An overview of ZTF and the science objectives is given in Bellm et al. 2019 and Graham et al. 2019. The ZTF Science Data System (ZSDS) is housed at IPAC/Caltech and is described in Masci et al. 2019. This page provides a summary and quick guide to the ZTF Public DR2 products.
Please familiarize yourself with all advisories highlighted in red before accessing and using the products.
ZTF observing time is split three ways:
(i) The Public Survey (40%);
(ii) Private Collaboration and Partnership Surveys (40%);
(iii) Programs granted by the Caltech Time Allocation Committee (20%).
Funding is provided by both the ZTF collaboration and the U.S. National Science Foundation through the Mid-Scale Innovations Program (MSIP).
The Public Survey in particular enables a wide range of community science and constitutes the following:
For publications that use ZTF Science Data Products, please include the following text in your acknowledgments:
Based on observations obtained with the Samuel Oschin 48-inch Telescope at the Palomar Observatory as part of the Zwicky Transient Facility project. ZTF is supported by the National Science Foundation under Grant No. AST-1440341 and a collaboration including Caltech, IPAC, the Weizmann Institute for Science, the Oskar Klein Center at Stockholm University, the University of Maryland, the University of Washington, Deutsches Elektronen-Synchrotron and Humboldt University, Los Alamos National Laboratories, the TANGO Consortium of Taiwan, the University of Wisconsin at Milwaukee, and Lawrence Berkeley National Laboratories. Operations are conducted by COO, IPAC, and UW.
Furthermore, we appreciate you citing the following publication:
Masci, F. J., Laher, R. R., Rusholme, B., et al. 2018, The Zwicky Transient Facility: Data Processing, Products, and Archive, PASP, 131, 995.
The Second ZTF Public Data Release (DR2) builds upon the First Data Release (DR1) to include products from (i) an additional six months of data acquired under the Public Survey (+ January to June 2019) and (ii) data acquired under Private Survey time (from both partnership and Caltech programs) from approximately the first 3.4 months of science operations (~ March to June 2018). The latter is included due to the 18 month embargo being lifted on the products.
More specifically, DR2 includes the following:
NOTE: The public distribution of transient alerts extracted from difference images constructed from products (1) and (3) above commenced on June 4, 2018. These alerts continue to be generated and distributed using new (unreleased) image data from the Public Survey.
In accord with the criteria for data-inclusion in Section 2, the following products are available in DR2:
For details on data and file formats, associated ancillary products, product construction and usage, see the ZSDS Explanatory Supplement. See Section 10 below for a list of MUST READ ADVISORIES about these products. See Section 11 below for a more detailed list of advisories and known caveats.
The ZTF camera consists of 16 CCDs, each of which is partitioned into 4 readout quadrants. Therefore, 64 CCD-quadrant images are generated per ZTF exposure. A CCD-quadrant is the basic image-unit for pipeline processing and from which all science data products are derived. A CCD-quadrant covers ≈ 0.854° x 0.854° on the sky. Table 1 summarizes the CCD-quadrant-based (single exposure) image counts. The second column shows the number of full camera exposures from which these were generated. The CCD-quadrant image counts are separated into "bad" (probably unusable due to non-photometric conditions) and "good" images. The criteria used to identify "bad" vs "good" images are described in Section 2.4 of the ZSDS Advisories & Cautionary Notes. The relative fractions of bad and good images in this table provides an indicator of the overall fraction of "bad" (likely suspect) single-epoch photometry measurements within individual lightcurves.
Filter(s) | #Exposures | #Good (usable) | #Bad (suspect) | Total number | Bad / Total [%] |
---|---|---|---|---|---|
g | 54,477 | 3,088,885 | 198,410 | 3,287,295 | 6.03 |
r | 58,127 | 3,236,044 | 247,088 | 3,483,132 | 7.09 |
i | 1,871 | 99,876 | 3,721 | 103,597 | 3.59 |
g + r + i | 114,475 | 6,424,805 | 449,219 | 6,874,024 | 6.53 |
The number of CCD-quadrant-based reference images (co-adds) per filter in DR2 are shown in Table 2. Note: unless brought to our attention, all of these are expected to have good photometric and astrometric quality in general. This is because they were constructed from good-quality single-exposure images satisfying a range of criteria, which are more stringent than those used to tag the "good" images in Table 1. The criteria used to select inputs for generating reference images are described in Section 6.7 of the ZSDS Explanatory Supplement.
