Spectroscopy Reductions using IRAF

1 Data needed for spectroscopy

As for imaging, all the spectroscopy images have to be correctly processed, which meanswe apply bias, dark and flat corrections. The zero and the dark corrections remain thesame. However, before dividing the object frame by the super-flat (produced by dome flatscombined with flatcombine) we have to first correct the“super-flat” image by the responsefunction, included in noao.twodspec.longslit, to remove wavelength dependence of thelamp spectrum. Then, we can apply the flat correction with ccdproc.

A dome flat taken with an incondescent lamp shining on a screen is shown in Figure1 This image has been corrected for dark and bias, and has already been trimmed. This

Figure 1: Reduced Dome Flat image

means that overscan region is not in the image anymore. In order to use response functioncorrectly, you need to specify the region by image name[x0 : x1, y0 : y1]. To do this, you can

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find the appropriate coordinates using display in ds9. In our picture, we will use the regionbounded by the red lines. If you haven’t trimmed the overscan region, then region has beset so overscan is not included in it. The parameters we used are:

calibration = "t_Flat_dome[*,126:164]" Longslit calibration images

normalizatio = "t_Flat_dome[*,126:164]" Normalization spectrum images

response = "nFlat" Response function images

(interactive = yes) Fit normalization spectrum interactively?

(threshold = INDEF) Response threshold

(sample = "*") Sample of points to use in fit

(naverage = 1) Number of points in sample averaging

(function = "spline3") Fitting function

(order = 8) Order of fitting function

(low_reject = 3.) Low rejection in sigma of fit

(high_reject = 3.) High rejection in sigma of fit

(niterate = 1) Number of rejection iterations

(grow = 0.) Rejection growing radius

(graphics = "stdgraph") Graphics output device

(cursor = "") Graphics cursor input

(mode = "ql")

Note, that first two fields calibration, normalization are always the same and thethird is the name of final normalized image produced by this function. When we runresponse, it asks us if we want to fit the normalization spectrum interactively. After an-swering yes, a new window will pop up and we will be in interactive fitting mode. As in theusual IRAFterm window, we can list all possible commands by hitting ?. In this case, theonly parameters we want to change are either :function which can be followed by its type(chebyshev, spline, spline3, legendre) and :order, followed by number. For the latter, weused :order 8. After changing these parameters, you always have to hit key f that appliesre-fit of the function and redraws this new fit on the screen. Figures 2 and 3 show the fitwith the default parameters and then after interactive fitting, including a higher order fit.

After correcting the super-flat image by the response function, the final normalized super-flat is shown in Figure 4.

Now, you are ready to normalize your images with this super-flat. First, we start withmaking list of images that we want to process. This means that this list should containimages of spectra of objects and reference spectra, such as lamps. Note that you can notuse the same image as object and reference as well. If the object and reference spectra areon the same image, a copy needs to be made so IRAF can work with separate images.

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Figure 2: Response function fitting using de-faults. We can see that the fit is notvery good.

Figure 3: Response function fitting withhigher order fitting function :order

8. The fit is almost perfect.

Figure 4: Normalized Dome Flat image using response function.

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2 Aperture finding

Of course spectroscopy data are only present on a specific region of the ccd which images theslit in one direction and the dispersion on the perpendicular. The target object may not fillthe slit, so we define an aperture which is a subset of the spectroscopy data. This aperturecontains signal from our target as well as a small region of sky or background to each side.Our final output will be a one dimensional spectrum whose axes are counts versus column,after integrating vertically across the aperture.

This is done via task apall that can be found in package imred.kpnoslit. Before startingthis task, IRAF needs to know the direction of dispersion axis. IRAF reads this from theimage header so we must use hedit to modify the headers of spectral images that we wantto process. Add the field DISPAXIS with value 1 (1 stands for dispersion axis running alonglines and 2 along columns).

