Metallicity Evolution of Damped Lyman-alpha Systems out to z~ 5

24 Pages·2012·3.94 MB·English

ACCEPTEDBYAPJMAY21,2012
PreprinttypesetusingLATEXstyleemulateapjv.5/2/11
METALLICITYEVOLUTIONOFDAMPEDLy-αSYSTEMSOUTTOz∼5
MARCRAFELSKI1,ARTHURM.WOLFE2,J.XAVIERPROCHASKA3,MARCELNEELEMAN2,ALEXANDERJ.MENDEZ2
AcceptedbyApJMay21,2012
ABSTRACT
Wepresentchemicalabundancemeasurementsfor47dampedLy-αsystems(DLAs),30atz>4,observed
2
withtheEchelletteSpectrographandImagerandtheHighResolutionEchelleSpectrometerontheKecktele-
1
scopes. HI column densities of the DLAs are measured with Voigt profile fits to the Ly-α profiles, and we
0
find an increased number of false DLA identifications with SDSS at z>4 due to the increased density of
2
theLyman-αforest. Ioniccolumndensitiesaredeterminedusingthe apparentopticaldepthmethod,andwe
y combineournewmetallicitymeasurementswith195fromprevioussurveystodeterminetheevolutionofthe
a
cosmicmetallicityofneutralgas. WefindthemetallicityofDLAsdecreaseswithincreasingredshift,improv-
M ingthesignificanceofthetrendandextendingitto higherredshifts, witha linearfitof- 0.22±0.03dexper
unitredshiftfromz=0.09- 5.06. Themetallicity“floor”of≈1/600solarcontinuesouttoz∼5,despiteour
2 sensitivity for finding DLAs with much lower metallicities. However, this floor is not statistically different
2
fromasteeptailtothedistribution. WealsofindthattheintrinsicscatterofmetallicityamongDLAsof∼0.5

dex continues out to z∼5. In addition, the metallicity distribution and the α/Fe ratios of z>2 DLAs are
]
O consistentwithbeingdrawnfromthesameparentpopulationwiththoseofhalostars. Itisthereforepossible
thatthehalostarsintheMilkyWayformedoutofgasthatcommonlyexhibitsDLAabsorptionatz>2.
C
Subject headings: galaxies: abundances — galaxies: ISM — galaxies: evolution — galaxies: general —
.
h Galaxy:halo—quasars:absorptionlines
p
-
o 1. INTRODUCTION abundance of [M/H]=- 1.4 (Pettini 2006), the damped Ly-α
r absorption systems (DLAs; see Wolfeetal. 2005, for a re-
t The recent detection of star-forming galaxies out to z∼8
s view)aregalactic-scaleobjectsthatliebetweenthesetwoex-
(Bouwensetal.2010;Bunkeretal.2010)providesnewinfor-
a tremes. Thepurposeofthispaperistopresenttheresultsof
[ mationaboutthecrucialformativestagesofgalaxyevolution.
One ofthe importantgoalsofthese studiesis to identifythe anewsurveyforthemetalabundancesofDLAsouttoz≈5.

1 high-redshiftprogenitorsofcurrentgalaxiesand theirstellar We focuson DLAs for severalreasons. First, since theyare
v detected in absorption, DLAs are unbiassed with respect to
populations. A valuable diagnostic tool that links the prop-
7 luminosity and presumably mass. Second, in contrast to all
erties of high-redshift galaxies to their descendants is their
4 otherclasses of quasar absorptionsystems, the gasin DLAs
chemical properties (Pettini 2006). While chemical proper-
0 is mainly neutral. In fact, DLAs dominate the neutral-gas
tiesareexceedinglydifficulttoextractfromthefaintstarlight
5 contentof the Universeout to z≈5, (Prochaskaetal. 2005;
emitted by star-forming galaxies at high redshift, they are
. O’Mearaetal. 2007), and exhibit properties indicating that
5 moreeasilydeterminedfromprotogalacticgasdetectedinab-
0 sorptionagainstbrightbackgroundquasars(e.g.Pettini2006; theyareneutral-gasreservoirsforstarformationathighred-
2 Prochaskaetal.2003a). Ifthemetallicityofsuchgaswereto shift(Nagamineetal. 2004a,b; Wolfe&Chen 2006). More-
1 resemblethemetallicityof,say,globularclusters,thenarea- over,thelargeopticaldepthattheLymanlimitoftheneutral
v: sonablefirstguessisthatstarsinglobularclustersformoutof gasinDLAs(typicallyτLL≈104)eliminatestheneedforun-
i thisgas. Theevolutionofthemetallicityandotherproperties certainionizationcorrectionstodeducethemetalabundances.
X ofthisgascouldthenprovideinformationaboutthesequence Accordingly, the most accurately determined abundances at
highredshiftareforDLAs(Wolfeetal.2005).Third,because
r ofeventsleadingtotheformationofcurrentgalaxies.
a The high-redshift Universe is occupied by populations of DLAgaslikelyoriginatesintheouterregionsofhigh-zgalax-
ies(e.g.Rafelskietal.2011),chemicalanddynamicalinfor-
objects spanning a wide range of metallicities. While the
mean metal abundances of dense, compact objects such as mationwouldbepreservedduetothelongtime-scalesfordis-
quasars is given by [M/H]4 ≈ 0 (Hamann&Ferland 1999), sipationanddynamicalmixing(Freeman&Bland-Hawthorn
diffuse large-scale configurations such as the Ly-α forest 2002).
clouds have [M/H]=- 3 (Aguirreetal. 2004). In fact, ob- Our primary goal is to measure the cosmic metallicity,
servers have now even identified gas without any trace of hZi ≡ log10(Ωmetals/Ωgas) - log10(M/H)⊙ (Lanzettaetal.