The existence of a reference image for a specific survey field, CCD-quadrant, and filter is important since it means that for this region of sky: (i) image differencing and alerts can be triggered, and (ii) objects can be extracted and then used as seeds to generate lightcurves. The third column in Table 2 shows the percentage of ZTF survey fields/CCD-quadrants with at least 15 single-exposure images (regardless of quality) that have a reference image. 15 good-quality images is the minimum number to generate a reference image. These percentages are < 100 since a number of fields/CCD-quadrants do not yet have ≥ 15 good-quality science images. These fields are not visited as often during the survey.
Filter(s) | #Reference Images | Visited-sky coverage [%] |
---|---|---|
g | 57,337 | 96.95 |
r | 62,651 | 95.52 |
i | 14,867 | 88.05 |
g + r + i | 134,855 | 95.23 |
Table 3 reports the number of sources in all PSF-fit-based and aperture-based catalog file products (summarized in Section 3), separately for single-exposure (sci) images and reference (ref or co-add) images. The PSF-fit and aperture catalogs are treated independently (with no merging or cross-linking of records) in the Data System. This means a large fraction of the same sources are present in both flavors of catalog. The PSF-fit-based catalogs contain more sources since first, PSF-fitting generally yields more accurate photometry at faint fluxes and hence is more sensitive, and second, it includes deblending of closely-separated sources. Deblending is more important in high source-density regions such as the Galactic plane.
Only sources from the PSF-fit-based sci catalogs are positionally-matched across observation epochs to construct lightcurves (see Table 4 for numbers). As mentioned above, sources in the deeper PSF-fit-based ref catalogs are initially used as seeds to trigger source-matching and generate lightcurves.
Filter(s) | #PSFcat-sci sources | #Aperturecat-sci sources | #PSFcat-ref sources | #Aperturecat-ref sources |
---|---|---|---|---|
g |
34,799,157,939 |
22,008,868,967 |
2,053,507,697 |
656,772,487 |
r |
64,698,158,346 |
40,249,465,415 |
2,954,247,127 |
1,013,085,916 |
i |
868,042,655 |
495,178,759 |
557,831,277 |
163,240,538 |
g + r + i | 100,365,358,940 | 62,753,513,141 | 5,565,586,101 | 1,833,098,941 |
Table 4 reports the number of lightcurves from positional-matching of sources in the single-exposure PSF-fit-based science catalogs with length (number of independent epochs) greater than some limit. The distribution in the number of observation epochs and corresponding timespans is shown in Figure 3. All observation epochs, regardless of data quality are included in the counts in Table 4. For an estimate of the average fraction of "bad" epochs per lightcurve (with likely suspect and unusable photometry), see Table 1. The criteria used to identify "bad" vs "good" epochal data are described in Section 2.4 of the ZSDS Advisories & Cautionary Notes.
Filter(s) | #lightcurves with Nobs ≥ 1 | #lightcurves with Nobs ≥ 2 | #lightcurves with Nobs ≥ 5 | #lightcurves with Nobs ≥ 10 | #lightcurves with Nobs ≥ 20 |
---|---|---|---|---|---|
g |
842,336,216 |
688,078,153 |
544,738,590 |
465,644,983 |
375,217,175 |
r |
1,413,965,706 |
1,189,124,111 |
949,233,735 |
786,798,231 |
623,969,068 |
i |
108,853,073 |
78,026,346 |
50,717,481 |
21,792,536 |
0 |
g + r + i | 2,365,154,995 | 1,955,228,610 | 1,544,689,806 | 1,274,235,750 | 999,186,243 |
Figure 1 shows the approximate spatial distribution in the number of single-exposure epochs in each filter included in DR2, as Aitoff-Hammer projections in Galactic coordinates. These are approximate since the spatial resolution (bin size) of each map is 1° while a CCD-quadrant subtends ≈ 0.854° x 0.854° at the center of a map. The small-scale dark regions are not holes in coverage, but due to aliasing from the warped reprojection and resampling of CCD-quadrant centers onto larger scales. The presence of ~ 3 arcmin gaps between the camera's CCDs also contributes to these holes.