In this paper, we will extract apertures of a spectrum of the star SAO120648, shown inFigure 5, and then some reference spectra of the lamps. Then, we are going to do wavelengthcalibration using reference spectra. Finally, we will flux calibrate our images using spectraof standard stars.

Figure 5: Spectrum of SAO120648, trimmed image.

After loading packages imred and kpnoslit,we set the apall task to its defaults usingunlearn. Apall has these parameters:

input = "" List of input images

nfind = 1 Number of apertures to be found automatically

(output = " ") List of output spectra

(apertures = "") Apertures

(format = "multispec") Extracted spectra format

(references = "") List of aperture reference images

(profiles = "") List of aperture profile images\n

(interactive = yes) Run task interactively?

(find = yes) Find apertures?

(recenter = yes) Recenter apertures?

(resize = yes) Resize apertures?

(edit = yes) Edit apertures?

(trace = yes) Trace apertures?

(fittrace = yes) Fit the traced points interactively?

(extract = yes) Extract spectra?

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(extras = yes) Extract sky, sigma, etc.?

(review = yes) Review extractions?\n

(line = INDEF) Dispersion line

(nsum = 10) Number of dispersion lines to sum or median\n\n

(lower = -5.) Lower aperture limit relative to center

(upper = 5.) Upper aperture limit relative to center

(apidtable = "") Aperture ID table (optional)\n\n# DEFAULT BACKG

(b_function = "chebyshev") Background function

(b_order = 1) Background function order

(b_sample = "-10:-6,6:10") Background sample regions

(b_naverage = -3) Background average or median

(b_niterate = 0) Background rejection iterations

(b_low_reject = 3.) Background lower rejection sigma

(b_high_rejec = 3.) Background upper rejection sigma

(b_grow = 0.) Background rejection growing radius\n\n# APERTU

(width = 5.) Profile centering width

(radius = 10.) Profile centering radius

(threshold = 0.) Detection threshold for profile centering\n\n#

(minsep = 5.) Minimum separation between spectra

(maxsep = 1000.) Maximum separation between spectra

(order = "increasing") Order of apertures\n\n# RECENTERING PARAMETERS\n

(aprecenter = "") Apertures for recentering calculation

(npeaks = INDEF) Select brightest peaks

(shift = yes) Use average shift instead of recentering?\n\n#

(llimit = INDEF) Lower aperture limit relative to center

(ulimit = INDEF) Upper aperture limit relative to center

(ylevel = 0.1) Fraction of peak or intensity for automatic wid

(peak = yes) Is ylevel a fraction of the peak?

(bkg = yes) Subtract background in automatic width?

(r_grow = 0.) Grow limits by this factor

(avglimits = no) Average limits over all apertures?\n\n# TRACING

(t_nsum = 10) Number of dispersion lines to sum

(t_step = 10) Tracing step

(t_nlost = 3) Number of consecutive times profile is lost bef

(t_function = "legendre") Trace fitting function

(t_order = 2) Trace fitting function order

(t_sample = "*") Trace sample regions

(t_naverage = 1) Trace average or median

(t_niterate = 0) Trace rejection iterations

(t_low_reject = 3.) Trace lower rejection sigma

(t_high_rejec = 3.) Trace upper rejection sigma

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(t_grow = 0.) Trace rejection growing radius\n\n# EXTRACTION

(background = "none") Background to subtract

(skybox = 1) Box car smoothing length for sky

(weights = "none") Extraction weights (none|variance)

(pfit = "fit1d") Profile fitting type (fit1d|fit2d)

(clean = no) Detect and replace bad pixels?

