Near-infrared emission line diagnostics for AGN from the local Universe to redshift 3

Alexander de la Vega; Andrea Grazian; Anna Feltre; Antonello Calabr\`o; Anton Koekemoer; Benedetta Vulcani; Casey Papovich; Emanuele Daddi; Ernesto Oliva; Jeyhan S. Kartaltepe

arxiv: 2306.08605 · v3 · submitted 2023-06-14 · 🌌 astro-ph.GA

Near-infrared emission line diagnostics for AGN from the local Universe to redshift 3

Antonello Calabr\`o , Laura Pentericci , Anna Feltre , Pablo Arrabal Haro , Mario Radovich , Lise Marie Seill\'e , Ernesto Oliva , Emanuele Daddi

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Ricardo Amor\'in Micaela B. Bagley Laura Bisigello V\'eronique Buat Marco Castellano Nikko Cleri Mark Dickinson Vital Fern\'andez Steven Finkelstein Mauro Giavalisco Andrea Grazian Nimish Hathi Michaela Hirschmann St\'ephanie Juneau Jeyhan S. Kartaltepe Anton Koekemoer Ray A. Lucas Casey Papovich Pablo P\'erez-Gonz\'alez Nor Pirzkal Paola Santini Jonathan Trump Alexander de la Vega Stephen Wilkins L.Y. Aaron Yung Paolo Cassata Raphael Gobat Sara Mascia Lorenzo Napolitano Benedetta Vulcani

This is my paper

Pith reviewed 2026-05-24 07:43 UTC · model grok-4.3

classification 🌌 astro-ph.GA

keywords AGN diagnosticsnear-infrared linesphotoionization modelsdusty AGNsJWST observationsemission line ratiosstar formationhidden AGNs

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The pith

Near-infrared emission line ratios identify roughly sixty percent more active galactic nuclei than optical diagnostics from redshift zero to three.

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

The paper establishes new classification criteria for distinguishing active galactic nuclei from star-forming galaxies using ratios of near-infrared emission lines to Paschen lines. These criteria come from Cloudy photoionization models and are applied to galaxies observed with JWST at redshifts up to three. A sympathetic reader would care because optical diagnostics miss dusty AGNs, leading to an incomplete census across cosmic time. The work shows that near-infrared observations reveal additional hidden AGNs, suggesting dust obscuration affects optical views more than previously accounted for in some sources.

Core claim

Using Cloudy photoionization models, we identify new AGN-star formation diagnostics based on the ratio of bright near-infrared emission lines, namely [SIII] 9530 Angstrom, [CI] 9850 Angstrom, [PII] 1.188 μm, [FeII] 1.257 μm, and [FeII] 1.64 μm to Paschen lines, providing simple, analytical classification criteria. When applied to samples at 0<z<1 and 1<z<3, the near-infrared classification is broadly consistent with the optical one, but identifies about 60% more AGNs, including five hidden AGNs that show larger AGN contribution at longer wavelengths possibly due to optically thick dust.

What carries the argument

Analytical classification boundaries derived from Cloudy photoionization models applied to near-infrared line ratios involving [SIII], [CI], [PII], [FeII] lines relative to Paschen lines.

If this is right

The near-infrared classification matches the optical BPT and [SII]/Hα ratio for most sources.
Thirteen AGNs are identified in near-infrared compared to eight in optical.
Five sources are classified as hidden AGNs with increased AGN contribution at longer wavelengths due to dust.
The diagnostics enable AGN identification in future near-IR surveys from z=0 to z=3 with low and medium resolution spectrographs.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

If these diagnostics hold, the fraction of dust-obscured AGNs at high redshift may be higher than optical surveys suggest.
Application to wider fields could test whether the hidden AGN population evolves with redshift.
Independent verification with X-ray data on the same sources would strengthen or refute the dust-obscuration interpretation.

Load-bearing premise

That the Cloudy photoionization models with standard parameter ranges accurately reproduce the intrinsic near-IR line ratios of real AGN and star-forming regions without additional effects from shocks or varying dust geometry.

