Archives of Photographic PLates for Astronomical USE

Plate image processes (applause_dr4.process)

The table has 110918 rows, 32 columns.


The process table contains data on pyplate's processing of source extraction and astrometric calibration of plate scans. Unique Identifier process_id


If you have made substantial use of the data provided by APPLAUSE DR4, kindly include this acknowledgement

Funding for APPLAUSE has been provided by DFG (German Research Foundation, Grant), Leibniz Institute for Astrophysics Potsdam (AIP), Dr. Remeis Sternwarte Bamberg (University Nürnberg/Erlangen), the Hamburger Sternwarte (University of Hamburg) and Tartu Observatory. Plate material also has been made available from Thüringer Landessternwarte Tautenburg, and from the archives of the Vatican Observatory.


Name Type UCD Unit Description
process_id int Process identification number
scan_id int Scan identification number
plate_id int Plate identification number
archive_id int Archive identification number
filename char meta.ref
Name of the processed file
hostname char Name of the computer that carried out the plate process
num_exposures short Number of exposures of the plate
plate_epoch float Decimal year of the plate exposure
timestamp_start char time.start
Time[yyyy-mm-dd hh:mm:ss] Timestamp of the start of process
timestamp_end char time.start
Time[yyyy-mm-dd hh:mm:ss] Timestamp of the end of process
duration int time.duration s Duration of the process
sky float phot.count
Sky background value
sky_sigma float stat.stdev
Standard deviation of the sky background value
use_psf short meta.code 1 if PSF fitting was used in the process, 0 otherwise
threshold float phot.count
Threshold above which sources were detected
num_sources int meta.number Number of sources extracted from the image
num_psf_sources int meta.number Number of sources for which image coordinates were determined using PSF photometry
solved short meta.code.status 1 if astrometric solution was found for the image, 0 otherwise
num_true_sources int Number of sources classified as true sources (model_prediction > 0.9)
num_artifacts int Number of sources classified as artifacts (model_prediction < 0.1)
num_solutions short Number of astrometric solutions found for the image
color_term float Color term of the plate, characterizing color response of the emulsion and filter used, based on the Gaia EDR3 photometry
pattern_ratio float Ratio of the scanner pattern amplitude in the y direction to the amplitude in the x direction
bright_limit float phot.mag
mag Brightest source magnitude in the plate natural photometric system in the image among calibration stars
num_gaia_edr3 int Number of matched Gaia EDR3 sources
faint_limit float phot.mag
mag Estimated faint limit of the plate in the plate natural photometric system. In case of multiple solutions, the faintest of the individual faint limits.
mag_range float phot.mag
mag Magnitude range between the brightest and faintest source magnitudes in the plate natural photometric system in the image
num_calib int meta.number Number of calibration stars in the image
calibrated short meta.code.status 1 if photometric calibration was completed, 0 otherwise
num_iterations short Number of iterations in the photometric calibration
completed short meta.code.status 1 if process was completed, 0 otherwise
pyplate_version char meta.version
Version number of the PyPlate software used for the process