FITS-formatted image representations of Figure 1 with Word Coordinate System metadata in their headers can be downloaded for each filter:
These maps can be visualized using a FITS-image viewer to determine if a specific sky-position is covered by a survey-field/CCD-quadrant. If so, the approximate number of overlapping epochs on/near this position (to within ≈ 1°) can be determined from examining the pixel values.
Figure 2 shows the approximate spatial distribution in CCD-quadrants per filter from which lightcurves were generated for inclusion in DR2. These maps closely track the Reference Image coverage since (PSF-catalog-based) sources extracted therefrom were used as seeds to trigger the lightcurve generation. As in Figure 1, these maps are approximate due to their finite spatial resolution (bin size) of 1° compared to the remapped CCD-quadrants that subtend ≈ 0.854° x 0.854° at the center of a map. The small-scale dark regions are not holes in coverage, but due to aliasing from the warped reprojection and resampling of CCD-quadrant centers onto larger scales. The presence of ~ 3 arcmin gaps between the camera's CCDs also contributes to these holes.
FITS-formatted image representations of Figure 2 with Word Coordinate System metadata in their headers can be downloaded for each filter:
These maps can be visualized using a FITS-image viewer to determine if a specific position is covered by a survey field/CCD-quadrant. If so, one can determine if lightcurves (and/or Reference Images) exist on/near this position, to within ≈ 1°.
To complement the epoch-coverage maps in Figure 1 and lightcurve numbers in Table 4, Figure 3 shows the distribution in overall timespan per survey-field (latest minus earliest exposure in DR2) versus the number of observation epochs in each.
Figure 3 - Timespan of observations per survey-field as a function of the number of epochs in each. These timespans are proxies for the overall spans of lightcurves in DR2. |
Figure 4 encapsulates the available timespans and cadences (separation between consecutive epochs) in DR2, for each filter. These plots can be used as follows: for a given observation or effective lightcurve timespan per survey field (or pointing), one would take a horizontal slice to infer the distribution of visit separations (cadences) therein. The number of times a lightcurve is sampled at that cadence is indicated by the color bar. The bins located at lower right (timespans <~ 90 days) represent data from the partnership and Caltech (private) surveys. DR2 includes approximately the first 3.4 months of data from these programs due to the 18 month embargo being lifted. The i-filter data included in DR2 was acquired only under these private programs.
The following is a gzipped text file listing some metadata and the archive path/filenames of all single-exposure science image files in DR2:
DR2_sci_data.txt.gz (932 MB uncompressed).
The columns in this file are: internal productID; Observation JD [days]; Center R.A. [decimal degrees]; Center Dec. [decimal degrees]; archive path/filename of primary science image. Some of these columns are also present in the archive metadata database to support more generic spatial queries (see Section 12).
Any archive path/filename in the above file can be prepended with the following root URL to access and download the specific sciimg.fits file:
https://irsa.ipac.caltech.edu/ibe/data/ztf/products/
For example, the first listed science image has URL:
https://irsa.ipac.caltech.edu/ibe/data/ztf/products/sci/2018/0325/251921/ztf_20180325251921_000314_zg_c03_o_q3_sciimg.fits
Alternatively, the sciimg.fits suffix can be replaced with any of the following ancillary file suffixes, with products summarized in Section 3:
mskimg.fits - bit-mask image corresponding to sciimg.fits psfcat.fits - PSF-fit source catalog for sciimg.fits sexcat.fits - aperture-based (SExtractor) photometry catalog for sciimg.fits sciimgdao.psf - PSF for sciimg.fits in DAOPhot look-up-table format sciimgdaopsfcent.fits - PSF stamp at center of sciimg.fits scimrefdiffimg.fits.fz - difference image in fpack'd FITS format diffimgpsf.fits - effective PSF stamp for difference-image alerts.tar.gz - gzipped tar-directory of all alert packets sciimlog.txt - processing log for sciimg.fits (instrumental calibration) diffimlog.txt - processing log for difference image and event extraction log.txt - overall processing log for realtime pipeline run
The following is a gzipped text file listing some metadata and the archive path/filenames of all Reference Image files in DR2:
DR2_ref_data.txt.gz (21 MB uncompressed).
