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The CIViL* Survey: The Discovery of a C IV Dichotomy in the CGM of L* Galaxies

T0 review · 3 major / 5 minor · reviewed 2026-08-11 · deepseek-v4-flash

Pith's one-line read C IV absorption in galaxy halos splits sharply by star formation state.

desk verdict A genuinely useful C IV dataset and a probably-true dichotomy, but the headline confidence is overstated and the analysis never controls for the radial gradient shown in its own Figure 2. read the letter →

arxiv 2412.12302 v1 pith:FGMWX2MP submitted 2024-12-16 astro-ph.GA

classification astro-ph.GA
keywords circumgalacticmediumCIVabsorptionL*galaxiesstarformationHST/COSquasarspectroscopygalaxyhalosOVIdichotomy
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper reports that C IV absorption in the gas halos of typical-mass (L*) galaxies splits sharply according to whether the galaxy is actively forming stars. Combining 11 new HST/COS sightlines with archival measurements, the authors find C IV above a column density of $10^{13.5}$ cm$^{-2}$ in 72% of star-forming galaxies but only 23% of passive galaxies, a difference they place above 99% confidence. The result matters because C IV sits between well-studied low-ionization and high-ionization tracers, and if the dichotomy is real it means this intermediate-ionization gas is tied to recent or ongoing star formation, matching the known O VI dichotomy. The paper also derives a minimum carbon mass in the CGM of roughly $3 \times 10^6$ $M_\odot$ within 120 kpc, indicating a substantial carbon reservoir in these halos.

What carries the argument

The load-bearing object is the C IV doublet ($\lambda\lambda1548, 1550$ \AA) seen in absorption against background quasars, which reports the column density of triply ionized carbon along each sightline. The argument runs on detection fractions above a fixed threshold ($\log N_{\rm CIV}/{\rm cm}^{-2} = 13.5$), computed with 2$\sigma$ Wilson binomial confidence intervals, and on comparing the star-forming and passive samples with Anderson-Darling and interval-censored survival tests. The survey design adds NUV COS coverage to galaxies with existing O VI data, so each C IV measurement sits on a galaxy with known stellar mass, impact parameter, and specific star formation rate.

What would settle it

Deep COS spectra of the four star-forming sightlines whose current upper limits exceed $\log N_{\rm CIV}/{\rm cm}^{-2} = 13.5$ would settle whether the 72% fraction is real: if all four turn out to be non-detections, the star-forming fraction drops to 64% and the gap to the passive 23% shrinks though it does not vanish.

Watch

Extended reading notes

Core claim

The central discovery claim is that the circumgalactic medium of L* galaxies contains a C IV dichotomy: star-forming galaxies (sSFR $> 10^{-11}$ yr$^{-1}$) show C IV absorption above $\log N_{\rm CIV}/{\rm cm}^{-2} = 13.5$ in $72^{+14}_{-18}\%$ [21/29] of sightlines, while passive galaxies show it in only $23^{+27}_{-15}\%$ [3/13]. The authors reject the null hypothesis that the two column-density distributions come from the same parent population, at $>99.5\%$ confidence by an Anderson-Darling test ($p = 0.0016$) and at $>2\sigma$ by interval-censored survival tests ($p = 0.017$ and $p = 0.034$). They interpret this as C IV behaving like O VI rather than like low-ionization gas: it traces warm, metal-enriched gas present when galaxies are actively forming stars and largely absent around passive galaxies. A minimum carbon mass of about $3 \times 10^6$ $M_\odot$ out to 120 kpc follows from the mean column densities in three radial bins.

Load-bearing premise

The comparison assumes that excluding upper limits that sit above the detection threshold does not bias the result: four star-forming sightlines are thrown out while no passive ones are, and if those four were true non-detections the star-forming fraction would fall from 72% to 64%.

