XShooter DESI Lens Program: Sample characterization

Aleksandar Cikota; Christophe Boghossian; Christopher Storfer; Eric Jullo; Felipe Urcelay; Jens-Kristian Krogager; Luderic Chapel; Raphael Gavazzi; Xiaosheng Huang

REVIEW 2 major objections 5 minor 54 references

XShooter DESI Lens Program: Sample characterization

T0 review · 2 major / 5 minor · reviewed 2026-07-10 · grok-4.5

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Pith's one-line read XShooter redshifts for 58 lenses and 57 sources show no measurement bias, so the source-z distribution can calibrate large imaging surveys.

desk verdict Solid southern XShooter redshift catalog for DESI Legacy lenses; the “no bias / representative zs” claim is only qualitatively supported by color–magnitude plots and should be treated as provisional. read the letter →

arxiv 2607.08562 v1 pith:XLUED2U6 submitted 2026-07-09 astro-ph.CO

Eric Jullo , Christophe Boghossian , Luderic Chapel , Felipe Urcelay , Christopher Storfer , Xiaosheng Huang , Raphael Gavazzi , Jens-Kristian Krogager

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Aleksandar Cikota

This is my paper · ORCID

classification astro-ph.CO

keywords stronggravitationallensingspectroscopicredshiftsDESILegacySurveysXShootersourceredshiftdistributionsamplecharacterizationgalaxyevolutioncosmology

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

Huge imaging surveys are finding far more strong gravitational lenses than before, but those catalogs only become useful for cosmology and galaxy evolution once redshifts are known and selection effects are under control. This paper reports VLT/XShooter spectra of 67 grade-A lens systems found by neural-network searches in the southern DESI Legacy Imaging Surveys. Redshifts are secured for 58 lenses and 57 sources (45 systems with both). Lenses mostly lie below z ~ 1 and are measured from continuum absorption features; sources span 0.28 < z < 4.34 (median 1.54) and are measured mainly from emission lines. Color–magnitude distributions of successfully measured objects look like those of the full observed sample, so the authors conclude that the spectroscopic success function introduces no obvious bias. The measured source redshift distribution can therefore be treated as representative of the true parent population and used to calibrate forward models and training sets for Euclid, LSST and similar surveys. Along the way the spectra also flag two sources with outflow signatures and seven with rotating disks.

What carries the argument

Quality-flagged XShooter redshifts (Qz = 1–4) extracted from continuum absorption (lenses) and emission lines (sources), combined with a direct comparison of g−r / r−z colors and z-band magnitudes between successful measurements and the full observed set.

What would settle it

A larger, deeper spectroscopic campaign of the same parent catalog that recovers redshifts for a substantial fraction of the currently failed or low-Qz sources and finds a systematically different redshift distribution would falsify the claim of representativeness.

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Extended reading notes

Core claim

Spectroscopic redshifts for 58 lenses and 57 sources drawn from neural-network-selected DESI Legacy Survey lenses show no color- or magnitude-dependent bias relative to the parent observed sample; the resulting source redshift distribution (median zs = 1.54) can therefore be used as a representative calibrator for large imaging-survey analyses.

Load-bearing premise

That matching color and magnitude distributions between systems with good redshifts and the full observed sample is enough to prove the spectroscopic success rate is uniform across the true source-redshift range.

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Signed reviews

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Editorial analysis

A structured set of objections, weighed in public.

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

Desk Editor's Note

read the letter

This is a useful infrastructure paper: 58 lens and 57 source redshifts (45 systems with both) from XShooter on the southern Huang/Storfer grade-A DESI Legacy candidates, with clear Qz flags, success rates (82%/85%), and a long appendix of 1D/2D spectra that let you judge the line IDs yourself. That catalog is the real product. Parallel northern DESI, MUSE, and Keck efforts already exist; this fills the Dec < −20° gap and adds a few kinematic notes (two outflows, seven rotating disks).

What they do well is the observational bookkeeping. Slit placement, reduction choices, quality grades, magnitude limits (lenses mostly need zAB < 20; sources go to 25.2), and the per-system figures are transparent. Citations to the parent imaging papers and the other spectroscopic campaigns are complete. No circularity: redshifts come from standard absorption/emission features against known wavelengths.

The soft spot is exactly the one the stress-test flags, and it is real but not fatal. The abstract and conclusion assert that “no particular bias” in the measurement step means the measured source-z histogram (median 1.54, range 0.28–4.34) is “likely representative” and can calibrate Stage-IV analyses. Support is only the visual color–magnitude comparison (Figs. 3–4) between successful Qz > 2 systems and the observed sample, plus the statement that sources of any magnitude were recovered. Color similarity does not test whether the spectroscopic success function is flat across redshift; emission-line detectability in the NIR arm varies with which lines land where and with sky-line density. They never build a selection function or compare successes vs. failures in redshift-sensitive observables. So the representativeness claim is qualitative and should be used with that caveat. Everything else in the paper stands without it.

