NED), along the line of sight to the match position
    SpectrumFlagnonenoneY/N indicator of whether there is a spectrum in the Hubble Legacy Archive for this match. If the value is Y, then there is an entry in table SpecCat for the match.

    The SumMagAper2Cat table has the information on magnitudes.  Note this table has many columns. There are 133 filters with 3 columns for every filter: the magnitude (e.g., A_F814W), the median absolute deviation scatter among the magnitude measurements (e.g., A_F814W_MAD) and the number of visits for that filter (e.g., A_F814W_N).  
    Table SumMagAper2Cat
    Description: This table provides Source Extractor MagAper2 information for each match based on sources with valid Source Extractor aper2 magnitudes. This table contains the same information as table SumMagAper2, but has a row for each for each MatchID and columns for each Filter and Detector. Table SumMagAper2 has a row for each MatchID, Filter, and Detector. The companion table SumPropMagAper2Cat contains other summary information for each corresponding match.
    nameunitsdatatypedescription
    MatchIDnonebigintidentifier for the match
    <Instrument>_<Filter>nonefloatmedian aper2 magnitude in match for instrument and filter, with instrument encoded as A for ACS, W2 for WFPC2, and W3 for WFC3
    <Instrument>_<Filter>_MADnonefloatmedian absolute deviation of the aper2 magnitudes in match for instrument and filter
    <Instrument>_<Filter>_Nnonefloatnumber of magnitude values in match for instrument and filter

    The SumMagAper2 table contains the same information in a more compact form, with one row for each filter. In many cases, it is easier to work with the SumMagAper2 table instead of the SumMagAper2Cat table.  The ...Cat version has a single row for each MatchID , which may sound simpler until you realize that almost all of the magnitudes are null because there are few places in the sky where there are observations in many filters.  The more compact version has multiple rows for each match (if there are multiple filters), but presents the data in a compact form without all the null column values.
    Table SumMagAper2
    Description: This table provides Source Extractor MagAper2 information for each match based on sources with valid Source Extractor aper2 magnitudes. This table contains the same information as table SumMagAper2Cat, but has a row for each MatchID, Filter, and Detector. Table SumMagAper2Cat has a row for each MatchID and columns for each Filter and Detector. The companion table SumPropMagAper2Cat contains other summary information for the corresponding match.
    nameunitsdatatypedescription
    MatchIDnonebigintMatchID of a match
    Filternonestringname of filter used in match
    Detectornonestringname of detector used in match
    nnoneintnumber of contributing visit based exposures
    MagMedmagnitudesfloatmedian value of the contributing aper2 magnitudes
    MagMADmagnitudesfloatmedian absolute deviation of the contributing aper2 magnitudes

    There are similar tables available that give data on the segment magnitudes ("MagAuto") rather than the aperture magnitudes: SumPropMagAutoCat, SumMagAutoCat  and SumMagAuto .  There are also many other tables available that give metadata on the observations.  Here is a brief description of some other tables:
    Table NameDescription
    Science Image name, date of observation, exposure time, number of exposures, etc.
    Groups, GroupMembers Overlapping observations that were processed together
    Images, ImageMembersFilters that are included in each visit, numbers of objects in source lists, astrometric correction information
    XMatchV3 Links between objects in HSCv4 and objects in HSCv3 (see below for more details)


  5. What information is available in the HSC detailed tables?

    More information about the individual detections that went into a given match can be obtained by searching the detailed tables for the appropriate MatchID value. The primary information is in the DetailedCatalog table.  A single row in the summary table can match many rows in the DetailedCatalog table, depending on the number of different camera/filter observations that were made for that source. 

    Note that this table also includes some information on non-detections: entries with Det='Y'  are normal detections of the match object, but entries with Det='N' are cases where the particular filter overlapped the source but the source was not detected.  Such entries exists only when the object was detected in some other filter in the same visit.  In many cases you will only want the rows from the DetailedCatalog  table where Det='Y'.

