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Get high-fidelity stars in given area

Goal/Description

We want to get all objects with R degrees of a given position that are high fidelity stellar-like objects.

We get all objects within 0.2 degree of RA=334.0 and Dec=0.0 which have mean magnitudes in griz (i.e. at least 1 detection in each band that can be used for the mean mag). In addition, we require QfPerfect>0.85 in all bands. We select stars with the difference between Kron and PSF magnitude as described here.

Note that the search radius is in arcminutes.  This is a recent change in the interface to make the PS1 database functions consistent with those used for SDSS, GALEX, Kepler, the HSC, and other MAST catalogs.

Tables used

Query

Results

696 objects, here are the first 10:

107763340006509592334.00067427-0.192394010.001920.002456019.63130.0076211418.36530.0065281517.24440.0023472616.72250.0024551216.48510.0158981318.46990.0097619316173412141150000.9998731150000.9992911150000.9996341150000.9990441150000.99962211
107763340149672418334.01502523-0.198394020.005180.002855221.97510.083929320.79480.0316931519.64860.0130221719.11140.0128571218.80210.0265641420.98950.053647653152013141150000.9994621150000.9996441150000.9993091150000.9996281150000.99898211
107763340365446394334.03656773-0.19510620.024250.027075221.80920.062935621.32680.07511221.09110.0276632420.51950.044181019.35650.000343121.41590.0682166381429102168922160.9993251150000.9996361150000.9993671150000.999632168922160.99898211
107773339339718616333.93399766-0.184857650.004220.007986021.09670.0578641219.8960.0112421218.6140.006882918.02340.0046131017.77390.022577920.01170.0311778512123712121150000.9994041150000.9997151150000.9998561150000.9995151150000.99952611
107773339418197028333.94187857-0.186141460.019710.039595221.57050.012027220.9810.008091620.5860.028582720.32250.049434820.32660.143002120.97790.1531026049351111150000.9991150000.9990291150000.9996281150000.9992531149920.99776511
107773339602519327333.96026447-0.184273450.004520.00796021.0790.018093619.76090.014422618.4560.0046372117.86120.0060051017.60790.035327619.82380.015897658112510111150000.9991681150000.9991581150000.9996131150000.9992121150000.99813311
107773339666312601333.96664968-0.18987530.002620.002376018.33170.0055231417.77110.0027631417.5310.0031372717.42430.006355717.36890.016866817.85090.00506771416298101150000.9994791150000.9997421150000.9995481150000.998681150000.99890611
107773339901521365333.99016194-0.190867220.003920.007325221.94950.067887920.83390.0248211319.37540.0051453318.6420.011191218.29680.01511220.87940.082054819143313121150000.9990951150000.9997291150000.9994281150000.9997061150000.9991111
107773339922175058333.99225189-0.18784710.003560.021736017.81180.0058681217.05280.0025851216.75430.00222616.62070.005681216.50890.0097861217.11910.0033358714143114141150000.9997041150000.9994421150000.9995771150000.9992381150000.99930711
107773340107508029334.01078438-0.185362360.00570.00576017.14060.0018981216.58370.0029451316.33750.0018912216.22930.0022241316.1460.008295916.64360.0011668716153014121150000.9996841150000.9994641150000.9999121150000.9994351150000.99902211