Who it is for: anyone building or calibrating strong-lens samples for Euclid/LSST cosmology or galaxy evolution who needs southern spectroscopic redshifts and quality flags. It is not a methods or theory paper. A serious editor should send it to referees; the catalog is solid enough to publish after the authors either quantify the selection function or soften the language around “representative.” I would cite the redshifts and flags; I would not lean on the unbiased-zs claim without further work.

Referee Report

2 major / 5 minor

Summary. The paper reports VLT/XShooter spectroscopy of 67 grade-A strong-lens candidates from the DESI Legacy Imaging Surveys (Huang et al. 2021; Storfer et al. 2024) at Dec < −20°. Redshifts are measured for 58 lenses and 57 sources (45 systems with both), with quality flags Qz = 1–4 based on continuum and emission-line features. The sample yields a source redshift range 0.28 < zs < 4.34 (median zs = 1.54) and a lens distribution mostly at z < 1. The authors also note two sources with outflow signatures and seven with rotating disks. On the basis of magnitude and g−r / r−z color comparisons (Figs. 3–4) between systems with successful redshifts (Qz > 2) and the observed sample, they conclude that no particular bias is associated with the redshift measurement operation, so the measured source-z distribution is likely representative of the true parent distribution and can be used to calibrate analyses in large imaging surveys.

Significance. A homogeneous spectroscopic characterization of a southern DESI Legacy Survey lens sample is a useful community resource, especially given the forthcoming Euclid and LSST strong-lens catalogues. The 82 % / 85 % success rates, the tabulated redshifts with quality flags (Table 2), and the extensive per-system 1D/2D spectral figures constitute a concrete, reusable data product. The identification of outflows and rotating disks adds modest astrophysical interest. The central claim that the measured source-z histogram can be treated as representative for survey calibration is of clear practical value if it holds, but it currently rests on an incomplete empirical test.

major comments (2)

The central claim (Abstract; end of §3; §4) that the measured source redshift distribution is “likely representative of the true one” is supported only by the visual similarity of g−r / r−z colors and magnitudes between systems with Qz > 2 and the observed sample (Figs. 3–4). Color–magnitude similarity does not constrain whether the spectroscopic success function S(z) is flat across 0.28 < zs < 4.34. Emission-line detectability (the dominant Qz = 4 channel) depends on which lines fall into the NIR arm, sky-line density, and continuum S/N—all of which vary strongly with redshift. The paper never constructs a selection function, nor does it compare successful versus failed subsets in any redshift-sensitive observable beyond broadband colors. Without such a test (or an explicit caveat that the histogram is an observed, not completeness-corrected, distribution), the claim that the sample “ca
§3 and Table 2 report 33 % of lens redshifts with Qz < 2 and several source redshifts with Qz = 1–2 (single-line or continuum-only). The text does not state whether the histograms in Fig. 2 or the “representative” claim include only Qz ≥ 3 systems or the full set. Because low-Qz redshifts are more susceptible to line misidentification and sky residuals (explicitly noted for several systems in the appendix figures), the paper should either restrict the science sample to a well-defined quality cut or quantify how the distribution changes when low-Qz objects are excluded.

minor comments (5)

Storfer et al. is cited as 2022 in the Abstract and as 2024 in the body and references; the year should be made consistent.
Table 1 lists program IDs and OB counts but does not give the total on-source exposure or the fraction of grade-A nights; a one-line summary would help readers assess data quality.
Several appendix figure captions (e.g., DESI-024.5133-21.9299, DESI-033.8095-29.1570) discuss alternative line identifications or photometric-redshift tensions; these caveats should be cross-referenced in Table 2 or the main text so that users of the catalogue are aware of them.
Fig. 2 caption and axis labels would benefit from explicit statement of the quality cut (if any) applied to the plotted redshifts.
Minor typographical issues: “XSchooter” (p. 2), “HandK” for H and K lines, and occasional missing spaces around redshifts (e.g., z=0.295).

Circularity Check

1 steps flagged · score 1.0 of 10

Empirical sample characterization with no derivation that reduces to its inputs; only minor non-load-bearing self-citation of the parent imaging catalog.

self citation load bearing [§3, paragraph discussing Fig. 4; also Abstract and §4]
"Given that Huang et al. (2021) did not perform any selection on the sources, this suggests that our redshift distribution of the sources is likely representative of the true one."