    Table DetailedCatalog
    Description: This table contains the properties of each source in the Hubble Source Catalog.
    nameunitsdatatypedescription
    CatIDnonebigintunique row identifier
    MatchIDnonebigintmatch identifier
    MemIDnoneintsource number within match
    SourceIDnonebigintwhite light source identifier
    ImageIDnonebigintwhite light image identified
    DetnonecharY/N indicator of whether source was detected in the specified filter
    MatchRAdegreesfloatright ascension coordinate of the match position
    MatchDecdegreesfloatdeclination coordinate of the match position
    SourceRAdegreesfloatright ascension coordinate of the source position
    SourceDecdegreesfloatdeclination coordinate of the match position
    Dmilliarcsecondsfloatoffset distance of source from match position
    DSigmamilliarcsecondsfloatstandard deviation of source positions from match position
    AbsCorrnonecharY/N indicator of whether the astrometric correction included alignment with a standard catalog
    XImagepixelsfloatx position of source in image coordinates
    YImagepixelsfloaty position of source in image coordinates
    ImageNamenonestringHubble Legacy Archive image name
    Instrumentnonestringinstrument name
    Modenonestringobservation mode
    Detectornonestringdetector
    Aperturenonestringaperture
    ExposureTimesecondsfloatexposure time
    StartTimetimedatetimeearliest start time of exposures in image
    StopTimetimedatetimelatest stop time of exposures in image
    StartMJDtimefloatmodified Julian date (MJD) for earliest start time of exposures in image
    StopMJDtimefloatmodified Julian date (MJD) for latest start time of exposures in image
    WaveLengthAngstromsfloatcentral wavelength of filter
    Filternonestringfilter
    TargetNamenonestringtarget name
    FluxAper2counts per secfloataper2 flux
    MagAper2magnitudefloataper2 magnitude
    MagAutomagnitudefloatauto magnitude
    PropIDnoneintHST proposal ID
    CInonefloatnormalized concentration index
    KronRadiusarcsecondsfloatKron radius
    Flagsnoneintbit encoded representation of source properties: 0 for point source, 1 for extended source, 4 for saturated source

FAQ - About Spectroscopic Cross Matching

  1. What spectra are included?

    NOTE: The initial release of HSC version 4 does not have any spectral links, and we do not currently have the staffing support required to add those links. This section will be updated if and when the links are added. See the documentation for older versions of the HSC for more information.


FAQ - About Accessing the HSC

  1. How can I use the MAST Discovery Portal to access the HSC?

    The MAST (Mikulski Archive for Space Telescopes) Discovery Portal was designed to provide "one-stop" web access to the MAST missions (e.g., HST, Kepler, GALEX, FUSE, IUE, EUVE, Swift, XMM, ...), and the even broader world of the Virtual Observatory (VO). Here is a general description of the Discovery Portal and here is the Portal User Guide. With the Version 1 release, the Discovery Portal also becomes the primary way to access the HSC. The tools include:

    -- Searching and filtering the HSC database.
    -- Viewing the HSC or filtered subsets overplotted on images (e.g, DSS, Pan-STARRS, GALEX, SDSS, and HST). Access to the HLA Interactive Display is also available.
    -- Viewing the HSC in a table format. Creating new columns and plotting one column vs. another.
    -- Cross matching with a wide range of surveys including GALEX, SDSS, 2MASS, as well as tables available from CDS (Strasbourg Astronomical Database).
    -- Uploading or downloading tables data from/to local files.
    -- And as of HSC version 2, showing spectroscopic data from the ACS Grisms, COS, FOS and GHRS cross matched with the HSC. See the FAQ - About Spectroscopic Cross Matching for details.

  2. How can I cross match objects between Version 3 and Version 4?

    There may be circumstances when a researcher has a list of objects they were working on from HSC version 3 but would now like to identify their counterparts in Version 4. This can be done using a table called xMatchV3 which is available via HSC CasJobs. Here is a description of the table.
    Table XMatchV3
    Description: For each match, this table contains a list of possible corresponding matches from Version 3 of the HSC.
    nameunitsdatatypedescription
    MatchIDV3nonebigintMatchID from Version 3
    MatchIDV4nonebigintMatchID from current HSCv4 that lies within 0.3 arcseconds of MatchIDV3
    DistArcSecarcsecondsfloatseparation of matches MatchIDV3 and MatchIDV4
    Ranknoneintfor a given MatchIDV3, this number is in order of increasing separation for each MatchID4

    The maximum value of Rank  is 3 (more distant matches are omitted to reduce the table size in crowded regions).  The maximum value of DistArcSec is 0.3 arcsec.