heavyelements(Fumagallietal.2011a). Withameanmetal 1995), at redshifts z>4. Previously we determined hZi by
measuring the column-density weighted mean metal abun-
dances (see Prochaskaetal. 2003b) in redshiftbins contain-
1Infrared Processing and Analysis Center, Caltech, Pasadena, CA ingequalnumbersofDLAs. Thedatarevealedastatistically
91125,USA
2Department of Physics and Center for Astrophysics and Space Sci- significant decline in hZi with increasing redshift, given by
ences,UCSD,LaJolla,CA92093,USA hZi=(- 0.26±0.07)z- (0.59±0.18),which was confirmedat
3Department of Astronomy & Astrophysics, UCO/Lick Observatory, z < 4 by independent measurements (Kulkarnietal. 2005,
1156HighStreet,UniversityofCalifornia,SantaCruz,CA95064 2007, 2010). While the evolution of hZi appears linear in
4 We adopt the standard notation in which the metal abundance [M/H]
redshift, it is non-linearin time, with the slope, dhZi/dt, be-
signifies the logarithmic abundance of element M relative to solar; i.e.,
[M/H]≡log10(M/H)- log10(M/H)⊙. comingsignificantlysteeperatearliercosmictimes.Sincethe
2 Rafelski,Wolfe,Prochaska,Neeleman,Mendez
Prochaskaetal.(2003b)samplecontainedonly10DLAswith parerecentsimulationstoourdataanddiscussthemetallicity
z>4,hZi,anditsderivativeswerepoorlydeterminedatsuch evolutionin§4.1,andconsidertheimplicationsofthemetal-
high redshifts. Therefore, we aim to determinewhether this licities and α-enhancementof DLAs for halo star formation
trendcontinuesback to z ≈ 5. Prochaskaetal. (2003b) also in§4.2. In§5wesummarizetheresults.
reported(1)a “metallicityfloor” at[M/H]=- 3.0,becauseno Throughout this paper we adopt a cosmology with
metal abundances were found below this value despite their (ΩM,ΩΛ,h)=(0.3,0.7.0.7).
sensitivity to [M/H] values well below - 4.0, and (2) a large
dispersion of [M/H] at all redshifts. We wish to investigate
2. OBSERVATIONSANDDATAREDUCTION
whether these phenomena persist at higher redshifts, as at
somepointintimethegasshouldbepristine(Fumagallietal. The primary scientific goals of our survey are to: (i) per-
2011a). Althoughincreasingtheredshiftrangeofoursurvey form an unbiased evaluation of the metallicity in neutral
toz≈5correspondstoanincreaseinsurveytimeintervalof atomic-dominatedhydrogengasatz>4;(ii)confirmandre-
only≈0.5Gyr,weshallshowthatthisisacriticaltimeinter- finepreviousestimatesontheincidenceandHImassdensity
val in which, as stated above, dhZi/dt becomes increasingly in z>4 DLAs; and (iii) identify new targets for follow-up
steepwithdecreasingt. ALMAobservationsintheCII*158microntransition.These
In addition, we wish to assess if there is a systematic bias goalswerewellsuitedtothespectroscopiccharacteristicsof
intheSloanDigitalSkySurvey(SDSS)N statisticsatz>4 the Echellette Spectrograph and Imager (ESI; Sheinisetal.
HI
(Prochaska&Wolfe 2009; Noterdaemeetal. 2009), such as 2002),withthepossibilityoffollowupobservationswiththe
thecolumndensitydistributionfunction,totalcoveringfrac- High Resolution Echelle Spectrometer (HIRES; Vogtetal.
tion,andcosmologicalN massdensity. Thesestatisticsare 1994)ontheKeckIandII10mtelescopes. Wethereforere-
HI
determined solely from the discovery spectra of the SDSS quiredasetofz>4DLAsthatcouldbeobservedfromKeck
database,withlowresolutionofFWHM∼2Åandsometimes observatory.
atlowsignal-to-noise(S/N)(withacutatS/N>4).Theanal- ThefirstsampleoftargetsweredrawnfromtheSDSS-DR3
ysis of the damped Ly-α profile is significantly affected by andSDSS-DR5surveysfordampedLy-αsystemsperformed
line-blendingwiththeLy-αforest‘clouds’,andtheincrease byProchaskaetal.(2005)andProchaska&Wolfe(2009)re-
of the density of the Ly-α forest at high redshift may lead spectively. We restricted the list to sources that were suffi-
toanoverestimateoftheN measurementsandanincreased cientlybrightsuchthatwecouldobtainS/N>15spectraina
HI
falsepositiveidentificationrateforDLAs. Whilesuchbiases non-prohibitiveobservingtime. Afterthefirstfewnights,we
arelikelytobesmallat2.z.4(Prochaskaetal.2005),our neededtosupplementthesamplewithadditionalz>4DLAs,
newmeasurementsresolveouttheLy-αforestandenablethe and we searched for new z > 4 quasars from SDSS-DR7.
