main.dvi

Transcription

1 /MOIRCS

2

3 MOIRCS MOS MOIRCS MOIRCS MOS MOIRCS MOS MCSMDP IRAF PyRAF A-B

4 A MCSMDP 59 A.1 MCSMDP A A A A A A A A

5 1 5

6 6 1 MOIRCS (MOS) IRAF (Image Reduction and Analysis Facility) python PyRAF UNIX PyRAF IRAF (R ) PyRAF MCSMDP (MOIRCS MOS Data Pipelines) MCSMDP 2010 S07A-083 (SMOKA ) PI ( ) (MDP Yoshikawa et al [5]

7 2 MOIRCS MOS 7

8 8 2 MOIRCS MOS 2.1 MOIRCS MOIRCS (Multi-Object InfraRed Camera and Spectrograph) ( µm) YJHK s 4 7 VPH (R 700) (R 1500) (R 3000) 2.1 MOIRCS 40 FOCAS (Faint Object Camera and Spectrograph) MOIRCS 2µm 100K a 2.1: MOIRCS [µm] [R] b [Å/pixel] zj HK H 820 K c R J 4 c H 3 c K 2 d VPH J d VPH H a Web b 0. 5 c J, H, K J K d Web MOIRCS HAWAII-2 HAWAII pixel 2048pixel HgCdTe MOIRCS /pixel MOIRCS

9 2.1. MOIRCS 9 2.1: MOIRCS x 1 x 2 VPH-J VPH-H ( 300pixel) (PA) x y 1 x 2 VPH-J VPH-H MOIRCS (Suzukietal. 2008[4]) Web (

10 10 2 MOIRCS MOS MOIRCS FITS (Flexible Image Transport System) FITS ID ( ID).fits ID MCSA MCS MOIRCS A 8 MOIRCS 1 2 FITS FITS FITS 3 MOIRCS FITS ID FRAMEID ID MOIRCS FITS MOS 2.2 FITS IRAF/PyRAF FITS FITS FITS FITS FITS ( kanamitu/fits/index.html)

11 : MOIRCS FITS FRAMEID EXP-ID DET-ID OBS-MOD DATA-TYP OBJECT SLIT DISPERSR EXPTIME K DITWID K DITCNT DATE-OBS HST-STR UT-STR MCSA ID MCSA ID 1 2 ID 1 2 SPEC MOS IMAG SPEC OBJECT DARK, DOMEFLAT, INSTFLAT CDFN MASK01 CDFN1 HK UT 22:25: :25: UT FOCAS MOIRCS FOCAS Suprime-Cam CCD (Charge Coupled Device) 1µm MOIRCS HAWAII-2 HgCdTe MOIRCS HAWAII-2 CCD (H 2 O) (CO 2 ) 2.2 MOIRCS 1 MOIRCS µm

12 12 2 MOIRCS MOS HK µm H K 1.9µm 2.2 MOIRCS OH O 3 FMOS OHS (OH Suppressor) OH saturate A-B IRCS COMICS 3µm MOIRCS cold stop 2.5µm 8m Ian McLean Electronic Imaging in Astronomy; Detectors and Instrumentation [2] 2.3 MOIRCS MOS MOIRCS MOS FOCAS MOIRCS MOS

13 2.3. MOIRCS MOS 13 transmission MOIRCS Ks MOIRCS H MOIRCS J atmosphere J H K s A] [erg/s/cm 2 / F [ A] 2.2: : MOIRCS J: H: K s : : MOIRCS MOIRCS MOIRCS MOS (PA) PI PA PI 2 mdp FOCAS mdp wmdp moircs MDP wmdp moircs sbr 2 MOS

14 14 2 MOIRCS MOS 100K pixel 3 4

15 2.3. MOIRCS MOS 15 OH OH A0V MOS

16 16 2 MOIRCS MOS sky image sky + mask image sky + mask image Mask install Telescope shift/rotate Detect star positions Detect hole positions (Calcuration of shift/rotate) Rough pointing Telescope shift MOIRCS PA rotation detector 2 Spectroscopy start! detector 1 Precision pointing (Alignment stars come to each hole center) 2.3: MOS 2006,

17 3 17

18 MOIRCS MOS MOS (Hα) Hα 2 S/N x y specific flux (F λ [ergs 1 cm 2 Å 1 ]) IRAF MOS 3.1 A-B x y OH

19 3.1. MOIRCS MOS : MOIRCS MOS

20 20 3 A-B OH A-B 2 (F λ [ergsec 1 cm 2 Å 1 ]) 3.2 MCSMDP MCSMDP (MOIRCS MOS Data Pipelines) MOIRCS MOIRCS MOS PyRAF 1 Web IRAF PyRAF IRAF (Image Reduction and Analysis Facility) NOAO (National Optical Astronomical Observatories) NOAO 2 IRAF (cl ) ( ) NOAO IRAF PyRAF IRAF Python NASA STScI (Space Telescope Science Institute) 3 PyRAF cl IRAF PyRAF Python Python IRAF MCSMDP PyRAF PyRAF MCSMDP IRAF version (lnux ) PyRAF version PyRAF 1 tomohiro/mcsmdp/ hardware/pyraf IRAF version 2.15 PyRAF

