Page History
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MeanObjectViewStackObjectAttributes
Query
| Code Block | ||
|---|---|---|
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SELECT o.objID, |
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o.raMean, o.decMean, o.raMeanErr, o.decMeanErr, |
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o.qualityFlag, |
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o.gMeanPSFMag, o.gMeanPSFMagErr, o.gMeanPSFMagNpt, |
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o.rMeanPSFMag, o.rMeanPSFMagErr, o.rMeanPSFMagNpt, |
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o.iMeanPSFMag, o.iMeanPSFMagErr, o.iMeanPSFMagNpt, |
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o.zMeanPSFMag, o.zMeanPSFMagErr, o.zMeanPSFMagNpt, |
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o.yMeanPSFMag, o.yMeanPSFMagErr, o.yMeanPSFMagNpt, |
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o.rMeanKronMag, o.rMeanKronMagErr, |
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o.nDetections, o.ng, o.nr, o.ni, o.nz,o.ny, |
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o.gFlags, o.gQfPerfect, |
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o.rFlags, o.rQfPerfect, |
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o.iFlags, o.iQfPerfect, |
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o.zFlags, o.zQfPerfect, |
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o.yFlags, o.yQfPerfect, |
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soa.primaryDetection, soa.bestDetection |
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INTO mydb.[HighFidelityStarsDR2] |
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FROM dbo.fGetNearbyObjEq(334, 0.0, 0.2*60.0) as x |
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JOIN MeanObjectView o on o.ObjID=x.ObjId |
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LEFT JOIN StackObjectAttributes AS soa ON soa.objID = x.objID |
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WHERE o. |
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nDetections>5 AND soa. |
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primaryDetection>0 AND o. |
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gQfPerfect>0.85 and o. |
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rQfPerfect>0.85 and o. |
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iQfPerfect>0.85 and o. |
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zQfPerfect>0.85 |
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AND (o.rmeanpsfmag - o.rmeankronmag < 0.05) |
Results
696 objects, here are the first 10:
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The Kepler Extra-Galactic Survey (KEGS) is a program using the Kepler telescope to search for supernovae, active galactic nuclei, and other transients in galaxies. We have to identify galaxies in a suitable redshift range (z<=0.12) a priori, which will be monitored by K2. Here is an example to get galaxies for Campaign 14. We only select objects with r<=19.5, and we make a cut on (rmeanpsfmag - rmeankronmag)>=0.05 in order to remove stars (More info about Star-Galaxy Separation is here). We only want to use objects for which the majority of pixels were not masked, thus the cut on QFperfect>=0.95. We also obtain the petrosian radii in order to be able to select galaxies by size.
Query
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| Code Block | ||
|---|---|---|
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SELECT o.objID, |
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ot.raStack, ot.decStack, ot.raMean, ot.decMean, |
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ot.ng, |
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o.gMeanPSFMag,o.gMeanPSFMagErr,o.gMeanKronMag,o.gMeanKronMagErr, |
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ot.nr, |
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o.rMeanPSFMag,o.rMeanPSFMagErr,o.rMeanKronMag,o.rMeanKronMagErr, |
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ot.ni, |
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o.iMeanPSFMag,o.iMeanPSFMagErr,o.iMeanKronMag,o.iMeanKronMagErr, |
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ot.nz, |
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o.zMeanPSFMag,o.zMeanPSFMagErr,o.zMeanKronMag,o.zMeanKronMagErr, |
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ot.ny, |
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o.yMeanPSFMag,o.yMeanPSFMagErr,o.yMeanKronMag,o.yMeanKronMagErr, |
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o.gQfPerfect,o.rQfPerfect,o.iQfPerfect,o.zQfPerfect,o.yQfPerfect, |
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ot.qualityFlag,ot.objInfoFlag, |
