Low Mass Group Environments have no Substantial Impact on the Circumgalactic Medium Metallicity
Stephanie K. Pointon, Glenn G. Kacprzak, Nikole M. Nielsen, Michael T. Murphy, Sowgat Muzahid, Christopher W. Churchill, Jane C. Charlton
DD RAFT VERSION M AY
5, 2020
Preprint typeset using L A TEX style emulateapj v. 05/12/14
LOW MASS GROUP ENVIRONMENTS HAVE NO SUBSTANTIAL IMPACT ON THE CIRCUMGALACTIC MEDIUMMETALLICITY S TEPHANIE
K. P
OINTON , , G LENN
G. K
ACPRZAK , , N IKOLE
M. N
IELSEN , , M ICHAEL
T. M
URPHY , S OWGAT M UZAHID ,C HRISTOPHER
W. C
HURCHILL , AND J ANE
C. C
HARLTON Centre for Astrophysics and Supercomputing, Swinburne University of Technology, Hawthorn, Victoria 3122, Australia; [email protected] ARC Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D) Leiden Observatory, University of Leiden, PO Box 9513, NL-2300 RA Leiden, The Netherlands Department of Astronomy, New Mexico State University, Las Cruces, NM 88003, USA and Department of Astronomy and Astrophysics, The Pennsylvania State University, State College, PA 16801, USA
Draft version May 5, 2020
ABSTRACTWe explore how environment affects the metallicity of the circumgalactic medium (CGM) using 13 low massgalaxy groups (2–5 galaxies) at (cid:104) z abs (cid:105) = 0 .
25 identified near background quasars. Using quasar spectra fromHST/COS and from Keck/HIRES or VLT/UVES we measure column densities of, or determine limits on,CGM absorption lines. We use a Markov chain Monte Carlo approach with Cloudy to estimate metallicities ofcool ( T ∼ K) CGM gas within groups and compare them to CGM metallicities of 47 isolated galaxies. Bothgroup and isolated CGM metallicities span a wide range ( − < [Si/H] < − . ± . − . ± .
14) CGM metallicities are similar. Group and isolated environments have similar dis-tributions of H I column densities as a function of impact parameter. However, contrary to isolated galaxies, wedo not find an anti-correlation between H I column density and the nearest group galaxy impact parameter. Weadditionally divided the groups by member luminosity ratios (i.e., galaxy–galaxy and galaxy–dwarf groups).While there was no significant difference in their mean metallicities, a modest increase in sample size shouldallow one to statistically identify a higher CGM metallicity in galaxy–dwarf groups compared to galaxy–galaxygroups. We conclude that either environmental effects have not played an important role in the metallicity ofthe CGM at this stage and expect that this may only occur when galaxies are strongly interacting or merging,or that some isolated galaxies have higher CGM metallicities due to past interactions. Thus, environment doesnot seem to be the cause of the CGM metallicity bimodality. Keywords: galaxies: halos — quasars: absorption lines INTRODUCTIONThe gas surrounding galaxies outside their disks/interstellarmedium (ISM) and residing within their virial radii is knownas the circumgalactic medium (Tumlinson et al. 2017). Ourunderstanding of the CGM has mainly been derived fromstudies of isolated galaxies revealing that within 1 R vir ,the CGM contains a mass comparable to the ISM and iscomprised of accreting, outflowing, and recycling gas (e.g.Kacprzak et al. 2008, 2011, 2016; Chen et al. 2010a; Rudieet al. 2012; Thom et al. 2011; Tumlinson et al. 2011; Nielsenet al. 2013a,b; Werk et al. 2013; Peeples et al. 2014).It is expected that the CGM in group environments wouldbe affected by galaxy–galaxy interactions, and hence, bemore complex. The effects of galaxy–galaxy interactions areclearly visible as tidal streams in H I emission around theM81/M82 galaxy group (Yun et al. 1994; Chynoweth et al.2008; de Blok et al. 2018). Further observations of H I gasin the CGM have found evidence for interactions in the formof tidal streams, warped disks and high-velocity clouds (e.g.Puche et al. 1992; Swaters et al. 1997; Rand 2000; Frater-nali et al. 2002; Chynoweth et al. 2008; Sancisi et al. 2008;Mihos et al. 2012; Wolfe et al. 2013). Additionally, absorp-tion studies of group environment CGM gas have detectedthe presence of tidal streams or intragroup gas (Whiting et al.2006; Kacprzak et al. 2010; Nestor et al. 2011; Gauthier 2013;Bielby et al. 2017; Péroux et al. 2017; Pointon et al. 2017;Nielsen et al. 2018; Chen et al. 2019). The tidal streamsand increased star-formation rates that occur during mergershave been suggested to increase the halo gas mass and cross- section (York et al. 1986; Rubin et al. 2010). Furthermore,FIRE simulations have demonstrated that intergalactic trans-fer is the dominant mode of gas accretion for z < ∼
200 kpc for L ∗ galaxies atredshifts z < .
0; Tumlinson et al. 2011; Werk et al. 2014), itis possible that the CGM will be influenced by a merger be-fore the visible components of the host galaxy (Nielsen et al.2018).Using Mg II as a tracer of cool gas in cluster environments,Lopez et al. (2008) detected an overabundance of strong Mg II absorbers near clusters compared to field galaxies. A sim-ilar enhancement of weak Mg II absorbers beyond the clus-ter center was not observed, consistent with expectations thatthese absorbers should be destroyed by the hot cluster envi-ronment. The distributions of the weak and strong Mg II ab-sorbers within the cluster is then evidence for a truncated coldgas halo, consistent with simulations (Padilla et al. 2009; An-drews et al. 2013).Chen et al. (2010a) investigated group environments us-ing Mg II as a tracer of cool gas. In seven out of eight ofthe group environments identified, Mg II was detected. Whilethe group environment Mg II absorption appeared to span thesame equivalent width versus impact parameter range as iso-lated galaxies, the authors did not detect a significant anti-correlation. This is contrary to the strong and well-knownanti-correlation for isolated galaxies (e.g. Lanzetta & Bowen a r X i v : . [ a s t r o - ph . GA ] M a y P OINTON ET AL .1990; Steidel et al. 1994; Kacprzak et al. 2008, 2012; Chen &Tinker 2008; Chen et al. 2010b; Bordoloi et al. 2011; Nielsenet al. 2013a). Indeed, Nielsen et al. (2013a) found the anti-correlation between Mg II equivalent width and impact param-eter for isolated galaxies to be highly significant (7 . σ ).Further studies have found that the radial distribution ofMg II is flatter in group environments compared to isolatedgalaxies (e.g. Bordoloi et al. 2011; Nielsen et al. 2018). Bor-doloi et al. (2011) found that the average Mg II equivalentwidths decreased beyond 140 kpc in group environments,whereas they began to decrease beyond 70 kpc for isolatedgalaxies. They further found that the radial distribution for thegroup environments CGM is consistent with a superpositionof individual overlapping halos. Thus the authors suggestedthat the group environment CGM is not strongly influenced bytidal stripping or outflows driven by increased star-formation.However, using the kinematic structure of Mg II absorbers ingroup environments, Nielsen et al. (2018) found that a super-position model can reproduce the equivalent widths required,but over-predicts absorption at high velocities due to the largevelocity separations between the galaxies in the group. In-stead, the authors suggest that the cool gas in group environ-ments forms an intragroup medium, created by intergalactictransfer or tidal stripping.Major mergers are able to disrupt the structure of involvedgalaxies more than minor mergers. Thus is it possible thatthe type of merger/interaction affects the CGM gas differ-ently. Nielsen et al. (2018) found that galaxy–galaxy groups(where the two brightest galaxies have similar luminosi-ties, L / L < .