21 3.2. MCSMDP 21 Ubuntu Linux 10.4 IRAF/PyRAF MCSMDP (Ubuntu Linux *-dev ) (apt, yum ) IRAF, Python stsci python stsci python PyRAF python STScI Web Web IRAF, Python PyRAF ds9, xpa Harvard-Smithonian Center for Astrophysics Web 5 ximtools RO Python Package RusselOwen 6 Python Python setuptools easy install matplotlib python 7 Linux scipy python 8 Linux ipython python PyRAF PyRAF 9 Linux R, rpy python 1011 Linux

22 MCSMDP MDPDB MCSMDP 12 home $ wget cc.kyoto su.ac. jp/ tomohiro/mcsmdp/mcsmdp v tgz $ wget cc.kyoto su.ac. jp/ tomohiro/mcsmdp/mdpdb v tgz $ tar xvfz MCSMDP v tgz $ tar xvfz MDPDB v tgz MCSMDP setup.sh $ cd MCSMDP v1 0 1 $./ setup.sh 13 bash, ksh, sh, zsh.bash profile (bash ).profile (ksh, sh, zsh ) source ${HOME}/MCSMDP v1 0 1/etc/mcsmdp.sh tcsh, csh.cshrc source ${HOME}/MCSMDP v1 0 1/etc/mcsmdp. csh mcsmdp mcsmdp iraf mkiraf 14 pyraf (-->) $ mcsmdp mkiraf? (yes ):... > 12 $ bash mkiraf iraf mkiraf no

23 3.2. MCSMDP 23 mcsmdp mcsmdp 15 > mcsmdp... > pyraf IRAF cl pyraf STScI The PyRAF Tutrial 16 mdpdisplay > lpar mdpdisplay file = HK500 MODS fl. fits Image ( list ) to be loaded (frame = 1) Display frame to be loaded (multiframe = no) Increment frame number for image list? ( scale = linear ) scale type (smode = zscale ) scale mode (z1 = INDEF) minimum greylevel to be displayed (z2 = INDEF) maximum greylevel to be displayed (cmap = BB ) color map ( invert = no) invert color map? (mode = al ) > epar mdpdisplay 3.2 () iraf pyraf epar Save & Quit pyraf Execute Unlearn Cancel Mdpdisplay Help MCSMDP iraf 15 iraf loginuser.cl pyraf 16 python epydoc/docs/pyraf tutorial.pdf

24 : mdpdisplay pyraf = 1 > mdpdisplay MCSA fits frame=2 mcsmdp.exit >. exit $ ipython mcsmdp --ipython pyraf ipython $ mcsmdp ipython... In [1]:

25 3.2. MCSMDP 25 ipython /.ipython/ipythonrc-pyraf ipython mcsmdp Ctrl+D import mod pylab execfile pylabinit.py ipython matplotlib python pyraf IRAF cl pyraf

26

27 4 27

28 $ mkdir p /mfs02a/tomohrys/mcsmdp work # $ cd /mfs02a/tomohrys/mcsmdp work $ cp /mfs01b/tomohrys/mcsmdp sample/.. mdp, fits 2 mdp MDP fits FITS mcsmdp hselect $ mcsmdp > mcsmdp > hselect. fits $I,OBS MOD,DATA TYP,OBJECT,DISPERSR yes MCSA fits SPEC MOS OBJECT DOMEFLAT HK500 MCSA fits SPEC MOS OBJECT DOMEFLAT HK500 MCSA fits SPEC MOS OBJECT DOMEFLAT HK MCSA fits SPEC OBJECT M53735(A0V:J8.9:H8.9:K8.9) HK500 MCSA fits SPEC OBJECT M53735(A0V:J8.9:H8.9:K8.9) HK500 MCSA fits SPEC MOS OBJECT CDFN MASK02 HK500 MCSA fits SPEC MOS OBJECT CDFN MASK02 HK500 MCSA fits SPEC MOS OBJECT CDFN MASK02 HK OBS-MOD (SPEC MOS) (SPEC) DATA-TYP DOMEFLAT OBJECT DISPERSR HK500 hselect 2 > hselect MCSA. fits $I OBJECT = DOMEFLAT DET ID = 1 > flat1. lst > hselect MCSA. fits $I OBJECT = DOMEFLAT DET ID = 2 > flat2. lst 1 tomohiro/mcsmdp/mcsmdp sample.tbz 2