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sp.gpetRadius,sp.rpetRadius,sp.ipetRadius,sp.zpetRadius,sp.ypetRadius, |
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sp.gpetR50,sp.rpetR50,sp.ipetR50,sp.zpetR50,sp.ypetR50, |
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soa.primaryDetection, soa.bestDetection |
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INTO mydb.[C14] |
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FROM MeanObject AS o |
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JOIN fgetNearbyObjEq(160.68333, 6.85167 , 8.5*60.0) cone ON cone.objid = o.objID |
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JOIN ObjectThin AS ot ON ot.objID = o.objID |
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LEFT JOIN StackPetrosian AS sp ON sp.objID = o.objID |
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LEFT JOIN StackObjectAttributes AS soa ON soa.objID = o.objID |
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WHERE ot.ni >= |
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3 AND ot.ng >= |
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3 AND ot.nr >= |
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3 AND soa.primaryDetection>0 AND (o.rMeanKronMag > 0 AND o.rMeanKronMag <= 19.5 |
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) AND (o.gQfPerfect >= 0.95) |
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AND (o.rQfPerfect >= 0.95) |
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AND (o.iQfPerfect >= 0.95) |
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AND (o.zQfPerfect >= 0.95) |
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AND (o.rmeanpsfmag - o.rmeankronmag > 0.05) |
Results
First 10 out of 161,920 Rows of MyDB Table C14
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We search for objects in the PS1 DB that are within 3 arcsec of the Catalina positions. Most of the parameters (mean mags, # of detections, etc) we get from the MeanObjectView table. We also join the StackObjectAttributes table in order to get primaryDetection and bestDetection (BestDetection is corrupted in DR2, but will be fixed in DR2.1, see the description of StackObjectThin table for a more detailed description). These RR Lyrae stars are bright, thus we can expect many detections, and we therefore require o.nDetections>5. We only want to use objects for which the majority of pixels were not masked, thus the cut on QFperfect>=0.95. In order to select only stars (and exclude galaxies), we require (o.rmeanpsfmag - o.rmeankronmag)< 0.05, as described here.
| Code Block | ||
|---|---|---|
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SELECT d.CSS_ID, d.RA as CSSRA, d.Dec as CSSDec, d.V, d.Period, d.Amp, d.Npts, d.Dist, d.Red, d.CSIDnum, |
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o.objID, |
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o.raMean, o.decMean, o.raMeanErr, o.decMeanErr, |
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o.qualityFlag, |
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o.gMeanPSFMag, o.gMeanPSFMagErr, o.gMeanPSFMagNpt, |
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o.rMeanPSFMag, o.rMeanPSFMagErr, o.rMeanPSFMagNpt, |
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o.iMeanPSFMag, o.iMeanPSFMagErr, o.iMeanPSFMagNpt, |
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o.zMeanPSFMag, o.zMeanPSFMagErr, o.zMeanPSFMagNpt, |
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o.yMeanPSFMag, o.yMeanPSFMagErr, o.yMeanPSFMagNpt, |
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o.rMeanKronMag, o.rMeanKronMagErr, |
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o.nDetections, o.ng, o.nr, o.ni, o.nz,o.ny, |
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o.gFlags, o.gQfPerfect, |
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o.rFlags, o.rQfPerfect, |
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o.iFlags, o.iQfPerfect, |
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o.zFlags, o.zQfPerfect, |
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o.yFlags, o.yQfPerfect, |
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soa.primaryDetection, soa.bestDetection |
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INTO mydb.[RRLPS1] |
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FROM mydb.[RRLcatalina] d |
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CROSS APPLY dbo.fGetNearbyObjEq(d.RA, d.Dec, 3.0/60.0) as x |
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JOIN MeanObjectView o on o.ObjID=x.ObjId |
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LEFT JOIN StackObjectAttributes AS soa ON soa.objID = x.objID |
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WHERE o. |