Galaxy Candidates for K2 SN Search

Goal/Description

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

Results

First 10 out of 161,920 Rows of MyDB Table C14

125391633203089697163.3203034114.49934933163.3202888214.499330921021.00930.03608920.67310.0748271419.77030.02660119.25630.015281019.26810.01153818.63970.0214551418.99570.01690118.37290.015641318.69680.03064218.12660.0375910.9995660.9996350.9992130.9992090.999349615120245768.61662.719812.660622.670842.774831.258871.191921.087371.06831.0298511
125391634958624964163.4958642914.49541362163.4958360214.49541251020.33360.03003819.55830.0204551419.79660.0355818.92140.0223741519.53160.02587218.62780.0093251319.3670.03379518.56210.0329861419.12710.03827218.38290.0511010.9996190.9994570.9989650.9990230.999377534449157125.274075.047874.279134.715885.211242.087631.805381.59331.465893.2760511
125391635282559255163.5282652714.49899141163.5282394114.49899527820.95980.06209120.17410.0267351420.39230.06290219.4170.0290261520.07270.03636619.01680.0244431119.86520.02521118.82080.031221819.24060.09263518.77780.1411020.9997260.9994350.99920.9991130.999185534449157124.604355.280314.940895.314334.20822.207382.365342.079092.097791.9896211
125391636122615271163.6122480114.49564107163.6122231214.49563751021.01580.04507520.31790.0733741620.08380.03902419.3610.0320282319.67380.02457218.96320.0144861319.44870.02020718.70970.0242551219.21020.06318618.59490.0731460.9996030.9997630.9996560.9988140.999592534449157123.830933.526663.353484.647193.175081.433111.456911.246871.440551.1315811
118791643648704345164.364864278.99489954164.364887298.994907111219.14290.05265218.22540.017751018.15850.04725417.19220.0106842417.83590.01458216.73990.0064931517.5290.03420716.4750.0163071217.38210.03268516.52170.0167640.9994060.9999250.9996270.9991770.998446615120245769.411887.510378.155576.791086.692493.2392.899722.987122.585672.5330311
118791644119204724164.412068318.9951804164.412073118.995164071120.44820.04995519.99320.0312261019.45950.05505819.06360.0349542119.13870.00994218.69940.0129181818.90020.02813118.42240.0170081618.75510.0390618.34530.0484060.9998240.9995250.9995360.9996980.999067534449157123.2393.364073.611282.587155.268741.321491.371881.332321.0671.5481911
118791644639089117164.46390888.99886558164.46388938.998823951220.58450.01395420.52220.025129919.53920.01418219.46730.0280322519.22910.00958219.09120.010408818.98440.01937218.86410.0121951018.86940.0333218.72610.0509690.9998240.9997270.9997520.9986580.99909534449157121.710522.177271.846351.717991.601210.8105680.9024190.7862210.696830.68577111
112311673903612557167.390365823.59342292167.390346433.593426791020.61910.02881920.08520.0347351319.22420.01542418.60720.0199273018.65170.02910318.03810.0102671518.69670.02440817.8330.0164861518.27450.05080717.59220.0294650.9995420.9997520.9999180.9996680.999759615120245764.499315.25925.9236.452039.718261.71361.894712.121162.273822.5015111
112311673903612557167.390365823.59342292167.390346433.593426791020.61910.02881920.08520.0347351319.22420.01542418.60720.0199273018.65170.02910318.03810.0102671518.69670.02440817.8330.0164861518.27450.05080717.59220.0294650.9995420.9997520.9999180.9996680.999759615120245765.759976.378285.776225.69016.939461.832952.146781.961951.986651.9688711
112311673927395135167.39276133.59560997167.392744753.59561368821.29230.07546420.53470.038571219.88380.03419.27460.0205443719.35580.02375218.79830.0136541419.31370.03371318.55080.0255011218.91650.03519418.19120.033290.9996550.9996030.999760.9992070.999066534449157122.693253.553842.872813.02684139.1430.8211871.099991.063841.13938-99911

Obtain lightcurves for a given set of objects

Goal/Description

The goal is to obtain light curves for a list of objects. The list of objects with their RA/Dec position is uploaded into Mydb, the PS1 objects are identified, and then the light curves are obtained. Here we upload a list of 13 RR Lyrae stars from the Catalina sky survey into mydb.[RRLcatalina]

Query #1: Match Catalina RR Lyrae stars to PS1 objects

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

Results (25 minutes)