(saturation = INDEF) Saturation level

(readnoise = "0.") Read out noise sigma (photons)

(gain = "1.") Photon gain (photons/data number)

(lsigma = 4.) Lower rejection threshold

(usigma = 4.) Upper rejection threshold

(nsubaps = 1) Number of subapertures per aperture

(mode = "ql")

You don’t need to worry about most these parameters, as you are going to modify theminteractively. The only parameter that can save you some work is ylevel which automati-cally defines the aperture width based on the ratio of peak intensity and this user-suppliedvalue. Depending on background level, a sensible value should be chosen. For our spectra,apertures are typically automatically defined too narrow so you want to modify ylevel tosmaller value within the order of 0.01 or similar. You will find a good value after someexperience with apall. You can always modify it interactively, but it is good to have thisvalue correct so you don’t to do many modifications during reduction. Don’t forget to setGAIN and READOUTNOISE correctly according to our ccd chip. For the AP7, gain is 5 andreadout noise is 15.

When running apall on our image, answer yes to find aperures (or y) and then it needs toknow how many apertures you want (normally one). Type yes to the remaining questions.The IRAFterm window pops up and we are in editing mode. You may list all possiblecommands with ?. In Figure 6

you can see the aperture found by IRAF, which is bounded by two white bars and tinybackground regions. If you want to change the size of this aperture, you may move themouse to the new left boundary and hit u, followed by hitting u on the new boundary onthe right. To delete it and start over, move your mouse near the existing aperture anddelete by typing d. Then, new aperture is found by hitting f and you may start over withresizing. To fit background, you hit b and you proceed to background fitting. For objects,background is usually well-determined and you can leave it as it is. However, the backgroundof reference spectrum usually needs some modifications. To change background regions,in the irafterm window type: :sample valueleft,min : valueleft,max, valueright,min : valueright,max

and then followed by hitting f to see changes on the screen. Once you are satisfied withbackground region, we exit with q and you are back in aperture finding window. As well,after aperture is set properly, continue by hitting q.

Answer yes to questions if you want to trace aperture interactively and if you want tofit traced positions. Now, you can a function to the aperture in IRAFterm. If you examine

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Figure 6: Spectra aperture extracting

Figure 7 in detail, you may see that y axis corresponds to lines and x axis to columns.This means that you are correcting for misalignments of camera and spectrograph. In otherwords: by that, we correct if the slit was not placed orthogonally according to the image.Thus, this fit has to be always linear

Sometimes, if the fit of the spectrum contains many error points, you may want modifyfitting by adding some extra points. We are showing example of spectra which went reallybad in Figures 9 and 10. The left side of these images contains a lot of error points thatnegatively influence the fit and fit gives us irrational values. Original image, where theregions of error points is labeled is shown in Figure 8

The areas where new points were added are indicated in Figure 10. To do this, you movemouse over the regions that are at the ends of the line and at each region, you add newfitting point by hitting a and then typing weight. Weight has to be very big in order toaffect fit, values in order of hundreds may work well, or you may add more points at theregion. To delete points hit d and nearest point to the cursors will be deleted. This anotherway how to fix tracing. To see how new points affected the fit, hit f and re-fit will be doneand replotted on the screen.

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Figure 7: Aperture fitting window

Figure 8: The region that negatively influenced fit for tracing the aperture

When the fit is OK, you may exit with q. You will be asked if you want to write apertureto the database and your answer should yes. Next question is if want to extract aperturespectra for this image, answering yes pops up last question if you want to review extractedspectra. Type yes and you can see extracted absorption spectra which is not calibrated yes.Spectra extracted from the image shown in Figure 5 is shown in the Figure 11. This is nota final spectra because it is not wavelength calibrated yet.

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Figure 9: Tracing of aperture of spectra with many error points on the left side wherespectrum is very weak

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Figure 10: To correct for error points that negatively influence the fit, we need to add someextra points with very high weight

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Figure 11: Extracted uncalibrated spectra

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2.1 Aperture finding for lamp spectra

First, we need to reduce our reference spectra (given by our Hg and Ne lamps) in thesame way as we did object spectra. A reference image is shown in Figure 12. The strong