5) may have larger equivalent widths (1 . σ )and absorber velocity dispersions (2 . σ ) than galaxy–dwarfgroups ( L / L ≥ . II , is likely to beconstrained to high density structures surrounded by highlyionized gas, traced by C IV and O VI . This highly ionized gashas also been investigated in group environments (e.g. Stockeet al. 2013; Burchett et al. 2016; Pointon et al. 2017; Ng et al.2019). Burchett et al. (2016) found that as the number ofgalaxies in a group increases, the C IV equivalent width de-creases, with no C IV detected in groups with more than sevengalaxies. Similarly, O VI has lower velocity spreads and col-umn densities in group environments compared to isolated en-vironments (Stocke et al. 2013; Pointon et al. 2017; Ng et al.2019). These results are consistent with the picture that thevirial temperature, which scales with halo mass, leads to oxy-gen and carbon ionising to higher states than O VI and C IV ,respectively (Oppenheimer et al. 2016; Bielby et al. 2019; Za-hedy et al. 2019; Ng et al. 2019).All of this evidence suggests that it is possible for CGMmetallicities to also be impacted by environment. Simulationsby Hani et al. (2018) investigated the changes in CGM metal-licity during a major merger. The authors found that, com-pared to the pre-merger state, the metallicity of the gas in-creased during the merger by 0 . − . . − < log N H I < . − ) and Lymanlimit systems (LLS; 17 . − < log N H I < . − ), thehigh metallicity systems are more likely to be associated withgroup environments while the low metallicity systems are as-sociated with isolated environments. While the authors cau-tioned that this result is preliminary and refrained from mak-ing any interpretations, it may suggest that interactions ingroups of galaxies may be causing increased metallicity. Thisresult is somewhat challenged by Pointon et al. (2019), whostudied the metallicity of the CGM in isolated environments.They found that the CGM metallicities of isolated galaxiesspan the full range detected by Lehner (2017), even whenthe sample is restricted to the same H I column density range.This suggests that high metallicity systems are not only foundin group environments.Following on from Lehner (2017), we investigate the ef-fect of environment on the metallicity of the CGM by com-paring the isolated galaxy sample from Pointon et al. (2019)to group environments. We investigate the metallicity of 13group environments using the combination of UV spectrafrom HST /COS and
FUSE , as well as optical spectra fromKeck/HIRES and VLT/UVES.This paper is organized as follows: In Section 2 we describeour sample of group galaxy–absorber pairs. We also describehow we obtain the metallicity of the CGM. We present the re-sults comparing the group environment CGM metallicity withthe same properties for isolated galaxies, as well as investigateany trends with H I column density, impact parameter and lu-minosity in Section 4 and discuss the implications in Section5 . In Section 6 we summarize our results and provide con-cluding remarks. We use a standard Λ CDM cosmology with H o = 70 km s − Mpc − , Ω M = 0 . Ω Λ = 0 . OBSERVATIONSIn order to study the CGM of the group environments, weuse the “Multiphase Galaxy Halos” Survey which is com-prised of UV
HST /COS spectra from our program (PID13398) (Kacprzak et al. 2015, 2019; Muzahid et al. 2015,2016; Pointon et al. 2017, 2019; Nielsen et al. 2017; Ng et al.2019) as well as data taken from literature (Chen et al. 2001b;Chen & Mulchaey 2009; Meiring et al. 2011; Werk et al.2012; Johnson et al. 2013). A group environment is definedas having the nearest of two or more galaxies within 18 to150 kpc of the quasar sight-line in order to replicate the im-pact parameter distribution of the isolated sample. The galax-ies in the group must have line-of-sight velocity separationsof less than 1000 km s − and a maximum impact parameterof 500 kpc. We investigate 13 group environments from theliterature for which we have UV spectra (Lanzetta et al. 1995;Chen et al. 2001b; Chen & Mulchaey 2009; Prochaska et al.2011; Werk et al. 2012; Johnson et al. 2015; Muzahid et al.2015; Nielsen et al. 2018). The groups have associated H I ab-sorption with a redshift range of 0 . < z abs < .
38 ( (cid:104) z abs (cid:105) =0 . L ) and second brightest ( L )galaxies (1 . < L / L < .
7; median L / L = 2 . z abs = 0 . . ETALLICITIES IN G ROUP E NVIRONMENTS Table 1
Quasar Observations(1) (2) (3) (4) (5) (6) (7) (8) (9)J-Name z qso RA (J2000) DEC (J2000) UV Inst. COS Gratings COS PID(s) Optical Spectrograph Optical PID(s)J0125 1 .
074 01:25:28 . − .
93 COS G160M 13398 UVES 075.A-0841(A)J0228 0 .
493 02:28:15 . − .
29 COS G130M, G160M 11541 ··· ···
J0351 0 .
616 03:51:28 . − .
71 COS G130M, G160M 13398 UVES 076.A-0860(A)J0407 0 .
572 04:07:48 . − .
66 COS, FUSE G130M, G160M 11541 HIRES G01H, U68HJ0853 0 .
514 08:53:34 . + .
33 COS G130M, G160M 13398 ··· ···
J0910 0 .
463 09:10:29 . + .
61 COS G130M, G160M 11598 ··· ···
J0925 0 .
472 09:25:54 . + .
17 COS G130M, G160M 11598 HIRES U059HbJ0928 0 .
296 09:28:37 . + .
02 COS G130M, G160M 11598 HIRES U066HbJ1009 0 .
456 10:09:02 . + .
87 COS G130M, G160M 11598 HIRES U066HbJ1119 0 .
176 11:19:08 . + .
01 COS, FUSE G130M, G160M 12038 HIRES U152HbJ1139 0 .
556 11:39:10 . − .
63 COS G130M 12275 ··· ···
Table 2
Galaxy Properties(1) (2) (3) (4) (5) (6) (7) (8) (9) (10)J-Name z gal REF a ∆ α ∆ δ θ D M B L B / L ∗ B v G − v GX b (J2000) (J2000) (deg) (kpc) (km s − )J0125 0 . − . − . .
07 78 − .
21 0 . − . − . − . .
80 238 − .
21 0 .
57 108J0228 0 . − . − . .
87 34 − .
42 0 . − . − . − . .
04 109 − .
32 0 .
15 323J0228 0 . . − . .
21 63 − .
43 0 . − . . − . .
26 154 − .
78 0 .
02 2840 . . − . .
98 164 − .
01 0 .
08 47J0351 0 . . − . .
72 126 − .
15 0 . − . − . . .
33 162 − .
95 1 .
09 1070 . − . . .
31 288 − .
27 0 .
58 706J0407 0 . . − . .
08 72 − .
45 0 . − . − . . .
01 105 − .
88 0 . − . − . − . .
89 133 − .
84 0 . − . − . − . .
44 300 − .
12 0 . − . . − . .
64 439 − .
29 0 . − . − . . .
81 99 − .
