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REVIEW 6 minor 49 references

Adding WISE mid-infrared bands to DES optical photometry improves photometric redshifts, especially at high z, while VHS near-IR adds little at the depths tested.

Reviewed by Pith at T0; open to challenge. T0 means a machine referee read the full paper against a public rubric. the ladder, T0–T4 →

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2026-07-10 18:31 UTC pith:DPQR5BCL

load-bearing objection Solid empirical ranking of WISE vs VHS for DES Y6 photo-z plus a usable public catalogue; incremental but clean and worth having.

arxiv 2607.07771 v1 pith:DPQR5BCL submitted 2026-07-08 astro-ph.CO

Infrared-enhanced Photometric Redshifts for the Dark Energy Survey Y6 Gold catalogue

M. M. Puebla , I. Sevilla-Noarbe , J. de Vicente , L. Toribio San Cipriano , J. Carretero , A. Drlica-Wagner , J. Garc\'ia-Bellido , D. Gruen
show 8 more authors
J. Gschwend T. A. Manning M. de la Osa A. Porredon N. Reynes E. S\'anchez P. Tallada N. Weaverdyck
This is my paper
classification astro-ph.CO
keywords photometric redshiftsDark Energy SurveyWISEVHSinfrared photometryDNFgalaxy surveysY6 Gold catalogue
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

The pith

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

The Dark Energy Survey maps hundreds of millions of galaxies in optical light, but estimating redshifts from photometry alone suffers from colour degeneracies once key spectral features leave the optical window. This paper tests whether infrared photometry from WISE and VHS, when combined with DES Year-6 Gold data and the DNF neighbourhood-fitting estimator, reduces scatter, bias and outlier rates. On a spectroscopic matched sample the answer is clear: WISE W1 and W2 bands deliver statistically significant gains, strongest above z approximately 1, whereas VHS J and Ks at the available depth add only marginal further improvement. Low signal-to-noise infrared measurements contribute nothing. The authors therefore release an updated Y6 Gold catalogue that includes unWISE forced-photometry fluxes and the corresponding infrared-enhanced DNF redshifts for public use.

Core claim

The combined use of DES optical photometry with WISE W1 and W2 mid-infrared data improves the photometric-redshift metrics (bias, sigma_68 scatter and Banerji outlier fraction) relative to optical-only estimates, particularly at higher redshifts; adding VHS near-infrared bands at the depths explored yields no further statistically meaningful gain for z less than 1.5.

What carries the argument

Directional Neighbourhood Fitting (DNF) with the angular-neighbourhood metric, which estimates a galaxy's redshift by fitting a hyperplane to spectroscopically calibrated neighbours that share similar multi-band colours rather than absolute magnitudes.

Load-bearing premise

The spectroscopic training sample of roughly half a million high-quality galaxies is assumed to be representative enough that the measured improvements will transfer to the full photometric catalogue, even though the paper itself notes the metrics are not directly extrapolable.

What would settle it

Re-running the identical DNF comparison on an independent, deeper spectroscopic sample that reaches fainter magnitudes and higher redshifts than the present training set, and checking whether the WISE-only improvement still holds while VHS remains marginal.

Watch this falsifier — get emailed when new claim-graph text bears on it.

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

0 major / 6 minor

Summary. The paper quantifies photometric-redshift improvements for the DES Y6 Gold catalogue obtained by adding infrared photometry from AllWISE/unWISE (W1, W2) and VHS (J, Ks) to the optical grizY bands. Using the DNF algorithm on a common spectroscopic training sample of ~545k high-quality galaxies, the authors show that DES+WISE reduces median bias, σ68 scatter and Banerji outlier fraction (especially at z ≳ 1), while VHS yields only marginal gains at the depths and sky coverage examined; low-S/N infrared data add nothing beyond optical-only results. They release a public value-added catalogue (DES Y6 Gold IR) containing unWISE forced-photometry fluxes and the corresponding DNF photo-z estimates via CosmoHub.