The columns in this file are: internal referenceID; number of science images co-added; 5σ limiting magnitude; observation JD of earliest input science image; observation JD of latest input science image; Center R.A. [decimal degrees]; Center Dec. [decimal degrees]; archive path/filename of primary reference image. Some of these columns are also present in the archive metadata database to support more generic spatial queries (see Section 12).
Any archive path/filename in the above file can be prepended with the following root URL to access and download the specific refimg.fits file:
https://irsa.ipac.caltech.edu/ibe/data/ztf/products/
For example, the first listed reference image has URL:
https://irsa.ipac.caltech.edu/ibe/data/ztf/products/ref/000/field000872/zr/ccd04/q2/ztf_000872_zr_c04_q2_refimg.fits
Alternatively, the refimg.fits suffix can be replaced with any of the following ancillary file suffixes, with products summarized in Section 3:
refcov.fits - pixel depth-of-coverage image refunc.fits - pixel (1σ) uncertainty image refpsfcat.fits - PSF-fit source catalog for refimg.fits refsexcat.fits - aperture-based (SExtractor) photometry catalog for refimg.fits refimlog.txt - processing log for sciimg.fits (instrumental calibration) log.txt - overall processing log for realtime pipeline run
Other relevant root URLs to access file-based products in DR2 are as follows.
The root URL to access raw CCD-based image files is: https://irsa.ipac.caltech.edu/ibe/data/ztf/products/raw/
The root URL to access calibration (cal) related files is: https://irsa.ipac.caltech.edu/ibe/data/ztf/products/cal/
For a description of all path and filename identifiers, see Section 7 of the ZSDS Explanatory Supplement.
The ZTF Observing System is fully robotic. One limitation is that it cannot determine in advance when conditions are non-photometric, for example, when intermittent clouds partially (or fully) cover the field-of-view during an exposure. Scattered moonlight can also wreak havoc. This severely affects the accuracy of the derived photometric calibration solutions. There is one estimate of the photometric zeropoint (magzp) with accompanying color term (clrcoeff) per CCD-quadrant, where each of the 64 quadrants is calibrated independently in processing. Spatial variations in transparency at the intra-quadrant level will have led to unusable science products. The lightcurve photometry extracted from the single-exposure image products will also be suspect.
There are two flavors of science products that can be queried from the archive for which data quality flags are available for filtering: (a) single-exposure CCD-quadrant-based files; and (b) Lightcurves. The quality filters for each are as follows:
Bad-quality or generally unusable CCD-quadrant-based images from individual epochs (including accompanying source catalog files) can be omitted when querying the archive by thresholding the INFOBITS value in the archive metadata. If INFOBITS for an image has value < 33554432 (i.e., does not contain bit 25), the image and catalog data are probably usable.
The metrics and criteria used to set this "bad" data quality flag are described in Section 2.4 of the ZSDS Advisories & Cautionary Notes.
Examples of image-based queries that include filtering on INFOBITS are given in Section 12b.i below.
Analogous to the flagging of “bad-quality” images (Section 9a), bad or generally unusable observation epochs in lightcurves can be omitted by thresholding the catflags column in the lightcurve metadata. If catflags for an image has value < 32768 (i.e., does not contain bit 15), the photometry at that epoch is probably usable.
This flagging removes epochs based on their overall image/calibration quality. catflags also encodes possible issues at the source level, for example, contamination by bad pixels. These bits are defined in Section 10.6 of the ZSDS Explanatory Supplement. If you demand perfectly clean extractions at every epoch, we advise specifying catflags = 0 when querying lightcurve epochs.
Examples of lightcurve queries that include filtering on catflags are given in Section 12b.iii below.
The following are high-level advisories. Visit the link in Section 11 for a more detailed list.