29 > hselect MCSA. fits $I OBJECT = CDFN MASK02 DET ID = 1 & K DITCNT = 1 > obj1a. lst > hselect MCSA. fits $I OBJECT = CDFN MASK02 DET ID = 1 & K DITCNT = 2 > obj1b. lst > hselect MCSA. fits $I OBJECT = CDFN MASK02 DET ID = 2 & K DITCNT = 1 > obj2a. lst > hselect MCSA. fits $I OBJECT = CDFN MASK02 DET ID = 2 & K DITCNT = 2 > obj2b. lst flat1, flat2 1, 2 obj1a, obj1b 1 A B obj2a, obj2b craverage BPM.pl sed UNIX BPM >! sed s /\(. \)\. fits /BPM\/\1\.pl/ obj1a. lst > bpm1a. lst >! sed s /\(. \)\. fits /BPM\/\1\.pl/ obj1b. lst > bpm1b. lst > mkdir BPM MCSMDP 1 mdpdb$bpm/nlbpm1 FF64r.fits 2 mdpdb$bpm/nlbpm2 FF64r.fits craverage > imcopy mdpdb$bpm/nlbpm1 FF64r. fits,mdpdb$bpm/nlbpm1 FF64r. fits, mdpdb$bpm/nlbpm1 FF64r. fits,mdpdb$bpm/nlbpm1 FF64r. lst > imcopy mdpdb$bpm/nlbpm1 FF64r. fits,mdpdb$bpm/nlbpm1 FF64r. fits, mdpdb$bpm/nlbpm1 FF64r. fits,mdpdb$bpm/nlbpm1 FF64r. lst

30 30 4 epar craverage input = output = (crmask = ) (average = ) (sigma = ) List of input images List of output images List of output cosmic ray and object masks List of output block average filtered images List of output sigma images (navg = 15) (nrej = 100) (nbkg = 5) (nsig = 10) (var0 = 0.0) (var1 = 0.0) (var2 = 0.0) Block average box size Number of high pixels to reject from the average Background annulus width Box size for sigma calculation Variance coefficient for DNˆ0 term Variance coefficient for DNˆ1 term Variance coefficient for DNˆ2 term (crval = 1) Mask value for cosmic rays ( lcrsig = 100.0) Low cosmic ray sigma outside object ( hcrsig = 10.0) High cosmic ray sigma outside object (crgrow = 0.0) Cosmic ray grow radius (objval = 0) Mask value for objects ( lobjsig = 10.0) Low object detection sigma (hobjsig = 5.0) (objgrow = 0.0) High object detection sigma Object grow radius craverage > lst crmask=@bpm1a. lst > lst crmask=@bpm1b. lst fixpix Y cr >! sed s/\(. \)/ cr\1/ obj1a. lst > crobj1a. lst >! sed s/\(. \)/ cr\1/ obj1b. lst > crobj1b. lst fixpix > lst > lst

31 epar fixpix images = masks = List of images to be fixed List of bad pixel masks ( linterp = INDEF ) Mask values for line interpolation (cinterp = 1 ) (verbose = no) Mask values for column interpolation Verbose output? ( pixels = no) List pixels? fixpix > lst > lst MCSMDP MCSMDP crrejection 1. ( 1) 2. A-B A A/B , 2, OR crrejection inimage1 = inimage2 = outimage1 = outimage2 = bpm = (navg = 15) input frame at A position input frame at B position output frame at A position output frame at B position badpixel mask Block average box size

32 32 4 (nrej = 100) (nbkg = 5) (nsig = 10) (var0 = 0.0) (var1 = 0.0) (var2 = 0.0) Number of high pixels to reject from the average Background annulus width Box size for sigma calculation Variance coefficient for DNˆ0 term Variance coefficient for DNˆ1 term Variance coefficient for DNˆ2 term ( lcrsig = 100.0) Low cosmic ray sigma outside object ( hcrsig = 10.0) High cosmic ray sigma outside object (crgrow = 0.0) Cosmic ray grow radius (bpmdir = BPM ) directory name to store bad pixel masks crrejection ( cr2* BPM2 ) >! sed s/\(. \)/ cr2\1/ obj1a. lst > cr2obj1a. lst >! sed s/\(. \)/ cr2\1/ obj1b. lst > cr2obj1b. lst > lst mdpdb$bpm/ nlbpm1 FF64r. f i t s bpmdir= BPM A-B A B imarith ab >! sed s/\(. \)/ab\1/ crobj1a. lst > abobj1a. lst > lst imcombine input = output = (headers = ) (bpmasks = ) (rejmasks = ) (nrejmasks = ) (expmasks = ) (sigmas = ) (imcmb = $I ) List of images to combine List of output images List of header files (optional) List of bad pixel masks (optional) List of rejection masks (optional) List of number rejected masks (optional) List of exposure masks (optional) List of sigma images (optional) Keyword for IMCMB keywords