Editorial extensions

If this is right

  • C IV joins O VI as a tracer of star-formation-linked gas in galactic halos, so intermediate-ionization carbon can be used to track feedback and accretion in the circumgalactic medium.
  • The minimum carbon mass of about $3 \times 10^6$ $M_\odot$ within 120 kpc means the CGM of L* galaxies holds a carbon reservoir comparable to the galaxies' own interstellar medium, not a negligible halo component.
  • The lower-limit CGM gas mass and the depletion time of roughly 1.9 Gyr imply that galaxies need ongoing gas resupply to sustain star formation, since the CGM alone cannot fuel them for more than a couple of gigayears.
  • The dichotomy gives a new observational handle on galaxy transition from the blue cloud to the red sequence: the warm C IV-bearing gas disappears as star formation shuts off.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • If the dichotomy holds in a larger sample, C IV could serve as a practical alternative or complement to O VI for mapping warm gas around galaxies, since C IV is visible in the NUV where COS is efficient.
  • The sharpness of the split suggests a physical connection between star-formation-driven outflows and the presence of warm ionized carbon; simulations of galaxy halos should be tested against the 72% versus 23% numbers rather than only against O VI.
  • Five galaxies near the sSFR cutoff were classified by eye from spectra and morphology, so a blind or automated classification on a larger sample would test whether the dichotomy is as sharp as it appears.
  • Extending the same C IV measurement to higher redshift or to lower-mass galaxies could reveal whether this dichotomy is a universal feature of galaxy halos or specific to L* galaxies at $z \lesssim 0.25$.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 5 minor

Summary. Garza et al. present CIViL*, a new HST/COS program targeting C IV in the CGM of L* galaxies, and combine their 11 new sightlines with archival data from COS-Halos, COS-Dwarfs, and COS-Holes. After restricting to log10 M*/M_sun >= 9.5, they compare C IV detection fractions above log10 N_CIV = 13.5 between star-forming (sSFR > 1e-11 yr^-1) and passive galaxies, finding 72% (21/29) versus 23% (3/13). They claim a dichotomy at over 99% confidence using an Anderson-Darling test, with supporting interval-censored tests at p = 0.017 and p = 0.034. The paper also derives a minimum CGM carbon mass of about 3.03e6 M_sun within 120 kpc and interprets the results as evidence that C IV, like O VI, traces warm gas associated with recent star formation in the halos of L* galaxies.

Significance. If the central claim holds, this is a valuable extension of the well-known O VI dichotomy to C IV in L* galaxies, strengthening the picture that the warm, highly ionized CGM is coupled to recent star formation. The paper's strengths include new public HST/COS data that substantially increase C IV coverage in this regime, the use of Wilson binomial confidence intervals, and a genuinely useful appendix of censored-data tests and threshold variations. The main limitations are the small sample size (46 sightlines after the mass cut, including only 13 passive galaxies) and the fact that the central star-forming/passive comparison has not been controlled for the strong radial gradient in C IV detection fraction that the paper itself demonstrates.