constraintofsuchabiasatz>4. TheseadditionaltargetswillnotbeincludedintheHIanaly-
Another goal is to compare the metallicity distribution of sisastheywereselectedinamoreheterogeneousmannerthan
DLAs with those of known stellar populations. Previous theoriginalset. Theyareunbiased,however,withrespectto
studies (Pettinietal. 1997; Pettini 2004, 2006) have shown the gas metallicity because they were selected solely on the
that the distribution of metallicities at z > 2 disagree with presence of strong HI Ly- α absorption. In addition to this
known stellar populations in the Galaxy. However, if high primaryhigh redshift quasar sample obtained in 2009-2011,
redshift galaxies are surrounded by a thick disk of neu- we also include new observations of lower redshift quasars
tralgas(Prochaska&Wolfe 1997b;Wolfeetal. 2003, 2008; (2.5.z.3.5) obtained in 2008 to augment the number of
Rafelskietal.2009,2011;Fumagallietal.2011b),thenstars unbiasedmetallicitymeasurements(seebelow). Wenotethat
that formed in situ in such gas at high redshift should be the effectiveupper limit to the redshiftsof our DLA sample
presentin z=0 galaxies, such as the Milk Way. These stars isabout5.3;DLAswithhigherredshiftsareessentiallyunde-
would presumably have a similar metallicity distribution as tectable because line blanketing by the Ly-α forest severely
theDLAgas. Wewishtoinvestigatewhetherornotthisdis- attenuatesthequasarcontinuumatwavelengthsshortwardof
agreementpersistsinoursamplethatislargerinsizeandex- Ly-αemission; i.e. atwavelengthswheresuchDLAswould
tendstohigherredshifts. belocated(Fanetal.2006;Songaila&Cowie2010)
The outline of this paper is as follows: The observations The new observations comprise a total of 6 nights (effec-
anddatareductionarepresentedin§2andtheanalysisofthe tively5 nightswhen consideringthe losses to poorweather)
resultantspectraisdetailedin §3. In§3.1, Voigtprofilesare onESIand7nightsonHIRES.InTable1wepresentajour-
fitted to the damped Ly-α profiles to determine the H I col- nalof observationsdescribingthe 50 quasars in our sample.
umndensities,N . We discussthepossibleelementalabun- Column(1)givesthe quasar coordinatenameobtainedfrom
HI
dancesthatcanbeusedtodeterminethemetallicityofDLAs theSDSSsurvey. Columns(2)and(3)givetheRAandDec.
in §3.2. Column densities of the metal lines are determined of the quasar in J2000. Columns (4) and (5) give the AB r
fromthe apparentopticaldepthmethod(Savage&Sembach andimagnitudesofthequasar:inmostcasestheimagnitude
1991; Prochaskaetal. 2001b), and combined with the N gives a realistic measure of the unattenuated quasar bright-
HI
valuestodetermineelementabundancesfortheDLAsin§3.3. nesssinceattheredshiftsofmostoftheDLAs, theifilteris
This sample is augmentedby unbiasedabundancesobtained placedredwardofLy-αemission.Column(6)givestheemis-
from the literature as described in §3.4. We justify the use sion redshift of the quasars, and column (7) lists candidate
ofvariouselementsfordeterminingthemetallicitiesofDLAs DLA absorption redshifts obtained from SDSS. Column (8)
in§3.5. ThedeterminationofhZiasfunctionofredshiftand provides the UT date of the observations, column (9) states
timeispresentedin§3.6,andacomparisonoftheDLAmetal- theinstrumentused, andcolumn(10)lists theslit size. Col-
licitydistributionwiththatofhalostarsisshownin§3.7. In umn (11) gives the exposure time, and column (12) the S/N
§4 we discuss the metallicity distributionandevolution, and pixel- 1ofthedata.
itsimplicationsforhalostarformation.Specifically,wecom- Ingeneral,weobtained2-3exposuresperquasarwithESI,
withsufficientexposuretimetoreachS/Nvalueslargerthan
MetallicityEvolutionofDLAsouttoz∼5 3
Table1
JournalofObservations
QSO R.A. Dec. r i zem zabs Date Instr. Slit texp S/Na
(J2000) (J2000) (AB) (AB) (UT) (arcsec) (s) pixel- 1
(1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12)
J0040- 0915 004054.7 - 091527 20.48 19.18 4.98 4.74 2010Jan20 ESI 0.50 2280 16
2011Jan16 HIRESr 0.86 7200 6
2011Jan24 HIRESr 0.86 3600
J0210- 0018 021043.2 - 001818 20.48 19.20 4.72 4.57b 2010Jan20 ESI 0.50 2880 9
J0331- 0741 033119.7 - 074143 20.56 19.12 4.71 4.19b 2010Jan20 ESI 0.75 4320 18
J0747+4434 074749.7 +443417 19.62 17.35 4.43 4.02 2009Mar22 ESI 0.75 3600 15
2011Jan16 HIRESr 0.86 3601 9
2011Jan24 HIRESr 0.86 10800
J0759+1800 075907.6 +180055 21.06 19.16 4.86 4.66 2010Jan20 ESI 0.75 4320 18
J0813+3508 081333.3 +350811 20.81 19.13 4.92 4.30b 2010Apr21 ESI 0.75 1400 14
Note.—Unitsofrightascensionareinhours,minutes,andseconds,andunitsofdeclinationareindegrees,arcminutes,andarcseconds.Photometry
fromSDSS(Abazajianetal.2009).Thistableisavailableinitsentiretyinamachine-readableformintheonlinejournal. Aportionisshownherefor
guidanceregardingitsformandcontent.
aMediansignal-to-noiseperpixelatλ≈8300Å,exceptintheHIRESobservationsofJ1353+5328andJ1541+3153,whereitisatλ≈7300Å.
bMarkedasaDLAinSDSS,butisnotaDLAbasedonhigherresolutionESIdata
15pixel- 1(11kms- 1). Observationswerereducedonthefly wealsoanalyzeESIobservationsandHIRESfollowupfrom
to determine if the DLA candidate did not meet our thresh- 2008whichwereobtainedinasimilarunbiasedfashion.
oldcriteriaforbeingaDLA,i.e. N(HI)≥2×1020cm- 2. Ifit All the data were reduced with the XIDL6 package devel-
didnot,thenweabandonedobtainingmoreexposures,result- opedinIDLbyJ.X.Prochaska.Specifically,theESIobserva-
inginreducedS/Nvaluesforthosetargets.Thesequasarsare tionswerereducedwithESIRedux7(Prochaskaetal.2003a)
nonethelesslistedinTable1,andthecorrespondingDLAsare and the HIRES observations were reduced with HIRedux8,
markedwiththefootnoteb. Table1alsoliststhemedianS/N both of which are publicly available. All the data were ex-
perpixelatλ≈8300Å5, correspondingto thetypicalwave- tractedwithoptimalextraction,andthedatawerecontinuum
length of the measured metal absorption lines. The average fitusingthex_continuumroutinewithinXIDL.