Figure 12: Reference spectra image; lamp spectra are marked

spectraum in the middle of the image is the absorption spectrum of Saturn, but in thiscase, we are going to extract lamp spectra of dispersion lines either above or below Saturn’sspectrum. We can use IRAF to define image regions to extract lamp spectra even if thereis a strong object spectrum in the image. In this particular case, we found that the upperlamp spectra is roughly between lines(rows) 190 - 240 so we specified apall input images as:image name[*,190:240]. Doing the same procedure as with object spectra, up to the pointof resizing the default apertures. In Figure 13, the results IRAF found can not be used atall, and we need to modify them interactively. Using u, we change the aperture width andusing b, we jump to background fitting mode. There, by using the :sample command, wemodify the background region, with results shown in Figure 14.

Next, we need to trace the appertue: fitting the function that describes rotation (mis-alignment) of the dispersion axis. As previously mentioned, this fit should always be linear.In Figure 15, we show the fit of this trace. In this Figure, notice that it is not necessaryto fit all the points. It is more important to fit the trend or slope of the aperture. In thisexample, we see that the center of the aperture is rising from line 11, at column 0, to line17, at column 500. This gives a slope of 1.6%. The result can be seen in Figure 16, showingthe spectrum of the Neon lamp.

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Figure 13: Extracting aperture of lamp spectra, automatic results need to be manuallymodified

Figure 14: Extracting aperture of lamp spectra, final fit after corrections

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Figure 15: Tracing aperture of lamp spectra

Figure 16: Review of extracted spectra of the reference Neon lamp

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3 Wavelength calibration

Wavelength calibration provides a transformation bewteen coordinate along the dispersionaxis in units of pixels to wavelength values in units of Angstroms or nm. For our spectra, thedispersion axis is horizontal, so wavelength calibration means transforming column numberto wavelength. For wavelength calibration, we begin with reference or lamp spectra and weassign correct wavelength values to two or more peaks (assuming emmision line spectra).Naively, there would be a linear relationship, but in practice, a higher order fit is usuallyneeded. Many lines are not needed because IRAF has line lists and only needs a head start.

3.1 Identify spectral lines

Function which is used to assign wavelength values to peaks in object spectra is calledidentify and we can find it in package noao.onedspec. When the aperture of the spectrais found and traced, these information are stored in the image with extension .ms anddatabase folder. We used CCD Image 33.fit so we will run identify CCD Image 33.ms.Running identify pops up the same window as in Figure 16 and we are able to assignwavelength values to lamp spectral lines. Note that we need to provide IRAF a list ofspectral lines in the field coordlist of parameters of identify. You can find it in directorywith scripts. Move the mouse cursor near to spectral line and hit m, identify asks you forwavelength, type its value and hit enter. You can do that for some other lines and then typef to fit the wavelength calibration function. If there are some points that do not agree withfit you may remove them (hitting d deletes the nearest line to the cursor) or reconsider ifidentification of lines was correct and if not, modify it. When satisfied, you exit with q andinformation about spectra is written to database. Parameters used are shown here:

images = "" Images containing features to be i

crval = Approximate coordinate (at reference pixel)

cdelt = Approximate dispersion

(section = "middle line") Section to apply to two dimensional images

(database = "database") Database in which to record feature data

(coordlist = "/home/..../HgNe.dat") User coordinate list

(units = "") Coordinate units

(nsum = "10") Number of lines/columns/bands to sum in 2D imag

(match = 10.) Coordinate list matching limit

(maxfeatures = 50) Maximum number of features for automatic identi

(zwidth = 100.) Zoom graph width in user units

(ftype = "emission") Feature type

(fwidth = 7.5) Feature width in pixels

(cradius = 5.) Centering radius in pixels

(threshold = 10.) Feature threshold for centering

(minsep = 2.) Minimum pixel separation

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(function = "spline3") Coordinate function