33 ( logfile = STDOUT ) Log file (combine = median ) Type of combine operation ( reject = sigclip ) Type of rejection ( project = no) Project highest dimension of input images? (outtype = real ) Output image pixel datatype ( outlimits = ) Output limits (x1 x2 y1 y2...) ( offsets = none ) Input image offsets (masktype = none ) Mask type (maskvalue = 0 ) Mask value (blank = 0.0) Value if there are no pixels ( scale = exposure ) Image scaling (zero = none ) Image zero point offset (weight = none ) Image weights ( statsec = ) Image section for computing statistics (expname = EXPTIME ) Image header exposure time keyword ( lthreshold = INDEF) Lower threshold (hthreshold = INDEF) (nlow = 1) (nhigh = 1) (nkeep = 1) (mclip = yes) (lsigma = 3.0) (hsigma = 3.0) Upper threshold minmax: Number of low pixels to reject minmax: Number of high pixels to reject Minimum to keep (pos) or maximum to reject (neg) Use median in sigma clipping algorithms? Lower sigma clipping factor Upper sigma clipping factor (rdnoise = 0. ) ccdclip : CCD readout noise ( electrons ) (gain = 1. ) ccdclip : CCD gain ( electrons/dn) ( snoise = 0. ) ccdclip : Sensitivity noise ( fraction ) ( sigscale = 0.1) Tolerance for sigma clipping scaling corrections ( pclip = 0.5) pclip : Percentile clipping parameter (grow = 0.0) imcombine Radius ( pixels ) for neighbor rejection > lst HK500 CDFN2 Domeflat1. fits 1 > imarith HK500 CDFN2 Domeflat1. fits / HK500 CDFN2 Domeflat1. fits

34 34 4 fixpix > fixpix HK500 CDFN2 Domeflat1. fits mdpdb$bpm/nlbpm1 FF64r. fits A-B fl >! sed s/\(. \)/ fl \1/ abobj1a. lst > flobj1a. lst > lst / HK500 CDFN2 Domeflat1. lst geotran input = output = database = transforms = Input data Output data Name of GEOMAP database file Names of coordinate transforms in database file (geometry = geometric ) Transformation type ( linear, geometric) (xin = INDEF) (yin = INDEF) X origin of input frame in pixels Y origin of input frame in pixels ( xshift = INDEF) X origin shift in pixels ( yshift = INDEF) Y origin shift in pixels (xout = INDEF) (yout = INDEF) (xmag = INDEF) (ymag = INDEF) (xrotation = INDEF) (yrotation = INDEF) (xmin = INDEF) (xmax = INDEF) (ymin = INDEF) X origin of output frame in reference units Y origin of output frame in reference units X scale of input picture in pixels per reference unit Y scale of input picture in pixels per reference unit X axis rotation in degrees Y axis rotation in degrees Minimum reference x value of output picture Maximum reference x value of output picture Minimum reference y value of output picture

35 (ymax = INDEF) Maximum reference y value of output picture ( xscale = 1.0) X scale of output picture in reference units per pixel ( yscale = 1.0) Y scale of output picture in reference (ncols = INDEF) units per pixel Number of columns in the output picture ( nlines = INDEF) Number of lines in the output picture (xsample = 1.0) (ysample = 1.0) Coordinate surface sampling interval in x Coordinate surface sampling interval in y ( interpolant = linear ) Interpolant (boundary = constant ) Boundary extension (nearest, constant, (constant = 0.0) (fluxconserve = yes) (nxblock = 512) (nyblock = 512) (verbose = yes) reflect,wrap) Constant boundary extension Preserve image flux? X dimension of working block size in pixels Y dimension of working block size in pixels Print messages about the progress of the task geotran gc >! sed s/\(. \)/gc\1/ flobj1a. lst > gcobj1a. lst > lst mdpdb$geomap/mcsdistcrr1 feb07new.dbs mcsdistcrr1 feb07new.gmp geotran MDPDB mdpdb$geomap/mcsdistcrr1 feb07new.dbs mcsdistcrr1 feb07new.gmp 1 mdpdb$geomap/mcsdistcrr2 feb07new.dbs mcsdistcrr2 feb07new.gmp 2 database transform MCSRED

36 36 4 MCSMDP maskplot MDP > maskplot CDFN MASK02.mdp image=gcflabcrmcsa fits raw+ MODS imcopy >! sed s /\(. \)\. fits /\1 MODS \. fits / gcobj1a. lst > gcmods l s t >! sed s/\(. \)/\1[,1755:1840]/ gcobj1a. lst > cut. lst > lst X OH A-B >! sed s/\(. \)/ flsky \1/ crobj1a. lst > flsky1a. lst > lst / HK500 CDFN2 Domeflat1. lst >! sed s/\(. \)/gc\1/ flsky1a. lst > gcsky1a. lst > lst mdpdb$geomap/mcsdistcrr2 feb07new.dbs mcsdistcrr2 feb07new.gmp >! sed s /\(. \)\. fits /\1 MODS \. fits / gcsky1a. lst > gcskymods lst >! sed s/\(. \)/\1[,1755:1840]/ gcsky1a. lst > cut. lst > lst identify identify X images = Images containing features to be identified