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nDetections>5 AND soa.primaryDetection>0 AND o.gQfPerfect>0.85 and o.rQfPerfect>0.85 and o.iQfPerfect>0.85 and o.zQfPerfect>0.85 AND (o.rmeanpsfmag - o.rmeankronmag < 0.05) |
Results (25 minutes)
There are 12 out of 13 matches, and below are the first 10 entries
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Now we get all detections associated with these objIDs
| Code Block | ||
|---|---|---|
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SELECT |
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o.objID, o.raMean, o.decMean, |
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d.ra, d.dec, d.raErr, d.decErr, |
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d.detectID, d.obstime, d.exptime, d.airmass, d.psfflux, d.psffluxErr, d.psfQf, d.psfQfPerfect, d.psfLikelihood, d.psfChiSq, d.extNSigma, d.zp, d.apFlux, d.apFluxErr, |
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d.imageID, d.filterID, |
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d.sky, d.skyerr, d.infoflag, d.infoflag2, d.infoflag3, |
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o.qualityFlag, |
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o.gMeanPSFMag, o.gMeanPSFMagErr, o.gMeanPSFMagNpt, |
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o.rMeanPSFMag, o.rMeanPSFMagErr, o.rMeanPSFMagNpt, |
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o.iMeanPSFMag, o.iMeanPSFMagErr, o.iMeanPSFMagNpt, |
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o.zMeanPSFMag, o.zMeanPSFMagErr, o.zMeanPSFMagNpt, |
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o.yMeanPSFMag, o.yMeanPSFMagErr, o.yMeanPSFMagNpt, |
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o.rMeanKronMag, o.rMeanKronMagErr, |
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o.nDetections, o.ng, o.nr, o.ni, o.nz,o.ny, |
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o.gFlags, o.gQfPerfect, |
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o.rFlags, o.rQfPerfect, |
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o.iFlags, o.iQfPerfect, |
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o.zFlags, o.zQfPerfect, |
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o.yFlags, o.yQfPerfect, |
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o.primaryDetection, o.bestDetection |
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INTO mydb.[RRLPS1det] |
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FROM mydb.[RRLPS1] o |
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JOIN Detection d on d.ObjID = o.ObjID |
Results (30 seconds)
There are 946 detection entries for the 12 objects, and below are the first 10 entries
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Now we get the forced photometry
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| Code Block | ||
|---|---|---|
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SELECT o.objID, o.raMean, o.decMean, |
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fwm.detectID, fwm.obstime, fwm.exptime, fwm.airmass, fwm.Fpsfflux, fwm.FpsffluxErr, fwm.FpsfQf, fwm.FpsfQfPerfect, fwm.FpsfChiSq, fwm.zp, fwm.FapFlux, fwm.FapFluxErr, |
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fwm.forcedWarpID, fwm.filterID, |
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fwm.Fsky, fwm.Fskyerr, fwm.Finfoflag, fwm.Finfoflag2, fwm.Finfoflag3, |
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o.qualityFlag, |
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o.gMeanPSFMag, o.gMeanPSFMagErr, o.gMeanPSFMagNpt, |
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o.rMeanPSFMag, o.rMeanPSFMagErr, o.rMeanPSFMagNpt, |
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o.iMeanPSFMag, o.iMeanPSFMagErr, o.iMeanPSFMagNpt, |
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o.zMeanPSFMag, o.zMeanPSFMagErr, o.zMeanPSFMagNpt, |
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o.yMeanPSFMag, o.yMeanPSFMagErr, o.yMeanPSFMagNpt, |
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o.rMeanKronMag, o.rMeanKronMagErr, |
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o.nDetections, o.ng, o.nr, o.ni, o.nz,o.ny, |
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o.gFlags, o.gQfPerfect, |
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o.rFlags, o.rQfPerfect, |
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o.iFlags, o.iQfPerfect, |
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o.zFlags, o.zQfPerfect, |
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o.yFlags, o.yQfPerfect, |
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o.primaryDetection, o.bestDetection |
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INTO mydb.[RRLPS1forceddet] |