    After logging into HSC CasJobs (see HSCv3 Use Case #2 if you are not familiar with CasJobs), click on MyDB and then set the context to HSCv4. Under Tables you will find the file XMatchV3. Click on that to see the help file. Try running this short script showing how to do a match for a specific region of the sky around M83:

    select s4.MatchRA, s4.MatchDec, x.MatchIDV4, x.MatchIDV3,
	d=dbo.fDistanceArcMinEq(s3.MatchRA, s3.MatchDec, s4.MatchRA, s4.MatchDec)*60.0*1000, Rank
from xmatchv3 x 
join hscv3.SumPropMagAper2Cat s3 on x.MatchIDV3=s3.MatchID
join SumPropMagAper2Cat s4 on x.MatchIDV4=s4.MatchID
where s3.MatchRA > 204.252 and s3.MatchRA < 204.256
  and s3.MatchDEC > -29.867 and s3.MatchDEC < -29.863
  and x.Rank < 2 and x.DistArcSec < 0.1
    casjob Note that this script assumes:

    1. Only the nearest source should be listed (i.e., x.rank < 2, there may be circumstances when you relax this to look for other nearby sources.)
    2. The largest value of the distance between the V3 and V4 source should be 0.1 arcsec (i.e., 100 mas (i.e., xDistArcSec < 0.1)

      These two parameters (and others such as the RA and DEC of course) can be modified in the script if different values are wanted.

      The output can be saved as a file and then read into the Discovery Portal to examine the quality of the cross matching. Modifications (e.g., a different upper limit in D) can also be made in the Discovery Portal (see the graphic on the right for an example) and then saved in a file, or the user can go back to the HSC CasJobs query and make modifications there if they prefer.

      DP_example Here we show an example (from HSC Use Case # 1 of using the Discovery Portal to make a color-magnitude diagram, highlighting a specific object (yellow) and showing its location in the image, its values in the table, and its position in the plot.

      NOTE: Both HSC versions 2 and 3 are available using the cross-match capabilities and the "Select a collection" box of the Discovery Portal.

  3. FAQs specific to the Discovery Portal

    Note that these are not currently relevant to HSCv4, which is at this time not searchable via the Portal.

    Question: I looked at the HLA Interactive Display and saw that there were 100,000 objects in the HSC for a specific image. Why does the Discovery Portal (DP) query only return 50,000? 
    Answer: 50,000 is the maximum number of records currently supported for query results in the Discovery Portal. Larger queries can be handled in the HSC CasJobs tool.

    Question: Can I import my own catalog of objects into the DP?
    Answer: Yes, using the "Upload Target List" button just below the "Select a collection" box (i.e., the icon).

    Question: How can get get the MagAuto magnitudes instead of MagAper2 in the DP?
    Answer: The Discovery Portal can now access both aperture magnitudes (i.e., MagAper2) and estimates of total magnitudes (i.e., using the MagAuto algorithm in Source Extractor). Select the magnitude you want using the popup menu underneath the Collection menu that was used to select HSCv3.

    Question: Where is the plot icon you mention in the use case? I don't see it on the screen.
    Answer: Depending on the size of the box with the target position (entering a target position generally makes the box big while entering a target name does not), the AstroView window can COVER UP the icon. By grabbing the side of the AstroView window and dragging to the right, you can shrink the window and reveal the row of icons.

    DP_example Question: Can I overlay the HSC on HST images?
    Answer: Yes. After doing your query, click on the icon under Actions (Load Detailed Results) . This will show you the details for a particular MatchID, including cutouts for all the HST images that went into this match. If you then click on the icon under Action (Toggle Overlay Image) (blue circle in the image - see Use Case # 1), the HST image will be displayed over the DSS image in AstroView.

    Question: Can I bring up the HLA interactive viewer from the DP?
    Answer: Yes. After doing your query, click on the first icon under Actions (Load Detailed Results). This will show you the details for a particular MatchID, including cutouts for all the HST images that went into this match. If you click on the cutout (green circle in the image - see Use Case # 1) , the HLA interactive viewer will come up.

    Question: Can I change the contrast control in the AstroView window?
    Answer: Not at this time. The HLA Interactive Display, discussed above, can be used for this.

    Question: Can I center the field on a selected target?
    Answer: Yes, click on the bulls-eye icon for the target of interest.