04 0 . − . . − . .
36 115 − .
65 2 .
49 0J0853 0 . . − . .
45 79 − .
75 0 . − . − . . .
81 53 − .
28 0 .
05 330J0910 0 . . . .
99 54 − .
70 0 . − . − . − . .
42 132 − .
00 1 . − . − . − . .
69 96 − .
52 0 . − . − . − . .
64 84 − .
25 1 .
57 192J0928 0 . . − . .
38 95 − .
14 0 . − . . − . .
19 51 − .
84 0 .
48 520 . − . − . .
82 40 − .
76 0 . − . . − . .
41 47 − .
98 0 . − . . . .
13 16 − .
87 0 . − . − . − . .
01 136 − .
75 0 . − . − . − . .
99 219 − .
56 0 . − . . − . .
79 18 − .
24 1 . − . − . − . .
39 39 − .
54 0 . − a Galaxy identification references: (1) Muzahid et al. (2015), (2) Chen et al. (2001b), (3) Chen & Mulchaey(2009), (4) Nielsen et al. (2018), (5) Johnson et al. (2015), (6) Lanzetta et al. (1995), (7) Werk et al. (2012)and (8) Prochaska et al. (2011). b Line-of-sight velocity separations between the first galaxy in the group ( G
1) and each of the other groupgalaxy members ( GX ). P OINTON ET AL .ies. Therefore, our study probes the low mass end of groupenvironments.All quasars in the sample have COS UV spectra, whiletwo also have reduced UV spectra from the
FUSE tele-scope, provided by B. Wakker (2016, private communica-tion). Eight quasars have optical spectra from Keck/HIRESor VLT/UVES. The details of the quasar spectra are shown inTable 1. 2.1.
UV Quasar Spectra
The COS quasar spectra used in our survey have a medianresolving power of R ≈ , FUSE quasar spec-tra have a resolving power of R ≈ , FUSE quasar spectraare in Table 1. The range of ions covered by the UV spec-tra includes the H I Lyman series, C II , C III , C IV , N II , N III ,N V , O I , O VI , Si II , Si III and Si IV . The reduction processfor the HST /COS spectra is described in detail in Kacprzaket al. (2015). The raw data were reduced using the CALCOSpipeline software and then flux calibrated. Individual gratingintegrations were co-added and rebinned by three pixels toimprove the signal-to-noise ratio (Danforth et al. 2010) . TheCOS and FUSE
UV spectra were then continuum normalizedby fitting low-order polynomials to the spectra while exclud-ing absorption and emission lines from the fitting region.2.2.
Optical Quasar Spectra
The UV spectra were complemented by additional opticalspectra, which cover ionic transitions including Mg I , Mg II ,Fe II , Mn II and Ca II for redshifts of z > .
2. Eight quasarshave optical spectra from Keck/HIRES and VLT/UVES witha resolving power of R ≈ , Optical Galaxy Spectra
Optical spectra of the galaxies in three group environmentquasar fields were obtained using the Keck Echelle Spectro-graph and Imager (ESI; Sheinis et al. 2002) since the wave-length range (4000–10 , α . The reduction method is described inKacprzak et al. (2019), Nielsen et al. (2018) and Pointon et al.(2019). However, we summarise the process here. The data,taken through slits of 20 (cid:48)(cid:48) by 1 (cid:48)(cid:48) , were binned by two, resultingin a spatial pixel size of 0 . (cid:48)(cid:48) − . (cid:48)(cid:48) and a spectral resolu-tion of 22 km s − . The reduction process was completed usingIRAF, after which heliocentric and vacuum corrections wereapplied to the data. Galaxy redshifts are shown in column(2) of Table 2. The redshifts for the remaining galaxies wereobtained from literature, indicated in column (3) of Table 2.2.4. Isolated Galaxy Sample
We use the metallicity study of 47 isolated environments byPointon et al. (2019) with a redshift range of 0 . < z < . (cid:104) z (cid:105) = 0 .
27) to compare to the group environments. An iso-lated galaxy is defined as having no neighboring galaxies http://casa.colorado.edu/~danforth/science/cos/costools.html within a spatial separation of 150 kpc and within a line-of-sight velocity separation of 1000 km s − . Where the spatialor kinematic criteria were not met, the system was classi-fied as a group environment. The impact parameters rangefrom 18 < D <
203 kpc. The isolated galaxies are roughly L ∗ galaxies, with a halo mass range of 10 . < log M h / M (cid:12) < . (cid:104) log M h / M (cid:12) (cid:105) = 11 . I col-umn densities ranging from 13 . < log N H I < .
9. Using thesame methods we use here, Pointon et al. (2019) estimatedCGM metallicities ranging from − . < [Si/H] < . (cid:104) [Si/H] (cid:105) = − . Sample Comparison
The sample investigated here is a collation of quasar fieldsthat have been previously spectroscopically surveyed (see Ta-ble 2 and Pointon et al. 2019). Consequently, each survey hasdifferent levels of completeness but typically have a luminos-ity sensitivity of 0 . L ∗ . Fields drawn from the COS Halossurvey have been probed out to a distance of 150 kpc (seeTumlinson et al. 2013; Werk et al. 2013), while other fieldshave been investigated out to at least 350 kpc (see Pointonet al. 2017; Nielsen et al. 2018; Kacprzak et al. 2019; Ng et al.2019, for further details). It is possible that isolated galaxiesidentified in the COS Halos survey may be a member of agroup which extends beyond the survey regions. To investi-gate this, we repeated all statistical tests with the COS Halosgalaxies removed from the isolated sample. We do not findany difference in results with the COS Halos fields removedand hence, included all galaxies in our full isolated sample(Tables 3 and 6).The isolated and group environment samples both probe asimilar range of impact parameters and luminosities as shownin Figure 1(a) and (b). The isolated galaxies are orange, thenearest group galaxy members are solid purple and the re-maining group galaxy members are hatched purple. We testthe null hypothesis that the group galaxies are drawn fromthe same population as the isolated sample with an Anderson-Darling test and find that there is no significant difference be-tween the impact parameter (0 . σ ) and luminosity (1 . σ ) dis-tributions. The details of this test and additional Anderson-Darling tests are shown in Table 3.Furthermore, we show the redshift distribution of isolatedand group environment absorbers in Figure 1(c). Isolatedgalaxy-absorber pairs are shown in orange, while group envi-ronment absorbers are shown in purple. Although the redshiftdistribution of group environments covers a smaller rangethan that of the isolated environments, an Anderson-Darlingtest cannot rule out the null hypothesis that both are drawnfrom the same population (1 . σ ).The galaxy redshift and luminosity relationship for thegroup and isolated environments is then compared in Fig-ure 1(d). The group and isolated environment samples covera similar range of luminosities, although the group environ-ments only cover a range of redshifts up to z = 0 . . We do not have galaxy groups or pairs above z=0.4, whichraises the possibility that the isolated galaxies at redshifts z > . z < .
4. Anderson-Darling tests between the z < . . σ , 0 . σ and 0 . σ , respectively). Throughout the pa-per, we find that comparisons between group environmentsGM M ETALLICITIES IN G ROUP E NVIRONMENTS z < . ANALYSISThe metallicities of each group environment have beeninferred using the same method describe in Pointon et al.(2019). We summarize the analysis in the following section.3.1.
