LargeSynopticSurveyTelescop
CharacterizationMetric
PipelinesVersion12.0
JohnSwinbank,JimBosch,andSimonKrughoff
DMTR-14
LatestRevision:2016-03-08
Abstract
Thisbriefreportdescribemeasurementsofinterestthat
v12.0oftheSciencePipeline.
ThereportforthepreviousversioncanbefoundinDMTR-11.
LARGESYNOPTICSURVEYTELESCOPE
LARGESYNOPTICSURVEYTELESCOPE
V12.0CharacterizationRepoDMTR-14rtLatestRevision2016-03-08
Contents
1PhotometricRepeatabilityMeasurements1
2AlgorithmicPerformanceMeasurements2
3SummaryofComputationalPerformanceMeasurements2
ii
LARGESYNOPTICSURVEYTELESCOPE
V12.0CharacterizationRepoDMTR-14rtLatestRevision2016-03-08
CharacterizationMetricReport:Science
12.0
1PhotometricRepeatabilityMeasurements
SubmittedbyJimBosch
Thisdatasetisaselectionof?-bandHyperSuprime-Camengineeringdat
Stripe82region.Thisdatasetconsistsof30sexposures,
LSSTdataindepth.Ourcurrentcalibrationapproachhas
weultimatelyplantoimplementforLSST:
•There’scurrentlynorelativecalibrationbeingrunat
•Wehaveonlylimitedcorrectionforchromaticeffects.
•There’scurrentlynoallowanceforzeropointvariations
•WealsouseamuchsimplersampleselectionthanthatproposedSRD.
AJupyternotebooktocomputethemetricscanbefoundat
https://github.com/lsst/afw/
blob/tickets/DM-3896/examples/repeatability.ipynb
Metric Characterized
Metric Ref Target
Measured
Value
Measurement
Method
Photometric
repeatability
DLP-307
≤ 13
mmag
10.6
DM-3338
(
?
band)
Photometric
DLP-315
≤ 13
mmag
10.6
DM-3338
Photometric
DLP-316
≤ 13
mmag
10.6
DM-3338
(
?
band)
1
LARGE SYNOPTIC SURVEY TELESCOPE
V12.0 Characterization RepoDMTR-14
rt
Latest Revision 2016-03-08
2 Algorithmic Performance Measurements
Submitted by John Swinbank
The
?
-band HSC engineering data (described above) was used
caveats apply. Consult the tickets in the Measurement Method
Metric Characterized
Metric Ref Target
Measured
Value
Measurement
Method
Ellipticity
Correlations (TE1)
DLP-290
≤ 5 ×
−3
10
6 × 10
DM-3040
Ellipticity
Correlations (TE2)
DLP-290
≤ 5 ×
−3
10
2 × 10
DM-3047
Relative
DLP-310
(AM1)
< 60
mas
masDM-3057
Relative
DLP-311
(AM2)
< 60
mas
masDM-3064
3 Summary of Computational Performance Measurements
Submitted by John Swinbank and Simon Krughoff
At this point of Construction, the computational performance
tion of precursor data processing and extrapolation from
DECam/HITS data was used for the OTT1 estimate and for the
surement of the Alert Production Computational Budget in
3rd Data Challenge
.
For the Data Release Production of the computational budget,
estimating diffim performance, HSC-I for assembling and measuring
measurement, estimates from FDR for multifit, and data from
SDQADocument-26217
[
]. Calculations for the DRP
this iPython
notebook
.
2
LARGE SYNOPTIC SURVEY TELESCOPE
V12.0 Characterization RepoDMTR-14
rt
Latest Revision 2016-03-08
Metric
Characterized
Metric Ref Target
Measured
Value
Measurement
Method
DLP-328
≤ 240
200-250DM-3724
sec
Computational
Budget
DLP-329
≤ 231
TFLOPS 34-39
DM-3267
Computational
Budget
DLP-314
≤ 645
TFLOPS 318
DM-3083
References
[1]
[DMTR-11]
, Economou, F., Swinbank, J., Bosch,
Characterization
J., Krughoff,
ric Report: Science Pipelines
,DMTR-11,URLhttps://ls.st/
Version 11.0 (Summer
DMTR-11
[2][LPM-17],Ivezić,Ž.,TheLSSTScienceCollaboration,2011,LSSTScienceRequirements
ument,LPM-17,URLhttps://ls.st/LPM-17
[3][Document-26217],Kantor,J.,2010,DataChallenge3bPerformanceTest,Document-
26217,URLhttps://ls.st/Document-26217
3
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