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FROM mydb.[RRLPS1] o |
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JOIN ForcedWarpMeasurement fwm on fwm.ObjID = o.ObjID |
Results (3:45 minutes)
There are 824 forced detection entries for the 12 objects, and below are the first 10 entries
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Query #1: Get the ObjID for the star
| Code Block |
|---|
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SELECT o.objID, |
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o.raMean, o.decMean, o.raMeanErr, o.decMeanErr, |
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o.qualityFlag, |
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o.gMeanPSFMag, o.gMeanPSFMagErr, o.gMeanPSFMagNpt, |
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o.rMeanPSFMag, o.rMeanPSFMagErr, o.rMeanPSFMagNpt, |
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o.iMeanPSFMag, o.iMeanPSFMagErr, o.iMeanPSFMagNpt, |
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o.zMeanPSFMag, o.zMeanPSFMagErr, o.zMeanPSFMagNpt, |
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o.yMeanPSFMag, o.yMeanPSFMagErr, o.yMeanPSFMagNpt, |
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o.rMeanKronMag, o.rMeanKronMagErr, |
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o.nDetections, o.ng, o.nr, o.ni, o.nz,o.ny, |
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o.gFlags, o.gQfPerfect, |
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o.rFlags, o.rQfPerfect, |
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o.iFlags, o.iQfPerfect, |
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o.zFlags, o.zQfPerfect, |
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o.yFlags, o.yQfPerfect |
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INTO mydb.[RRL_584630948352256_PS1] |
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FROM dbo.fGetNearbyObjEq(46.341468915923, 1.54199810825252, 1.0/60.0) as x |
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JOIN MeanObjectView o on o.ObjID=x.ObjId |
Results (1 entry, < 1 min)
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Query #2: Get the detections
| Code Block | ||
|---|---|---|
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SELECT |
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o.objID, o.raMean, o.decMean, |
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d.ra, d.dec, d.raErr, d.decErr, |
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d.detectID, d.obstime, d.exptime, d.airmass, d.psfflux, d.psffluxErr, d.psfQf, d.psfQfPerfect, d.psfLikelihood, d.psfChiSq, d.extNSigma, d.zp, d.apFlux, d.apFluxErr, |
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d.imageID, d.filterID, |
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d.sky, d.skyerr, d.infoflag, d.infoflag2, d.infoflag3, |
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o.qualityFlag, |
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o.gMeanPSFMag, o.gMeanPSFMagErr, o.gMeanPSFMagNpt, |
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o.rMeanPSFMag, o.rMeanPSFMagErr, o.rMeanPSFMagNpt, |
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o.iMeanPSFMag, o.iMeanPSFMagErr, o.iMeanPSFMagNpt, |
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o.zMeanPSFMag, o.zMeanPSFMagErr, o.zMeanPSFMagNpt, |
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o.yMeanPSFMag, o.yMeanPSFMagErr, o.yMeanPSFMagNpt, |
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o.rMeanKronMag, o.rMeanKronMagErr, |
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o.nDetections, o.ng, o.nr, o.ni, o.nz,o.ny, |
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o.gFlags, o.gQfPerfect, |
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o.rFlags, o.rQfPerfect, |
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o.iFlags, o.iQfPerfect, |
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o.zFlags, o.zQfPerfect, |
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o.yFlags, o.yQfPerfect |
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INTO mydb.[RRL_584630948352256_PS1det] |
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FROM mydb.[RRL_584630948352256_PS1] o |
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JOIN Detection d on d.ObjID = o.ObjID |
Results (92 entries, < 1 min)
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Query #3: Get the forced detections
| Code Block | ||
|---|---|---|
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SELECT |
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o.objID, o.raMean, o.decMean, |
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fwm.detectID, fwm.obstime, fwm.exptime, fwm.airmass, fwm.Fpsfflux, fwm.FpsffluxErr, fwm.FpsfQf, fwm.FpsfQfPerfect, fwm.FpsfChiSq, fwm.zp, fwm.FapFlux, fwm.FapFluxErr, |