(order = 1) Order of coordinate function

(sample = "*") Coordinate sample regions

(niterate = 1) Rejection iterations

(low_reject = 3.) Lower rejection sigma

(high_reject = 3.) Upper rejection sigma

(grow = 0.) Rejection growing radius

(autowrite = no) Automatically write to database

(graphics = "stdgraph") Graphics output device

(cursor = "") Graphics cursor input

(aidpars = "") Automatic identification algorithm parameters

(mode = "ql")

3.2 Assign dispersion solution to objects

After finding dispersion solution for the lamps spectra, we need to apply it to object images.The link is provdided by keyword REFSPEC1=comparison image name in the header of objectimages. What you need to do is to prepare a list of images containing object spectra (with.ms extension)and then modify their header by hedit, adding name of the image containingcomparison spectrum(with .ms extension as well!).

3.3 Apply dispersion solution to objects

Once the object images have link to reference spectra, we can apply a dispersion solutionto them and finally calibrate them for wavelength. The only thing you need to do is to runtask dispcor on .ms images of objects. You can view your solution by using splot task.Our solution is shown in Figure 17.

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Figure 17: Wavelength calibrated spectra

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4 Flux calibration

We are going to flux calibrate our images using spectrum of Standard stars. We assumethat object spectra (including standard stars) are already wavelength calibrated. We loadpackage imred and then we edit task kpnoslit with epar. We need to tell it folder ofstandard stars data. As a calibration here, we use star Alkaid, with identification numberHR5191 or SAO120648. In the Appendix A, you can find lists of standard stars and theirfolders. Our values of kpnoslit are shown here;

(extinction = "onedstds$kpnoextinct.dat") Extinction file

(caldir = "onedstds$bstdscal/") Standard star calibration directory

(observatory = "observatory") Observatory of data

(interp = "poly5") Interpolation type

(dispaxis = 2) Image axis for 2D/3D images

(nsum = "1") Number of lines/columns/bands to sum for 2D/3D

(database = "database") Database

(verbose = no) Verbose output?

(logfile = "logfile") Log file

(plotfile = "") Plot file\n

(records = "") Record number extensions

(version = "KPNOSLIT V3: January 1992")

(mode = "ql")

($nargs = 0)

After we have names of standard stars, that IRAF has in its database, we run task standar

for each of these stars, provide catalogue name and answering no to question of we want toedit bandpasses.

After running standard task, we need to run sensfunc to fit function describing the flux.Paramteres are listed here:

standards = "std" Input standard star data file (from STANDARD)

sensitivity = "sens" Output root sensitivity function imagename

answer = "yes" (no|yes|NO|YES)

(apertures = "") Aperture selection list

(ignoreaps = yes) Ignore apertures and make one sensitivity funct

(logfile = "logfile") Output log for statistics information

(extinction = )_.extinction) Extinction file

(newextinctio = "extinct.dat") Output revised extinction file

(observatory = )_.observatory) Observatory of data

(function = "spline3") Fitting function

(order = 6) Order of fit

(interactive = yes) Determine sensitivity function interactively?

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(graphs = "sr") Graphs per frame

(marks = "plus cross box") Data mark types (marks deleted added)

(colors = "2 1 3 4") Colors (lines marks deleted added)

(cursor = "") Graphics cursor input

(device = "stdgraph") Graphics output device

(mode = "ql")

Running this task pops up fitting window, shown in Figure 18.

Figure 18: Sensitivity function fitting

We do a fit as usual until we are satisifed with our results. List of all possible commandsis given by hitting ?. Once the fit is done, you exit hitting q and we are ready to maka afinal step: run fucntion calibrate. All you need is to prepare a list of images (dispersioncorrected) and then using epar calibrate tell it to process this list, possibly adding someextension to the output images.

input = "@filelist" Input spectra to calibrate

output = "flux_corr//@filelist" Output calibrated spectra

airmass = Airmass

exptime = Exposure time (seconds)

(extinct = yes) Apply extinction correction?

(flux = yes) Apply flux calibration?

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(extinction = )_.extinction) Extinction file

(observatory = )_.observatory) Observatory of observation

(ignoreaps = yes) Ignore aperture numbers in flux calibration?

