Updated: 14 March 2014

Go directly to: Paper and Abstract | Results Summary | Data Products | Codes and Calls

Notice:

Reference: Cooksey et al. (2013, ApJ, 763, 37: online, PDF)

Abstract: We have vastly increased the C IV statistics at intermediate redshift by surveying the thousands of quasars in the Sloan Digital Sky Survey Data-Release 7. We visually verified over 16,000 C IV systems with 1.46 < z < 4.55—a sample size that renders Poisson error negligible. Detailed Monte Carlo simulations show we are approximately 50% complete down to rest equivalent widths W_r ≈ 0.6 Å. We analyzed the sample as a whole and in ten small redshift bins with approximately 1500 doublets each. The equivalent width frequency distributions ƒ(W_r) were well modeled by an exponential, with little evolution in shape. In contrast with previous studies that modeled the frequency distribution as a single power law, the fitted exponential gives a finite mass density for C IV ions. The co-moving line density dN_C IV/dX evolved smoothly with redshift, increasing by a factor of 2.37 ± 0.09 from z = 4.55 to 1.96, then plateauing at dN_C IV/dX ≈ 0.34 for z = 1.96 to 1.46. Comparing our SDSS sample with z < 1 (ultraviolet) and z > 5 (infrared) surveys, we see an approximately ten-fold increase in dN_C IV/dX over z ≈ 6 → 0, for W_r ≥ 0.6 Å. This suggests a monotonic and significant increase in the enrichment of gas outside galaxies over the 12 Gyr lifetime of the universe.

Note −  Summary of the most common redshift bins and data used for the various analyses. Columns 1−2 give the median, minimum, and maximum redshifts for the observed number of doublets (Column 3), and the maximum co-moving pathlength in the redshift bin is given in Column 4. The 50% completeness from the Monte Carlo tests is in Column 5. The redshift and co-moving absorber line densities for W_r ≥ 0.6 Å are in Columns 6−7. In Column 8, the Ω_{C IV} from summing the mass in the W_r ≥ 0.6 Å absorbers is a lower limit, since the majority of absorbers are saturated. The frequency distribution was fit with an exponential ƒ(W_r) = k exp(αW_r) for N_fit absorbers with W_r ≥ 0.6 Å (Column 9), and the best-fit parameters are given in Columns 10−11. The reduced χ² from the best fit and ƒ(W_r) (in bins with ≈100 doublets each) is given in Column 12.

Go directly to: Directory Structure | Setting-up Codes | Working with C IV Structure | Continuum Fitting, Identifying Candidates, Generating Completeness Curves

You will need to set the environment variables SDSSPATH and SDSSDR; for example, in bash:

TERM>export SDSSPATH="$HOME/Work/SDSS"

TERM>export SDSSDR="DR7_QSO"

The codes will expect the following directories under $SDSSPATH/$SDSSDR/:

• spectro/
• conti/
• abslin/
• mcciv/

The main data processing and analysis codes are IDL-based and in the XIDL package. The majority of the custom codes are in $XIDL_DIR/SDSS/CIV. Several general programs and functions are in SDSS_FUNCTIONS.PRO, and this needs to be compiled before any XIDL SDSS codes are run. This can be done automatically at startup by adding the following lines to your .idlstartup file:

!quiet = 1 ; suppress messages

.r sdss_functions

!quiet = 0

The list and description of programs and functions in SDSS_FUNCTIONS.PRO can be seen by calling sdss_functions at the IDL prompt:

IDL>sdss_functions

Below, basic calls that other researchers may find useful are described. Other program and function options can often be seen by making the program or function calls without parameters or with the /help option. Several calls can return values in redshift (as opposed to co-moving pathlength) space when /dz is included as an option.