Huang is a co-author; the claim that the parent catalog is free of source selection is taken from the collaboration’s own prior imaging paper. This is only a minor premise supporting representativeness and does not force the measured redshifts or the color–magnitude comparison by construction; the redshifts remain independent spectral measurements.

full rationale

The paper reports new VLT/XShooter redshifts for 58 lenses and 57 sources drawn from an imaging neural-network catalog (Huang et al. 2021; Storfer et al. 2024). Redshifts are identified from observed absorption/emission lines against laboratory wavelengths and graded by continuum/line quality (Qz); this is direct measurement, not a fitted model or self-definitional construction. The central claim that the measured source-z distribution is “likely representative” rests on two empirical comparisons internal to the observed sample: (i) success rate versus zAB magnitude (Fig. 3) and (ii) g−r / r−z color distributions of systems with Qz>2 versus the full observed set (Fig. 4), plus the statement that Huang et al. imposed no source selection. These checks do not reduce by construction to any fitted parameter or to a uniqueness theorem; they are falsifiable photometric comparisons. The only self-citation of note is the parent-sample reference (authors overlap), which is used solely to establish that the imaging search did not pre-select sources; it is not load-bearing for the redshift values themselves nor for the color–magnitude test. No ansatz is smuggled, no prediction is a re-labeled fit, and no uniqueness result is imported. The skeptic’s concern that color similarity does not fully constrain S(z) is a completeness/correctness issue, not circularity. Score 1 reflects only the minor, non-circular self-citation of the imaging papers.

Assumptions & free parameters 0 free parameters · 3 assumptions · 0 invented entities

The work is an observational catalog paper. It inherits standard spectroscopic redshift practice and the parent imaging selection; it introduces no free cosmological parameters, no new physical entities, and only domain-standard assumptions about line identification and quality grading.

assumptions (3)

domain assumption Observed emission and absorption lines can be identified with rest-frame atomic transitions (e.g., [O II], Hα, Ca H&K) to assign spectroscopic redshifts.
Standard extragalactic spectroscopy practice used throughout §2–3 and the appendix figures.
domain assumption Quality flags Qz=1–4 correctly rank continuum and emission-line reliability for subsequent statistical use.
Defined in §2 and applied in Table 2; the ‘no-bias’ claim is restricted to Qz>2.
domain assumption The Huang et al. (2021) and Storfer et al. (2024) grade-A candidates form a parent sample whose source population is the target of the representativeness claim.
Selection described in §1–2; the paper does not re-derive the neural-network purity.

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Cite this review

Pith. "Pith review of XShooter DESI Lens Program: Sample characterization." pith.science (2026). https://pith.science/paper/XLUED2U6

@misc{pith2026260708562,
  author       = {Pith},
  title        = {Pith review of: XShooter DESI Lens Program: Sample characterization},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/XLUED2U6}},
  note         = {Machine review of arXiv:2607.08562}
}

abstract

Large imaging surveys in cosmology are detecting orders of magnitude more lens systems than known so far. This unprecedented dataset will lead to robust constraints on cosmology and galaxy evolution models. However, a preliminary careful characterization of the lens and source samples are mandatory. In this work, we report on a VLT/XShooter observation program of 67 lens systems to characterize their spectroscopic redshift distribution. These systems were previously detected on the Dark Energy Spectroscopic Instrument Legacy Imaging Surveys by Huang et al. 2021 and Storfer et al. 2022 with deep residual neural network. We manage to measure redshifts for 58 lenses and 57 sources. We also identify 2 sources with indication of outflow in the shape of the emission lines and 7 sources with rotating disks in $[OII]$ or $H\alpha$. We find no particular bias associated to the redshift measurement operation, meaning that our measured source redshift distribution is likely representative of the true one and can be used to calibrate analyses in large imaging surveys.

Figures

Figures reproduced from arXiv: 2607.08562 by the authors.

**Figure 3.** Magnitude distribution of lenses and sources observed [PITH_FULL_IMAGE:figures/full_fig_p003_3.png] view at source ↗

**Figure 2.** Spectroscopic redshift distributions measured for the ob [PITH_FULL_IMAGE:figures/full_fig_p003_2.png] view at source ↗

Figures from the paper (1 more)

**Figure 4.** Figure 4: Color color distributions and histograms of the lenses and [PITH_FULL_IMAGE:figures/full_fig_p004_4.png]

Discussion (0). Continue with ORCID to comment.

Reference graph

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Pith tools

Reviewed July 10, 2026 · model on record in the stance chip above.

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