There are 12 out of 13 matches, and below are the first 10 entries

CSS_J220309.8+051633330.790975.2759316.680.6386980.3829415.620.0571104118064018114333307910211643330.79101255.27596260.002170.004276017.06650.003394516.68730.002055316.59980.012561716.49210.018882816.54240.0122651216.72160.007911751272811171150000.9994971150000.9992651150000.9996391150000.9996971150000.99897811
CSS_J221949.2-024020334.95521-2.6722416.510.7094910.3724914.120.0851001120004060104793349551433447334.95514654-2.67250150.030630.020436016.74440.006159516.46110.006758616.47710.0044791316.37520.005638716.35940.018196716.50580.003776638112310111150000.9996461150000.9998251150000.9996721150000.9987271150000.99933111
CSS_J220559.8-023949331.49951-2.6636518.110.537170.8923427.820.1521001118004001104803314996713860331.49966923-2.663805670.005590.008575218.65980.034348718.44560.032674818.08950.0300171917.92960.0467951017.99230.00375918.48060.0248476712122112101150000.9991291150000.999311150000.9996381150000.9992171150000.99879811
CSS_J220457.2-051411331.23867-5.2365615.640.536430.751739.670.061004118010930101713312388786386331.23888082-5.236755940.004690.005296016.27170.027581615.59560.03394615.88790.0345061215.89230.017074315.85420.007946515.73680.076347731614241091150000.9996811150000.9993841150000.9995011150000.9987611150000.99799611
CSS_J215602.1-052021329.00905-5.3392116.510.7575580.4721814.770.0361004117008292101593290092623326329.00923968-5.339287190.01670.018416016.84940.0078616.42170.0220471516.37590.0080411516.34680.003574816.37210.0180631116.48270.0234157210162212121150000.9999211150000.9996771150000.9994061150000.9991671150000.99943511
CSS_J220820.9-020222332.08714-2.039717.010.5616870.9526317.610.0921001119018133105553320871392714332.08715134-2.039794720.00270.01026017.75550.003879817.3820.0089321317.16340.033642317.17830.007448416.94410.013463417.38460.00940480142129881150000.9996851150000.9992741150000.9998781150000.9988711150000.99967211
CSS_J222707.9+051259336.783115.2164616.190.5525570.7327511.290.1731104120055941114263367831840264336.783195465.216479990.001770.001886016.33580.006233616.22930.117566716.27940.0169042516.16580.024596916.0840.028519916.28070.1348978713153612111150000.9995581150000.998991150000.9996771150000.9992771150000.99857211
CSS_J215435.8-005450328.64951-0.9141617.750.5752120.925724.140.1261001117050169106903286496013281328.64959053-0.914316820.002190.001385218.14090.074842717.87060.0572561017.61590.0420861717.76570.024178917.6690.0111571017.90650.0623717512122613121150000.9996821150000.9993131150000.9992911150000.9996971150000.99902411
CSS_J222942.0-040519337.42517-4.0887618.080.4756991.1923029.630.0671004120034845103093374253263940337.42533413-4.088731280.002450.001945218.8380.022485918.5520.01008818.50710.0138251418.23550.118849818.34540.0194021018.63140.0117768214162612141150000.9995221150000.9995811150000.9994791150000.9996691150000.9993511
CSS_J223105.2+000538337.771770.0940416.970.6702280.427817.70.0711101121002733108113377718393164337.771859970.093919850.010240.010616017.19520.013075716.98060.0065821416.87660.0128723016.84650.015577816.74790.011255917.02360.0059729414223510131150000.9995021150000.9996831150000.9997331150000.9991911150000.99969411

Query #2: Get the detections

Now we get all detections associated with these objIDs

Results (30 seconds)

There are 946 detection entries for the 12 objects, and below are the first 10 entries