  4. How can I use CasJobs to access the HSC?

    The primary purpose of the HSC Catalog Archive Server Jobs System (CasJobs) is to permit large queries, phrased in the Structured Query Language (SQL), to be run in a batch queue. CasJobs was originally developed by the Johns Hopkins University/Sloan Digital Sky Survey (JHU/SDSS) team. With their permission, MAST has used version 3.5.16 of CasJobs to construct three CasJobs-based tools for GALEX, Kepler, and the HSC.

    While HSC CasJobs does not have the limitations of only including a small subsample of the HSC (i.e., 50,000 objects), as is the case for the MAST Discovery Portal, it also does not have the wide variety of graphic tools available in the Discovery Portal. Hence the two systems are complementary.

    This figure (from HSC Use Case # 2 and a MAST Jupyter notebook tutorial) provides a demonstration of the speed and power of the HSC CasJobs interface. Starting from scratch, imagine how long it would take to construct a color-magnitude diagram for all Hubble observations of the Small Magellanic Cloud (SMC). A search of the Hubble Mission archive shows 2,155 imaging observations in this region, 377 of them with ACS. With HSC CasJobs, a color-magnitude for 765 thousand ACS/WFC measurements can be made in less than five minutes.

    Casjobs also provides a personal database (i.e. MyDB) facility where you can store output from your queries and save stored procedures and functions. This powerful aspect of Casjobs can also be used as a group sharing facility with your collaborators.

  5. FAQs specific to CasJobs

    Question: Why does my query give me an error saying that the function I was using (e.g. SearchSumCatalog) is an invalid object name?
    Answer: This error usually indicates that the context is set incorrectly. Check that the context says HSCv4 and not MyDB. This is probably the MOST FREQUENT PROBLEM people have with HSC CasJobs. (See the blue oval under Context in the image, and see use case # 2 for more details.)

    casjob Question: I created an output catalog a while ago, and when I go to the Output tab it is no longer there. What happened to it?
    Answer: There is a lifetime for output of 1 week. Tables in your MyDB database do not get deleted though, so you can recreate the output.

    Question: When I tried to plot my table, I got an error message saying that the input string was not in a correct format. What is wrong?
    Answer: If there are any entries that have non-numeric values (such as NaN indicating no data), the plotting tool cannot handle them. The solution is to restrict your queries to only real numbers by adding a condition such as: A_F606W > 0 which will only include sources with measured values.

    Question: What does 'Query results exceed memory limitations' mean?
    Answer: This means the result of the query which you've submitted is greater than the memory buffer will allow. This message only applies to 'quick' queries; queries using 'submit' do not have any memory restrictions. The easiest thing to do is just use submit instead of quick.

    Question: How do I see all the searches I have done?
    Answer: The History page will show all the queries you have done, as well as summary information (submit date, returned rows, status). If you click on Info, you can see the exact query that executed, and resubmit the job if you like.

    Question: How do I see all the results I have generated?
    Answer: The MyDB page shows you all the tables you have generated. Clicking on the table name will show you the details of the table.

    Question: How do I see all the available HSC tables, functions, and procedures?
    Answer: Click on the MyDB at the top of the page, and then set the context to HSC. Clicking on the Views (currently empty), Tables, Functions, and Procedures will list the available material. Clicking on specific tables or functions will provide more information. (NOTE: When looking at functions, the default is to show the source code. To see the description instead, click on "Notes" near the top of the page.)

    Question: Where are some example queries to run?
    Answer: Several of the HSC Use Cases have examples (e.g., Use Cases #2 and #5). Another good place to look is by clicking the Samples button after you hit the Query button (e.g., provides examples of cross matching and making histograms). There are also pointers to SDSS training materials on the left of the HSC HELP page.

    Question: Where can I find the schema information for various HSC tables, functions and procedures (i.e., similar to the SDSS SkyServer Schema Browser)?
    Answer: To get the schema for different HSC tables, function and procedures, first go to the top of the page and click on MyDB to bring up the database page. Next go to the drop down menu in the upper left and select HSC as the "context". Now click on one of the tables to see its schema information. To view schema for views, functions and procedures, click on the appropriate link below the context menu.

  6. How can I use Python to access the HSC?

    The MAST CasJobs server has a programmatic interface that can be used to run SQL queries from scripting languages including Python. We have created the mastcasjobs Python module to make this relatively simple. See the Python Jupyter notebook created to access the SWEEPS data in HSC v3.1 for working examples of how to run these queries.

