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arxiv: 2606.17210 · v1 · pith:VHSQ6RN2new · submitted 2026-06-15 · 🌌 astro-ph.GA · astro-ph.CO

Testing masking effectiveness using multi-line image cubes based on COSMOS2020 for [CII] line intensity mapping at z_([CII]) > 3.5

Pith reviewed 2026-06-27 02:39 UTC · model grok-4.3

classification 🌌 astro-ph.GA astro-ph.CO
keywords line intensity mapping[CII] emissionCOSMOS2020 cataloguemasking techniquesCO contaminationPrime-Campower spectrumEoR-Spec
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The pith

Masking can recover the [CII] intensity mapping signal above 300 GHz under ideal conditions but realistic noise keeps the signal-to-noise ratio below 5 until late in the 2000-hour survey.

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

The paper builds simulated intensity cubes for CO and [CII] lines by applying line luminosity models to the COSMOS2020 galaxy catalogue across 1.44 square degrees. These cubes cover four 40 GHz bands from 205 to 420 GHz plus potential lower-frequency extensions, and include white plus correlated noise matching Prime-Cam on the Fred Young Submm Telescope. The authors then test two masking approaches: targeted masking that uses bright COSMOS2020 galaxies as a foreground catalogue to remove low-redshift CO, and blind masking that matches bright voxels across frequency bands. In the absence of noise both methods recover the [CII] power spectrum above 300 GHz at redshifts greater than 3.5, while CO is recoverable at lower frequencies; with noise added, [CII] recovery above 300 GHz requires the full planned integration time.

Core claim

Line luminosity models applied to the COSMOS2020 catalogue generate conservative lower-limit intensity cubes whose CO predictions match existing ALMA, VLA and NOEMA measurements. When targeted masking with a complete bright-source catalogue or blind masking across additional lower-frequency bands is applied, the [CII] power spectrum above 300 GHz is recovered in the zero-noise case. Addition of realistic instrument noise keeps the [CII] signal-to-noise ratio below 5 above 300 GHz until near the end of the 2000-hour observing period, while CO remains recoverable below 300 GHz.

What carries the argument

Multi-line image cubes constructed from COSMOS2020 galaxies with line luminosity models and Spectral Line Energy Distribution templates, combined with targeted and blind masking applied to 40 GHz bands in the 205-420 GHz range.

If this is right

  • Targeted masking recovers [CII] only when a complete foreground catalogue of bright CO sources is available.
  • Blind masking requires additional lower-frequency bands to remove CO contaminants effectively.
  • Noise levels delay usable [CII] recovery above 300 GHz until the end of the planned 2000-hour period.
  • CO emission can be recovered below 300 GHz with either masking method even in the presence of noise.
  • [CII] mapping above 300 GHz will require cross-correlation techniques unless extra observing time is allocated.

Where Pith is reading between the lines

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

  • Survey designs may need to allocate early time to lower-frequency bands or invest in deeper foreground catalogues to enable earlier [CII] detections.
  • Because the catalogue is incomplete, the true [CII] signal could be stronger than simulated, potentially allowing recovery with less total integration time.
  • The same cube-construction and masking framework could be applied to other intensity-mapping lines or instruments to test general contaminant-removal strategies.
  • Cross-correlation between [CII] and other tracers may become the default route for early high-redshift detections rather than auto-power spectrum measurements.

Load-bearing premise

The line luminosity models applied to the COSMOS2020 catalogue produce realistic emission estimates and the added white-plus-correlated noise accurately represents Prime-Cam performance.

What would settle it

Direct measurement of the [CII] power spectrum signal-to-noise ratio in actual Prime-Cam observations after 2000 hours, checking whether it reaches or stays below 5 above 300 GHz.

Figures

Figures reproduced from arXiv: 2606.17210 by A. Dev, C. Karoumpis, D. Riechers, F. Bertoldi, J. Clarke, K. Narita, T. Oak, Y. Okada.