(sensitivity = "sens") Image root name for sensitivity spectra

(fnu = no) Create spectra having units of FNU?

(mode = "ql")

Now, you have your spectra wavelength and flux calibrated.

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5 Appendix A

5.1 Standard stars

EXTINCTION TABLES

(eg extinction = onedstds$kpnoextinct.dat)

ctioextinct.dat - CTIO extinction table for ONEDSPEC (in Angstroms)

The CTIO extinction curve distributed with IRAF comes from the work of

Stone & Baldwin (1983 MN 204, 347) and Baldwin & Stone (1984 MN 206,

241). The first of these papers lists the points from 3200-8370A while

the second extended the flux calibration from 6056 to 10870A but the

derived extinction curve was not given in the paper. The IRAF table

follows SB83 out to 6436, the redder points presumably come from BS84

with averages used in the overlap region.

More recent CTIO extinction curves are shown as Figures in Hamuy

et al (92, PASP 104, 533 ; 94 PASP 106, 566).

Steve Heathcote, Mon, 19 Jul 1999

kpnoextinct.dat - KPNO extinction table for ONEDSPEC (in Angstroms)

MISCELLANEOUS

ctio - Directory containing CTIO decker comb positions and

neutral density filter curves (used with NDPREP).

FLUX STANDARD DIRECTORIES

(eg caldir = onedstds$iidscal/)

blackbody - Directory for using blackbody flux distributions in

various magnitude bands.

bstdscal - Directory of the brighter KPNO IRS standards (i.e. those

with HR numbers) at 29 bandpasses, data from various

sources transformed to the Hayes and Latham system,

unpublished.

ctiocal - Directory containing fluxes for the southern tertiary

standards as published by Baldwin & Stone, 1984, MNRAS,

206, 241 and Stone and Baldwin, 1983, MNRAS, 204, 347.

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ctionewcal - Directory containing fluxes at 50A steps in the blue range

3300-7550A for the tertiary standards of Baldwin and

Stone derived from the revised calibration of Hamuy et

al., 1992, PASP, 104, 533. This directory also contains

the fluxes of the tertiaries in the red (6050-10000A) at

50A steps as will be published in PASP (Hamuy et al

1994). The combined fluxes are obtained by gray

shifting the blue fluxes to match the red fluxes in the

overlap region of 6500A-7500A and averaging the red and

blue fluxes in the overlap. The separate red and blue

fluxes may be selected by following the star name with

"red" or "blue"; i.e. CD 32 blue.

iidscal - Directory of the KPNO IIDS standards at 29 bandpasses,

data from various sources transformed to the Hayes and

Latham system, unpublished.

irscal - Directory of the KPNO IRS standards at 78 bandpasses,

data from various sources transformed to the Hayes and

Latham system, unpublished (note that in this directory the

brighter standards have no values - the ‘bstdscal’ directory

must be used for these standards at this time).

oke1990 - Directory of spectrophotometric standards observed for use

with the HST, Table VII, Oke 1990, AJ, 99. 1621 (no

correction was applied). An arbitrary 1A bandpass

is specified for these smoothed and interpolated

flux "points". Users may copy and modify these files

for other bandpasses.

redcal - Directory of standard stars with flux data beyond 8370A.

These stars are from the IRS or the IIDS directory but

have data extending as far out into the red as the

literature permits. Data from various sources.

spechayescal - The KPNO spectrophotometric standards at the Hayes flux

points, Table IV, Spectrophotometric Standards, Massey

et al., 1988, ApJ 328, p. 315.

spec16cal - Directory containing fluxes at 16A steps in the blue

range 3300-7550A for the secondary standards, published

in Hamuy et al., 1992, PASP, 104, 533. This directory

also contains the fluxes of the secondaries in the red

(6020-10300A) at 16A steps as will be published in PASP

(Hamuy et al 1994). The combined fluxes are obtained by

gray shifting the blue fluxes to match the red fluxes in

the overlap region of 6500A-7500A and averaging the blue

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and red fluxes in the overlap. The separate red and

blue fluxes may be selected by following the star name

with "red" or "blue"; i.e. HR 1544 blue.

spec50cal - The KPNO spectrophotometric standards at 50 A intervals.