Spectral Analysis
Each transition was modeled using the VPFIT software(Carswell & Webb 2014) to measure the total column density.For COS spectra, we calculated the non-Gaussian line spreadfunction (LSF) for each absorption profile using the detailsin Kriss (2011) and the corresponding lifetime position. The
FUSE data were assumed to have a Gaussian LSF and a ve-locity resolution of 20 km s − (FWHM). For the optical datafrom HIRES and UVES, we assumed a Gaussian LSF and avelocity resolution of 6 . − .We searched for and identified up to 40 different ionic tran-sitions within ±
400 km s − of the median redshift of thegalaxy group members. We required each absorption sys-tem to have measurable H I absorption features, while ad-ditional metal lines had to have reasonably consistent kine-matic structure. That is, it is expected that Mg II absorptionshould have similar velocity structures to Si II absorption pro-files, though not necessarily to higher ionization lines whichcould arise in different phases. Where velocity profiles wereunsaturated and uncontaminated by other absorption features,we fit one or more Voigt components to the absorption pro-file. To ensure that we did not over-fit the spectra, we at-tempted to minimize the reduced chi-squared value. However,we also required that each component still had to maintain areasonable Doppler parameter, because extremely broad com-ponents ( b >
100 km s − for H I and b >
50 km s − for metals)are not physical. In some cases, this resulted in a model whichwas physically motivated, rather than determined by the chi-squared value.In some absorption profiles, blends due to either contam-inating gas at other redshifts or from overlapping ions wereidentified. In some cases, the blends were easily recognizabledue to the velocity structure of the absorption profiles of otherionic transitions. However, some blends were only apparentdue to the lack of consistency between the absorption profilesof different transitions of the same ionic species. Where pos-sible, additional Voigt profile components were added to thefit to model the blend. In some cases, it was not possible todistinguish the blended absorption from the absorption pro-file of interest. Instead, the total column density calculatedwas used as a conservative upper limit on the column density.We discuss the treatment of blends for individual systems inFigure Set 1 where we present the fits.Many of the H I absorption profiles were saturated, mak-ing it difficult to accurately determine the H I column den-sity. If some lines of the H I Lyman series were unsaturatedor damping wings were present in the absorption profile, itwas possible to obtain an accurate column density measure-ment. However, in the absence of unsaturated H I Lyman se-ries transitions, there exists a degeneracy between the H I col-umn density and Doppler parameter. That is, for a particularsaturated H I column density, the Doppler parameter may vary.Therefore, increasing the number of fitted components for asaturated absorption profile will increase the H I column den-sity. Although it is expected that the CGM is kinematically complex, resulting in many velocity components for H I , thestructure cannot be determined in a saturated absorption pro-file. Therefore, we assume that a basic one or two componentfit represents the lower limit on the H I column density. Due tothe lack of damping wings in the absorption profile, the upperlimit on the H I column density is then log N H I < . − .Absorbers with column densities above this limit have damp-ing wings are are classified as sub-DLAs or DLAs .Where metal transitions were saturated, we used the fit tothe profile as a lower limit on the column density. If no metalabsorption was detectable, we calculated 3 σ upper limits onthe column density using a single cloud with an assumedDoppler parameter of b ∼ − , derived from the averageSi II Doppler parameter. Pointon et al. (2019) found no signif-icant impact on the metallicity if a larger Doppler parameter( b = 30 km s − ) was used.We show the results of the fitting analysis in Figure 2 forabsorption associated with the galaxy group J0228, z abs =0 . z abs = 0 . Fig. Set 1. The fits to each system
The analysis method used enables the determination of col-umn densities for H I Lyman series, C II , C III , C IV , N II , N III ,N V , O I , Si II , Si III , Si IV , Ca II , Mg I , Mg II and Fe II , whichare then applied in the ionization modelling to determine themetallicity of the CGM. We note that the O VI column den-sities are presented in Pointon et al. (2017) and the fits areshown in this work for completeness.3.2. Ionization Modelling
A single low ionization phase metallicity for each groupenvironment is calculated by comparing a grid of predictedcolumn densities modeled by the ionization modeling suiteCloudy to the column densities calculated in the previous sec-tion. Cloudy uses the input ionization conditions, set by theH I column density, N H I , hydrogen density, n H and metallic-ity, [Si/H], to predict the column densities of the metals inthe gas (Ferland et al. 2013). Typical grids cover a range − . < log n H < − . − , 13 . < log N H I < . − and − . < [Si / H] < .
5. We assumed a uniform layer of gas,with no dust and solar abundance ratios, is irradiated by abackground UV spectrum. The gas is also assumed to besingle-phase, leading to the exclusion of the highly ionizedO VI gas from the analysis. For consistency with Lehner et al.(2013), Wotta et al. (2016), Wotta et al. (2019) and Pointonet al. (2019), we adopt the ionizing background spectrum de-scribed by the Haardt and Madau 2005 model (HM05; Haardt& Madau 2001, as implemented in Cloudy). The shape of We follow the definition in Lehner et al. (2018), Wotta et al. (2019)and Pointon et al. (2019) for the classification of H I absorbers. The H I column density ranges for pLLSs are 16 . < log N H I < .
2, LLS have17 . ≤ log N H I < .
0, sub–DLAs have 19 . ≤ log N H I < . N H I ≥ . P OINTON ET AL . N u m b e r o f G a l a x i e s . . . . . . . . . . L B /L ∗ B )024681012 N u m b e r o f G a l a x i e s Isolated Galaxies Nearest Group Galaxies Remaining Group Galaxies0 . . . . . . . z gal )024681012 N u m b e r o f A b s o r b e r s . . . z gal )0 . . . . . . . G a l a xy L u m i n o s i t y , ( L B / L ∗ B ) (a) (b)(c) (d) Figure 1.
The distribution of isolated galaxies (orange) compared to the distribution of the nearest group galaxy member (solid purple) and all group galaxiesmembers (hatched purple) for impact parameter (a), luminosity (b) and redshift (c). Anderson-Darling tests show that there is no significant difference betweenthe impact parameter (0 . σ ) and luminosity (1 . σ ) distributions. The galaxy luminosity as a function of redshift for isolated galaxies (orange circles) and allgroup members (purple crosses) are shown in (d). Our luminosity sensitivity is comparable between the group and isolated environment samples until below z = 0 .