S/N of the ESI spectra with confirmed DLAs is 25, with a
3. ANALYSISANDRESULTS
minimumS/Nof14. ThemeanS/NofthespectrawithDLA
candidatesnotmeetingourcriteriais15,withaminimumS/N In this section we present the analysis of the quasar spec-
of9. tra obtainedin thissurvey. We first confirmthe DLA candi-
All ESI observationsprior to 2010, and all HIRES obser- dates using Voigt profile fitting, determine their N values,
HI
vations were observed at the same slit position to facilitate andinvestigatethefalsepositiverateofSDSS-selectedDLAs
the removal of cosmic rays between exposures. In order to at high redshift. We discuss the possible elemental abun-
decrease the effects of fringing in ESI observations(∼15% dancesthatcanbeusedtodeterminethemetallicityofDLAs,
at 9000Å; Sheinisetal. 2002) at the longest wavelengths andthendescribethederivationofelementalabundances.We
thencompilethe latestliteraturemetallicities, justifytheuse
(λ>8,000Å),weusedathreepointditherpatternalongthe
ofmultipleelementsformetallicitydetermination,anddeter-
slitforallESIobservationsstartingin2010. Throughoutthe
ESIobservations,weprimarilyusedthe0.′′75slit, exceptin mine hZi as function of redshift. Finally, we compare the
twocaseswhenweusedthe0.′′5slit, whichcorrespondtoa metallicitydistributionofDLAstothatofknownstellarpop-
resolution of FWHM of ∼44 and ∼33 km s- 1 respectively ulationsintheMilkWay,focusingonthehalostars.
(R≈7,000- 10,000). FortheHIRESobservations,weused 3.1. HIColumnDensities
theC1decker,witha0.′′86slitcorrespondingtoaresolution
of FWHM of 6.2 km s- 1 or 1.5 km s- 1 pix- 1 (R≈50,000). We determinethe NHI valuesofthedampedLy-αsystems
inoursampleusingthesamemethodologyasProchaskaetal.
ESI has a fixed format echellette that coversthe spectral re-
(2003a). Specifically,wefittheLy-αlinewithaVoigtprofile
gionλ= 4,000to11,000Å,whiletheHIRESechellettecov- inthefluxed,butnotcontinuumfit,spectrausingtheroutine
eragevarieswitheachsetup. TheHIRESobservationsareall x_fitdla,partofthe XIDLpackage. We tie thecentroidof
followupobservationsoftheESIobservationsinordertode-
theVoigtprofiletotheredshiftofthelow-ionmetal-linetran-
blendlines,checkforsaturation,andmeasureweaklines,and sitions9, which yields a velocitycentroidto within ∼30 km
wethereforetargetedtheappropriatemetallinesformetallic- s- 1ofthetruelinecenter(Prochaskaetal.2003b). Wesimul-
itydeterminationwiththeHIRESsetups.
taneouslyfittheVoigtprofileandthecontinuumtoobtainafit
Figure 1 shows the 25 quasar spectra containing 32 con-
thatmatchesboththecoreandwingsoftheprofile. Theun-
firmedDLAswithz>4(see §3.1regardingconfirmationof
certaintiesassociatedwiththeredshifterrorsaresignificantly
DLAs), in order of increasing value of the largest redshift
lessthantheuncertaintyinthecontinuumfit,andthereforeare
DLAforeachspectrum.Wenotethatwhilethesespectraalso
notseparatelyincludedinthefittingprocedure.Whilethisfit-
containotherlowerredshiftDLAs, weonlyshowthosewith
tingprocedureisnotcompletelyquantitative,itisthestandard
z>4. In additionto the 25quasarscontainingz>4DLAs,
6Seehttp://www.ucolick.org/~xavier/IDL/
5TheHIRESobservationsofJ1353+5328andJ1541+3153havetheirS/N 7Seehttp://www2.keck.hawaii.edu/inst/esi/ESIRedux/
determined at λ≈7300Å due to their lower redshifts and corresponding 8Seehttp://www.ucolick.org/~xavier/HIRedux/
HIREScoverage. 9Allofthebona-fideDLAsexhibitatleastonepositivedetection.
4 Rafelski,Wolfe,Prochaska,Neeleman,Mendez
Figure1. ESIspectraof25quasarswith30DLAsatz>4. Fluxes(blackcurves)and1-σerrorarrays(greencurves)arenormalizedtounitcontinuum. The
orangelinesarezeroflux.z>4DampedLyαlines,denotedbyredarrows,arelistedinorderofincreasingvalueofthelargestredshiftDLAforeachspectrum
MetallicityEvolutionofDLAsouttoz∼5 5
methodology and is justified by the fact that the uncertain- Thisremoves5falsecandidateDLAs(4ofwhichareatz>4)
tiesaredominatedbysystematicerrors:continuumfittingand and9confirmedDLAsfromthesample,leavingatotalof56
line-blending.Inourexperience,astandardχ2analysisyields candidateDLAs. Outofthese 38candidatez>4 DLAs, 10
unrealisticallysmallerrorestimates(Prochaskaetal.2003a). arefalsepositives,leavingatotalof28confirmedDLAswith
We place very conservative error estimates on the N val- z>4, and a ∼26% misidentification rate. For the 18 z<4
HI
uesbymanuallyselectingvaluesthatensurethattheerrorre- DLAs, we find 2 false candidates, and a ∼11% misidentifi-
gionencompassesallpossiblesolutionsforN . Thesevalues cationrate. We notethatoneofthese two DLAsis foundin
HI
systematicallyincreasewithincreasingredshiftduetothein- aquasarwithzem=4.9,andthereforeisseverelyaffectedby
creasedLy-αforestblending,andthereadershouldconsider thez>4Ly- β forest,whichisuncommon,andthereforethe
themtoberoughlyatthe95%confidencelevel. misidentificationrateatz<4islikelycloserto∼6%.Despite
ThesampleofcandidateDLAsallhaveN ≥2×1020cm- 2 thesmallnumberstatistics,thereclearlyisalargerpercentage
HI
based on the SDSS spectra with spectral resolution FWHM offalsepositivesatz>4thanatz<4.
