SDSS-III Publication 33: A Simple Likelihood Estimator for Quasar Target Selection
Authors: Jessica A. Kirkpatrick (corresponding author)
David J. Schlegel, Nicholas P. Ross, Adam D. Myers, Joseph F. Hennawi
Abstract:
We present a new method for quasar target selection using a likelihood estimator. For our purposes we target quasars using Sloan Digital Sky Survey (SDSS) photometry to a magnitude limit of g=22. The efficiency and completeness of this technique is measured using Baryon Oscillation Spectroscopic Survey (BOSS) Commissioning Data, taken in late 2009. This technique was used as the CORE method for target selection for BOSS Year 1 spectroscopy to be realized in the 9th SDSS data release (DR9). When targeting at a density of 40 objects/deg2 we find the efficiency of this technique to be 41% and the completeness compared to all quasars identified in BOSS Commissioning Data to be 62%. This paper also describes possible extensions and improvements for this technique.
Comments:
SDSS-III participants have three weeks to send comments and to request changes. Participants comments should be sent to the Jessica Kirkpatrick.
The deadline to submit comments is Wednesday, April 6th 2011.
This is a BOSS science paper intended for submission to the Astrophysical Journal.
Downloads:
The most up to date .pdf of the paper can be found here:
likelihood paper (current) this version will be updated as I receive comments during the next three weeks.
The version of the paper submitted to the collaboration (3/16) is here:
likelihood collaboration submission
There is also a single column, double spaced version here (for easier editing):
likelihood paper one column
The .tex files and all associated figures, can be checked-out from the SVN at this location:
svn co svn+ssh://sdss3svn@sdss3.org/repo/boss/bosstarget/trunk/tex/likelihood/
Or downloaded here on the SDSS3 wiki.
Showing posts with label wiki. Show all posts
Showing posts with label wiki. Show all posts
Wednesday, March 16, 2011
Wednesday, March 2, 2011
Using the BOSS Randoms
I downloaded the latest BOSS data and randoms from Will Percival as Martin White suggested in my email exchange with him yesterday.
There are in the following location on the wiki:
https://trac.sdss3.org/wiki/BOSS/clustering/cats
I put them here on riemann:
/clusterfs/riemann/raid001/jessica/boss/
galaxy-wjp-main008-LOWZ-020211-cut.txt
random-wjp-main008-LOWZ-020211-cut-small.txt
galaxy-wjp-merge-CMASS-020211-cut.txt
random-wjp-merge-CMASS-020211-cut-small.txt
The format of these files is:
ra / degrees
dec / degrees
redshift
galaxy weight
sector completeness
close pair flag
THING_ID
MASK POLY ID
ID for galaxy in spAll file (not in std format)
I read them in and below are plots. As you can see, the distribution of the randoms matches the data. So there is something wrong with what I am doing. At this point though, I'm not going to waste more time trying to fix my masks/randoms. I'm going to use these catalogs and re-run the correlation functions to see if this fixes things.
I'm also going to ask Shirley or Eric to run a correlation function on the same data to check that we get the same answer.