37 crval = cdelt = Approximate coordinate (at reference pixel ) Approximate dispersion ( section = middle line ) Section to apply to two dimensional (database = database ) images Database in which to record feature data ( coordlist = mdpdb$ohlist/list NS HK500 ) User coordinate list (units = ) (nsum = 20 ) (match = 3.0) (maxfeatures = 50) (zwidth = 100.0) (ftype = emission ) (fwidth = 8.0) (cradius = 5.0) (threshold = 0.0) (minsep = 2.0) (function = chebyshev ) (order = 4) (sample = ) Coordinate units Number of lines/columns/bands to sum in 2D images Coordinate list matching limit Maximum number of features for automatic identification Zoom graph width in user units Feature type Feature width in pixels Centering radius in pixels Feature threshold for centering Minimum pixel separation Coordinate function Order of coordinate function Coordinate sample regions ( niterate = 10) Rejection iterations ( low reject = 3.0) Lower rejection sigma ( high reject = 3.0) Upper rejection sigma (grow = 0.0) (autowrite = no) (graphics = stdgraph ) (cursor = ) (aidpars = ) Rejection growing radius Automatically write to database Graphics output device Graphics cursor input Automatic identification algorithm parameters section nsum coordlist OH Rousselot et al. (2000) [3] HK500 MCSMDP 4.1 identify > identify gcflskycrmcsa MODS fits

38 x1e Angstrom OH line list for HK500 grism (mdpdb$ohlist/list_ns_hk500) : HK500 OH

39 X : identify m d c w f l q identify? b t x y X Y? m m 4 5 f 4.3 residual 3 Chebychev 5 identify iraf H 4 1 X 5 order=4 iraf order order-1

40 : identify 4.2: identify h,i,j,k,l f d u c s z :order n n-1 :function :niterate :low reject :high reject q sigma rejection sigma rejection sigma rejection?

41 : identify q l f HK [Å/pixel] RMS Å q q identify Write feature data to the database (yes)? return database (database/idgcflskycrmcsa MODS ) reidentify identify reidentify

42 42 4 reference = Reference image images = Images to be reidentified answer = yes Fit dispersion function interactively? crval = Approximate coordinate (at reference pixel ) cdelt = Approximate dispersion ( interactive = no ) Interactive fitting? ( section = middle line ) Section to apply to two dimensional images (newaps = yes) Reidentify apertures in images not in reference? (override = yes) Override previous solutions? ( refit = yes) Refit coordinate function? (trace = yes) Trace reference image? (step = 20 ) Step in lines/columns/bands for tracing an image (nsum = 20 ) Number of lines/columns/bands to sum ( shift = 0. ) Shift to add to reference features (INDEF to search) (search = 0.0) Search radius ( nlost = 100) Maximum number of features which may be lost (cradius = 5.0) Centering radius (threshold = 0.0) Feature threshold for centering (addfeatures = no) Add features from a line list? ( coordlist = mdpdb$ohlist/list NS HK500 ) User coordinate list (match = 3.0) Coordinate list matching limit (maxfeatures = 50) Maximum number of features for automatic identification (minsep = 2.0) Minimum pixel separation (database = database ) Database ( logfiles = logfile ) List of log files ( plotfile = ) Plot file for residuals (verbose = yes) Verbose output? (graphics = stdgraph ) Graphics output device (cursor = ) Graphics cursor input

43 (aidpars = ) Automatic identification algorithm parameters > reidentify gcflskycrmcsa MODS fits gcflskycrmcsa MODS f i t s 20 6 X,Y 2 X Y fitcoords fitcoords images = (fitname = ) Images whose coordinates are to be fit Name for coordinate fit in the database ( interactive = yes) Fit coordinates interactively? (combine = no) (database = database ) Combine input coordinates for a single fit? Database ( deletions = deletions.db ) Deletion list file (not used if null ) (function = chebyshev ) (xorder = 4) (yorder = 3) ( logfiles = STDOUT, logfile ) Log files Type of fitting function ( plotfile = plotfile ) Plot log file (graphics = stdgraph ) (cursor = ) X order of fitting function Y order of fitting function Graphics output device Graphics cursor input function xorder identify, reidentify > fitcoords gcflskycrmcsa MODS identify fitcoords 4.3 fitcoords X Y 6 interactive=yes

44 : fitcoords x[key],y[key] r f :order n X Y key n-1 :function q fitcoords? x y z s r [key] X Y (s-z) xxyy r X Y identify reidentify X x Y ( xxyr ) xorder RMS 2 X y Y xyyr Y q fitcoords 1 (MCSA ) MOIRCS fitcoords transform transform input = output = fitnames = (minput = ) Input images Output images Names of coordinate fits in the database Input masks 7 MCSMDP