WecomparetheN valuesdeterminedfromtheDR5SDSS
∼2Å. At low redshift, this is sufficiently high resolution to HI
data and from our ESI data in Figure 4. The top panel is
obtain relatively accurate N , and therefore yields only a
HI
the ESI N versus the SDSS N , while the bottom panel
small number of false candidates. However, as we move to HI HI
are number counts of misidentified DLAs. The dotted line
higher redshift, the Ly-α forest becomes significantly more
markstheminimumcriteriatobeaDLA,N ≥2×1020cm- 2.
dense,andthedampedLy-αprofilesintheSDSSspectraare HI
ThereisgeneralgoodagreementbetweentheESIN values
significantlyaffectedbyline-blendingwithrandomLy-αfor- HI
andthe SDSSN valueswithintheir uncertainties. Inaddi-
estclouds.SincetheESIspectraresolveoutmuchoftheLy-α HI
tion,thehistogramshowsthattheprimarymisidentifications
forest,wecanthereforeobtainmorerobustvaluesofN . In
order to confirm a candidate DLA from SDSS to be aHItrue occur for DLAs near the NHI=2×1020cm- 2 limit. Some of
DLA,werequireN ≥2×1020cm- 2intheESIspectrum. these misidentified systems are super Lyman limit systems,
HI
We fitted N Voigt profiles to 68 candidate DLAs from although the majority are due to a combination of lines in
HI
SDSS, and confirm 51 as bona-fide DLAs. Figures 2 and 3 theLyman-αforest. StudiesusingDLAidentificationsfrom
show the Voigt profile fits of 51 newly confirmed DLAs or- SDSS at z>4 (Prochaska&Wolfe 2009) therefore need to
dered by increasing RA. The velocity centroid of the DLA applyacorrectionfortheincreasedfalsepositiveratebefore
is determined from the low-ion metal transitions, and some determiningthecolumndensitydistributionfunction,theto-
panels have more than one DLA candidate marked, and in tal covering fraction, and the integrated mass density of HI
those cases the central DLA at zero velocity is the DLA for gas. The histogramin Figure 4 suggests that this correction
the informationgiven in that panel. The velocity intervalof mainlyneedstobeappliedforthelowestNHIDLAs.
theindividualpanelsvarieswithcolumndensitysuchthatthe For such future corrections, we break down the ∼26%
wingsofthedampedprofilearepresented. misidentification rate into random and systematic misidenti-
The higher density of the Ly-α forest at higher redshifts fications. Of the 10 false positivesfrom DR5, 3 are random
resultsinmorelineblendingthanatlowerredshift,andthere- misidentificationswithhighNHI absorbersatthecorrectred-
fore sometimes one or both of the wings are not clearly de- shiftthatdonotquitemeetthecriteriaofNHI≥2×1020cm- 2,
fined,andinthesecaseswerelyonthecoreoftheline. Ina but are within 1- 2σ of their previous measurements. The
few other cases, a strong Ly-α absorberis blendedwith one other7falsepositivesaresystematicmisidentificationsdueto
sideoftheDLA’score,andtheresultantprofileisconstrained acombinationofmanylowerNHI absorbersmasqueradingas
by the core on the other side, and the wings on one or both asinglehigherNHI absorber. Figure5showVoigtprofilefits
sides. For example, the Voigt profile fit of J1200+4618 at toboththeoriginalSDSSdataandthehigherresolutionESI
z =4.477 turns up more sharply than the data on the blue dataforthe7systematicmisidentificationsfromDR5.
abs
side of line center due to confusion with one or more Ly-α We expect that a number of absorbers with NHI< 2×
absorbersatv∼- 900kms- 1. Thesameeffectcanbeseenin 1020cm- 2 will randomly be measured above this value, and
J1201+2117atzabs=4.158,andafewotherDLAfits. These that a number of absorbers with NHI> 2×1020cm- 2 to be
challenges are not a problem, as the redshift is determined measured below this value. We check if the number of ran-
fromthelow-ionmetallines,andwethereforehavesufficient dommisidentificationsmeasuredisasexpectedfromtheun-
informationforarobustdeterminationofN . certaintiesandthecolumndensitydistributionfunctionusing
HI
The 17 false candidates consist of multiple lower column the Eddington bias formalism (Eddington 1913; Teerikorpi
density lines that are blended together in the lower resolu- 2004). WelimitourselvestoDLAswithN .20.5,asabove
HI
tion SDSS data. Of the 68 candidate DLAs in Table 1, 46 thisN theproblemissmall(seeFigure4)andarandomer-
HI
of them have z>4. Of those 46 candidate z>4 DLAs, 14 rorisunlikelytomoveanabsorberwithN <2×1020cm- 2to
HI
arefalsepositives,leavingatotalof32confirmedDLAswith ahigherN . TheobservednumberofDR5DLAswithz>4
HI
z>4. As a result, we find that ∼30% of z>4 DLAs are andN <20.5is9, towhichwe addthe3 randommisiden-
HI
misidentified in SDSS due to line-blending. In contrast, for tificationsfora totalof12absorbers. We use anuncertainty
our sample of 22 z <4 DLAs, we find 3 false candidates, of 0.2 dex, and model the column density distribution func-
none of which are one of the 14 z∼3 candidate DLAs ob- tion. TheexpectednumberofDLAsfromtheEddingtonbias
tained in our 2008 run. To investigate this further, we limit formalism is 8.4, resulting in an observed difference of 3.6
ourselves to the more homogeneous part of the sample that DLAs. This is consistent with the 3 random misidentifica-
were identified with the automated routine from DR5 SDSS tions measured, especially given the small number statistics
data (Prochaska&Wolfe 2009), excluding the manually se- consideredhere.