The data are from (1) Table V, Spectrophotometric Standards,

Massey et al., 1988, ApJ 328, p. 315 and (2) Table 3, The

Kitt Peak Spectrophotometric Standards: Extension to 1

micron, Massey and Gronwall, 1990, ApJ 358, p. 344.

STANDARD STAR MENUS

--------------------------------------------------------------------------------

Blackbody calibrations in onedstds$blackbody/

U B V R I J H K L Lprime M

Magnitude conversions are available between V, J, H, K, L, Lprime, and M

but for U, B, R, and I the star magnitudes must be in the same bandpass.

--------------------------------------------------------------------------------

Standard stars in onedstds$bstdscal/

hr718 hr3454 hr3982 hr4468 hr4534

hr5191 hr5511 hr7001 hr7596 hr7950

hr8634 hr9087 hd15318 hd74280 hd100889

hd188350 hd198001 hd214923 hd224926

--------------------------------------------------------------------------------

Standard stars in onedstds$ctiocal/

bd25 eg139 feige56 l2415 l93080

bd73632 eg149 feige98 l2511 l97030

bd8 eg158 g16350 l3218 lds235

cd32 eg248 g2631 l3864 lds749

eg11 eg274 g9937 l4364 ltt4099

eg21 f15 h600 l4816 ltt8702

eg26 f25 hz2 l6248 ross627

eg31 f56 hz4 l7379 w1346

eg54 f98 hz15 l7987 w485a

eg63 f110 kopf27 l8702 wolf1346

eg76 feige110 l377 l9239 wolf485a

23

eg79 feige15 l1020 l9491

eg99 feige25 l1788 l74546

--------------------------------------------------------------------------------

Standard stars in onedstds$ctionewcal/:

Combined red and blue 3300A-10000A:

cd32 f56 l2415 l4364 l7987

eg21 h600 l3218 l4816 l9239

eg274 l1020 l377 l6248 l9491

f110 l1788 l3864 l7379 l745

Blue 3300A-7550A:

cd32blue f56blue l2415blue l4364blue l7987blue

eg21blue h600blue l3218blue l4816blue l9239blue

eg274blue l1020blue l377blue l6248blue l9491blue

f110blue l1788blue l3864blue l7379blue

Red 6050A-10000A:

cd32red f56red l2415red l4364red l7987red

eg21red h600red l3218red l4816red l9239red

eg274red l1020red l377red l6248red l9491red

f110red l1788red l3864red l7379red l745red

--------------------------------------------------------------------------------

Standard stars in onedstds$iidscal/

40erib eg50 eg149 g16350 hz4 lds235b

amcvn eg54 eg158 g191b2b hz7 lds749b

bd253941 eg63 eg162 g2610 hz14 lft1655

bd284211 eg67 eg182 g2631 hz15 lp414101

bd332642 eg71 eg184 g4718 hz29 ltt13002

bd404032 eg76 eg193 g88 hz43 ltt16294

bd73632 eg77 eg247 g9937 hz44 ltt4099

bd7781 eg79 eg248 gd128 kopff27 ltt8702

bd82015 eg91 feige15 gd140 l13633 ross627

eg11 eg98 feige24 gd190 l140349 ross640

eg20 eg99 feige25 gh7112 l14094 sa29130

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eg26 eg102 feige34 grw705824 l151234b sao131065