101713312388786386331.23888082-5.23675594331.23887966-5.236737090.01421290.020436928104123120000023056911.4125766451.134790.002368083.23403E-050.07493820.02829960.0014811.221773.1783824.56090.0001011921.15941E-067921642037.38736E-053.65002E-06102760453128327686016.27170.027581615.59560.03394615.88790.0345061215.89230.017074315.85420.007946515.73680.076347731614241091150000.9996811150000.9993841150000.9995011150000.9987611150000.99799611
101713312388786386331.23888082-5.23675594331.2388835-5.23673670.008722090.013683628104006920000014856911.4009661451.120940.002357912.46269E-050.1154580.115458-0.6833521.38811-0.40789424.56060.0001150571.24099E-067921472036.59469E-053.4392E-06102760453128327686016.27170.027581615.59560.03394615.88790.0345061215.89230.017074315.85420.007946515.73680.076347731614241091150000.9996811150000.9993841150000.9995011150000.9987611150000.99799611
101713312388786386331.23888082-5.23675594331.23887945-5.236752670.002552730.0027200727215526814000005456822.5529494451.239780.001600255.42303E-060.9982730.9982730.7184581.851510.3605224.60310.001630744.55078E-067543441439.63136E-054.39628E-0610276045312873749126016.27170.027581615.59560.03394615.88790.0345061215.89230.017074315.85420.007946515.73680.076347731614241091150000.9996811150000.9993841150000.9995011150000.9987611150000.99799611
101713312388786386331.23888082-5.23675594331.23887517-5.236753570.002555730.0027983827215410114000005556822.5412889451.291010.001639925.55706E-060.9990950.9990950.5771441.655770.55756124.60160.001653624.55156E-067543271430.0001025064.54961E-0610276051712873749126016.27170.027581615.59560.03394615.88790.0345061215.89230.017074315.85420.007946515.73680.076347731614241091150000.9996811150000.9993841150000.9995011150000.9987611150000.99799611
101713312388786386331.23888082-5.23675594331.23888039-5.236754710.002511590.0025232527215643414000006156822.5646058451.198980.0015995.33245E-060.9991920.9991920.1627261.950351.3959624.60480.001656684.56818E-067543611439.17713E-054.18141E-0610276045312873749126016.27170.027581615.59560.03394615.88790.0345061215.89230.017074315.85420.007946515.73680.076347731614241091150000.9996811150000.9993841150000.9995011150000.9987611150000.99799611
101713312388786386331.23888082-5.23675594331.23888187-5.236758050.002280020.0022956627215759614000005856822.576232451.167190.001607265.26372E-060.9995010.9995010.2229331.891151.2187724.60470.001658194.55018E-067543781438.90853E-054.19146E-0610276051712873749126016.27170.027581615.59560.03394615.88790.0345061215.89230.017074315.85420.007946515.73680.076347731614241091150000.9996811150000.9993841150000.9995011150000.9987611150000.99799611
101713312388786386331.23888082-5.23675594331.23887668-5.236739140.00225780.001980327386105647000014956839.6107502301.137310.001971368.18044E-060.8851710-0.2267841.2275-1.2086824.22170.001724376.86483E-067638494745.24721E-055.20364E-06102760453160348806016.27170.027581615.59560.03394615.88790.0345061215.89230.017074315.85420.007946515.73680.076347731614241091150000.9996811150000.9993841150000.9995011150000.9987611150000.99799611
101713312388786386331.23888082-5.23675594331.23888109-5.236749940.003347480.0030812227416085747000008656842.6087543301.1480.001441267.36061E-060.9340250-0.3586471.03449-0.91794724.24020.001382926.01342E-067656154746.60553E-055.55748E-06102760517160348806016.27170.027581615.59560.03394615.88790.0345061215.89230.017074315.85420.007946515.73680.076347731614241091150000.9996811150000.9993841150000.9995011150000.9987611150000.99799611
101713312388786386331.23888082-5.23675594331.23887875-5.236744190.006211350.0062808128403513537000008856941.351618451.177460.001254425.51837E-060.9993670.9993670.05185081.202171.9443724.53480.001276984.00209E-068075623735.62479E-053.33006E-0610276045312873421446016.27170.027581615.59560.03394615.88790.0345061215.89230.017074315.85420.007946515.73680.076347731614241091150000.9996811150000.9993841150000.9995011150000.9987611150000.99799611
101713312388786386331.23888082-5.23675594331.23887939-5.23676170.006495790.0066217828403635937000008656941.3638651451.214370.001258445.59236E-060.999130.999130.02153912.12852.298424.52340.001148583.81474E-068075803735.97269E-053.37162E-0610276045312873749126016.27170.027581615.59560.03394615.88790.0345061215.89230.017074315.85420.007946515.73680.076347731614241091150000.9996811150000.9993841150000.9995011150000.9987611150000.99799611

Query #3: Get the forced detections

Now we get the forced photometry

Results (3:45 minutes)

There are 824 forced detection entries for the 12 objects, and below are the first 10 entries

101713312388786386331.23888082-5.23675594247394876066575312955509.1963096301.125280.002261558.89297E-060.9984470.8990651.7050924.21840.002258537.8829E-065730688442.44443E-075.58402E-0616986988901247815686016.27170.027581615.59560.03394615.88790.0345061215.89230.017074315.85420.007946515.73680.076347731614241091150000.9996811150000.9993841150000.9995011150000.9987611150000.99799611
101713312388786386331.23888082-5.23675594247394931579027613755509.2069606301.116110.002376238.73044E-060.9979870.6190151.9887424.20530.002344778.07563E-06573068864-7.89231E-084.77904E-06706740801806016.27170.027581615.59560.03394615.88790.0345061215.89230.017074315.85420.007946515.73680.076347731614241091150000.9996811150000.9993841150000.9995011150000.9987611150000.99799611
101713312388786386331.23888082-5.23675594247396038257882064956084.5997338301.160110.001540277.7769E-060.9981490.9981491.7997424.29260.001682086.49405E-065730688841.73045E-076.09569E-06169869889073410566016.27170.027581615.59560.03394615.88790.0345061215.89230.017074315.85420.007946515.73680.076347731614241091150000.9996811150000.9993841150000.9995011150000.9987611150000.99799611
101713312388786386331.23888082-5.23675594247396169844942596156439.5801154601.343190.001569169.80598E-060.2725970.1803291.1752624.25920.0004236372.32656E-06573068904-1.71004E-073.96178E-06169869889006016.27170.027581615.59560.03394615.88790.0345061215.89230.017074315.85420.007946515.73680.076347731614241091150000.9996811150000.9993841150000.9995011150000.9987611150000.99799611
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