The code to make the above plots is in the following log file:
../logs/110302log/pro
thisfile = '/clusterfs/riemann/raid001/jessica/boss/galaxy-wjp-main008-LOWZ-020211-cut.txt'
readcol,thisfile,slra,sldec,slz,x,x,x,x,x,x,format='(F,F,F,F,F,F,F,F,F)'
thisfile = '/clusterfs/riemann/raid001/jessica/boss/galaxy-wjp-merge-CMASS-020211-cut.txt'
readcol,thisfile,sra,sdec,sz,x,x,x,x,x,x,format='(F,F,F,F,F,F,F,F,F)'
sra = [sra,slra]
sdec = [sdec,sldec]
sz = [sz,slz]
thisfile = '/clusterfs/riemann/raid001/jessica/boss/random-wjp-main008-LOWZ-020211-cut-small.txt'
readcol,thisfile,rslra,rsldec,rslz,x,x,x,x,x,x,format='(F,F,F,F,F,F,F,F,F)'
thisfile = '/clusterfs/riemann/raid001/jessica/boss/random-wjp-merge-CMASS-020211-cut-small.txt'
readcol,thisfile,rsra,rsdec,rsz,x,x,x,x,x,x,format='(F,F,F,F,F,F,F,F,F)'
rsra = [rsra,rslra]
rsdec = [rsdec,rsldec]
rsz = [rsz,rslz]
xtit = 'Ra'
ytit = 'Dec'
mtit = 'Ra vs Dec'
window,xsize=700,ysize=600
plot, sra, sdec, ps = 3, xrange = [110,130], yrange=[40,55],XTITLE = xtit, YTITLE =ytit, TITLE = mtit, charsize = 1.5, charthick = 1
oplot, rsra, rsdec, ps=3, color = fsc_color('green')
;Make histogram of the dec distributions
data = sdec
datamin = min(sdec)
datamax = max(sdec)
binsize = (datamax - datamin)/100
xtit = 'Dec Distribution'
ytit = '% in bin'
mtit = 'Histogram of Spectroscopic Dec'
window,xsize=700,ysize=600
hist = HISTOGRAM(data, binsize = binsize, min = datamin, max = datamax)
bins = FINDGEN(N_ELEMENTS(hist))*binsize + datamin
plot, bins, hist*1.0/n_elements(data), PSYM = 10, xrange = [datamin,datamax], yrange=[0,1.0*max(hist)/n_elements(data)],XTITLE = xtit, YTITLE =ytit, TITLE = mtit, charsize = 1.5, charthick = 1
data = rsdec
datamin = min(rsdec)
datamax = max(rsdec)
hist = HISTOGRAM(data, binsize = binsize, min = datamin, max = datamax)
bins = FINDGEN(N_ELEMENTS(hist))*binsize + datamin
oplot, bins, 1.0*hist/n_elements(data), PSYM = 10, color = fsc_color('green')
;Make histogram of the dec distributions
data = sdec
datamin = min(sdec)
datamax = max(sdec)
binsize = (datamax - datamin)/1000
xtit = 'Dec Distribution'
ytit = '# in bin'
mtit = 'Histogram of Spectroscopic Dec'
window,xsize=700,ysize=600
hist = HISTOGRAM(data, binsize = binsize, min = datamin, max = datamax)
bins = FINDGEN(N_ELEMENTS(hist))*binsize + datamin
plot, bins, hist*1.0, PSYM = 10, xrange = [datamin,datamax], yrange=[0,1.0*max(hist)],XTITLE = xtit, YTITLE =ytit, TITLE = mtit, charsize = 1.5, charthick = 1
data = rsdec
datamin = min(rsdec)
datamax = max(rsdec)
hist = HISTOGRAM(data, binsize = binsize, min = datamin, max = datamax)
bins = FINDGEN(N_ELEMENTS(hist))*binsize + datamin
oplot, bins, 1.0*hist, PSYM = 10, color = fsc_color('green')
;Make histogram of the dec distributions
data = sra
datamin = min(sra)
datamax = max(sra)
binsize = (datamax - datamin)/100
xtit = 'Ra Distribution'
ytit = '% in bin'
mtit = 'Histogram of Spectroscopic Ra'
window,xsize=700,ysize=600
hist = HISTOGRAM(data, binsize = binsize, min = datamin, max = datamax)
bins = FINDGEN(N_ELEMENTS(hist))*binsize + datamin
plot, bins, hist*1.0/n_elements(data), PSYM = 10, xrange = [datamin,datamax], yrange=[0,1.0*max(hist)/n_elements(data)],XTITLE = xtit, YTITLE =ytit, TITLE = mtit, charsize = 1.5, charthick = 1