Figure 1
Figure 1. Figure 1: Flowchart showing the steps of forming our combined intensity cubes and masks. (149 − 151 RA, 1.4 − 3.1 Dec) for z < 6.3, with four Ultra￾Deep stripes of Ultra-VISTA covering 0.7 deg2 for 6.3 < z < 9, with cutouts to remove noise from foreground stars (Weaver et al. 2022). As with C24, we used the smaller UVISTA area of 1.2 × 1.2 = 1.44 deg2 (149.6 − 150.8 RA, 1.6 − 1.8 Dec) to remove edge artefacts, and e… view at source ↗
Figure 2
Figure 2. Figure 2: Change of observed frequency with redshift for [CII] and the CO rotational transition lines up to J = 13−12. The shaded horizontal bars show the four bands nominally covered by EoR-Spec (CCAT Collabo￾ration 2023), with the hatched ones covering the extension from Roy & Battaglia (2024). The lines show how redshift changes with observed frequency for the emission lines (CO blue/dashed, [CII] red/solid). com… view at source ↗
Figure 3
Figure 3. Figure 3: Flowchart showing how we apply targeted masking. We do this separately for each mask radius [PITH_FULL_IMAGE:figures/full_fig_p008_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Different radii masks, from σ = 0.5-2.5 subdivided voxels. Upper subplots show the profile on the map (Gaussian), lower sub￾plots show the frequency space profile (Lorentzian). We convolve these with galaxy locations, so locations marked as 1 are unmasked, locations marked as 0 are fully masked. and so is useful for fields where this is incomplete. This is rele￾vant for E-COSMOS in particular as it is only… view at source ↗
Figure 5
Figure 5. Figure 5: Flowchart of the steps for blind masking, for all the total summed intensity cubes we made. We repeat this procedure for every % cutoff. valid (Choi et al. 2020), and there are no structural components to the noise. However, realistic observations will contain ad￾ditional correlated noise components including inhomogeneous water vapour distribution, atmospheric turbulence which evolves over the sky and tim… view at source ↗
Figure 6
Figure 6. Figure 6 [PITH_FULL_IMAGE:figures/full_fig_p010_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Variation of the mean cube slice intensity with observed fre￾quency (shaded bands being EoR-Spec and the extension), shown for [CII] (red) and the combined CO (blue), with or without extrapolation (upper/lower subplots). The average [CII] intensity decreases faster than CO as observed frequency decreases. The total CO and [CII] emission is equivalent for >300 GHz, though for <300 GHz CO dominates by more t… view at source ↗
Figure 8
Figure 8. Figure 8: Power spectra and S/N of [CII] (red) and CO (blue) from the simulated cubes, for the 410, 350 and 280 GHz EoR-Spec bands, and the 150 and 90 GHz lower bands, using k bins of width ∆k = 0.3 Mpc−1 . Upper subplots do not include extrapolated galaxies, middle subplots include them. [CII] and combined CO power spectra have the same order of magnitude above 300 GHz, with CO dominating below. CO is stronger in t… view at source ↗
Figure 9
Figure 9. Figure 9: Masking without extrapolation for cubes representing the 410, 350 and 280 GHz bands, for all mask radii. CO is represented by blue, [CII] by red, combined by black, with solid lines representing the median models Li and Sc20 respectively. These illustrate how the power spectra at k ≈ 0.15 Mpc−1 (∆k = 0.3 Mpc−1 ) changes as more cube is masked, with broader masks covering more volume but removing more CO. i… view at source ↗
Figure 11
Figure 11. Figure 11: Demonstrating targeted masking and blind masking on an ex￾trapolated intensity cube with and without optimal conditions, where we would expect [CII] to dominate post-masking. This was for a ∆k = 0.3 Mpc−1 bin at k = 0.15 Mpc−1 . For all cases we use 2σ masks at 410 GHz, Sc20 for [CII], SargSB for CO. Targeted masking is left, with top-left including extrapolated galaxies in the masking catalogue, and lowe… view at source ↗
Figure 12
Figure 12. Figure 12: Demonstrating challenges in blind masking signal recovery in￾cluding cleaned white and correlated noise in our cubes. The left and right subplots show blind masking including or excluding lower fre￾quency bands respectively. All use 2σ masks, with the upper subplots using 280 GHz for the bright CO and [CII] models (SargMS, C24_m3), middle suplots using 350 GHz, and the lower at 410 GHz with the same model… view at source ↗
read the original abstract