4, above which we currently do not have group environment data. Although the lack of group environments above z = 0 . z < . the ionizing background, which can have an impact on themetallicity (Fechner 2011), is also assumed to only evolvewith redshift.The metallicity and ionization parameter of each absorptionsystem are then inferred by a MCMC technique described byCrighton et al. (2013). The column densities in each grid pointcalculated by Cloudy are compared to the measured columndensities. Upper and lower limits are treated as one-sidedGaussians by the likelihood function. Priors were set to theboundaries of the Cloudy ionization grids in most cases or tothe upper or lower limits of the H I column density, shown inthe column density tables. For each group, we initialize theMCMC analysis with 100 walkers and a burn-in of 200 steps.The final distributions of the MCMC walkers, from which weinfer the metallicity and ionization parameter, are then deter-mined by another 200 steps. Fig. Set 2. The posterior distribution profiles from theMCMC analysis
The MCMC posterior distributions and histograms for J0228, z abs = 0 . U , hydrogen number density, log n H and H I col-umn density, log N H I , from left to right. The posterior dis-tributions of the MCMC walkers are shown. Darker orangeindicates regions of higher probability. The final distributionsof the MCMC walkers for each parameter are the green his-tograms at the end of each row, with the 68% uncertaintiesand their average or the 95% upper limit labelled above andindicated by black lines. The plots for the remaining systemsare shown in Figure Set 2. Table 5 shows the inferred modelparameters for the full sample, where we quote the most likelyvalue, using the 68% level as the uncertainty or the 95% levelfor an upper limit. RESULTSHere we present the group environment CGM metallicitiesand their relation with HI column densities and impact pa-rameters. We also compare the group environment propertiesto the isolated galaxy properties presented in Pointon et al.GM M
ETALLICITIES IN G ROUP E NVIRONMENTS Table 3
Anderson-Darling Test ResultsVariable Anderson-Darling Test Statistic p -value Confidence Level σ Comparison of the Isolated Sample without COS Halos galaxies with the Group Sample (see Section 2.5)Metallicity, ([Si/H]) 2 .
72 0 .
03 96 .
80 2 . D ) 0 .
15 0 .
98 2 .
15 0 . D ) 0 .
19 0 .
93 6 .
60 0 . D ) 3 .
10 0 .
04 96 .
05 2 . D ) 0 .
16 0 .
96 3 .
85 0 . L B / L ∗ B ) 2 .
56 0 .
06 93 .
60 1 . z ) 1 .
10 0 .
29 70 .
95 1 . .
17 0 .
02 98 .
45 2 . D ) 0 .
41 0 .
70 30 .
40 0 . D ) 0 .
28 0 .
88 11 .
70 0 . D ) 2 .
16 0 .
09 90 .
70 1 . D ) 0 .
44 0 .
66 33 .
60 0 . L B / L ∗ B ) 2 .
42 0 .
07 92 .
65 1 . z ) 1 .
47 0 .
23 76 .
95 1 . z < . .
81 0 .
06 93 .
65 1 . D ) 0 .
22 0 .
90 9 .
55 0 . D ) 0 .
17 0 .
96 4 .
50 0 . D ) 2 .
42 0 .
08 92 .
00 1 . D ) 0 .
25 0 .
86 14 .
05 0 . L B / L ∗ B ) 1 .
75 0 .
16 84 .
00 1 . z ) 0 .
37 0 .
73 26 .
70 0 . Table 4
J0228, z abs = 0 . N (cm − ) log N Error (cm − )H I .
26 0 . II < . ··· C III .
89 0 . II < . ··· N III .
89 0 . V .
53 0 . I < . ··· Si II < . ··· Si III < . ··· Si IV < . ··· Note . — Table 3 is published in its entirety in the electronic edition ofthe
Astrophysical Journal . A portion is shown here for guidance regard-ing its form and content. The full version contains all 13 sources. (2019).It is possible that group environments may alter the CGMmetallicity. To test this, we compare the metallicity as a func-tion of H I column density between group and isolated en-vironments in Figure 4(a). Group absorbers are purple cir-cles while isolated absorbers are grey squares. Filled sym-bols indicate metallicity measurements, while open symbolsrepresent limits. The group environment sample appears tooverlap the isolated sample. A 1D Anderson-Darling testwhich accounts for upper limits indicated that the metallicitydistribution of the group and isolated environment absorbersare drawn from the same population (2 . σ ; 1 . σ for the z < . − . ± . − . ± .
23) and [Si/H] = − . ± .
16 ( − . ± . . σ or 0 . σ , respectively). Similarly, the median (mean) metallicity for the z < . − . ± .
18 ( − . ± .
14) and hence thereis no significant difference compared to the isolated samplefor the median or mean (0 . σ or 0 . σ , respectively).Using Illustris simulations, Hani et al. (2018) studied the ef-fect of a major merger on the CGM. They found that the post-merger CGM metallicity was 0 . . > . σ difference betweenthe mean metallicity of the group and isolated environments.We use N = (3 × ( σ g + σ i ) / | µ g − µ i | ) , where the mean and er-ror on the mean for the group environments are represented by µ g and σ g , respectively. Similarly, the mean and error on themean for the isolated environment sample is given by µ i and σ i , respectively. We determine that we would need to observeat least 36 group environments to observe a difference in themean metallicity, assuming that the observed distributions arerepresentative of the true metallicity distribution.Previous studies have not detected an anti-correlation be-tween the H I column density and the CGM metallicity ofisolated galaxies when the HM05 ionizing background wasused in the Cloudy model (Chen et al. 2017; Zahedy et al.2019; Wotta et al. 2019; Pointon et al. 2019). The presence ofan anti-correlation in Prochaska et al. (2017) is thought to bedue to the use of the HM12 ionizing background (Wotta et al. P OINTON ET AL . . . . λ o =1215.67 CIII λ o =977.02 OI λ o =1039.23 SiII λ o =1193.290 . . . λ o =1025.74 NII λ o =1083.99 OI λ o =988.77 SiII λ o =1260.420 . . . λ o =972.54 NIII λ o =989.80 OVI λ o =1031.93 SiII λ o =1304.370 . . . λ o =949.74 NV λ o =1238.82 OVI λ o =1037.62 SiIII λ o =1206.500 . . . λ o =1334.54 NV λ o =1242.80 SiII λ o =989.87 SiIV λ o =1393.76 − −
100 0 1000 . . . λ o =1036.34 − −
100 0 100OI λ o =1302.17 − −
100 0 100SiII λ o =1190.42 − −
100 0 100SiIV λ o =1402.77 Velocity (km/s) N o r m a li ze d F l u x Figure 2.
The fits for J0228, z abs = 0 . III transitionwas real or a part of the complex of lines on the positive side of the spectra. Therefore, we have assumed that the column density from the Si
III fit is an upperlimit and it is shown in cyan. The total O VI fit is shown from Pointon et al. (2017) for completeness, but is not used in the models. Plots for the rest of the sampleare shown in Figure Set 1. Table 5
MCMC OutputJ-Name z abs Meas. log N H I a [Si/H] b log N H I b log n H b log U b (cm − ) (cm − ) (cm − )J0125 0 . . ± . < .
06 15 . . . < − . < − . . . ± . − . − . − . . . . − . . . − . . . J0228 0 . . ± . < .
65 14 . . . < − . < − . . . ± . − . − . − . . . . − . . . − . . . J0407 0 . . ± . − . − . − . . . . − . . . − . . . J0407 0 . c . ± . − . − . − . . . . − . . . − . . . J0853 0 . . ± . − . − . − . . . . − . . . − . . . J0910 0 . . ± . − . − . − . . . . − . . − . − . . − . J0925 0 . . ± . − . − . − . . . . − . . . − . . . J0928 0 . . ± . − . − . − . . . . − . . . − . . . J1009 0 . . ± . − . − . − . . . . − . . . − . . . J1119 0 . . ± . < .
69 13 . . . < − . < − . . . , . − . − . − . . . . − . . . − . . . H I column density measured from the Voigt profile modelling of the absorption profiles. b The most likely value with the 68% uncertainties from the MCMC analysis. For upper limits,we take the 95% upper uncertainty. c Results from ionization modelling taken from Muzahid et al. (2018).