lectedDR7SDSSDLAs(see§2). Also,weexclude2DLAs We note that in our survey for DLAs, we reject proxi-
thatwerelowerthanN ≥2×1020cm- 2intheSDSSdata,but mate DLA systems that are found to be within 3000 km
HI
weremeasuredintheESIspectratomeettheDLAcriterion. s- 1 of the quasar emission redshift, as these DLAs may be
6 Rafelski,Wolfe,Prochaska,Neeleman,Mendez
Figure2. Voigtprofilefitsto51confirmedDLAsorderedbyRA,withthex-rangebasedontheNHI. Bluecurvesarebest-fitprofilesandgrayshadeincludes
95%confidencelimitssurroundingbestfits. ThereddottedlinemarksthevelocitycentroidoftheDLAdeterminedfromthelow-ionmetaltransitions,with
possiblemultiplecomponentsasdeterminedbythemetallines. Individualpanelsincludequasarname,DLAredshiftandHIcolumndensity. Thegreenline
representstheuncertainty.
MetallicityEvolutionofDLAsouttoz∼5 7
Figure3. ContinuationofFigure2.
8 Rafelski,Wolfe,Prochaska,Neeleman,Mendez
estimatethetotalmetalabundance(Prochaska&Wolfe2002;
22.0
Vladiloetal.2011).Consideringalloftheseaspectstogether,
weconcludethatSisthebestoptionanduseitsabundanceas
21.5
a proxy for the heavy element mass density in DLAs wher-
NHI everpossible10. Undertheexpectationthatmetal-poorgasis
g 21.0 relativelyundepleted,weadoptSiasthesecondchoice,espe-
o
SI l cially in low metallicity systems. We further investigate the
E
possibilityofdepletionofSiin§3.5,wherewedeterminethat
20.5
itisnotsignificantlydepletedinDLAsbasedoncurrentmea-
surements.
20.0 Within the DLA literature, zinc (Zn) has played a spe-
10
As cialroleinestimatingthemetallicity(e.g.Meyeretal.1989;
L
−D 5 Pettinietal. 1990, 1994, 1997; Akermanetal. 2005). This
n
o
N 0 reflects both observational convenience and the fact that Zn
20.0 20.5 21.0 21.5 22.0 is non-refractory. Specifically, Zn has two strong transitions
SDSS log NHI
Figure4. ComparisonoftheNHI values determined fromtheDR5SDSS at 2026 and 2062 Å, that almost always lie outside the Ly-
dataandfromourESIdata inFigure2. Thetoppanel istheESINHI vs. α forest, and are rarely saturated due to their low oscillator
theSDSSNHI, whilethebottom panelarenumbercounts ofmisidentified strengthsandlow Zn abundances. Unfortunately,Znis only
DlinLeAms,arbkassethdeomnitnhiemhuimghcerritreersioonluttoiobneaandDLhiAgh,eNrHSI≥/N2E×SI10d2a0tac.mT- 2h.edotted asittyrafcoeretlheemheenatvwyheilcehmceonntstr.ibFuutersth≈erm10o-r4e,otfhethweemakasnsesdseno-f
the Zn transitions make it impossible to measure its abun-
physically associated or otherwise affected by the quasar
danceinlowmetallicityDLAs,andthelargerest-framewave-
(see Prochaskaetal. 2008; Ellisonetal. 2010, 2011). This
lengths of the transitions make them difficult to measure at
removes our highest redshift confirmed DLA (z = 5.18,
high redshift. In addition, the nature of Zn is not fully un-
J1626+275),anditisnotincludedintheanalysisofthemetal-
derstood; Zn is not an α-element, nor an Fe peak element.
licity evolution, although we include it for completeness in
While Zn is often observed to track Fe, theoretical work on
ourtables.
the nucleosynthesis of Zn often predicts it may originate in
massivestars(Woosley&Weaver1995;Hoffmanetal.1996;
3.2. DeterminingDLAMetallicities
Umeda&Nomoto 2002; Fenneretal. 2004). On the more
A principal goal of this paper is to trace the build-up of positiveside,ZntrackstherelativeabundancesofSandSiin
heavyelementsinneutralgasacrosscosmictime. IntheSun, DLAs, andempiricallyisa fair substituteforthese elements
oxygen(O) dominatesby numberand contributes≈50%of (see §3.5). Therefore,when O, S, and Si are either notcov-
the heavy element mass budget (Lodders 2010). This frac- eredbyourspectraoraresaturated,andtheZntransitionsare
tionis likely evenhigherin the early universewhenType Ia available,weusetheZnabundanceasa proxyfortheheavy
supernovaehavehadlesstimetoenrichtheiron(Fe)peakel- elementmassdensity.
ements(see§3.7). Indeed,Oiscommonlyobservedtobeen- In the small number of cases where none of the aboveel-
hancedinmetal-poorenvironmentssuchasourGalactichalo ements are available, we are left with using elements such
(e.g.Besselletal.1991). Ideally,onewouldassesstheheavy as Fe, nickel (Ni), or aluminum (Al). As Fe and Ni are re-
element mass density through measurementsof O. Unfortu- fractoryelements,theywillbedepletedathighmetallicities.