major comments (3)
  1. [Section 3.1 and Figure 2] The central detection-fraction comparison between star-forming and passive galaxies does not control for Rproj/R200c. The paper's own Figure 2 (top panel) and Table A.1 show a steep radial decline in C IV detection fraction, from roughly 70% inside 0.5 R200c to below 10% beyond 1 R200c. Because the combined sample is assembled from surveys with different selection functions and the star-forming and passive subsamples are not shown to have matching Rproj/R200c distributions, the observed 72% versus 23% difference could partly or wholly reflect radial selection rather than a physical dependence on sSFR. A stratified comparison within radial bins, or a regression of detection status on both sSFR and Rproj/R200c, is needed to support the dichotomy claim. This is the most load-bearing issue in the paper.
  2. [Section 3.1, Appendix D, Abstract, and Section 5] The headline claim of 'over 99% confidence' rests on an Anderson-Darling test that treats upper and lower limits as detections, a point the paper itself acknowledges. The interval-censored tests in Appendix D give p = 0.017 (one-sided log-rank) and p = 0.034 (two-sided k-sample test), corresponding to roughly 2.1-2.4 sigma. The abstract and summary should either present the censored-data significance as the primary evidence or explicitly state that the >99% value comes from a test that ignores the censoring structure. Reporting only the limit-naive Anderson-Darling p-value overstates the statistical confidence in the result.
  3. [Section 3.1 and Figure 3 caption] The treatment of upper limits above the detection threshold is asymmetric: four star-forming upper limits are excluded from the denominator while no passive ones are. If those four upper limits are reclassified as non-detections, the star-forming detection fraction drops from 21/29 = 72% to 21/33 = 64%, still higher than the passive 23% but with a larger uncertainty. The paper should present this sensitivity explicitly in the main text and clearly define, for each statistical test, whether the excluded upper limits are counted as detections, non-detections, or omitted.
minor comments (5)
  1. [Title and Section 2.4] The sample size is reported inconsistently: the abstract says 46 observations, Section 2.4 says the combined sample has 65 observations before cuts, and Section 5 says the final sample has 45 lines of sight. These numbers should be reconciled with a single consistent accounting of the mass cut and duplicates.
  2. [Table A.1] In the equal-number radial bins, the last bin is labeled '1.0-2.0' in the first column but the row appears to be missing a closing parenthesis in the confidence interval (the entry reads '0.77' rather than '(0.25, 0.75)'). Also, the 8-bin table lists a bin '1.75-1.0' that should presumably be '1.75-2.0'.
  3. [Appendix B] The 'grey area' classification of five galaxies uses a combination of sSFR, optical spectra, and morphology, but the criteria are not fully quantitative. It would be helpful to state explicitly how many galaxies were reclassified relative to their sSFR bins and whether the main result is robust to moving those borderline objects to the opposite class.
  4. [Section 3.2 and Equation (1)] The carbon mass estimate is based on the Bordoloi et al. (2014) formula with an assumed ionization fraction f_CIV = 0.3. The paper should clarify whether this is intended as a strict lower limit given the possibility of lower f_CIV values, and the role of saturated lower limits in the mean column densities should be explicitly discussed.
  5. [Figure 4] The statement that C IV and O VI 'statistically mirror' the dichotomy is descriptive rather than statistical. No formal comparison of the C IV and O VI samples is presented, so the language should be softened accordingly.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the C IV/sSFR dichotomy is an empirical detection-fraction comparison, not a derived prediction; the carbon-mass estimate is downstream and non-load-bearing.

full rationale

The paper's central claim—that star-forming L* galaxies show a higher C IV detection fraction (72% [21/29]) than passive galaxies (23% [3/13])—is a direct empirical count from the assembled HST/COS spectra and literature measurements. It is not derived from a model, and no fitted parameter is renamed as a prediction. The statistical tests (Anderson-Darling, interval-censored survival analyses) are computed on the observed column densities and limits, so the result is self-contained: the data are the input and the detection-fraction dichotomy is the output. The carbon-mass estimate in Section 3.2 reuses the Bordoloi et al. (2014) formula with an explicitly stated ionization correction (f_CIV = 0.3); this is an external calibration, and it is downstream of the main claim, so any error in that assumption would not feed back into the detection-fraction result. Self-citations (e.g., Garza et al. 2024, Bordoloi et al. 2014) supply data or methodology rather than an unverified uniqueness theorem, and the agreement with Tumlinson et al. (2011) is presented after computing the paper's own statistics. The paper also acknowledges the censor-dependent caveats in Appendix D, reporting p = 0.017 and p = 0.034 for interval-censored tests, which further shows the dichotomy is not an artifact of a single ad hoc choice. No circular step can be exhibited by quoting an equation that reduces to its own inputs.

Assumptions & free parameters 4 free parameters · 4 assumptions · 0 invented entities

The central result is an empirical census, so the ledger is light. The main free parameters are analysis thresholds (C IV detection threshold, sSFR cutoff, stellar mass cutoff) and an assumed ionization correction used only for the secondary carbon mass estimate. The key domain assumptions are that the absorption is associated with the target galaxy's CGM and that the archival samples are representative. No new physical entities are introduced.