GM M
ETALLICITIES IN G ROUP E NVIRONMENTS − . ± . − . − . − . l og U − . ± . − . − . − . l og n H − . ± . − . − . − . / H]15 . . . . l og N H I − . − . − . U − . − . − . n H . . . N HI . ± . Figure 3.
Posterior distribution profiles from the MCMC analysis of theCloudy grids for J0228, z abs = 0 . U , log n H and log N H I . On theend of each row, the distributions of each of those parameters are shown ingreen where the 68% confidence levels and the mean are shown above andindicated the black vertical lines. Plots for the rest of the sample are shownin Figure Set 2 I column density and CGM metallicity for groupenvironments. A Kendall-tau rank correlation test, which ac-counts for metallicity upper limits, finds that we do not de-tect a significant anti-correlation between group environmentCGM metallicity and H I column density (0 . σ ). The de-tails of this test and additional Kendall-tau rank correlationtests are shown in Table 6. This is consistent with the non-detection of an anti-correlation between the CGM metallicityand H I column density for isolated galaxies (2 . σ ; Pointonet al. 2019). Our ability to detect an anti-correlation is depen-dent on the size of the sample. Due to the large scatter andlimited sample size of the metallicity in group environments,it is impossible to rule out the presence of an anti-correlation.In Figure 4(b), we present the CGM metallicity as a func-tion of impact parameter for the group environment and iso-lated galaxy samples. The groups are purple, where the near-est and furthest galaxy members from the quasar sight-lineare represented by circles, while any other group membersare marked by a purple cross, all joined by a line. The iso-lated galaxy–absorber pairs are grey squares. Closed symbolsrepresent metallicity measurements, while open symbols rep-resent metallicity upper limits. We perform Anderson-Darlingtests, which accounts for upper limits, comparing the impactparameter distributions of the isolated sample to three dif-ferent measures of impact parameter in group environments:the nearest galaxy member, the mean impact parameter andthe most luminous galaxy. We find that the differences be-tween the isolated galaxy and the three group environmentimpact parameter distributions are statistically insignificant(1 . σ , 0 . σ and 0 . σ , respectively). Similarly, the differencebetween the z < . . σ , 0 . σ and 0 . σ ) Additionally we test for a correlation between the group CGM metallicity and thenearest galaxy impact parameter by doing a Kendall-tau rankcorrelation test, taking upper limits into account. We do notdetect a significant relationship (1 . σ ). This is consistent withPointon et al. (2019) who found no trend between the impactparameter of isolated galaxies and the CGM metallicity, al-though metallicities are rarely measured beyond 120 kpc dueto a lack of metal detections.Lehner (2017) presented results investigating the metallic-ity of 6 pLLS+LLS where they identified more than one po-tential galaxy which could be associated with the absorptionfeature. Due to the preliminary nature of the results, the au-thors refrain from drawing any conclusions from the data.However, they suggest it may be possible that for [X/H] ≥ − < −
1, may be associated with individual galaxies inall but one absorber. We investigate this possible cause ofa metallicity bimodality due to group environments by bifur-cating the group and isolated samples at [Si/H]= − I column density andimpact parameter for high and low metallicities.In both panels of Figure 5, the H I column density is plottedas a function of metallicity. Group environments are purple orgreen circles, while isolated galaxies are grey squares. Figure5(a) shows [Si/H] < − ≥ − I column density range compared to Lehner (2017) who in-vestigated pLLS and LLS with a H I column density rangeof 16 . < log N H I < .
0. However, since a comparable rangeof metallicities and H I column densities are observed for bothgroup environments surveyed in this paper and isolated galax-ies in Pointon et al. (2019), we suggest that the peaks of themetallicity bimodality observed by Lehner et al. (2013) andWotta et al. (2016, 2019) are not driven by environment.Additionally, we test for an anti-correlation between the H I column density and the impact parameter for group environ-ments using a Kendall-tau rank correlation test for the en-tire sample (1 . σ ), low metallicity absorbers (1 . σ ) or highmetallicity absorbers (0 . σ ), where the nearest galaxy impactparameter was used. For the isolated sample, a Kendall-taurank correlation test finds that the entire sample has a sig-nificant anti-correlation between the H I column density andthe impact parameter (3 . σ ). The same test on the z < . I column density and the impactparameter (2 . σ ), due to the smaller sample size. Isolatedgalaxy high and low metallicity absorbers do not have signifi-cant anti-correlations between the H I column density and im-pact parameter (1 . σ and 1 . σ , respectively for the full sam-ple; 1 . σ and 1 . σ , respectively for the z < . I column density andnearest galaxy impact parameter for the entire group sampleis most likely due to the limited sample size in group envi-ronments. However, if the lack of anti-correlation is due toa physical process in group environments such as tidal strip-ping, higher metallicity gas may be distributed to larger im-pact parameters.It is plausible to expect that the CGM of galaxies with simi-0 P OINTON ET AL .
14 15 16 17 18 19 20H i Column Density, log N H i (cm − ) − . − . − . − . − . . . M e t a lli c i t y ,[ S i / H ] Isolated Isolated Upper Limit Group Group Upper Limit0 50 100 150 200 250 300 350Impact Parameter (kpc) − . − . − . − . − . . . M e t a lli c i t y ,[ S i / H ] (a) (b) Figure 4.
CGM metallicities for group and isolated environments as a function of (a) H I column density and (b) impact parameter. Group environment CGMmetallicities are purple filled circles, while metallicity upper limits are purple open circles. Isolated environment CGM metallicities are grey squares, while themetallicity upper limits are grey open squares. Since a group has, by definition, multiple galaxies associated with a given absorption system, we plot the impactparameter of each galaxy in a group and connect these galaxies with a horizontal line. Group galaxies that are nearest to and farthest from the quasar sightlineare plotted as circles, while galaxies at intermediate impact parameters are plotted as crosses. Table 6
Kendall-Tau Test Results a Sample Independent Variable Dependent Variable Tau Statistic p -value Confidence Level σ Rank Correlation Tests for the Isolated Sample without COS Halos galaxies (see Section 2.5)Isolated Closest Galaxy Impact Parameter, D H I Column Density, N HI . < .
01 99 .
52 2 . > − . D H I Column Density, N HI .
00 0 .
80 19 .
54 0 . < − . D H I Column Density, N HI .
00 0 .
19 81 .
43 1 . I Column Density, (log N H I ) Metallicity, ([Si/H]) − .
38 0 .
86 14 .
23 0 . D ) Metallicity, ([Si/H]) − .
38 0 .
33 67 .
48 0 . D ) H I Column Density, (log N H I ) 0 .
00 0 .
25 75 .
45 1 . ≥ − . D ) H I Column Density, (log N H I ) − .
14 0 .
88 11 .
94 0 . < − . D ) H I Column Density, (log N H I ) 0 .
00 0 .
22 77 .
93 1 . D ) H I Column Density, (log N H I ) 2 . < .
01 99 .
93 3 . ≥ − . D ) H I Column Density, (log N H I ) 0 .
00 0 .
34 66 .
30 0 . < − . D ) H I Column Density, (log N H I ) 0 .
00 0 .
12 88 .
25 1 . z < . D H I Column Density, N HI . < .
01 99 .
23 2 . > − . D H I Column Density, N HI .
00 0 .
34 66 .
30 0 . < − . D H I Column Density, N HI .