nately in DLA analysis, the OI transitions are generally ei- Atlowmetallicities,wecanmeasuretheintrinsicabundance
thertooweakortoostrongtopermitapreciseestimateofits ofFe andNi, whichtracksthe abundancesofS andSiwell,
abundancerelativetohydrogen.Afteroxygen,carbon(C)and withanoffsetduetotheα-enhancementofDLAs. Wedeter-
neon(Ne)contribute≈30%oftheheavyelementmassinthe minetheα-enhancementin§3.3and§3.5fromtheabundance
Sun.ThesamechallengesasforoxygenapplytoC,andthere ofFe combinedwith anα-elementabundance. We applyan
arenoNetransitionsavailableforDLAs. Itisevidentthatwe [α/Fe] offsetof 0.3 dex, which is slightly differentthan that
areforcedtouseaproxyfortheheavyelementabundance. used in some previous studies (0.4; e.g. Prochaska&Wolfe
The elementsnitrogen(N), magnesium(Mg), silicon (Si), 2002; Prochaskaetal. 2003b), but is more representative of
sulfur(S),andFeeachcontribute≈5%oftheheavyelement [α/Fe] of DLAs (Wolfeetal. 2005, and see below in §3.4
mass density in the Sun and each of these can, in principle, and§3.5)11. Inaddition,wealsodetermine[Fe/H]fromiron
be measured in DLAs. To best trace the dominantelements peakelementsforallDLAs,asthisisusefulforstudyingthe
(O, C, Ne), one would prefer an element that is produced chemistryofDLAs,andforanestimateofthedust-to-gasra-
andexpelledintandem,i.e. predominantlyinthesupernovae tio, as Fe is a depleted element for DLAs with [M/H] >- 1
explosions of massive stars. Both Si and S are good can- (Wolfeetal.2005).IncaseswhereFeisnotavailable,wede-
didates since they lie along the α-element sequence of nu- termine[Fe/H]useingNiwitha0.1dexcorrection,orAl. We
cleosynthesis, are produced in massive stars, and are easily notethatwheneverweuseanFepeakelementforthemetal-
measurable in high redshift DLAs. S is a volatile element licity, we addtheuncertaintyin [α/Fe] of0.16to the [Fe/H]
with negligible depletion and with multiple lines of varying uncertaintyinquadrature.
oscillator strengths. Alas, these lines are often in the Ly-α
forest, makingthem measurablein onlya fractionof DLAs.
Si has many lines of varying oscillator strengths at multiple
wavelengths, which results in at least one line being unsatu-
ratedandoutsidetheforestforthemajorityofDLAs. While 10Asidefromthefewcaseswhereoxygenismeasuredprecisely.
Si has nearly twice the mass density of S, it is a mildly re- 11 Wenotethatthey-axisofFigure8inWolfeetal.(2005)ismislabeled.
fractoryelementand its gas-phase measurementmay under- Theticklabeled0.5shouldbelabeled0.7
MetallicityEvolutionofDLAsouttoz∼5 9
Figure5. Voigtprofilefitstothe7systematicmisidentificationsofDLAsfromSDSS.WealternatepanelsshowingtheSDSSdataandtheESIdata,andlabel
eachpanelaccordingly. Thebluecurvesarebest-fitprofilestotheSDSSdatafromProchaskaetal.(2005)andProchaska&Wolfe(2009),ortheESIdatafrom
thiswork. Individualpanelsincludequasarname,DLAredshiftandHIcolumndensity. Thegrayshadeincludes95%confidencelimitssurroundingbestfits,
thereddottedlinemarksthevelocitycentroidoftheDLAsasdeterminedfromthelow-ionmetaltransitions,andthegreenlinerepresentstheuncertainty.
3.3. MeasuredElementAbundances narrow(Penpraseetal.2010),andsuchlinesshouldnormally
betreatedaslowerlimits. However,inthisstudyweobtained
In this subsection we describe the derivation of ionic col-
HIRES followup in order to 1) check for saturation of nar-
umn densities for all of the new confirmed DLAs using the
rowweakmetallinesfromtheESImeasurementsbyresolv-
apparent optical depth method (AODM; Savage&Sembach
ingthelines,and2)obtainmetallicitiesthatwouldotherwise
1991). This method can uncover hidden saturated lines by
notbemeasurablewithESIduetoblendingoflinesorweak
comparing the apparent column density per unit velocity,
transitions. By targeting the most likely problematic candi-
N (v), for multiple transitions of a single ion. We then cal-
a dates with HIRES, we reduce the saturation issues. Specifi-
culate N (v) for each pixel from the optical depth equation,
a cally,wefollowedupDLAswithnarrowlineswhosemetal-
and sum over the velocity profile of each transition to ob-
licity was based on single metal lines, as these are the most
tain the total column density, N. If multiple lines for a sin-
likely culprits. In the cases where a line looked potentially
gleion areavailable, thenwe takethe weightedmeanof the
saturated without available HIRES data, we used a different
column densities from unsaturated lines. The AODM tech-
line instead. In a few cases, this resulted in an Fe-element
niqueyieldscolumndensitiesthatagreewellwithlinefitting,
basedmetallicityratherthananα-elementbasedmetallicity.
and it is easier to apply to a large data sets such as this one
We therefore use the remaining ESI sample without apply-
(Prochaskaetal.2001b). Weusethewavelengthsandoscilla-
ingsaturationcorrections. Inaddition,ifwedidmissasmall
torstrengthsshowninTable2ofMorton(2003)andtheme-
number of saturated DLAs, they would not affect the main
teoritic solar abundancesshown in Table 1 of Asplundetal.
conclusions,aswehavesufficientmeasurementsperredshift
(2009).
bin such that hZi is not sensitive to any individualmeasure-
ThemediumresolutionofESIcouldresultinpossiblesatu-
ment (see §3.4). Lastly, as we probe higher redshifts, the
rationofunresolvedweakmetallinesiftheywereparticularly
10 Rafelski,Wolfe,Prochaska,Neeleman,Mendez
10.3Gyr 11.4Gyr 12Gyr 12.3Gyr 0Gyr 7.7Gyr 10.3Gyr 11.4Gyr 12Gyr 12.3Gyr
S II O I
0 SFei I III 0 SSi IIII
Zn II
Fe II
Other
−1 −1
H] H]
M/ M/
[ [
−2
−2
−3
−3
2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 0 1 2 3 4 5
Redshift (z) Redshift (z)
Figure6. DLAmetalabundance,[M/H],versusredshiftforthe46DLAsin Figure7. DLAmetalabundance,[M/H],versusredshiftfor195DLAsfrom
Table2(notincludingtheproximateDLA).Thesymbolsandcolorsindicate theliterature.Thesymbolsandcolorsindicatetheoriginofthe[M/H]values:
theoriginofthe[M/H]values:SIImeasurements(bluetriangles)SiIImea- SiIImeasurements(greenfilledcircles),SIImeasurements(bluetriangles),
surements(greenfilledcircles), andFeIImeasurements(redcrosses). We ZnIImeasurements (brown boxes), FeIImeasurements (redcrosses), and
notethattheFeII[M/H]valuesaregivenby[Fe/H]+0.3dex. otherssuchasOI(goldstars)andthecombinationoflimits(blackdiamonds).