45 : 2 : (moutput = ) (database = database ) (interptype = linear ) Output masks Identify database Interpolation type (x1 = INDEF) Output starting x coordinate (x2 = INDEF) Output ending x coordinate (dx = INDEF) (nx = INDEF) (xlog = no) Output X pixel interval Number of output x pixels Logarithmic x coordinate? (y1 = INDEF) Output starting y coordinate (y2 = INDEF) Output ending y coordinate (dy = INDEF) (ny = INDEF) (ylog = no) Output Y pixel interval Number of output y pixels Logarithmic y coordinate? ( flux = yes) Conserve flux per pixel? (blank = INDEF) Value for out of range pixels ( logfiles = STDOUT, logfile ) List of log files transform tr >! sed s/\(. \)/ tr\1/ gcmods lst > trmods lst > lst gcflskycrmcsa MODS transform ds9 4.4 Y transform FITS ds9 information panel > mdpdisplay gcflabcrmcsa MODS f i t s frame=1 > mdpdisplay trgcflabcrmcsa MODS f i t s frame=2

46 A-B A-B transform Y Y background bg input = output = (axis = 2) Input images to be background subtracted Output background subtracted images Axis along which background is fit and subtracted ( interactive = yes) Set fitting parameters interactively? (sample = ) (naverage = 1) (function = chebyshev ) (order = 3) Sample of points to use in fit Number of points in sample averaging Fitting function Order of fitting function ( low reject = 3.0) Low rejection in sigma of fit ( high reject = 3.0) High rejection in sigma of fit ( niterate = 3) Number of rejection iterations (grow = 0.0) (graphics = stdgraph ) (cursor = ) Rejection growing radius Graphics output device Graphics cursor input >! sed s/\(. \)/bg\1/ trmods lst > bgmods lst > l s l s t Fit column X ds9 1 background identify 2 (order=3) s

47 q Fit column ds A-B A B A B 8 B A > lst $I,K DITWID yes bgtrgcflabcrmcsa MODS fits bgtrgcflabcrmcsa MODS fits bgtrgcflabcrmcsa MODS fits bgtrgcflabcrmcsa MODS fits MOIRCS arcsec/pixel 3.0/ pixel imshift >! sed s/\(. \)/sh\1/ bgmods lst > shmods lst > lst 0 26 imarith >! sed s/\(. \)/ng\1/ shmods lst > ngmods lst > lst lst imcombine median imcombine input = output = (headers = ) (bpmasks = ) (rejmasks = ) (nrejmasks = ) List of images to combine List of output images List of header files (optional) List of bad pixel masks (optional) List of rejection masks (optional) List of number rejected masks

48 48 4 (optional) (expmasks = ) List of exposure masks (optional) (sigmas = ) List of sigma images (optional) (imcmb = $I ) Keyword for IMCMB keywords ( logfile = STDOUT ) Log file (combine = median ) Type of combine operation ( reject = sigclip ) Type of rejection ( project = no) Project highest dimension of input images? (outtype = real ) Output image pixel datatype ( outlimits = ) Output limits (x1 x2 y1 y2...) ( offsets = none ) Input image offsets (masktype = none ) Mask type (maskvalue = 0 ) Mask value (blank = 0.0) Value if there are no pixels ( scale = exposure ) Image scaling (zero = none ) Image zero point offset (weight = exposure ) Image weights ( statsec = ) Image section for computing statistics (expname = EXPTIME ) Image header exposure time keyword ( lthreshold = INDEF) Lower threshold (hthreshold = INDEF) Upper threshold (nlow = 1) minmax: Number of low pixels to reject (nhigh = 1) minmax: Number of high pixels to reject (nkeep = 1) Minimum to keep (pos) or maximum to reject (neg) (mclip = yes) Use median in sigma clipping algorithms? (lsigma = 3.0) Lower sigma clipping factor (hsigma = 3.0) Upper sigma clipping factor (rdnoise = 0. ) ccdclip : CCD readout noise ( electrons ) (gain = 1. ) ccdclip : CCD gain ( electrons/dn) ( snoise = 0. ) ccdclip : Sensitivity noise ( fraction ) ( sigscale = 0.1) Tolerance for sigma clipping scaling corrections ( pclip = 0.5) pclip : Percentile clipping parameter (grow = 0.0) Radius ( pixels ) for neighbor rejection (mode = al )

49 > l s t,@ngmods l s t HK500 MODS ADU (F λ [ergsec 1 cm 2 Å 1 ]) N obs (λ) F λ,int R(λ) N obs (λ) = R(λ) F λ,int (4.1) A Castelli (2004) [1] HK500 M53735.fits 2 apall yes > apall HK500 M fits Recenter apertures for HK500 M53735? ( yes ): Resize apertures for HK500 M53735? ( yes ): Edit apertures for HK500 M53735? ( yes ): 8