    Note that you will still need to write SQL queries to use this interface via Python. But the ability to script queries in order to run many similar queries using variable parameters can make certain projects far easier.


FAQ - About Quality

  1. What are specific limitations and artifacts that HSC users should be aware of?

    NOTE: Unless otherwise noted, the graphics in this section are taken from version 1.

    The Hubble Source Catalog is composed of visit-based, general-purpose source lists from the Hubble Advanced Products and the Hubble Legacy Archive. While the catalog may be sufficient to accomplish the science goals for many projects, in other cases astronomers may need to make their own catalogs to achieve the optimal performance that is possible with the data (e.g., to go deeper). In addition, the Hubble observations are inherently different than large-field surveys such as SDSS, due to the pointed, small field-of-view nature of the observations, and the wide range of instruments, filters, and detectors. Here are some of the primary limitations that users should keep in mind when using the HSC .

    LIMITATIONS:

    Uniformity: Coverage can be very non-uniform (unlike surveys like SDSS), since a wide range of HST instruments, filters, and exposure times have been combined. We recommend that users pan out to see the full HSC field when using the Interactive Display in order to have a better feel for the uniformity of a particular dataset. Adjusting the value of NumImages used for the search can improve the uniformity in many cases. See image below for an example.


    Astrometric Uniformity: In version 4, about 88% of HSC images have calibrations from Gaia DR3, and another 8% have coverage in Pan-STARRS (or rarely in 2MASS or SDSS) that permits absolute astrometric corrections of the images (i.e., AbsCorr = Y). For Gaia matches, we use the proper motions and parallaxes (when available) to shift the Gaia reference stars to the epoch of the HST observation.  That leads to significant improvement in the HSC astrometric calibration for observations that are not near the Gaia reference epoch (2016.0 for DR3).  The absolute median error is about 10–15 mas for objects in Gaia-calibrated images, depending on the camera. (For HSCv3 the error was 10 mas at the Gaia epoch and increased due to proper motions by about 5 mas/yr at earlier and later epochs.) The errors when using the other reference catalogs (only when there are too few Gaia reference stars) may be larger, up to 0.1 arcsec. See Whitmore et al. (2016) for more details about astrometry and to see the corresponding map for version 1. In version 4 we always prefer Gaia DR3 when possible, and fall back on Pan-STARRS, SDSS and 2MASS (in that order) for fields where there are fewer than 4 matches to Gaia stars. Note that the Pan-STARRS astrometry has been recalibrated using Gaia DR3 so that it is also accurate (see Lubow et al. 2021 and White et al. 2022 for details).

    See the HSCv4 Astrometry page for many more details about both absolute and relative astrometry in HSCv4 and for comparisons with HSCv3.

    Depth: The HSC does not go as deep as it is possible to go. This is due to a number of different reasons, ranging from using an early version of the WFPC2 catalogs (see "Five things you should know about the HSC"), to the use of visit-based source lists rather than a deep mosaic image where a large number of images have been added together.

    Completeness: The current generation of HLA WFPC2 Source Extractor source lists have problems finding sources in regions with high background. The ACS and WFC3 source lists are much better in this regard. The next generation of WFPC2 source lists will use the improved ACS and WFC3 algorithms, and will be incorporated into the HSC in the future.

    Visit-based Source Lists: The use of visit-based, rather than deeper mosaic-based source lists, introduces a number of limitations. In particular, much fainter completeness limits, as discussed in Use Case # 1. Another important limitation imposed by this approach is that different source lists are created for each visit, hence a single, unique source list is not used. A more efficient method would be to build a single, very deep mosaic with all existing HST observations, and obtain a source list from this image. Measurements at each of these positions would then be made for all of the separate observations (i.e., "forced photometry"). This approach will be incorporated into the HSC in the future.

    ARTIFACTS:

    False Detections: Uncorrected cosmic rays are a common cause of blank sources. Such artifacts can be removed by requiring that the detection be based on more than one image. This constraint can be enforced by requiring NumImages > 1.

    Another common cause of "false detections" is the attempt by the detection software to find large, diffuse sources. In some cases this is due to the algorithm being too aggressive when looking for these objects and finding noise. In other cases the objects are real, but not obvious unless observed with the right contrast stretch and field-of-view. It is not easy to filter out these potential artifacts without loosing real objects. One technique users might try is to use a size criteria (e.g., concentration index = CI) to distinguish real vs. false sources.