00 0 .
24 75 .
51 1 . a We use the Kendall-Tau formulation described by Brown et al. (1973) which accounts for upper limits, as implemented in ASURV (Feigelson & Nelson1985; Isobe et al. 1986; Isobe & Feigelson 1990). lar mass may be affected differently to those with higher massratios. Nielsen et al. (2018) found that groups with similarmass galaxies may have larger Mg II equivalent widths andvelocity dispersions compared to groups with differing massgalaxies. Assuming that the B -band luminosity is a proxy forgalaxy mass, we define galaxy–galaxy groups, which maylater form a major merger, as those with a luminosity ra-tio between the most and second most luminous galaxies of L / L < .
0. In contrast, a galaxy–dwarf group, which maybecome a minor merger, has a luminosity ratio of L / L ≥ .
0. To probe the effect of mass ratios on the CGM metallicitywe compare high and low metallicity for galaxy–galaxy andgalaxy–dwarf groups in Figure 5. Galaxy–galaxy groups arepurple circles, while galaxy–dwarfs are green circles.We find that all but one galaxy–dwarf groups have highmetallicities, while galaxy–galaxy groups have both highand low metallicities. The metallicity medians (means) forthe galaxy–galaxy and galaxy–dwarf group environments are − . ± . − . ± .
3) and − . ± . − . ± . ETALLICITIES IN G ROUP E NVIRONMENTS H i C o l u m n D e n s i t y ,l og N H i ( c m − ) Isolated Galaxy–Galaxy Groups Galaxy–Dwarf Groups0 50 100 150 200 250 300 350Impact Parameter (kpc)13141516171819 H i C o l u m n D e n s i t y ,l og N H i ( c m − ) Low Metallicity, [Si/H] < − . ≥ − . (a) (b) Figure 5. H I column densities of group and isolated environments as a function of impact parameter for (a) low metallicity ([Si/H] < − .
0) and (b) high metallicity([Si/H] ≥ − . and galaxy–dwarf samples differ by 1 . σ (1 . σ ) and thus itis unclear if the masses of the galaxies within group environ-ments play a role in the enrichment of the CGM.The errors on the median or mean metallicities are highlydependent on the sample size, limiting our ability to finda significant difference in the metallicities of the galaxy–galaxy and galaxy–dwarf group environments. Therefore,we attempted to predict how many groups would be requiredto measure a 3 σ difference between the two samples using N = (3 × ( σ gd + σ gg ) / | µ gd − µ gg | ) , where the mean and erroron the mean for the galaxy–galaxy sample are represented by µ gg and σ gg , respectively. Similarly, the mean and error on themean for the galaxy–dwarf sample is given by µ gd and σ gd ,respectively. We determine that we would need to observe atleast 6 group environments in each subsample to detect a sig-nificant difference in the mean metallicity, assuming the ob-served distributions are representative of the true metallicitydistribution. DISCUSSIONOur “Multiphase Galaxy Halos” Survey has probed theCGM metallicity in 13 z < . I column densities (13 . < log N H I < . z = 0 . I column density and metallicity in groupenvironments (0 . σ ), consistent with isolated environments(2 . σ ; Pointon et al. 2019). However, we note that the smallsample size of the groups makes it difficult to investigate thisfurther. The lack of anti-correlation is consistent with Wottaet al. (2019) who find that LLS and pLLS have a metallicityrange of − < [X/H] <
0, which narrows to − . < [X/H] < II gas through anintragroup medium. If it is assumed that Mg II detections areanalogous to CGM metallicity detections, we can predict thatan intragroup medium would also result in a flatter relation-ship between CGM metallicity and impact parameter. Un-fortunately, it is not possible to determine if the lack of rela-tionship between CGM metallicity and impact parameter ingroup environments results from an intragroup medium dueto the small sample size.It has been found in simulations that the post-merger CGMmetallicity is 0 . . . OINTON ET AL .ments in this survey are loose groups and may not yet be grav-itationally bound. The lack of difference between the CGMmetallicity of group and isolated environments is consistentwith the possibility that any interactions in the group environ-ments have not yet had sufficient time to increase the metal-licity and that differences between group and isolated envi-ronment metallicities may only be detected for major mergerssimilar to the event simulated by Hani et al. (2018).Using the FIRE simulations, Anglés-Alcázar et al. (2017)found that the dominant accretion mechanism for CGM gasat z < z < . . I columndensity around isolated galaxies decreases with increasing im-pact parameter (e.g., Lanzetta et al. 1995; Tripp et al. 1998;Chen et al. 2001a; Rao et al. 2011; Borthakur et al. 2015;Curran et al. 2016; Prochaska et al. 2017; Pointon et al.2019). However, given the flattened relationship betweenMg II equivalent width and impact parameter for group envi-ronments (e.g. Chen et al. 2010a; Bordoloi et al. 2011; Nielsenet al. 2018), it is reasonable to expect that the H I may be sim-ilarly affected. Indeed, the H I column density has no signifi-cant anti-correlation with the impact parameter of the nearestgroup galaxy. We also do not find any anti-correlation be-tween the H I column density and nearest galaxy impact pa-rameter for either high ([Si/H] ≥ − .
0) or low ([Si/H] < − . II is assumed to be a proxy for metallicity,the stronger equivalent widths in group environments foundby Chen et al. (2010a); Bordoloi et al. (2011); Nielsen et al.(2018) are somewhat in tension with our finding that the CGMmetallicity distribution is not significantly different to that ofisolated galaxies. However, it is important to note that of the7/13 group environments in the survey where Mg II was cov-ered, there were 4 absorbers and 3 non-absorbers. The in-ferred metallicities for 9/13 galaxies were dependent on thehigh ionization states of N V , Si IV or C IV . Therefore, the as-sumption that Mg II is a proxy for metallicity does not hold forall group environments. Studies of the highly ionized gas ingroup environments have found that oxygen and carbon tendto be ionized above O VI and C IV (e.g Burchett et al. 2016;Oppenheimer et al. 2016; Pointon et al. 2017; Ng et al. 2019).Therefore, it is possible that combining a single phase gasmodel with highly ionized gas has lead to the metal content ofcarbon, nitrogen or silicon to be underestimated, resulting in lower metallicities.Lehner (2017) also investigated the relationship betweenH I column density and impact parameter for group environ-ments. While they did not draw any conclusions from theirpreliminary results they find a hint that low metallicity sys-tems could be associated with isolated environments, whilehigh metallicity absorbers may be associated with groups.Following this suggestion, after bifurcating the metallicity ofgroup environments at centre of the bimodal metallicity dis-tribution found by Lehner et al. (2013) and Wotta et al. (2016,2019) ([Si/H]= − . II absorption (Nielsenet al. 2018), where groups with similar member galaxy lumi-nosities may have larger equivalent widths and velocity dis-persions than groups with different member galaxy luminosi-ties. The authors suggested that galaxy–galaxy group envi-ronments may be more efficient at causing enhanced star for-mation and/or tidal stripping of gas. We used the B -band lu-minosity ratio as a proxy for galaxy mass to classify groupsas galaxy–galaxy group ( L / L < .
0) or galaxy–dwarf group( L / L ≥ .
0) environments. Using the same metallicity cut([Si/H]= − .