eg28 eg119 feige56 grw708247 l74546a ton573

eg29 eg129 feige92 grw738031 l8702 wolf1346

eg31 eg139 feige98 he3 l93080 wolf485a

eg33 eg144 feige110 hiltner102 l97030

eg39 eg145 g12627 hiltner600 lb1240

eg42 eg148 g14563 hz2 lb227

--------------------------------------------------------------------------------

Standard stars in onedstds$irscal/

bd082015 eg50 feige34 hd117880 hd60778 hr7001

bd174708 eg71 feige56 hd161817 hd74721 hz44

bd253941 eg139 feige92 hd17520 hd84937 kopff27

bd262606 eg158 feige98 hd192281 hd86986 wolf1346

bd284211 eg247 feige110 hd19445 he3

bd332642 feige15 g191b2b hd217086 hiltner102

bd404032 feige25 hd109995 hd2857 hiltner600

--------------------------------------------------------------------------------

Standard stars in onedstds$oke1990/

bd284211 feige110 feige67 g191b2b g249 gd248 ltt9491 eg71

bd75325 feige34 g13831 g19374 gd108 hz21 eg158 eg247

--------------------------------------------------------------------------------

Standard stars in onedstds$redcal/

40erib eg63 eg139 eg248 gd140 hz44 ltt16294

amcvn eg67 eg144 feige24 gd190 l13633 ltt4099

bd7781 eg76 eg145 g12627 grw705824 l14094 ltt8702

bd73632 eg79 eg148 g14563 grw708247 l151234b ross627

bd174708 eg91 eg149 g16350 grw738031 l74546a ross640

bd262606 eg98 eg162 g191b2b hd19445 l93080 sa29130

eg20 eg99 eg182 g2610 hd84937 l97030 sao131065

eg33 eg102 eg184 g2631 he3 lds235b wolf1346

eg50 eg119 eg193 g4718 hz29 lds749b wolf485a

eg54 eg129 eg247 g9937 hz43 lft1655

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Standard stars in onedstds$spec16cal/:

25

Combined red and blue 3300A-10300A:

hd15318 hd74280 hd114330 hd188350 hd214923

hd30739 hd100889 hd129956 hd198001 hd224926

hr1544 hr4468 hr5501 hr7596 hr8634

hr3454 hr4963 hr718 hr7950 hr9087

Blue 3300A-7550A:

hd15318blue hd74280blue hd114330blue hd188350blue hd214923blue

hd30739blue hd100889blue hd129956blue hd198001blue hd224926blue

hr1544blue hr4468blue hr5501blue hr7596blue hr8634blue

hr3454blue hr4963blue hr718blue hr7950blue hr9087blue

Red 6020A-10300A:

hd15318red hd74280red hd114330red hd188350red hd214923red

hd30739red hd100889red hd129956red hd198001red hd224926red

hr1544red hr4468red hr5501red hr7596red hr8634red

hr3454red hr4963red hr718red hr7950red hr9087red

--------------------------------------------------------------------------------

Standard stars in onedstds$spec50cal/ (3200A - 8100 A)

bd284211 eg247 feige34 hd192281 pg0205134 pg0934554 wolf1346

cygob2no9 eg42 feige66 hd217086 pg0216032 pg0939262

eg139 eg71 feige67 hilt600 pg0310149 pg1121145

eg158 eg81 g191b2b hz14 pg0823546 pg1545035

eg20 feige110 gd140 hz44 pg0846249 pg1708602

Standard stars in onedstds$spec50cal/ (3200A - 10200A)

bd284211 eg247 feige34 g191b2b hz44

eg139 eg71 feige66 gd140 pg0823546

eg158 feige110 feige67 hilt600 wolf1346

--------------------------------------------------------------------------------

Standard stars in onedstds$spechayescal/

bd284211 eg139 feige67 hd217086 pg0216032 pg0939262

26

cygob2no9 eg158 feige110 hiltner600 pg0310149 pg1121145

eg42 eg247 g191b2b hz14 pg0823546 pg1545035

eg71 feige34 gd140 hz44 pg0846249 pg1708602

eg81 feige66 hd192281 pg0205134 pg0934554 wolf1346

27