    Yet another source of false detections is artifacts around bright stars due to bleeding, diffraction spikes, and other PSF features.

    Doubling: There are occasionally cases where not all the detections of the same source are matched together into a single objects. In these cases, more than one match ID is assigned to the object, and two pink circles are generally seen at the highest magnification in the display.  See the known problems discussion above for more details on this issue.

    Mismatched Sources: The HSC matching algorithm uses a friends-of-friends algorithm, together with a Bayesian method to break up long chains (see Budavari & Lubow 2012) to match detections from different images. In some cases the algorithm has been too aggressive and two very close, but physically separate objects, have been matched together. This is rare, however.

    Bad Images: bad_image Images taken when Hubble has lost lock on guide stars (generally after an earth occultation) are the primary cause of bad images. We attempt to remove these images from the HLA, but occasionally a bad image is missed and a corresponding bad source list is generated. A document showing these and other examples of potential bad images can be found at the HLA Images FAQ. If you come across what you believe is a bad image please inform us at archive@stsci.edu.

  2. Is there a summary of known image anomalies?

    anomalies Yes — see the HLA Images FAQ. Here is a figure from the document showing a variety of artifacts associated with very bright objects.

  3. How good is the photometry for the HSC?

    See the new HSCv4 Photometry page for a detailed answer to this question.  We have taken a multi-faceted approach to text the both the absolute and relative accuracy of the HSCv4 photometry. In summary:
    • The WFC3/UVIS and ACS/WFC photometry is significantly improved in HSCv4 compared with HSCv3 (by as much as a factor of 2) when measured by the variation of repeated measurements of the same object in globular cluster M4 and the SWEEPS field in the Galactic halo. Repeated measurements in the HSC typically now have noise smaller than 0.01 magnitudes.
    • The WFC3/IR data is significantly poorer in HSCv4 than in HSCv3. We attribute this to the larger pixel size for the HAP images compared with the HLA images.  For the other cameras, the overall noise distribution looks similar in the two versions.
    • In a single tested field, HSCv4 has smaller biases in absolute photometry compared with HSCv3, and both agree very well with the deep photometric catalog.  The HSCv4 offsets in two filters are 0.006 and 0.003 magnitudes. The absolute photometry was tested by comparing with the Brown et al. (2009) deep ACS/WFC catalog of the outer disk of M31.

  4. How does the HSC version 4 photometry compare with version 3?

    In short, the photometry in HSCv4 is significantly improved for ACS/WFC and WFC3/UVIS compared with HSCv3.  The noise level in the HSCv4 is (in many fields at least) a factor of 2 better than HSCv4.

    The WFPC2 photometry in HSCv4 is based on the same HLA catalogs as HSCv3 and so is essentially identical to HSCv3.

    On the other hand, the HSCv4 WFC3/IR photometry is definitely inferior to HSCv3.  We believe that is due to the larger pixel size used for the HAP images compared with the HLA images.

    See the HSCv4 Photometry page for detailed discussion of all these points and for direct comparisons between HSCv3 and HSCv4.

  5. What is the "Normalized" Concentration Index and how is it calculated?

    In version 1, one of the items in the List of "Known Problems" was that raw values of the Concentration Index (the difference in magnitude for aperture photometry using magaper1 and magaper2) were added together to provide a single mean value in the summary form. The reason this is a problem is that each instrument/filter combination has a different normalization. For example, the Peak of Concentration Index for Stars and Aperture Correction Table shows the raw values of the concentration index for stars is 1.08 for the ACS_WFC_F606W filter, 0.88 for WFC3_UVIS_F606W and 0.86 for WFPC2_F606W. Similarly, the raw values of the concentration index vary as a function of wavelength for some detector. For example, WFC3_F110W has a peak value of 0.56 while WFC3_160W has a value of 0.67.

    Hence, averaging the mean values of the Concentration Index together in Version 1 resulted in values that were not always very useful, and were often misleading.

    Starting with version 2 we have corrected this by normalizing (dividing by) the value of the peak of the raw concentration index for stars using observations from each instrument and filter, as provided in the table listed above. The values are then averaged together to provide an estimate of the "Normalized" Concentration Index, which is listed as the value of CI in the summary table.

    With this change, objects with values of CI ~ 1.0 are likely to be stars while sources with much larger values of CI are likely to be extended sources, such as galaxies. There are cases where this is still not true (e.g., saturated stars, cosmic rays, misaligned exposures within a visit, ...), hence caution is still required when using values of CI.