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fwm.forcedWarpID, fwm.filterID, |
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fwm.Fsky, fwm.Fskyerr, fwm.Finfoflag, fwm.Finfoflag2, fwm.Finfoflag3, |
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o.qualityFlag, |
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o.gMeanPSFMag, o.gMeanPSFMagErr, o.gMeanPSFMagNpt, |
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o.rMeanPSFMag, o.rMeanPSFMagErr, o.rMeanPSFMagNpt, |
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o.iMeanPSFMag, o.iMeanPSFMagErr, o.iMeanPSFMagNpt, |
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o.zMeanPSFMag, o.zMeanPSFMagErr, o.zMeanPSFMagNpt, |
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o.yMeanPSFMag, o.yMeanPSFMagErr, o.yMeanPSFMagNpt, |
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o.rMeanKronMag, o.rMeanKronMagErr, |
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o.nDetections, o.ng, o.nr, o.ni, o.nz,o.ny, |
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o.gFlags, o.gQfPerfect, |
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o.rFlags, o.rQfPerfect, |
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o.iFlags, o.iQfPerfect, |
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o.zFlags, o.zQfPerfect, |
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o.yFlags, o.yQfPerfect |
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INTO mydb.[RRL__584630948352256_PS1forceddet] |
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FROM mydb.[RRL_584630948352256_PS1] o |
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JOIN ForcedWarpMeasurement fwm on fwm.ObjID = o.ObjID |
Results (84 entries, <1 min)
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We start with a cone search of ObjectThin within a 3 degree radius of the nominal HDF position (169.2,61.3). We select only mean objects with at least three detections and mean PSF magnitude r < 21.0 (Gaia sources are sparse at fainter magnitudes). The following search was run in CasJobs and took 8:29, returning 192,611 objects.
| Code Block | ||
|---|---|---|
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select o.objID, o.raMean, o.decMean, o.raMeanErr, o.decMeanErr, |
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o.raStack, o.decStack, o.raStackErr, o.decStackErr, o.epochMean, |
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o.nDetections, o.ng, o.nr, o.ni, o.nz, o.ny, o.objInfoFlag, o.qualityFlag, |
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m.gMeanPSFMag, m.rMeanPSFMag, m.iMeanPSFMag, m.zMeanPSFMag, m.yMeanPSFMag, |
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m.gMeanPSFMagErr, m.rMeanPSFMagErr, m.iMeanPSFMagErr, m.zMeanPSFMagErr, m.yMeanPSFMagErr, |
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m.gMeanKronMag, m.rMeanKronMag, m.iMeanKronMag, m.zMeanKronMag, m.yMeanKronMag, |
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m.gFlags, m.rFlags, m.iFlags, m.zFlags, m.yFlags |
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into mydb.MyTable_HDF_3deg_extended from fGetNearbyObjEq(169.20,62.30,180.0) nb |
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inner join ObjectThin o on o.objid=nb.objid and o. |
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nDetections>3 inner join MeanObject m on o.objid=m.objid and o.uniquePspsOBid=m.uniquePspsOBid and m. |
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rMeanPSFMag<21.0 |
The output table is 48,200 kb; here is a sample of the first few rows:
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The following query identifies all detections associated (i.e., having the same ObjID) as the mean objects obtained in Step 1, and extracts relevant parameters for each. The query ran for 3:18 and returned 8,560,632 rows (detections), or an average of over 40 per mean object.
| Code Block | ||
|---|---|---|
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select d.detectID, d.objid, d.obstime, d.exptime, d.airmass, d.psfflux, d.psffluxErr, d.psfQF, |
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d.imageID, d.filterID, d.sky, d.skyerr, d.infoflag, d.infoflag2, d.infoflag3, d.ra, d.dec, d.raerr, d.decerr |
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into mydb.MyTable_HDF_det2 |
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from Detection d |
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inner join MyDB.MyTable_HDF_3deg mm on d.objid=mm.objid |
The resulting table is about 1.3 GB, exceeding the standard limit in CasJobs. A sample of the first several rows follows.
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