Significance. If the controlled ranking holds, the work supplies a practical, immediately usable enhancement to the DES Y6 Gold legacy product and a clear empirical guide for multi-wavelength photo-z strategies in forthcoming surveys (LSST, Euclid). Strengths include identical-sample comparisons (Table 4, Figs. 6–8), standard metrics with properly propagated errors, an honest caveat that spectroscopic metrics do not fully extrapolate to the photometric catalogue, and the public release of both the matched training sets and the full IR-enhanced catalogue. The demonstration that mid-IR WISE already captures the essential infrared leverage at these depths is a useful, falsifiable result for survey planning.

minor comments (6)
  1. Section 2.1 heading and first sentence contain a typographical space (“Y ear 6”); correct to “Year 6” throughout.
  2. Axis labels in Figs. 6 and 7 render as “zphot zspec” and “68/(1 + zspec)” without proper mathematical formatting; replace with Δz/(1+z) and σ68/(1+z) for readability.
  3. Abstract and final paragraph of §5 state that “low signal-to-noise (<10) infrared data does not contribute”; specify the band(s) and exact S/N definition used to draw this cut.
  4. Table 3 caption notes that DES+all includes unWISE forced photometry, yet the table itself lists only four rows; either expand the table or clarify the “DES+all” entry in the notes.
  5. Appendix A Table A.1 lists DNF_Z_IR and DNF_ZN_IR both as “using GRIZY”; the second should read “using GRIZYW1W2” to avoid confusion with the optical-only columns.
  6. A short sentence in §4.1 noting that the Y-band was tested and found non-critical would help readers who recall earlier DES analyses that discarded Y.

Circularity Check

0 steps flagged

No significant circularity: empirical photo-z metric comparison on independent spectroscopic truth sample

full rationale

The paper's central claim is an empirical ranking of infrared contributions (WISE W1/W2 vs VHS J/Ks) under controlled DNF runs on the same spectroscopic matches, plus a public catalogue release. Metrics (median bias, σ68, Banerji outlier fraction) are standard external definitions evaluated against spectroscopic redshifts treated as truth; they are not defined in terms of the DNF fit parameters or the IR fluxes. DNF is a nearest-neighbour hyperplane fit trained on the spectroscopic set, but the reported improvements are differences between optical-only and optical+IR runs on identical objects (Table 4, Figs. 6–7). No quantity is tautologically equal to a fitted parameter by construction, no uniqueness theorem is imported from the authors, and self-citations (DNF algorithm, Y6 Gold) supply the estimator and parent catalogue rather than load-bearing premises that force the ranking. The authors themselves flag that the spectroscopic training set is not fully representative of the full photometric sample, so the result is self-contained against external benchmarks and does not reduce to its inputs.

Axiom & Free-Parameter Ledger

3 free parameters · 3 axioms · 0 invented entities

The central claim rests on standard survey photometry, an established photo-z algorithm, and conventional performance metrics. No new physical entities or free parameters are introduced; the only modelling choices are matching radius, magnitude cuts and the decision to use ANF distance inside DNF.

free parameters (3)
  • matching radius = 1 arcsec
    Positional cross-match radius fixed at 1 arcsec after testing 1.3 and 1.5 arcsec; choice affects sample size but is not fitted to photo-z metrics.
  • i-band magnitude cut = i < 26
    i<26 applied to the spectroscopic sample; practical cut for weak-lensing relevance, not optimised against photo-z metrics.
  • outlier threshold = 0.15
    Fixed |Δz| > 0.15 following Banerji et al. (2015); conventional but arbitrary constant.
axioms (3)
  • domain assumption Spectroscopic redshifts with high FLAG_DES quality are the ground-truth redshifts against which photo-z metrics are computed.
    Standard in the photo-z literature; invoked throughout Section 3.2 and the results.
  • domain assumption DNF with the Angular Neighbourhood Fitting (ANF) metric is an adequate photo-z estimator for the multi-band magnitude space.
    DNF is the DES Y6 Gold reference estimator; the paper adopts it without re-deriving its optimality (Section 3.1).
  • domain assumption A 1-arcsec positional match is sufficient to associate DES, VHS and WISE sources without significant contamination or incompleteness.
    Justified by PSF FWHM values and match-count tests in Section 2.5 / Tables 1–2.

pith-pipeline@v1.1.0-grok45 · 22379 in / 2578 out tokens · 25447 ms · 2026-07-10T18:31:05.708537+00:00 · methodology