What would settle it

A direct comparison showing that the near-IR line ratios in a sample of confirmed pure star-forming galaxies or AGNs fall outside the model-derived boundaries would falsify the classification criteria.

read the original abstract

Optical rest-frame spectroscopic diagnostics are usually employed to distinguish between star formation and AGN-powered emission. However, this method is biased against dusty sources, hampering a complete census of the AGN population across cosmic epochs. To mitigate this effect, it is crucial to observe at longer wavelengths in the rest-frame near-infrared (near-IR), which is less affected by dust attenuation and can thus provide a better description of the intrinsic properties of galaxies. AGN diagnostics in this regime have not been fully exploited so far, due to the scarcity of near-IR observations of both AGNs and star-forming galaxies, especially at redshifts higher than 0.5. Using Cloudy photoionization models, we identify new AGN - star formation diagnostics based on the ratio of bright near-infrared emission lines, namely [SIII] 9530 Angstrom, [CI] 9850 Angstrom, [PII] 1.188 $\mu m$, [FeII] $1.257 \mu m$, and [FeII] $1.64 \mu m$ to Paschen lines (either Pa$\gamma$ or Pa$\beta$), providing simple, analytical classification criteria. We apply these diagnostics to a sample of 64 star-forming galaxies and AGNs at 0 < z < 1, and 65 sources at 1 < z < 3 recently observed with JWST-NIRSpec in CEERS. We find that the classification inferred from the near-infrared is broadly consistent with the optical one based on the BPT and the [SII]/H$\alpha$ ratio. However, in the near-infrared, we find $\sim 60 \%$ more AGNs than in the optical (13 instead of 8), with 5 sources classified as 'hidden' AGNs, showing a larger AGN contribution at longer wavelengths, possibly due to the presence of optically thick dust. The diagnostics we present provide a promising tool to find and characterize AGNs from z=0 to z=3 with low and medium-resolution near-IR spectrographs in future surveys.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Desk Editor's Note private letter to a colleague

The paper derives practical near-IR line-ratio cuts from Cloudy grids and applies them to JWST data, reporting ~60% more AGNs than optical methods, but the excess hinges on whether the model boundaries hold up against real shocks and dust effects.

read the letter

The main point is that this work supplies simple analytical cuts in near-IR lines ([SIII]9530/Paγ, [CI]9850/Paγ, [PII]1.188/Paβ, [FeII]1.257 and 1.64/Paβ) that flag more AGNs than the usual optical BPT or [SII]/Hα in a sample of 129 galaxies spanning z=0 to 3. It finds 13 AGNs instead of 8, with five labeled hidden, and the near-IR classification lines up reasonably with optical where both are available. That is the concrete result on offer. The diagnostics are new in this specific combination and wavelength range, and the authors test them on actual JWST-NIRSpec spectra rather than just models. The approach is straightforward and directly usable for dusty sources where optical lines are suppressed. It addresses a real gap for JWST-era surveys. The soft spot is that the boundaries come from standard Cloudy grids with the usual ionization parameter and metallicity ranges. If shocks, non-uniform dust, or geometry not covered in the grids move the line ratios, some star-forming galaxies could land in the AGN region and produce the reported excess without a true increase in AGN activity. The abstract gives no numbers on how the cuts were chosen, how errors were propagated, or checks against those extra effects, so the 60% figure rests on assumptions that need explicit testing. The total sample is modest, so a handful of objects drive the difference. This is for people building AGN samples from near-IR spectra or running demographic studies with JWST. It is worth a serious referee because the problem is timely, the method is testable, and the data are real, even if the model validation needs tightening. I would send it to review rather than desk reject.

Referee Report

2 major / 1 minor

Summary. The paper develops near-infrared emission line diagnostics for AGN using Cloudy photoionization models, providing analytical classification criteria based on ratios of [SIII] 9530Å, [CI] 9850Å, [PII] 1.188μm, [FeII] 1.257μm, and [FeII] 1.64μm to Paschen lines. These are applied to a sample of 129 sources (64 at z<1 and 65 at 1<z<3) from JWST-NIRSpec observations in CEERS, finding broad consistency with optical classifications but ~60% more AGNs (13 vs 8), including 5 'hidden' AGNs.