We created line intensity mapping intensity cubes for CO and [CII] emission lines using the COSMOS2020 galaxy catalogue, forming predictions based on empirical data, for observations from Prime-Cam mounted on the Fred Young Submm Telescope. We also included simulated noise including white and correlated components, and tested masking techniques to recover [CII] signal at $3.5<z<8.2$. We applied line luminosity models to the COSMOS2020 galaxy catalogue, spanning 1.44deg$^2$, to estimate the [CII] and CO J=1-0 emission, with other CO transitions derived using Spectral Line Energy Distribution templates. From these we made cubes for four 40 GHz bands in the EoR-Spec frequency range (205-420GHz), as well as a potential future upgrade to EoR-Spec including bands at 150 and 90GHz. Given the incompleteness of the empirical catalogue, these predictions are conservative lower limits, which we subsequently extrapolated from. We applied masks to recover the [CII] power spectra, using bright galaxies of COSMOS2020 as a foreground catalogue to target CO at low z (targeted masking), and matching bright voxels across frequency bands to eliminate those associated with CO emission (blind masking). Our CO intensity cube predictions are consistent with ALMA, VLA and NOEMA observations, indicating that this method gives realistic CO estimates for E-COSMOS. In ideal conditions, masking can recover [CII] above 300GHz, with targeted masking requiring a complete foreground catalogue of bright CO sources to prevent them from contributing to contaminant emission, and blind masking needing additional lower frequency ranges to be effective. However, noise will hinder [CII] recovery above 300 GHz until near the end of the currently planned 2000 hour observing period, as $S/N<5$ without extra observing time. Whilst CO can be recovered below 300GHz, [CII] will be unavailable without cross correlation techniques.

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.

Referee Report

3 major / 2 minor

Summary. The paper constructs simulated line intensity mapping cubes for multiple CO transitions and the [CII] line at 3.5 < z < 8.2 by applying empirical line luminosity models to the COSMOS2020 catalog over 1.44 deg², derives other CO lines via SLED templates, adds white-plus-correlated noise matching Prime-Cam on the Fred Young Submm Telescope, and tests targeted masking (using bright COSMOS2020 galaxies as a foreground catalog) and blind masking (cross-band voxel matching) to recover the [CII] auto-power spectrum in four 40 GHz bands (205–420 GHz) plus potential lower-frequency extensions. It reports that the CO cubes are consistent with existing ALMA/VLA/NOEMA observations and concludes that masking can recover [CII] above 300 GHz under ideal (noiseless) conditions, but that noise prevents S/N > 5 recovery until near the end of the planned 2000-hour integration, while CO is recoverable below 300 GHz.

Significance. If the simulation fidelity holds, the work supplies concrete, observationally anchored forecasts for masking strategies in [CII] LIM with Prime-Cam, quantifies the catalog-completeness and frequency-coverage requirements for targeted versus blind approaches, and highlights the S/N limitations imposed by realistic noise; the explicit consistency check against ALMA/VLA/NOEMA CO data is a positive reproducibility anchor.

major comments (3)
  1. [Abstract; line-luminosity modeling section] Abstract and the section on line-luminosity modeling: the central claim that masking recovers the [CII] power spectrum above 300 GHz rests on the fidelity of the [CII] luminosity model applied to COSMOS2020, yet the manuscript provides no equivalent validation (error bars, residual statistics, or comparison to independent [CII] data) to the CO consistency check against ALMA/VLA/NOEMA; this is load-bearing because any systematic offset in the [CII] model directly scales the recovered power spectrum and the voxels selected by both masking schemes.
  2. [Catalog incompleteness and extrapolation paragraph] The paragraph on catalog incompleteness and extrapolation: the cubes are stated to be conservative lower limits that are subsequently extrapolated, but the impact of this extrapolation on the [CII] auto-power spectrum amplitude or on the fraction of voxels masked in the targeted/blind schemes is not quantified; because the masking performance metrics are derived from these extrapolated cubes, the absence of an uncertainty envelope undermines the quantitative statements about recovery above 300 GHz.
  3. [Noise-model description] Noise-model description: the white-plus-correlated noise is asserted to represent Prime-Cam performance, but no validation metrics (e.g., power-spectrum residuals against on-sky data or simulated beam-convolved maps) are reported; this assumption directly controls the S/N < 5 conclusion for the 2000-hour survey and therefore the practical recommendation on when [CII] recovery becomes feasible.
minor comments (2)
  1. [Figure captions] Figure captions and axis labels should explicitly state whether the plotted power spectra include the extrapolated component or are limited to the catalog volume.
  2. [Band definition paragraph] The frequency ranges of the four 40 GHz bands and the potential 150/90 GHz extensions should be tabulated with the corresponding redshift intervals for both CO and [CII] to improve readability.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for their constructive and detailed comments, which have helped us identify areas where the manuscript can be strengthened. We provide point-by-point responses to the major comments below.