0 comments
read the original abstract

The Dark Energy Survey (DES) provides optical data across 5000 square degrees of the southern sky, enabling a broad range of extragalactic and cosmological studies. Combining DES data with infrared surveys offers the opportunity to improve its photometric redshift (photo-z) estimates. We aim to investigate improvements in photometric redshift estimation achieved by combining DES optical data with infrared measurements from the VISTA Hemisphere Survey (VHS) and the Wide-field Infrared Survey Explorer (WISE), and release an updated version of the catalogue. We performed a positional sky cross-match between the DES Y6 Gold catalogue matched to a spectroscopic dataset, the 2013 AllWISE Data Release, and VHS Data Release 5, in order to test these improvements using the Directional Neighbourhood Fitting (DNF) algorithm (Y6 Gold catalogue reference estimator). We additionally matched it to the unWISE catalogue to verify the performance against this deeper dataset. Adding infrared data reduces all the metrics (scatter, bias and outlier fraction) in photo-z estimates, particularly at higher redshifts in comparison with only using optical data from DES. The obtained results are globally better for the DES+WISE sample, with improvements that are statistically significant. On the other hand, the addition of the VHS bands to available depth is only marginal. The combined use of DES and WISE W1 and W2 data improves the photometric redshift metrics analysed here. The addition of VHS data at the DES and VHS depths explored here does not provide any further improvement at z less than 1.5, indicating that, under these constraints, WISE data may already capture the key infrared features and depth needed for accurate photo-z estimation. In addition, low signal-to-noise (less than 10) infrared data does not contribute to any improvement beyond the DES optical dataset.

Figures

Figures reproduced from arXiv: 2607.07771 by A. Drlica-Wagner, A. Porredon, D. Gruen, E. S\'anchez, I. Sevilla-Noarbe, J. Carretero, J. De Vicente, J. Garc\'ia-Bellido, J. Gschwend, L. Toribio San Cipriano, M. de la Osa, M. M. Puebla, N. Reynes, N. Weaverdyck, P. Tallada, T. A. Manning.

Figure 1
Figure 1. Figure 1: shows the transmission curves for the g, r, i, z, Y filters from DES (1a), the Y, J, H, K s filters from VHS (1b) and the W1, W2, W3, W4 filters from WISE (1c). They illustrate the transmission efficiency of each photometric band used within this work. They are essential for the interpretation of the con￾tribution of different wavelengths to the observed fluxes, which directly impact on photometric redshif… view at source ↗
Figure 2
Figure 2. Figure 2: Distribution of the sources in the matched spectroscopic [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: The distribution of separations between DES and VHS [PITH_FULL_IMAGE:figures/full_fig_p005_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Distribution of i-band magnitudes for the four matched catalogues, DES+AllWISE (green), DES+VHS (orange), DES+VHS+AllWISE (red) and DES+unWISE (purple). 2.5.1. Matching the complete Y6 Gold catalogue For the comparison case of the information from the unWISE (deeper) dataset, we make use of the catalogue information from DECaLS DR10, and perform a similar positional matching10 be￾tween said catalogue and Y… view at source ↗
Figure 5
Figure 5. Figure 5: Photometric vs spectroscopic redshift for the [PITH_FULL_IMAGE:figures/full_fig_p006_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Metrics for the matched catalogue as a function of photo [PITH_FULL_IMAGE:figures/full_fig_p007_6.png] view at source ↗
Figure 8
Figure 8. Figure 8: The σ68 scatter shown comparatively for the optical and optical + AllWISE data, as in Figure 6b, plus the metric for the matched spectroscopic catalogue using forced photometry from unWISE (deeper dataset). 0.4 0.6 0.8 1.0 1.2 1.4 Photo-z bin 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 |z p h oto z s p e c| DES DES+VHS DES+VHS (without H) (a) Bias as a function of photometric redshift. 0.4 0.6 0.8 1.0 1.2 1.4 … view at source ↗
Figure 7
Figure 7. Figure 7: Metrics for the matched catalogue as a function of i-band [PITH_FULL_IMAGE:figures/full_fig_p009_7.png] view at source ↗

discussion (0)

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