The absorber structure is described in SDSSCIVSTRCT__DEFINE.PRO. Here are basic ways of manipulating the structure. First, SDSS_GETCIVSTRCT() (in SDSS_FUNCTIONS.PRO) can be used to grab various sub-samples. For example, to extract the doublets with redshifts 1.5 ≤ z < 2 and rest equivalent widths W_r ≥ 0.6 Å that are more than 5000 km s⁻¹ from the background QSO (i.e., δv_QSO < −5000 km s⁻¹) and not in visual BAL QSO sightlines, the call would be:

IDL>civstrct = sdss_getcivstrct('sdss_civ_cookseyetal13.fit', zlim=[1.5,2], ewlim=[0.6,!values.f_infinity], /noBAL, dvqso=-5000)

More options for SDSS_GETCIVSTRCT() can be found by using the /help option. The redshift, equivalent widths, and column densities (from the apparent optical depth method) are stored in the arrays tagged as ZABS_ORIG, EW_ORIG, and NCOLM_ORIG, with errors in the SIGZABS_ORIG, SIGEW_ORIG, and SIGNCOLM_ORIG arrays. The zeroth array element is for the C IV 1548 line and the first is for the 1550 line. The 1548 and 1550 column density measurements can be combined into a system column density estimate as follows:

IDL>ncolm = sdss_calncolmdblt(civstrct, 'CIV', signcolm=signcolm, /log, ncolmflg=ncolmflg)

The column density (limit) flags can be estimated by forcing all doublets with ratio W_r,1548/W_r,1550 < (2 − combined error) to be lower limits, assuming they are saturated.

A quick way to view a lot of information about the systems is to use the rating GUI SDSS_CHKCIV.PRO, which needs the directory structure defined above. The program can accept a structure or file name as an input and needs an output variable or file:

IDL>sdss_chkciv, civstrct, outstrct

If you have a completeness curve for 1.5 ≤ z < 2 and δv_QSO < −5000 km s⁻¹ called cmpltrec_CIV_1.5z2.0.fit (see below), you can view the completeness curve and errors, if the IDLUTILS package is installed (available e.g., here), with the following command:

IDL>cxw = sdss_getdxw('cmpltrec_CIV_1.5z2.0.fit', civstrct.zabs_orig[0], civstrct.ew_orig[0], sigewabs=civstrct.sigew_orig[0], sigma=sigcxw, /czw)

IDL>plot, civstrct.ew_orig[0], dxw, psym=4, xtitle='EW', ytitle='C(W)'

IDL>oploterror, civstrct.ew_orig[0], civstrct.sigew_orig[0], sigcxw[*,0], /lobar

IDL>oploterror, civstrct.ew_orig[0], civstrct.sigew_orig[0], sigcxw[*,1], /hibar

You can generate an equivalent width frequency distribution ƒ(W_r) as follows:

IDL>fw = sdss_calcfxw(civstrct, 'cmpltrec_CIV_1.5z2.0.fit', [1.5,2])

This returns a structure that can be plotted with the errors as follows:

IDL>plot, fw.ewcenter, fw.fxw, psym=4, xtitle='EW', ytitle='f(W)', /ylog

IDL>oploterror, fw.ewcenter, fw.fxw, fw.sigewcenter[*,0], fw.sigfxw[*,0], /lobar

IDL>oploterror, fw.ewcenter, fw.fxw, fw.sigewcenter[*,1], fw.sigfxw[*,1], /hibar

You can fit the 1.5 ≤ z < 2 frequency distribution with an exponential and overplot the results on the previous plot with the following calls:

IDL>sdss_fitfxw, 'cmpltrec_CIV_1.5z2.0.fit', intlim=[0.6, 3.5, 3.5], /exp, civstrct_fil=civstrct, ostrct_fil='fwfit_CIV_1.5z2.0.fit', psfil='fwfit_CIV_1.5z2.0.ps', /plot, sigma=1.

IDL>fwfit = sdss_calcfxwfit(fw.ewcenter, fitstrct='fwfit_CIV_1.5z2.0.fit')

IDL>oplot, fw.ewcenter, fwfit, thick=2, linestyle=2

You can generate and plot a structure with the absorber line density dN_C IV/dX for an equivalent width range, as a function of redshift, given a completeness curve with multiple redshift bins cmpltrec_CIV_1z6cum.fit.