read point-by-point responses
  1. Referee: [Abstract; line-luminosity modeling section] Abstract and the section on line-luminosity modeling: the central claim that masking recovers the [CII] power spectrum above 300 GHz rests on the fidelity of the [CII] luminosity model applied to COSMOS2020, yet the manuscript provides no equivalent validation (error bars, residual statistics, or comparison to independent [CII] data) to the CO consistency check against ALMA/VLA/NOEMA; this is load-bearing because any systematic offset in the [CII] model directly scales the recovered power spectrum and the voxels selected by both masking schemes.

    Authors: We agree that the [CII] model lacks the direct observational validation shown for CO lines. This stems from the limited availability of resolved [CII] observations at z > 3.5 suitable for such comparisons. In revision we will expand the line-luminosity modeling section to explicitly discuss the empirical basis and reported uncertainties of the [CII] relations used, and we will qualify the recovery claims with these model caveats. We cannot add new data comparisons that do not exist in the literature. revision: partial

  2. Referee: [Catalog incompleteness and extrapolation paragraph] The paragraph on catalog incompleteness and extrapolation: the cubes are stated to be conservative lower limits that are subsequently extrapolated, but the impact of this extrapolation on the [CII] auto-power spectrum amplitude or on the fraction of voxels masked in the targeted/blind schemes is not quantified; because the masking performance metrics are derived from these extrapolated cubes, the absence of an uncertainty envelope undermines the quantitative statements about recovery above 300 GHz.

    Authors: We acknowledge that the quantitative impact of the extrapolation was not assessed. In the revised manuscript we will add a short analysis (e.g., by comparing power spectra and masked-voxel fractions before and after extrapolation) to provide an uncertainty range on the reported recovery metrics. revision: yes

  3. Referee: [Noise-model description] Noise-model description: the white-plus-correlated noise is asserted to represent Prime-Cam performance, but no validation metrics (e.g., power-spectrum residuals against on-sky data or simulated beam-convolved maps) are reported; this assumption directly controls the S/N < 5 conclusion for the 2000-hour survey and therefore the practical recommendation on when [CII] recovery becomes feasible.

    Authors: The noise model follows the published Prime-Cam specifications and instrument-team simulations. Because the instrument has not yet taken on-sky data, direct residuals against observations cannot be provided. We will add explicit references to the noise-model derivations and any available end-to-end simulations from the instrument papers to better justify the S/N estimates. revision: partial

Circularity Check

0 steps flagged

No circularity: forward simulation from external catalog with independent validation for CO.

full rationale

The paper applies published line luminosity models to the external COSMOS2020 catalog to generate simulated CO and [CII] cubes, adds modeled noise, and evaluates masking recovery on those cubes. The target [CII] power spectrum recovery is not reduced to any fitted parameter or self-citation within the paper; CO cubes are checked for consistency against independent ALMA/VLA/NOEMA data. No self-definitional steps, fitted-input predictions, or load-bearing self-citations appear in the derivation chain. The result is a self-contained forward test whose central claim does not collapse to its own inputs by construction.

Axiom & Free-Parameter Ledger

1 free parameters · 1 axioms · 0 invented entities

Ledger extracted from abstract only. The work rests on empirical catalog completeness and standard line-luminosity models; no new entities postulated.

free parameters (1)
  • line luminosity model parameters
    Models applied to COSMOS2020 galaxies to assign [CII] and CO luminosities; specific fitted values not stated in abstract.
axioms (1)
  • domain assumption COSMOS2020 provides a representative lower-limit sample for E-COSMOS emission after extrapolation for incompleteness
    Explicitly used to generate conservative predictions.

pith-pipeline@v0.9.1-grok · 5953 in / 1264 out tokens · 55395 ms · 2026-06-27T02:39:32.215048+00:00 · methodology

discussion (0)

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Reference graph

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