50 : apall ( : : : : ) 4.5 b 4.5 s q Trace apertures for HK500 M53735? Fit traced positions for HK500 M53735 interactively? Fit curve to aperture 1 of HK500 M53735 interactively 4.5 s :order Write apertures for HK500 M53735 to database? Extract aperture spectra for HK500 M53735? Review extracted spectra from HK500 M53735? 4.5 HK500 M53735.ms.fits N(λ)

51 R(λ) MCSMDP rescurve stddata = one D standard star data stdmag = Vega magnitude of the standard at magfilter output = output response curve ( magfilter = mdpdb$filter/2mass K. fits ) transmission curve of filter for stdmag (moddata = mdpdb$standard/a0v g50. spc ) standard star model spectrum (vegamodel = mdpdb$filter/alpha lyr stis 003. fits ) Vega model spectrum (A0V g50.spc) K Vega Vega Vega MDPDB HIPPARCOS A0 M53735 K 2MASS > rescurve HK500 M53735.ms. fits resc CDFN2 HK500. fits resc CDFN2 HK500.fits R(λ) 9 2 R(λ) 2 MCSMDP mdpfcalib 1 (= > mdpfcalib HK500 MODS fits resc CDFN2 HK500. fits HK500 MODS fl. fits HK500 MODS fl.fits [ergsec 1 cm 2 Å 1 ] 9 FITS ds9

52

53 5 53

54 z 2 (Yoshikawa et al [5]) 2 2 ds9 A-B 2 Y > mdpdisplay HK500 MODS fl. fits frame=1 splot 2 1 splot > splot HK500 MODS fl. fits splot 5.1 :nsum ds ( w ) a k k Gaussian FWHM HK µm 2.5µm z Å 5.2 AGN 1 2 1

55 : splot a w k s q a Gaussian k fitcoords? :nsum n n 5.2: [Å] [SII] Hα 6716, : [NII] 6548, 6583 Hα 1:2 [OIII] 4959, :3 Hβ splot Hα (F) (L) L = F 4πd 2 L(z) (5.1) d L (z) MCSMDP 2 1 > cosmology 2.0 Luminosity Distance(m): 4.800e+26 Angular Diameter Distance(m): 5.333e+25 Look Back Time(yr ): 1.024e+10

56 56 5 Hα 1 NED Extinction Calculator 2 E(B V) =

57 57 [1] Castelli, F., Kurucz, R. L. 2004, arxiv:astro-ph/ [2] McLean, 1997, Electronic Imaging in Astronomy; Detectors and Instrumentation (John Wiley & Sons Ltd., 1997) [3] Rousselot et al. 2000, A&A, 354, 1134 [4] Suzuki, R., et al. 2008, PASJ, 60, 1347 [5] Yoshikawa, T., et al. 2010, ApJ, 718, 112

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59 A MCSMDP 59

60 60 A MCSMDP A.1 MCSMDP MCSMDP 3.1 mdpproc, mdpcombine MCSMDP S/N A-B MDP : OH 1 OH - : OH 1 OH multiextention FITS (MEF) 2 extention Poisson 3 extention SPECFIT STSDAS specfit [NII]-Hα HK500 Gaussian Poisson MOIRCS Poisson g xi σ i = 1 g r = 1 xi r g, (A.1) x i g e ADU 1 r response curve ADUerg 1 seccm 2 Å 1 2Σ obj σi 2 σ obj =, (A.2) t exp t exp 2 A-B

61 A A.2 A.2.1 mkdflat infile outfile bpm (MDPDB ) offfile normilize imstat > lst HK500 CDFN2 Domeflat1. fits mdpdb$bpm/nlbpm1 FF64r. fits A.2.2 mktemplate pyraf mktemplate MCSMDP mktemplate.conf mktemplate > copy MCSMDP$doc/mktemplate. conf. >! vi mktemplate. conf > mktemplate mktemplate. conf > log.py mktemplate.conf bash = $ ## parameters coordlist= mdpdb\$ohlist/list NS HK500 mdpfile= CDFN MASK02.mdp prefix= HK500 # calibration data for chip1 bpm1= mdpdb\$bpm/nlbpm1 FF64r. fits

62 62 A MCSMDP flat1= HK500 CDFN2 Domeflat1. fits gdb1= mdpdb\$geomap/mcsdistcrr1 feb07new.dbs gmp1= mcsdistcrr1 feb07new.gmp # calibration data for chip2 bpm2= mdpdb\$bpm/nlbpm2 FF64r. fits flat2= HK500 CDFN2 Domeflat2. fits gdb2= mdpdb\$geomap/mcsdistcrr2 feb07new.dbs gmp2= mcsdistcrr2 feb07new.gmp coordlist mdpfile prefix 2 prefix + + MDP + ḟits bpm[12 ] flat[12 ] A.2.3 mktemplate.sh AB A (B ) B(A) list DET ID = 1 & K DITCNT = 1 > files1a. list list DET ID = 1 & K DITCNT = 2 > files1b. list list DET ID = 2 & K DITCNT = 1 > files2a. list list DET ID = 2 & K DITCNT = 2 > files2b. list mdpproc unlearn mdpproc iraf.mdpproc.bpmask= mdpdb$bpm/nlbpm1 FF64r. fits iraf.mdpproc.gdb= mdpdb$geomap/mcsdistcrr1 feb07new.dbs iraf.mdpproc.gmp= mcsdistcrr1 feb07new.gmp iraf.mdpproc. flat= HK500 CDFN2 Domeflat1. fits lst Multi Extention FITS (MEF) 0 ab 1 ( )