free parameters (4)
  • C IV detection threshold = log N_CIV/cm^-2 = 13.5
    Defines detection versus non-detection in the headline fractions; upper limits above this threshold are excluded. Alternatives at 13.75 and 14.0 are tested in Appendix C.
  • sSFR star-forming/passive cutoff = 10^-11 yr^-1
    Adopted from Tumlinson et al. (2011) and Tchernyshyov et al. (2023); galaxies within plus or minus 0.2 dex are reclassified by morphology and spectra in Appendix B.
  • Stellar mass cutoff = log Mstar/Msun >= 9.5
    Applied in Section 3 to remove the dwarf-dominated regime; leaves 46 observations.
  • C IV ionization correction = f_CIV = 0.3
    Assumed in the carbon mass estimate in Section 3.2, following Bordoloi et al. (2014); affects only the mass and depletion-time numbers, not the dichotomy.
assumptions (4)
  • domain assumption Absorption features within about 300 km/s of the galaxy redshift trace the target galaxy's CGM, not unrelated intervening gas.
    Invoked implicitly in Section 2.3 when assigning absorption to galaxies; interloper contamination could in principle differ between star-forming and passive samples.
  • domain assumption The Behroozi et al. (2019) stellar mass-halo mass relation and the Hu and Kravtsov (2003) conversion are valid for the virial radii used to normalize impact parameters.
    Used in Section 2.1 to compute R200c from stellar masses; errors here propagate into radial binning and sample matching.
  • standard math The statistical tests applied (Wilson binomial intervals, Anderson-Darling, interval-censored survival analysis) are valid for small, censored samples.
    The authors rely on these throughout Section 3.1 and Appendix D; the Anderson-Darling test ignores censoring, which is why the censored tests give weaker significance.
  • domain assumption Upper limits that exceed the detection threshold can be excluded without biasing the detection-fraction comparison.
    Four star-forming upper limits are excluded and no passive ones are; if the excluded limits are true non-detections, the star-forming fraction drops from 72% to 64%.

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Cite this review

Pith. "Pith review of The CIViL* Survey: The Discovery of a C IV Dichotomy in the CGM of L* Galaxies." pith.science (2026). https://pith.science/paper/FGMWX2MP

@misc{pith2026241212302,
  author       = {Pith},
  title        = {Pith review of: The CIViL* Survey: The Discovery of a C IV Dichotomy in the CGM of L* Galaxies},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/FGMWX2MP}},
  note         = {Machine review of arXiv:2412.12302}
}
abstract

This paper investigates C IV absorption in the circumgalactic medium (CGM) of L* galaxies and its relationship with galaxy star formation rates. We present new observations from the C IV in L* survey (CIViL*; PID$\#$17076) using the Hubble Space Telescope/Cosmic Origins Spectrograph. By combining these measurements with archival C IV data (46 observations total), we estimate detection fractions for star-forming (sSFR $>$ 10$^{-11}$ yr$^{-1}$) and passive galaxies (sSFR $\leq$ 10$^{-11}$ yr$^{-1}$) to be 72$_{-18}^{+14}$\% [21/29] and 23$_{-15}^{+27}$\% [3/13], respectively. This indicates a significant dichotomy in C IV presence between L* star-forming and passive galaxies, with over 99% confidence. This finding aligns with Tumlinson et al. (2011), which noted a similar dichotomy in O VI absorption. Our results imply a substantial carbon reservoir in the CGM of L* galaxies, suggesting a minimum carbon mass of $\gtrsim$ 3.03 $\times$ 10$^{6}$ M$_{\odot}$ out to 120 kpc. Together, these findings highlight a strong connection between star formation in galaxies and the state of their CGM, providing insight into the mechanisms governing galaxy evolution.

Figures

Figures reproduced from arXiv: 2412.12302 by the authors.

Figure 1
Figure 1. Regions of the HST/COS continuum spectrum showing the C iv λλ 1548 1550 line absorption features of the CIViL⋆ QSO-galaxy pairs set in the rest frame of each individual galaxy. For lines of sight that have multiple components, the individual fits are shown as the dashed purple line where the sum of the components is shown as the solid purple line. The red line in each spectrum represents the continuum flux error. Th… view at source ↗
Figure 2
Figure 2. Top Panel: The C iv detection fraction vs. normalized impact parameter. The shaded areas repre￾sent 2σ Wilson Binomial Confidence Intervals across equal width radial bins. Upper limits exceeding the threshold (log10NCIV/cm−2 = 13.5) are excluded from the analysis. Middle and Bottom Panels: C iv column densities as￾sembled from previous QSO absorption line surveys prob￾ing the CGM of low-z, galaxies (diamonds) with t… view at source ↗
Figure 3
Figure 3. Measured C iv column densities versus sSFR for CIViL⋆ and the additional literature sample, with star forming galaxies (sSFR > 10−11 yr−1 ) are colored in blue while passive galaxies (sSFR ≤ 10−11 yr−1 ) are colored in red. For galaxies in the grey shaded area, we examine their spectra and morphology, in addition to sSFR for classification. Like the previous figure, non-detections (upper limits) are represented with… view at source ↗
Figures from the paper (1 more)
Figure 4
Figure 4. Figure 4: C iv and O vi correlations with galaxy properties. If the marker is dark/ bold, they are from galaxies where both ions were observed. These observations overlay lightly shaded O vi column densities from Tumlinson et al. (2011) and Werk et al. (2013) and C iv observatio…