A more detailed compilation of advisories and known caveats specific to each data product are given in:
ZSDS Advisories & Cautionary Notes
These notes are progressively updated as issues are resolved, new ones become known, or as we learn of new tips or software that could be of use to the community.
Access to all ZTF data products is through the online (GUI-based) web-tools and API services of the NASA/IPAC Infrared Science Archive (IRSA) linked from: https://irsa.ipac.caltech.edu/Missions/ztf.html.
Below we provide links to specific GUIs and documentation describing how to access the archive products. Examples using the API services are also given.
![]() |
Figure 5 - Schematic of the workflow for retrieving and analyzing lightcurves using the GUI services (see Section 12a). Click to enlarge. |
Application Programming Interfaces (APIs) accompany most of the GUI data-retrieval services. These APIs can be executed from within your own software to enable repetitive and/or bulk data downloads.
An overview for retrieving file-based products using APIs is given on the Image/Catalog API Page. API queries can include thresholding on any of the available archive image metadata parameters.
Examples of using APIs to retrieve file-based products and lightcurves are given below.
i. Querying Single-Exposure Science Image Products using the API
To retrieve file-based single-exposure science-image products that touch a fixed R.A.,Dec position, fall within an observation JD range, and are likely to be of "good" (usable) quality with INFOBITS < 33554432 (see Section 9a), first query their metadata using the wget utility, e.g.,
wget "https://irsa.ipac.caltech.edu/ibe/search/ztf/products/sci? POS=255.9302,11.8654&WHERE=obsjd>2458219.9678+AND+obsjd<2458228.8155+ AND+infobits<33554432" -O out.tbl
where all inputs reside on one line. Then use the output metadata table (out.tbl) contents to construct the image URL-paths/filenames. Using the metadata column names, a science-image will have the generic URL-path/filename:
https://irsa.ipac.caltech.edu/ibe/data/ztf/products/sci/ YYYY/MMDD/fracday/ztf_filefracday_000field_filtercode_ cccdid_imgtypecode_qqid_sciimg.fits
where identifiers in bold green are the values of actual columns in the out.tbl table, and YYYY (year), MM (month), DD (day), and fracday (fractional time of day) can be extracted from filefracday. These images can then be retrieved using the wget utility. For the example above, the first metadata record in out.tbl would be retrieved using:
wget https://irsa.ipac.caltech.edu/ibe/data/ztf/products/sci/ 2018/0411/467847/ztf_20180411467847_000535_zr_c11_o_q3_sciimg.fits
Any of the accompanying products can be retrieved by replacing sciimg.fits with another filename suffix (see Section 8a). Instead of retrieving the entire image, you can download a square cutout centered at a specific R.A.,Dec and specific size, and save the output to a file (optionally gzipped). For the example above:
wget "https://irsa.ipac.caltech.edu/ibe/data/ztf/products/sci/ 2018/0411/467847/ztf_20180411467847_000535_zr_c11_o_q3_sciimg.fits? center=255.8535,12.0503&size=60arcsec&gzip=false" -O cutout.fits
If the API fails to return a file (or its metadata), you can try navigating the archive tree directly to search for the specific product: https://irsa.ipac.caltech.edu/ibe/data/ztf/products/sci/. For guidance, listings of the DR2 single-exposure Science products are given in Section 8a. A description of the path and filename identifiers is given in Section 7 of the ZSDS Explanatory Supplement.