0) as Lehner (2017), we found that all but onegalaxy–dwarf group environments were associated with highmetallicity gas, while galaxy–galaxy groups were associatedwith both high and low metallicity gas. Although, we did notfind a significant difference in the median or mean metallic-ities of galaxy–galaxy group and galaxy–dwarf group envi-ronments, a simple model of the group subsamples predictsthat observing nine or more high and low metallicity groupenvironment CGM absorbers could find a significant differ-ence between the means of the subsample metallicities. Wenote that many of the inferred metallicities rely on highly ion-ized gas phases. However, previous studies of O VI and C IV in group environments have found that the high halo mass issufficient to push oxygen to higher ionization states (Burchettet al. 2016; Oppenheimer et al. 2016; Pointon et al. 2017; Nget al. 2019). Galaxy-galaxy group environments may havesufficient mass to have further ionized carbon, nitrogen or sil-icon, resulting in an underestimation of the metal content ofthe gas, which in turn could result in lower metallicities. How-ever, galaxy-dwarf environments may not yet have sufficientmass, and hence temperature, to further ionize the CGM.The metallicities in this study were calculated using thetotal column density along the line-of-sight in the absorber.However, studies of the CGM metallicity around isolatedenvironments have found that the metallicity is not con-stant across an absorption profile (e.g. Churchill et al. 2012;Crighton et al. 2015; Muzahid et al. 2015; Rosenwasser et al.2018; Zahedy et al. 2019; Peeples et al. 2018). In essence,this means that low metallicity gas along the line-of-sight canbe obscured by the presence of high metallicity gas structures,such as accretion, outflows and tidal streams. This effectivelymasks any information about the structure of metals in theCGM. Future studies should attempt to calculate the metallic-ity structure of each individual absorber, which may assist indetermining the characteristics of the CGM in group environ-ments.Although integrated line-of-sight metallicities may obscureGM M ETALLICITIES IN G ROUP E NVIRONMENTS VI or Mg II absorption are associated withan intragroup medium, rather than a superposition of individ-ual halos, it is expected that other gas traces of the halo gas ingroup environments would have a similar structure (Pointonet al. 2017; Nielsen et al. 2018). Component-by-componentmetallicity studies could reveal how individual clumps of gaswithin the CGM halo are amalgamated into an intra-groupmedium. SUMMARY AND CONCLUSIONSWe used the “Multiphase Galaxy Halos” Survey to calcu-late the CGM metallicity of 13 z < . I column density of the CGM gas and theimpact parameters of the group members. Our findings are:1. Group environment CGM metallicities span a largerange of − < [Si/H] < (cid:104) [Si/H] (cid:105) = − . ± .
22. These are consistent with isolatedgalaxy CGM metallicities ( − . < [Si/H] < (cid:104) [Si/H] (cid:105) = − . ± .
14) at the 0 . σ level. There is no signif-icant enrichment of the group environment CGM at z < .
4. Indeed, the similar span of metallicities ingroup and isolated environments suggests that there isno general preferential association of group environ-ments with high metallicity gas.2. We do not detect a significant anti-correlation betweenthe CGM metallicity and the H I column density (0 . σ )in group environments. This is consistent with previ-ous studies which have used the HM05 ionizing back-ground to infer CGM gas metallicities.3. There is no significant anti-correlation between themetallicity and impact parameter of the nearest groupgalaxy, the mean impact parameter or the most lumi-nous galaxy (1 . σ , 0 . σ and 0 . σ , respectively). Thisis consistent with the absence of a relationship betweenthe metallicity and impact parameter in isolated envi-ronments. It may be possible that at low redshifts, pre-vious interactions have enriched the surrounding IGM,resulting in a lack of correlation between impact param-eter and CGM metallicity.4. We do not detect a significant anti-correlation betweenthe H I column density and the impact parameter of thenearest galaxy in group environments. This is contraryto what is detected in the entire isolated sample wherethe H I column density has been measured to decreaseas the distance from the galaxy increases. Although thelack of anti-correlation in group environments may bedue to low number statistics, the flattened relationshipis consistent with Mg II and O VI studies, which havefound evidence for an intragroup medium. 5. We further examine the environments of the groupsby bifurcating the sample at L / L = 3 . − . ± . − . ± . . σ ), all but onegalaxy-dwarf metallicity measurements have [Si/H] > − .
0, while galaxy–galaxy group environments haveboth low and high metallicities. Larger samples shouldbe able to determine if there is a difference between theCGM metallicities of galaxy–galaxy and galaxy–dwarfenvironments.With our sample size, we are unable to confidently detect asignificant enhancement in the CGM metallicity for group en-vironments. While we do not find any metallicity enhance-ment here with environment, samples larger than 36 groupenvironments may find a more metal-rich intragroup medium.Larger samples may also find that a large luminosity ratio,and hence mass ratio, of the galaxies involved increase themetallicity. Regardless, we expect that a strong, detectablemetallicity enhancement may only occur when galaxies arein the process of interacting or merging, which is not repre-sented in our sample. Future work should focus on creatingsamples of galaxy groups that are undergoing different phasesof evolution, e.g, loose groups, compact groups, interactionsand mergers, to fully understand how galaxy environment af-fects the evolution of the CGM metallicity. Furthermore, stud-ies should focus on understanding how the CGM metallicitydiffers along the line-of-sight of each absorption profile sothat high metallicity gas does not obscure metal-poor mate-rial. Such studies may also be able to use the information onthe contribution of each group galaxy to the CGM to test foran intragroup medium or a superposition model using metal-licity as a tracer.We would like to thank John O’Meara for providing HIRESspectra, B. Wakker for providing the
FUSE spectra, NicolasLehner for discussions on the UV ionizing background, andNeil Crighton for the MCMC analysis software and Cloudyionization training. Support for this research was providedby NASA through grants
HST
GO-13398 from the SpaceTelescope Science Institute, which is operated by the As-sociation of Universities for Research in Astronomy, Inc.,under NASA contract NAS5-26555. S.K.P acknowledgessupport through the Australian Government Research Train-ing Program Scholarship. G.G.K, N.M.N, and M.T.M ac-knowledge the support of the Australian Research Councilthrough the Discovery Project DP170103470. Parts of thisresearch were supported by the Australian Research CouncilCentre of Excellence for All Sky Astrophysics in 3 Dimen-sions (ASTRO 3D), through project number CE170100012.Some of the data presented herein were obtained at theW. M. Keck Observatory, which is operated as a scientificpartnership among the California Institute of Technology,the University of California and the National Aeronauticsand Space Administration. Observations were supported bySwinburne Keck programs 2014A_W178E, 2014B_W018E,2015_W018E, 2016A_W056E and 2017A_W248. The Ob-servatory was made possible by the generous financial supportof the W. M. Keck Foundation. The authors wish to recognizeand acknowledge the very significant cultural role and rever-ence that the summit of Maunakea has always had within theindigenous Hawaiian community. We are most fortunate to4 P
OINTON ET AL .have the opportunity to conduct observations from this moun-tain. Based on observations collected at the European Organi-sation for Astronomical Research in the Southern Hemisphereunder ESO programs listed in Table 2.REFERENCES.have the opportunity to conduct observations from this moun-tain. Based on observations collected at the European Organi-sation for Astronomical Research in the Southern Hemisphereunder ESO programs listed in Table 2.REFERENCES