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  1. Turbulence-dominated CGM: the origin of UV absorbers with equivalent widths of $\sim1$\AA

    astro-ph.GA 2025-04 conditional novelty 6.0 of 10

    FIRE simulations show that the inner CGM of halos below ~10^12 Msun is cool and supersonically turbulent before hot-phase formation, and this turbulence naturally yields the ~1 angstrom equivalent width UV absorbers o...

Reference graph

Works this paper leans on

56 extracted references · 9 canonical work pages · cited by 1 Pith paper

  1. [1]

    , " * write output.state after.block = add.period write newline

    ENTRY address archivePrefix author booktitle chapter doi edition editor eprint howpublished institution journal key month number organization pages publisher school series title misctitle type volume year version url label extra.label sort.label short.list INTEGERS output.state before.all mid.sentence after.sentence after.block FUNCTION init.state.consts ...

  2. [2]

    write newline

    " write newline "" before.all 'output.state := FUNCTION format.url url empty "" new.block "" url * "" * if FUNCTION format.eprint eprint empty "" archivePrefix empty "" archivePrefix "arXiv" = new.block " " eprint * " " * new.block " " eprint * " " * if if if FUNCTION format.doi doi empty "" " " doi * " " * if FUNCTION format.pid doi empty eprint empty ur...

  3. [3]

    adobe:ns:meta/

    thebibliography [1] 20pt to REFERENCES 6pt =0pt -12pt 10pt plus 3pt =0pt =0pt =1pt plus 1pt =0pt =0pt -12pt =13pt plus 1pt =20pt =13pt plus 1pt \@M =10000 =-1.0em =0pt =0pt 0pt =0pt =1.0em @enumiv\@empty 10000 10000 `\.\@m \@noitemerr \@latex@warning Empty `thebibliography' environment \@ifnextchar \@reference \@latexerr Missing key on reference command E...

  4. [4]

    2021, , 504, 65, 10.1093/mnras/stab871

    Anand , A., Nelson , D., & Kauffmann , G. 2021, , 504, 65, 10.1093/mnras/stab871

  5. [5]

    P., Tollerud , E

    Astropy Collaboration , Robitaille , T. P., Tollerud , E. J., et al. 2013, , 558, A33, 10.1051/0004-6361/201322068

  6. [6]

    M., Sip o cz , B

    Astropy Collaboration , Price-Whelan , A. M., Sip o cz , B. M., et al. 2018, , 156, 123, 10.3847/1538-3881/aabc4f

  7. [7]

    N., Jannuzi , B

    Bahcall , J. N., Jannuzi , B. T., Schneider , D. P., et al. 1991, , 377, L5, 10.1086/186103

  8. [8]

    H., Hearin , A

    Behroozi , P., Wechsler , R. H., Hearin , A. P., & Conroy , C. 2019, , 488, 3143, 10.1093/mnras/stz1182

Show all 56 references
  1. [9]

    Berg , T. A. M., Ellison , S. L., Tumlinson , J., et al. 2018, , 478, 3890, 10.1093/mnras/sty962

  2. [10]

    1986, , 155, L8

    Bergeron , J. 1986, , 155, L8

  3. [11]

    X., Tumlinson , J., et al

    Bordoloi , R., Prochaska , J. X., Tumlinson , J., et al. 2018, , 864, 132, 10.3847/1538-4357/aad8ac

  4. [12]

    J., Knobel , C., et al

    Bordoloi , R., Lilly , S. J., Knobel , C., et al. 2011, , 743, 10, 10.1088/0004-637X/743/1/10