IDL>dndx = sdss_calcdndx(civstrct_all, 'cmpltrec_CIV_1z6cum.fit', [0.6, !values.f_infinity]

IDL>plot, dndx.zcenter, dndx.dndx, psym=4, xtitle='z', ytitle='dN/dX'

IDL>oploterror, dndx.zcenter, dndx.dndx, dndx.sigzcenter[*,0], dndx.sigdndx[*,0], /lobar

IDL>oploterror, dndx.zcenter, dndx.dndx, dndx.sigzcenter[*,1], dndx.sigdndx[*,1], /hibar

The C IV mass density relative to the critical density, Ω_C IV, can be computed and plotted as a function of redshift in a similar way:

IDL>omciv = sdss_calcomega(civstrct_all, 'cmpltrec_CIV_1z6cum.fit', nlim=[10.^14, !values.f_infinity])

IDL>plot, omciv.zcenter, omciv.omega*1e8, psym=4, /ylog

IDL>oploterror, omciv.zcenter, omciv.omega*1e8, omciv.sigzcenter[*,0], omciv.sigomega[*,0]*1e8, /lobar

IDL>oploterror, omciv.zcenter, omciv.omega*1e8, omciv.sigzcenter[*,1], omciv.sigomega[*,1]*1e8, /hibar

Continuum Fitting:

There are three flavors of continuum fits: eigen, spline, and hybrid. The latter depends on the former, and the order of the following calls will lead to the hybrid-fit. The required file is a structure with the information for the QSOs to be fit, dr7qso_CIV.fit (formatted like the Schneider et al. (2010) catalog, see example above).

1. First fit the eigen-continua, which can be accomplished by running one line in IDL or using a shell script to divide up the task between multiple "processors" via multiple IDL sessions. (Make sure the shell script is executable.) The output will be written to the conti/ directory:

   XIDL>runeigqsoconti, sdsssum='dr7qso_CIV.fit'

   or

   TERM>$XIDL_DIR/SDSS/CIV/eig_runparallelfit.sh 4 dr7qso_CIV.fit

2. Search the eigen-normalized spectra of absorption features and create the SDSSCONTISTRCT__DEFINE.PRO structure in the abslin/ directory. This code will require a text file that lists the directory to write the output to on the first line, followed by the spectra names, in the same order as the QSO structure, e.g., dr7qso_CIV.list (see example above). This again can be accomplished by a single IDL call or by running a shell script:

   IDL>sdss_fndlin, 'dr7qso_CIV.list', 'dr7qso_CIV.fit', /noBAL, only_cflg=sdss_getcflg(/eig)

   or

   TERM>$XIDL_DIR/SDSS/CIV/sdss_runparallelsrch.sh 4 dr7qso_CIV.list dr7qso_CIV.fit "/noBAL, only_cflg=sdss_getcflg(/eig)"

3. The hybrid-fitting algorithm will use the lines found in the first eigen-normalized spectra to make a mask. Whether a given spectrum is corrected by a spline-fit to the eigen-normalized spectrum is determined by the S/N, and it is faster to just query the S/N structure, generated by SDSS_MKSNRTAB. This too can be done with one IDL call or via a shell script:

   IDL>sdss_dblfitconti, 'dr7qso_CIV.list', 'dr7qso_CIV.fit', snrstrct_fil='dr7qso_CIV_SNR.fit', dblt_name='CIV'

   or

   TERM>$XIDL_DIR/SDSS/CIV/hyb_runparallelfit.sh 4 dr7qso_CIV.list dr7qso_CIV.fit "snrstrct_fil='dr7qso_CIV_SNR.fit', dblt_name='CIV'"

4. [Optional] You can also use only a b-spline to fit the continua, via an IDL call or a shell script:

   IDL>sdss_fndlin_fitallspl, 'dr7qso_CIV.list', 'dr7qso_CIV.fit', pixlim=7

   or

   TERM>$XIDL_DIR/SDSS/CIV/spl_runparallelfit.sh 4 dr7qso_CIV.list dr7qso_CIV.fit "pixlim=7"

Identifying Candidates:

To generate a candidate structure, you first must search the normalized spectra for automatically detected lines and then pair these into candidate C IV doublets. You can generate candidates from any three of the continua stored in the abslin/ structure by changing the cflg. Focusing on the hybrid-normalized spectra:

1. To search the hybrid-normalized spectra and store the results in the abslin/ structures, use either of the following calls:

   IDL>sdss_fndlin, 'dr7qso_CIV.list', 'dr7qso_CIV.fit', /noBAL, only_cflg=sdss_getcflg(/hyb)

   or

   TERM>$XIDL_DIR/SDSS/CIV/sdss_runparallelsrch.sh 4 dr7qso_CIV.list dr7qso_CIV.fit "/noBAL, only_cflg=sdss_getcflg(/hyb)"

2. Now you can actually search for the candidates. Below, a secondary line search at the 2.5 σ level is called to find partners for un-matched, 3.5 σ lines:

   IDL>sdss_civsearch, 'dr7qso_CIV.list', 'dr7qso_CIV.fit', 'sdss_civcand_hyb.fit', lsnr2=2.5, cflg=sdss_getcflg(/hyb)

   or

   TERM>$XIDL_DIR/SDSS/CIV/sdss_runparallelsrch.sh 4 dr7qso_CIV.list dr7qso_CIV.fit sdss_civcand_hyb.fit "lsnr2=2.5, cflg=sdss_getcflg(/hyb)"

3. To rate your own candidates, you can use the GUI:

   IDL>sdss_chkciv, 'sdss_civcand_hyb.fit', 'sdss_civrate_hyb.fit'

Generating Completeness Curves:

There is a completeness file for each sightline tested. The information in these files need to be combined into the redshift bin or bins of interest, including any δv_QSO cut. This can be accomplished for an explicit redshift range as follows:

IDL>.r sdss_completeness

IDL>sdss_completeness_czw, 'dr7qso_CIV.list', 'dr7qso_CIV_SNR.fit', 'cmpltrec_CIV_1z6cum.fit', zmin=1.7, zbinsize=5, zlim=[1., 5.5], dvqso=-5000, /rec_param, civobs_corr=civstrct

The zmin= option sets the binning for averaging sightlines; since only a subset of sightlines have Monte Carlo tests, the un-tested sightlines are accounted for by the average of the tested sightlines in the same S/N and z_QSO bin. The zbinsize= is set to something large to make just one bin in the same file, for the full redshift range 1 < z < 5.5. The /rec_param option signals that the redshifts and equivalent widths used for combining the completeness curves are not the input, Voigt-profile values but the ones automatically measured from the simulated spectra. The civobs_corr=civstrct option (also works with /civobs_corr if sdss_getcivstrct() knows how to find the fiducial file) corrects the completeness or pathlength obscured by detected absorbers with greater equivalent width and folds in the error.

You can also combine the Monte Carlo files into little redshift bins either by forcing an approximate number per bin (first line below) or by explicitly setting the bins (second). You input the root of the output files that will be made.

IDL>sdss_completeness_cum, 1500, 'cmpltrec_CIV_', dvqso=-5000, /rec_param

IDL>zlim=fltarr(7,2) & zlim[*,0] = 0.5*lindgen(7)+1.5 & zlim[*,1] = zlim[*,0] + 0.5

IDL>sdss_completeness_cum, zlim, 'cmpltrec_CIV_', /z, dvqso=-5000, /rec_param

To actually run Monte Carlo tests yourself, you can use a single IDL call or the shell script:

IDL>sdss_completeness, 'dr7qso_CIV.list', 'dr7qso_CIV.fit', 1000, dblt_name='CIV', config_fil=getenv('XIDL_DIR')+'/SDSS/CIV/sdss_civprof.config', vpstrct_fil='vpstrct3200le500perEW.fit'

TERM>$XIDL_DIR/SDSS/CIV/sdss_runparallelcmplt.sh 4 dr7qso_CIV.list dr7qso_CIV.fit 1000 "dblt_name='CIV', config_fil=getenv('XIDL_DIR')+'/SDSS/CIV/sdss_civprof.config', vpstrct_fil='vpstrct3200le500perEW.fit'"

The use of the given simulated profile library (vpstrct3200le500perEW.fit) is optional. The code can call SDSS_GENPROF_MC() and use the sdss_civprof.config file to generate profiles on the fly, though this is slower.

igmabsorbers.info is funded by the National Science Foundation Astronomy & Astrophysics Postdoctoral Fellowship (AST-1003139).