common element transitions used for metallicity determina-
3.4. ElementAbundancesfromtheLiterature
tioninDLAsarelesslikelytobesaturatedduetotheirlower
metallicities at higher redshifts (Prochaskaetal. 2003b, and Inthissubsectionwedescribethecompilationofmetallic-
thisstudy). ities of DLAs from the literature. Over a thousand DLAs
InTable2wepresentnewmetallicitymeasurementsfor47 have been identified by SDSS (e.g. Prochaskaetal. 2005;
DLAs,with30ofthematz>4. FourDLAsdonothavemea- Prochaska&Wolfe2009;Noterdaemeetal.2009),andmany
surablemetallicitiesduetoalackofunsaturatedrelevantlines hundreds have been observed with a wide variety of tele-
redwardoftheLyman-αforest,andarenotinthetable. We scopes and instruments with varying resolution, S/N, and
donote,however,thateachoftheseexhibitsobviousmetalab- wavelengthcoverage.SimilartoProchaskaetal.(2003b),we
sorptionandthereforehasametallicity[M/H]>- 2. Another restrictouranalysistoDLAsobservedathigh-resolution(R>
is a proximate DLA, and is included in the table. Column 5000)andhighS/N(15pixel- 1),andrequirethemtomeetthe
(1)givesthequasarcoordinatenameobtainedfromtheSDSS DLA criteria of N ≥2×1020cm- 2. In addition, we avoid
HI
survey,column(2)givestheDLAabsorptionredshiftsdeter- samples with metallicity biases, such as metal poor sam-
mined from the metal transition lines, and column (3) gives ples(e.g.Pettinietal.2008;Penpraseetal.2010;Cookeetal.
the logarithmof the measured NHI values. Columns (4) and 2011) or metal rich samples (e.g. Herbert-Fortetal. 2006;
(5) give the alpha element flag and metallicity, and column Kaplanetal. 2010). We make an exception for low red-
(6)and (7) givethe Fe flag and metallicity. Column (8)and shift DLAs with z.1.5, as these are generally foundbased
(9)givetheflagandfinalmetallicityusedinthispaper. The on strong metal lines (e.g. Khareetal. 2004; Kulkarnietal.
flags in columns(4) and (6) state which transitionsare used 2005; Meiringetal. 2006; Pérouxetal. 2006). Therefore,
andif theyaredetectionsorlimits, asdescribedintheTable otherthanforDLAsin ourlowestredshiftbin, theliterature
notes. We alsoprovidethemeasuredelementalcolumnden- sampleisnot(explicitly)metallicitybiased.
sities of these DLAs in the online material in the appendix. InFigure7,weplotthecompilationof195metallicitieslit-
Inaddition,weshowthevelocityprofilesforthosemetal-line eratureabundancevaluesasafunctionofredshift.Thefigure
transitionsintheonlinematerial. outlineswhichelementsareusedtoobtain[M/H]andtheun-
Theuncertaintyin[α/H],[Fe/H],and[M/H]inTable2in- certainties of those measurements. The symbols and colors
clude the uncertainty of NHI added in quadrature, and there- indicatetheoriginofthe[M/H]measurements,withbluetri-
forearedominatedbythe uncertaintyin NHI. We ignorethe anglesrepresentingSII,greenfilledcirclesrepresentingSiII,
errorinthecontinuumfitinourerrorcalculationsformetal- redpluscrossesrepresentingFeII,brownboxesrepresenting
line transitions, although it may be importantfor very weak ZnII,andgoldstarsrepresentingOI,andcombinationoflim-
transitions. Wesetaminimumerrorof0.1dexforallmetal- its(blackdiamonds).WealsopresentthesevaluesinTable3,
licity measurements, and note that our main results are not wherecolumn(1)givesthequasarname,column(2)givesthe
sensitivetotheuncertaintiesinindividualmeasurements(see DLAabsorptionredshifts,andcolumn(3)givesthelogarithm
bootstrapmethodin§3.6). ofthemeasuredN values. Columns(4)and(5)givetheal-
HI
In Figure 6, we plot the 46 metallicities obtained in this phaelementflagandmetallicity,andcolumn(6)and(7)give
paper as a function of redshift (not including the proximate theFe flag andmetallicity. Column(8)and(9)givetheflag
DLA). The figure outlines which elements are used to ob- andfinalmetallicityusedinthispaper,andcolumn(10)cites
tain[M/H]andtheuncertaintiesofthosemeasurements. The thereferences.SimilartoTable3,theflagsincolumns(4)and
symbolsandcolorsindicatetheoriginofthe[M/H]measure- (6)statewhichtransitionsareusedandiftheyaredetections
ments, with blue triangles representing SII, green filled cir- orlimits,asdescribedintheTablenotes. Theuncertaintiesin
clesrepresentingSiII,andredpluscrossesrepresentingFeII. thetableincludetheuncertaintyinN addedinquadrature.
HI
We note that the metallicities derived from FeII include an We combine the 195 literature abundance values with our
α-enhancementcorrection,with[M/H]=[Fe/H]+0.3dex(see new ESI and HIRES observations for a total of 241 abun-
§3.4and§3.5). dances. We investigatethe abundancedistributionof DLAs,