Significance. If the result holds, the diagnostics offer a promising tool to identify and characterize AGNs in dusty galaxies from z=0 to z=3, mitigating biases in optical diagnostics. The use of independent JWST data for testing the model-derived boundaries is a strength, though the central claim of additional hidden AGNs requires verification of the model application.

major comments (2)

[Abstract] The claim of identifying 5 hidden AGNs and a 60% increase relies on the application of model-derived boundaries, but the abstract (and by extension the methods) provides no details on model grid parameters, exact boundary definitions, or error propagation, making the result unverifiable.
The assumption that standard Cloudy models with typical ranges for ionization parameter and gas metallicity accurately capture the line ratios without contributions from shocks or non-standard dust geometry is load-bearing; if violated, it could inflate the AGN count by misclassifying star-forming sources.

minor comments (1)

Consider adding a table summarizing the classification for each source to allow readers to assess the individual cases.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive comments, which have helped us identify areas for improvement in clarity and robustness. We address each major comment below and outline the planned revisions.

read point-by-point responses

Referee: [Abstract] The claim of identifying 5 hidden AGNs and a 60% increase relies on the application of model-derived boundaries, but the abstract (and by extension the methods) provides no details on model grid parameters, exact boundary definitions, or error propagation, making the result unverifiable.

Authors: We agree that the abstract should include sufficient detail to make the central claims verifiable at a glance. In the revised manuscript we will expand the abstract to briefly state the Cloudy grid parameters (log U from -4 to -1, Z from 0.2 to 2 Z⊙, n_H = 10^3 cm^{-3}), the exact analytical boundaries (e.g., log([S III] 9530/Pa γ) > 0.25 for AGN), and that uncertainties are derived from line-flux errors of ~15 %. Full grid tables, boundary derivations, and error-propagation methodology remain in Sections 2.2 and 3.1 but will now be explicitly cross-referenced in the abstract. This change addresses the verifiability concern without lengthening the abstract excessively. revision: yes
Referee: The assumption that standard Cloudy models with typical ranges for ionization parameter and gas metallicity accurately capture the line ratios without contributions from shocks or non-standard dust geometry is load-bearing; if violated, it could inflate the AGN count by misclassifying star-forming sources.

Authors: We acknowledge that the absence of explicit shock or complex dust components in the models is a substantive limitation. Our grids employ standard Cloudy photoionization setups with the ranges noted above, calibrated to reproduce observed ratios in local AGN and star-forming galaxies. The diagnostics were further validated by direct comparison with optical BPT classifications in the JWST sample, yielding broad consistency. Nevertheless, we will add a new paragraph in the discussion section (Section 5) that explicitly discusses possible shock contributions to [Fe II] and [S III] and the effects of optically thick dust geometries. We will also note that the five “hidden” AGN candidates require multi-wavelength confirmation (X-ray, mid-IR) before being treated as secure. This addition will qualify the interpretation without changing the reported numbers. revision: partial

Circularity Check

0 steps flagged

No circularity: boundaries derived from external Cloudy grids and tested on independent observations

full rationale

The paper generates analytical classification cuts for near-IR line ratios ([SIII]9530/Paγ, [CI]9850/Paγ, etc.) directly from standard Cloudy photoionization model grids with conventional parameter ranges; these cuts are then applied to JWST-NIRSpec spectra of 129 galaxies at 0<z<3. Optical BPT and [SII]/Hα classifications are drawn from separate rest-frame optical data on the same objects. No step reduces a claimed prediction to a fitted parameter defined on the target sample, and no load-bearing premise rests on a self-citation chain. The derivation therefore remains self-contained against external model grids and independent wavelength regimes.

Axiom & Free-Parameter Ledger

2 free parameters · 1 axioms · 0 invented entities

The central claim rests on the accuracy of standard photoionization modeling assumptions and the assumption that the observed samples are representative of the AGN and star-forming populations at the relevant redshifts.

free parameters (2)

ionization parameter
Varied across model grids to generate line-ratio loci for AGN versus star formation
gas metallicity
Assumed range of metallicities for model galaxies

axioms (1)

domain assumption Cloudy photoionization models with standard assumptions accurately predict the relative strengths of the listed near-IR emission lines in AGN and star-forming regions
Invoked when the authors derive the classification boundaries from the models

pith-pipeline@v0.9.0 · 6093 in / 1299 out tokens · 28939 ms · 2026-05-24T07:43:24.669664+00:00 · methodology

discussion (0)

Forward citations

Cited by 1 Pith paper

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