    The CI values are slightly improved in HSC version 4 because of the improved filter and exposure alignment in the HAP pipeline (using Gaia DR3) and also due to improved geometric distortion models for the cameras, which makes the alignment more uniform in the corners of images. The figure below shows that the images are consistently sharper, with the CI distribution concentrated more tightly around unity.

    Comparison of the concentration index distributions for HSCv4 and HSCv3. The y-axis shows the counts in bins of size 0.01. For HSCv3, the distribution has been normalized to have the same integral as in HSCv4. The HSCv4 distribution is very similar to HSCv3; it is slightly narrower and more tightly distributed around unity, which is the CI value for point sources. The improvement is due to better alignment algorithms and improved geometric distortion models in the HAP processing. There is a sharp cut around a CI value of 0.8 that is currently being explored. 

  6. How good is the astrometry for the HSC?

    See the HSCv4 Astrometry page for a detailed discussion of this question.  The short answer is that the astrometry in HSCv4 is excellent.  The absolute astrometry is typically good to 10 to 15 milliarcseconds, depending on the camera (WFPC2 is worst, the other cameras are all good).  88% of the images have absolute calibrations based on Gaia DR3, and 8% of the images are aligned using the Pan-STARRS catalog (which is itself aligned to Gaia DR3).  The relatively astrometry is even better, with typical errors of a few mas. 

    The HSC astrometric solution is designed to minimize the scatter among positions of objects in HST images.  This is not the same as minimizing the error relative to the Gaia reference frame (streaming motions within fields are removed). See the HSCv4 Astrometry page for more discussion.

  7. How does the HSC compare with Gaia astrometry?

    The HSCv4 Astrometry page discusses this in considerable detail.  Here is a sample figure showing the histogram of offsets between HSCv4 and Gaia DR3 sources for different instruments.  It also shows the results for HSCv3.   There are significant improvements between HSCv3 and HSCv4.

    Note that the reason the errors are as large as 10 mas is that the HSC astrometric solution is designed to minimize the scatter among positions of objects in HST images.  This is not the same as minimizing the error relative to the Gaia reference frame (in particular, streaming motions within fields are removed).  A future reanalysis of the HSCv4 data could improve the absolute astrometry by better preserving astrometry in fields with streaming motions, while simultaneously computing proper motions for many HSC fields.  A similar pilot project for HSCv3 produced HSCv3.1, which has proper motions in the SWEEPS field.

    Histogram of separations between Gaia DR3 positions and HSC positions for the four different cameras. The histograms have exactly the same number of points for HSCv4 and HSCv3 because they use a matched sample of objects.  In all cases, the HSCv4 distribution (solid blue line) has smaller astrometric errors than the HSCv3 distribution (dotted orange line).  The difference is smallest for WFPC2 because the same input source lists were used for the two versions of the HSC.

  8. Does the HSC include proper motions?

    Objects in HSC v4 do not have proper motions in the database, but it is possible to compute proper motions if the time coverage is sufficient. For HSC v3.1, we recalibrated the astrometry for the SWEEPS field using Gaia DR2 and have computed proper motions for more than 400,000 faint stars down to magnitude 27. See the additional HSC v3.1 documentation for more information.  That improvement has not been implemented yet for HSCv4.

  9. What are the future plans for the HSC?

    Tentative plans for future development of the HSC include:
    1. Improve the WFPC2 source lists using HAP pipeline products.
    2. Compute higher quality astrometry including proper motions as was done for the SWEEPS field included in HSC v3.1.
    3. Install the HSC database on a new, high-performance database server that will enable much faster large queries.
    4. Integrate JWST source lists into the HSC to create a cross-matched catalog of Hubble and Webb object measurements.

FAQ - About Use Cases and Documentation

  • Are there Use Cases available for the HSC?

    Yes. We have a variety of Use Cases. Most of these currently use older versions of the HSC, and they are still being updated to HSC version 4. The older catalog versions are similar enough that the older use cases are still good examples of how to use the data. Newly updated pages are indicated with `[HSCv4] labels.