63 A A.2.4 mdptran MDP FITS > mdptran CDFN MASK02.mdp CDFN MASK02tr1.mdp gcflabcrmcsa fits 1 MDP 2 MDP 3 FITS maskplot ds9 FITS select shape then return or q to quit : return click the object position : ds9 HK Å q +return MDP ds9 type q to write mdp database to file : q +return MDP q MDP cutspec mdpproc > lst CDFN MASK02tr1.mdp name=ale A.2.5 mdpcombine mdptran ds9 4

64 64 A MCSMDP > unlearn mdpcombine > iraf.mdpcombine. coordlist= mdpdb$ohlist/list NS HK500 > iraf.mdpcombine.ymin=42 > iraf.mdpcombine.ymax=2003 > list CDFN MASK02tr1.mdp HK500 MODS MODS id mode=manual 1 id mode=manual OH mktemplate sed MDP mdpcombine!awk {print $8} CDFN MASK02tr1.mdp sed s/\(. \)/mdpcombine\ \@gcflab1\. list \ CDFN MASK02 tr1 \.mdp\ HK500 \1 \1/ mdpcombine > iraf.mdpcombine.id mode= auto > iraf.mdpcombine. refname= MODS > iraf.mdpcombine. bg inter=no > list CDFN MASK02tr1.mdp HK500 MODS MODS A.2.6 MOS mdpproc mdpcombine MDP ymin, ymax > unlearn mdpproc > iraf.mdpproc.bpmask= mdpdb$bpm/nlbpm2 FF64r. fits > iraf.mdpproc.gdb= mdpdb$geomap/mcsdistcrr2 feb07new.dbs > iraf.mdpproc.gmp= mcsdistcrr2 feb07new.gmp > iraf.mdpproc. flat= HK500 CDFN2 Domeflat2. fits > mdpproc MCSA fits MCSA fits > unlearn mdpcombine > iraf.mdpcombine. coordlist= mdpdb$ohlist/list NS HK500 > mdpcombine gcflabmcsa f i t s INDEF HK500 M53735 M53735 id mode=manual coordlist= mdpdb$ohlist/list NS HK500 calframe= INDEF ymin=900 ymax=1030

65 A idenfity id section line # background s apall 1 rescurve mdpfcalib 2 apall MEF imcopy MEF mdpfcalib > imcopy HK500 M fits [0] HK500 M fits > apall HK500 M fits > rescurve HK500 M ms. fits resc CDFN2 HK500. fits > mdpfcalib HK500 MODS fits resc CDFN2 HK500. fits HK500 MODS fl. fits A matplotlib mcsmdp ipython $ mcsmdp ipython mdp2dplot mdpextract 2 mdp2dplot 2 (center) (width) nsum mdpextract SPECFIT fittype Halpha ([NII]- Hα) OIII ([OIII]-Hβ) emission SPECFIT SPECFIT mdpextract mdp2dplot In [1]: mcsmdp In [2]: unlearn mdp2dplot In [3]: iraf.mdp2dplot. xlabel=r $\lambda {\rm obs} \left [\AA\right ]$ In [4]: iraf.mdp2dplot. ylabel= r $F \lambda\,[\times10ˆ{ 18}\,erg\,cmˆ{ 2}sˆ{ 1}\AAˆ{ 1}]$ In [5]: iraf.mdp2dplot. bottomplot=false

66 66 A MCSMDP In [6]: iraf.mdp2dplot. yscale=1e18 In [7]: iraf.mdp2dplot. linelist= mdpdb$linelist/nebulae tex. gaia In [8]: iraf.mdp2dplot. linewidth=1 In [9]: iraf.mdp2dplot. linealpha=1 In [10]: iraf.mdp2dplot. lstyle= k In [11]: iraf.mdp2dplot.ymin=0 In [12]: mdp2dplot HK500 MODS fl width=800 nsum=5 In [13]: mdpextract HK500 MODS fl HK500 MODS fl Halpha width=800 nsum=5 sub frac=0.5 sub fwhm=42 In [14]: mdp2dplot HK500 MODS fl Halpha plotfit+ ymin=0 width =800 In [15]: pylab. savefig ( HK500 MODS fl Halpha.png ) A.1

67 A MODS [ A: A][57:61] 2.0 rest frame wavelength [A] ] A [N II ] 6548 H [N II ] s erg cm [ F [ obs A ] A.1: mdp2dplot 1