  5. [13]

    K., et al

    Bordoloi , R., Tumlinson , J., Werk , J. K., et al. 2014, , 796, 136, 10.1088/0004-637X/796/2/136

  6. [14]

    2015, , 813, 46, 10.1088/0004-637X/813/1/46

    Borthakur , S., Heckman , T., Tumlinson , J., et al. 2015, , 813, 46, 10.1088/0004-637X/813/1/46

  7. [15]

    2024, the Veeper , v1.0, Zenodo, 10.5281/zenodo.10993984

    Burchett, J. 2024, the Veeper , v1.0, Zenodo, 10.5281/zenodo.10993984

  8. [16]

    N., Tripp , T

    Burchett , J. N., Tripp , T. M., Bordoloi , R., et al. 2016, , 832, 124, 10.3847/0004-637X/832/2/124

  9. [17]

    M., & Webb , J

    Chen , H.-W., Lanzetta , K. M., & Webb , J. K. 2001, , 556, 158, 10.1086/321537

  10. [18]

    W., Keeney , B

    Danforth , C. W., Keeney , B. A., Tilton , E. M., et al. 2016, , 817, 111, 10.3847/0004-637X/817/2/111

  11. [19]

    P., & Shaw, P

    Fay, M. P., & Shaw, P. A. 2010, Journal of Statistical Software, 36, 1, 10.18637/jss.v036.i02

  12. [20]

    J., Porter , R

    Ferland , G. J., Porter , R. L., van Hoof , P. A. M., et al. 2013, , 49, 137. 1302.4485

  13. [21]

    S., & Green , J

    Froning , C. S., & Green , J. C. 2009, , 320, 181, 10.1007/s10509-008-9758-y

  14. [22]

    L., Werk , J

    Garza , S. L., Werk , J. K., Oppenheimer , B. D., et al. 2024, , 970, 115, 10.3847/1538-4357/ad4ecc

  15. [23]

    C., Froning , C

    Green , J. C., Froning , C. S., Osterman , S., et al. 2012, , 744, 60, 10.1088/0004-637X/744/1/6010.1086/141956

  16. [24]

    R., Millman, K

    Harris, C. R., Millman, K. J., van der Walt, S. J., et al. 2020, Nature, 585, 357, 10.1038/s41586-020-2649-2

  17. [25]

    2017, , 846, 151, 10.3847/1538-4357/aa80dc

    Heckman , T., Borthakur , S., Wild , V., Schiminovich , D., & Bordoloi , R. 2017, , 846, 151, 10.3847/1538-4357/aa80dc

  18. [26]

    Hu , W., & Kravtsov , A. V. 2003, , 584, 702, 10.1086/345846

  19. [27]

    Hunter, J. D. 2007, Computing in Science & Engineering, 9, 90, 10.1109/MCSE.2007.55

  20. [28]

    D., Chen , H.-W., & Mulchaey , J

    Johnson , S. D., Chen , H.-W., & Mulchaey , J. S. 2015, , 449, 3263, 10.1093/mnras/stv553

  21. [29]

    M., White , S

    Kauffmann , G., Heckman , T. M., White , S. D. M., et al. 2003, , 341, 33, 10.1046/j.1365-8711.2003.06291.x

  22. [30]

    Kwak , K., & Shelton , R. L. 2010, , 719, 523, 10.1088/0004-637X/719/1/523

  23. [31]

    2020, , 897, 97, 10.3847/1538-4357/ab989a

    Lan , T.-W. 2020, , 897, 97, 10.3847/1538-4357/ab989a

  24. [32]

    Lehner , N., & Howk , J. C. 2011, Science, 334, 955, 10.1126/science.1209069

  25. [33]

    B., Howk , J

    Lehner , N., Wotta , C. B., Howk , J. C., et al. 2018, , 866, 33, 10.3847/1538-4357/aadd03

  26. [34]

    2024, pandas-dev/pandas: Pandas , v2.2.1, Zenodo, 10.5281/zenodo.10697587

    pandas development team, T. 2024, pandas-dev/pandas: Pandas , v2.2.1, Zenodo, 10.5281/zenodo.10697587

  27. [35]