data = rsra
datamin = min(rsra)
datamax = max(rsra)
hist = HISTOGRAM(data, binsize = binsize, min = datamin, max = datamax)
bins = FINDGEN(N_ELEMENTS(hist))*binsize + datamin
oplot, bins, 1.0*hist/n_elements(data), PSYM = 10, color = fsc_color('green')
;Make histogram of the dec distributions
data = sra
datamin = min(sra)
datamax = max(sra)
binsize = (datamax - datamin)/1000
xtit = 'RA Distribution'
ytit = '# in bin'
mtit = 'Histogram of Spectroscopic RA'
window,xsize=700,ysize=600
hist = HISTOGRAM(data, binsize = binsize, min = datamin, max = datamax)
bins = FINDGEN(N_ELEMENTS(hist))*binsize + datamin
plot, bins, hist*1.0, PSYM = 10, xrange = [datamin,datamax], yrange=[0,1.0*max(hist)],XTITLE = xtit, YTITLE =ytit, TITLE = mtit, charsize = 1.5, charthick = 1
data = rsra
datamin = min(rsra)
datamax = max(rsra)
hist = HISTOGRAM(data, binsize = binsize, min = datamin, max = datamax)
bins = FINDGEN(N_ELEMENTS(hist))*binsize + datamin
oplot, bins, 1.0*hist, PSYM = 10, color = fsc_color('green')
;Make histogram of the z distributions
data = sz
datamin = min(sz)
datamax = max(sz)
binsize = (datamax - datamin)/50
xtit = 'Redshift Distribution'
ytit = '% in bin'
mtit = 'Histogram of Spectroscopic z'
window,xsize=700,ysize=600
hist = HISTOGRAM(data, binsize = binsize, min = datamin, max = datamax)
bins = FINDGEN(N_ELEMENTS(hist))*binsize + datamin
plot, bins, hist*1.0/n_elements(data), PSYM = 10, xrange = [datamin,datamax], yrange=[0,1.0*max(hist)/n_elements(data)],XTITLE = xtit, YTITLE =ytit, TITLE = mtit, charsize = 1.5, charthick = 1
data = rsz
datamin = min(rsz)
datamax = max(rsz)
hist = HISTOGRAM(data, binsize = binsize, min = datamin, max = datamax)
bins = FINDGEN(N_ELEMENTS(hist))*binsize + datamin
oplot, bins, 1.0*hist/n_elements(data), PSYM = 10, color = fsc_color('green')
;Plot Data that is inside the mask
window,xsize=700,ysize=600
xobject = sra
yobject = sdec
xtit = 'RA'
ytit = 'Dec'
mtit = 'SDSS Spectroscopic Data + Masks'
plot, xobject, yobject, psym=3, symsize=2, XTITLE = xtit, YTITLE = ytit, TITLE = mtit, charsize = 2, charthick = 1, thick = 2, xthick=2, ythick=2
oplot, xobject, yobject, ps=3, color=fsc_color('white')
oplot, rsra, rsdec, ps=3, color=fsc_color('green')
There are in the following location on the wiki:
https://trac.sdss3.org/wiki/BOSS/clustering/cats
I put them here on riemann:
/clusterfs/riemann/raid001/jessica/boss/
galaxy-wjp-main008-LOWZ-020211-cut.txt
random-wjp-main008-LOWZ-020211-cut-small.txt
galaxy-wjp-merge-CMASS-020211-cut.txt
random-wjp-merge-CMASS-020211-cut-small.txt
The format of these files is:
ra / degrees
dec / degrees
redshift
galaxy weight
sector completeness
close pair flag
THING_ID
MASK POLY ID
ID for galaxy in spAll file (not in std format)
I read them in and below are plots. As you can see, the distribution of the randoms matches the data. So there is something wrong with what I am doing. At this point though, I'm not going to waste more time trying to fix my masks/randoms. I'm going to use these catalogs and re-run the correlation functions to see if this fixes things.