ii. Querying Reference Image Products using the API
To retrieve file-based Reference Image products that touch a fixed R.A.,Dec position in only the r-filter (fid=2), first query their metadata using the wget utility, e.g.,
wget "https://irsa.ipac.caltech.edu/ibe/search/ztf/products/ref? POS=358,25.6&WHERE=fid=2" -O out.tbl
where all inputs reside on one line. Then use the output metadata table (out.tbl) contents to construct the image URL-paths/filenames. Using the metadata column names, a Reference Image will have the generic URL-path/filename:
https://irsa.ipac.caltech.edu/ibe/data/ztf/products/ref/ prefield/fieldfield/filtercode/ccdccdid/qqid/ ztf_field_filtercode_cccdid_qqid_refimg.fits
where identifiers in bold green are the values of actual columns in the out.tbl table, and prefield is the first three (left-zero-padded) digits of the six-digit field value. These images can then be retrieved using the wget utility. For the example above, the first metadata record in out.tbl would be retrieved using:
wget https://irsa.ipac.caltech.edu/ibe/data/ztf/products/ref/ 001/field001596/zr/ccd16/q2/ztf_001596_zr_c16_q2_refimg.fits
Any of the accompanying products can be retrieved by replacing refimg.fits with another filename suffix (see Section 8b). Instead of retrieving the entire image, you can download a square cutout centered at a specific R.A.,Dec and specific size, and save the output to a file (optionally gzipped). For the example above:
wget "https://irsa.ipac.caltech.edu/ibe/data/ztf/products/ref/ 001/field001596/zr/ccd16/q2/ztf_001596_zr_c16_q2_refimg.fits? center=357.46871,26.00549&size=100arcsec&gzip=false" -O cutout.fits
If the API fails to return a file (or its metadata), you can try navigating the archive tree directly to search for the specific product: https://irsa.ipac.caltech.edu/ibe/data/ztf/products/ref/. For guidance, listings of the DR2 Reference Image products are given in Section 8b. A description of the path and filename identifiers is given in Section 7 of the ZSDS Explanatory Supplement.
iii. Querying Lightcurves using the API
The API functionality corresponding to the GUI-driven recipe for retrieving lightcurves is described on the Lightcurve Programming Interface Page. Numerous examples are given on this page. Below we provide a more generic example that includes most parameters of interest. You will always want to exclude observation epochs associated with bad/unusable data by masking catflags values equal to 32768, -- the "cloud-affected and/or moon-contamination" flag (decimal bit 15); see Section 9b. Alternatively, you can exclude epochs with any non-zero bit by using the catflags mask value 65535 in the query below.
The following query returns a concatenated list of lightcurves for objects falling within a 10 arcsec (~0.0028°) radius from position R.A.,Dec = 255.9302°, 11.8654° in the r-filter, where each has ≥ 3 epochs that fall within the MJD range 58194.0...58483.0 and all consist of only "good" (likely usable) measurements. Lightcurves are stored in the output ASCII table: out.tbl. The concatenated lightcurves are distinguished by their ObjectIDs therein (column oid).
wget "https://irsa.ipac.caltech.edu/cgi-bin/ZTF/nph_light_curves? POS=CIRCLE+255.9302+11.8654+0.0028&BANDNAME=r&NOBS_MIN=3& TIME=58194.0+58483.0&BAD_CATFLAGS_MASK=32768&FORMAT=ipac_table" -O out.tbl
All inputs reside on one line. A lightcurve (with common oid values) is represented by columns mag ± magerr versus mjd or hjd. The out.tbl also contains metadata to reconstruct the single-exposure science image path/file names that you can later download using the wget utility, or alternatively, cutouts on your position of interest (see Section 12b.i).
You can also upload the out.tbl file from above to the Time Series Tool to enable visualization, analysis, and period finding, analogous to the GUI-driven method described in Section 12a. Ensure you select "ztf" from the menu before uploading. Following your upload, ensure only one ObjectID (oid) is selected for visualizing, using the filter ( ) icon in the Time Series Tool.
iv. Solar System Object Precovery using the API
The API equivalent of the Moving Object Search Tool (GUI) is described on the MOST Programming Interface Page. For example, to retrieve all single-exposure science images containing Asteroid 438973 Masci, first query their metadata using the wget utility:
wget "https://irsa.ipac.caltech.edu/cgi-bin/MOST/nph-most? catalog=ztf&input_type=name_input&obj_name=Masci& obs_begin=2018+03+17&obs_end=2018+12+31&output_mode=Brief" -O out.tbl
where all inputs reside on one line. Then use the output metadata table (out.tbl) contents to construct the science image URL-paths/filenames (see Section 12b.i above). These images can then be downloaded using the wget utility. Alternatively, cutouts centered on the object's R.A.,Dec in each image, as listed in out.tbl, can be downloaded.