    The following use cases have been updated for HSCv4:

HSC Use Case #2 [HSCv4] - Using CasJobs to Query the HSC - (Globular Clusters in M87 and a Color Magnitude Diagram for the SMC)

The following use cases utilize older versions of the HSC, pending updates:

SWEEPS Python Jupyter notebook - Using HSC v3.1 astrometry tables to study the proper motions of 400,000 stars in the SWEEPS field

HSCv3 Use Case #1 - Using the Discovery Portal to Query the HSC - (Stellar Photometry in M31 - Brown et al. 2009)

HSC Use Case #3 - Using the Discovery Portal to search for Variable Objects in the HSC - (Time Variability in the dwarf irregular galaxy IC 1613)

HSC Use Case #4 - Using the Discovery Portal to perform cross-matching between an input catalog and the HSC - (Search for the Supernova 2005cs progenitor in the galaxy M51)
NOTE: This use case was made using version 1. However, most of the changes are relatively minor, hence it is still quite useful.

HSC Use Case #5 - Using the Discovery Portal and CasJobs to search for Outlier Objects in the HSC - (White dwarfs in the Globular Cluster M4)

HSC Use Case #6 - Using the Discovery Portal to study the Red Sequence in a Galaxy Cluster - (The Red Sequence in the Galaxy Cluster Abell 2390)
NOTE: This use case was made using version 1. However, most of the changes are relatively minor, hence it is still quite useful.

HSC Use Case #7 - Comparing HSC "Sloan" filter magnitudes and SDSS magnitudes - (using the field around GRB110328A)
NOTE: This use case was made using version 1. However, most of the changes are relatively minor, hence it is still quite useful.

HSC Use Case #8 - Combining HSC magnitudes and HST spectra to Investigate Objects in the HSC (using objects in the LMC Cluster R136)

HSC Use Case #9 - Searching for Objects with both HST Imaging and Spectroscopic Data

HSC Use Case #10 - Using the HSC to determine positions for a JWST NIRSpec Multi-Object Spectroscopic (MOS) observation

Archived Use Cases from Beta 0.2:

NOTE: The following archival use cases are outdated, but included here since they provide some detailed information that may be of interest to people. They do not make use of the Discovery Portal, or CasJobs interface, and they may contain features that are no longer included in the HSC interfaces (e.g., VOPLOT).

M31 - Point Source Photometry (Beta 0.2 version)

Galaxy IC 1613 - Time Variable Phenomena (Beta 0.2 version)

M87 - Photometry of Slightly Resolved Objects (Beta 0.2 version) (video tutorial)

  • Are there training videos available for the HSC?

    There were previously two videos available, but because they rely on the Flash plugin (which has been retired), they no longer work.

    There is a Hubble Hangout that features the HSC.

  • Is there a Facebook page available to share information (e.g., your own use cases) about the HSC?

    Facebook_sn1987aThere is an HSC Facebook Page, but it is not actively updated.  Some of the items posted have been:

    February 26, 2015 - Comparing HSC and SDSS photometry of galaxies. This was eventually included in the Whitmore et al. (2016) article.

    March 17, 2015 - Announcement of a Hubble Hangout featuring the HSC.

    May 6, 2015 - Making a light curve for SN 1987A (see figure).



  • Is there a journal-level article on the HSC available for reference?

    Yes, see Whitmore et al. (2016), titled "Version 1 of the Hubble Source Catalog".

    There is also a description of the Beta version of the HSC and the matching algorithms used in Version 1 in Budavari & Lubow (2012).

  • How should I acknowledge that I have used HSC data in my papers?

    The HSC is based on data from the Hubble Legacy Archive (HLA). Refereed publications making use of the HSC should therefore include this footnote in the acknowledgements.

    "Based on observations made with the NASA/ESA Hubble Space Telescope, and obtained from the Hubble Legacy Archive, which is a collaboration between the Space Telescope Science Institute (STScI/NASA), the Space Telescope European Coordinating Facility (ST-ECF/ESAC/ESA) and the Canadian Astronomy Data Centre (CADC/NRC/CSA)."

    Authors are also asked to acknowledge the "Hubble Source Catalog" in the text of the paper, and reference the Whitmore et al. (2016) paper, if appropriate.

  • How can I provide feedback?

    Send an email to archive@stsci.edu. Please include enough information to make it possible to diagnose any problems. For example, it is helpful to include the version of the HSC you are using, the interface (MAST portal, CasJobs, HSC forms, etc.) and possibly a screen save of the problem. We also welcome suggestions for improvements.

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