I'm also going to ask Shirley or Eric to run a correlation function on the same data to check that we get the same answer.
The code to make the above plots is in the following log file:
../logs/110302log/pro
thisfile = '/clusterfs/riemann/raid001/jessica/boss/galaxy-wjp-main008-LOWZ-020211-cut.txt'
readcol,thisfile,slra,sldec,slz,x,x,x,x,x,x,format='(F,F,F,F,F,F,F,F,F)'
thisfile = '/clusterfs/riemann/raid001/jessica/boss/galaxy-wjp-merge-CMASS-020211-cut.txt'
readcol,thisfile,sra,sdec,sz,x,x,x,x,x,x,format='(F,F,F,F,F,F,F,F,F)'
sra = [sra,slra]
sdec = [sdec,sldec]
sz = [sz,slz]
thisfile = '/clusterfs/riemann/raid001/jessica/boss/random-wjp-main008-LOWZ-020211-cut-small.txt'
readcol,thisfile,rslra,rsldec,rslz,x,x,x,x,x,x,format='(F,F,F,F,F,F,F,F,F)'
thisfile = '/clusterfs/riemann/raid001/jessica/boss/random-wjp-merge-CMASS-020211-cut-small.txt'
readcol,thisfile,rsra,rsdec,rsz,x,x,x,x,x,x,format='(F,F,F,F,F,F,F,F,F)'
rsra = [rsra,rslra]
rsdec = [rsdec,rsldec]
rsz = [rsz,rslz]
xtit = 'Ra'
ytit = 'Dec'
mtit = 'Ra vs Dec'
window,xsize=700,ysize=600
plot, sra, sdec, ps = 3, xrange = [110,130], yrange=[40,55],XTITLE = xtit, YTITLE =ytit, TITLE = mtit, charsize = 1.5, charthick = 1
oplot, rsra, rsdec, ps=3, color = fsc_color('green')
;Make histogram of the dec distributions
data = sdec
datamin = min(sdec)
datamax = max(sdec)
binsize = (datamax - datamin)/100
xtit = 'Dec Distribution'
ytit = '% in bin'
mtit = 'Histogram of Spectroscopic Dec'
window,xsize=700,ysize=600
hist = HISTOGRAM(data, binsize = binsize, min = datamin, max = datamax)
bins = FINDGEN(N_ELEMENTS(hist))*binsize + datamin
plot, bins, hist*1.0/n_elements(data), PSYM = 10, xrange = [datamin,datamax], yrange=[0,1.0*max(hist)/n_elements(data)],XTITLE = xtit, YTITLE =ytit, TITLE = mtit, charsize = 1.5, charthick = 1
data = rsdec
datamin = min(rsdec)
datamax = max(rsdec)
hist = HISTOGRAM(data, binsize = binsize, min = datamin, max = datamax)
bins = FINDGEN(N_ELEMENTS(hist))*binsize + datamin
oplot, bins, 1.0*hist/n_elements(data), PSYM = 10, color = fsc_color('green')
;Make histogram of the dec distributions
data = sdec
datamin = min(sdec)
datamax = max(sdec)
binsize = (datamax - datamin)/1000
xtit = 'Dec Distribution'
ytit = '# in bin'
mtit = 'Histogram of Spectroscopic Dec'
window,xsize=700,ysize=600
hist = HISTOGRAM(data, binsize = binsize, min = datamin, max = datamax)
bins = FINDGEN(N_ELEMENTS(hist))*binsize + datamin
plot, bins, hist*1.0, PSYM = 10, xrange = [datamin,datamax], yrange=[0,1.0*max(hist)],XTITLE = xtit, YTITLE =ytit, TITLE = mtit, charsize = 1.5, charthick = 1
data = rsdec
datamin = min(rsdec)
datamax = max(rsdec)
hist = HISTOGRAM(data, binsize = binsize, min = datamin, max = datamax)
bins = FINDGEN(N_ELEMENTS(hist))*binsize + datamin
oplot, bins, 1.0*hist, PSYM = 10, color = fsc_color('green')