The lightcurves included in this release have been packaged into gzipped tar files. A selection of basic (most necessary) metadata accompany each lightcurve, primarily IDs to enable the retrieval of associated metadata from the archive, for example, images or Object Table metrics using the access methods above.
The following URL contains a listing of the tar-gzipped filenames and their (compressed) sizes:
https://irsa.ipac.caltech.edu/data/ZTF/lc_dr2/
When uncompressed, their total volume is ∼ 3.4 TB. You can click on individual files to download them, or use the wget utility to automate the downloads. If your operating system does not automatically unzip these, you can use gunzip file.tar.gz followed by tar -xvf file.tar to unpack. A list of corresponding MD5 checksums is also provided for those who want to verify file contents following a download. On a Unix/Linux OS, the files can be verified using md5sum -c checksums.md5.
The files are labelled by survey-Field ID where each Field spans ≈ 7° x 7°. Each filename also includes the minimum to maximum RA and Dec values spanned by all the objects contained therein. These RA, Dec ranges can be used to identify the sky region(s) of interest in case you are interested in downloading a subset. The DR2 lightcurves are spread across 856 fields.
Each file unpacks into an ASCII table with the following structure:
# ObjectID (oid), nDR2epochs, FilterID, FieldID, RcID, ObjRA, ObjDec HMJD, mag, magerr, clrcoeff, catflags ... Click for example (truncated)
The lightcurves are delimited by lines: "# Object / lightcurve metadata ...". Following this line is the actual lightcurve for that object. The columns are as follows:
ObjectID: Unique Object Identifier. This is the oid that is returned by queries on the Objects Database Table. This ID can be used to retrieve additional metadata for an Object or lightcurve. nDR2epochs: The number of observation epochs in the lightcurve for this object, included in this data release only. FilterID: Filter for the lightcurve photometry: 1 => g; 2 => r; 3 => i. FieldID: The survey Field Identifier. Lightcurves in DR2 are spread across 856 Fields. This identifier can be used to retrieve additional archive metadata. RcID: The readout-channel Identifier (or CCD-Quadrant index) that contains the object. The RcID runs from 0 to 63 over the ZTF focal plane. In combination with FieldID, this can be used to retrieve additional archive metadata. ObjRA: Object Right Ascension from the input Reference Image (seed) catalog corresponding to the FieldID, RcID, and FilterID [decimal degrees]. ObjDec: Object Declination from the input Reference Image (seed) catalog corresponding to the FieldID, RcID, and FilterID [decimal degrees]. ----------- HMJD: Heliocentric-based Modified Julian Date [days] corresponding to the middle of each exposure and approximate position of the object. The HMJD is derived from "HJD - 2400000.5" where HJD is the Heliocentric Julian Date. mag: Calibrated magnitude for a source with color g - r = 0 in the AB photometric system. See Cautionary Note #12 in Section 10. magerr: Corresponding 1-σ uncertainty in mag estimate; excludes the (usually small) uncertainty associated with the calibration zeropoint and possible systematics relative to external photometry catalogs (for example PS1). clrcoeff: Linear color coefficient term from photometric calibration that can be applied to the mag estimate if you know the AB g - r color of your source. See Cautionary Note #12 in Section 10. catflags: Photometric/image quality flags encoded as bits (Section 9b). In particular, you will always want to exclude observation epochs affected by clouds and/or the moon. These epochs have catflags = 32768 (decimal bit 15).
A utility to extract and parse the lightcurves in the unpacked ASCII tables is called zort. This tool enables custom filtering, the identification of lightcurves belonging to the same object across different filterIDs, and plotting.
For any archive or data-access related issues, which includes anomalies with any of the GUI tools or APIs for data retrieval and analysis, please email:
irsasupport@ipac.caltech.edu
For questions related to data-quality, format, content, processing algorithms, or product usage, including documentation, please email:
ztfdatasystem@gmail.com
A detailed description of the processing pipelines, data products (including alert packets), instructions for product retrieval, filename identifiers, data formats, and product usage can be found in:
The ZSDS Explanatory Supplement: Pipelines, Definitions, Data Products & Access
Two relevant publications from the special ZTF Focus Issue of PASP:
Last update: 2019 December 6