    S., Werk , J

    Peeples , M. S., Werk , J. K., Tumlinson , J., et al. 2014, , 786, 54, 10.1088/0004-637X/786/1/54

  28. [36]

    P \'e roux , C., & Howk , J. C. 2020, , 58, 363, 10.1146/annurev-astro-021820-120014

  29. [37]

    Planck Collaboration , Ade , P. A. R., Aghanim , N., et al. 2016, , 594, A13, 10.1051/0004-6361/201525830

  30. [38]

    X., Werk , J

    Prochaska , J. X., Werk , J. K., Worseck , G., et al. 2017, , 837, 169, 10.3847/1538-4357/aa6007

  31. [39]

    X., Tejos, N., Crighton, N., et al

    Prochaska, J. X., Tejos, N., Crighton, N., et al. 2017 a , Linetools/Linetools: Third Minor Release , v0.3, Zenodo, 10.5281/zenodo.1036773

  32. [40]

    X., Tejos, N., cwotta, et al

    Prochaska, J. X., Tejos, N., cwotta, et al. 2017 b , Pyigm/Pyigm: Initial release for publications , v1.0, Zenodo, 10.5281/zenodo.1045479

  33. [41]

    Rubin , K. H. R., Prochaska , J. X., Koo , D. C., et al. 2014, , 794, 156, 10.1088/0004-637X/794/2/156

  34. [42]

    2022, , 60, 319, 10.1146/annurev-astro-021022-043545

    Saintonge , A., & Catinella , B. 2022, , 60, 319, 10.1146/annurev-astro-021022-043545

  35. [43]

    K., Martin , D

    Schiminovich , D., Wyder , T. K., Martin , D. C., et al. 2007, , 173, 315, 10.1086/524659

  36. [44]

    T., Penton , S

    Stocke , J. T., Penton , S. V., Danforth , C. W., et al. 2006, , 641, 217, 10.1086/500386

  37. [45]

    K., Wilde , M

    Tchernyshyov , K., Werk , J. K., Wilde , M. C., et al. 2022, arXiv e-prints, arXiv:2211.06436, 10.48550/arXiv.2211.06436

  38. [46]

    2023, , 949, 41, 10.3847/1538-4357/acc86a

    ---. 2023, , 949, 41, 10.3847/1538-4357/acc86a

  39. [47]

    X., Crighton , N

    Tejos , N., Prochaska , J. X., Crighton , N. H. M., et al. 2016, , 455, 2662, 10.1093/mnras/stv2376

  40. [48]

    S., & Werk , J

    Tumlinson , J., Peeples , M. S., & Werk , J. K. 2017, , 55, 389, 10.1146/annurev-astro-091916-055240

  41. [49]

    K., et al

    Tumlinson , J., Thom , C., Werk , J. K., et al. 2011, Science, 334, 948, 10.1126/science.1209840

  42. [50]

    2013, , 777, 59, 10.1088/0004-637X/777/1/59

    ---. 2013, , 777, 59, 10.1088/0004-637X/777/1/59

  43. [51]

    E., et al

    Virtanen, P., Gommers, R., Oliphant, T. E., et al. 2020, Nature Methods, 17, 261, 10.1038/s41592-019-0686-2

  44. [52]

    K., Prochaska , J

    Werk , J. K., Prochaska , J. X., Thom , C., et al. 2012, , 198, 3, 10.1088/0067-0049/198/1/3

  45. [53]

    2013, , 204, 17, 10.1088/0067-0049/204/2/17

    ---. 2013, , 204, 17, 10.1088/0067-0049/204/2/17

  46. [54]

    K., Prochaska , J

    Werk , J. K., Prochaska , J. X., Tumlinson , J., et al. 2014, , 792, 8, 10.1088/0004-637X/792/1/8

  47. [55]

    S., Chen , H.-W., Johnson , S

    Zahedy , F. S., Chen , H.-W., Johnson , S. D., et al. 2019, , 484, 2257, 10.1093/mnras/sty3482

  48. [56]

    D., et al

    Zheng , Y., Faerman , Y., Oppenheimer , B. D., et al. 2024, , 960, 55, 10.3847/1538-4357/acfe6b

Pith tools

Reviewed August 11, 2026 · model on record in the stance chip above.