;Make histogram of the dec distributions
data = sra
datamin = min(sra)
datamax = max(sra)
binsize = (datamax - datamin)/100
xtit = 'Ra Distribution'
ytit = '% in bin'
mtit = 'Histogram of Spectroscopic Ra'
window,xsize=700,ysize=600
hist = HISTOGRAM(data, binsize = binsize, min = datamin, max = datamax)
bins = FINDGEN(N_ELEMENTS(hist))*binsize + datamin
plot, bins, hist*1.0/n_elements(data), PSYM = 10, xrange = [datamin,datamax], yrange=[0,1.0*max(hist)/n_elements(data)],XTITLE = xtit, YTITLE =ytit, TITLE = mtit, charsize = 1.5, charthick = 1
data = rsra
datamin = min(rsra)
datamax = max(rsra)
hist = HISTOGRAM(data, binsize = binsize, min = datamin, max = datamax)
bins = FINDGEN(N_ELEMENTS(hist))*binsize + datamin
oplot, bins, 1.0*hist/n_elements(data), PSYM = 10, color = fsc_color('green')
;Make histogram of the dec distributions
data = sra
datamin = min(sra)
datamax = max(sra)
binsize = (datamax - datamin)/1000
xtit = 'RA Distribution'
ytit = '# in bin'
mtit = 'Histogram of Spectroscopic RA'
window,xsize=700,ysize=600
hist = HISTOGRAM(data, binsize = binsize, min = datamin, max = datamax)
bins = FINDGEN(N_ELEMENTS(hist))*binsize + datamin
plot, bins, hist*1.0, PSYM = 10, xrange = [datamin,datamax], yrange=[0,1.0*max(hist)],XTITLE = xtit, YTITLE =ytit, TITLE = mtit, charsize = 1.5, charthick = 1
data = rsra
datamin = min(rsra)
datamax = max(rsra)
hist = HISTOGRAM(data, binsize = binsize, min = datamin, max = datamax)
bins = FINDGEN(N_ELEMENTS(hist))*binsize + datamin
oplot, bins, 1.0*hist, PSYM = 10, color = fsc_color('green')
;Make histogram of the z distributions
data = sz
datamin = min(sz)
datamax = max(sz)
binsize = (datamax - datamin)/50
xtit = 'Redshift Distribution'
ytit = '% in bin'
mtit = 'Histogram of Spectroscopic z'
window,xsize=700,ysize=600
hist = HISTOGRAM(data, binsize = binsize, min = datamin, max = datamax)
bins = FINDGEN(N_ELEMENTS(hist))*binsize + datamin
plot, bins, hist*1.0/n_elements(data), PSYM = 10, xrange = [datamin,datamax], yrange=[0,1.0*max(hist)/n_elements(data)],XTITLE = xtit, YTITLE =ytit, TITLE = mtit, charsize = 1.5, charthick = 1
data = rsz
datamin = min(rsz)
datamax = max(rsz)
hist = HISTOGRAM(data, binsize = binsize, min = datamin, max = datamax)
bins = FINDGEN(N_ELEMENTS(hist))*binsize + datamin
oplot, bins, 1.0*hist/n_elements(data), PSYM = 10, color = fsc_color('green')
;Plot Data that is inside the mask
window,xsize=700,ysize=600
xobject = sra
yobject = sdec
xtit = 'RA'
ytit = 'Dec'
mtit = 'SDSS Spectroscopic Data + Masks'
plot, xobject, yobject, psym=3, symsize=2, XTITLE = xtit, YTITLE = ytit, TITLE = mtit, charsize = 2, charthick = 1, thick = 2, xthick=2, ythick=2
oplot, xobject, yobject, ps=3, color=fsc_color('white')
oplot, rsra, rsdec, ps=3, color=fsc_color('green')
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