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The operational definition of DS and DN (and the exact masks/weights used in spectra and QE) is not specified with enough precision to interpret the near-null DS$\times$DN cross-spectra or the extreme TT and $\kappa\kappa$ ratios. The manuscript qualitatively suggests DS/DN are “largely disjoint,” but does not quantify $f_{\rm sky}$, overlap fraction, apodization, or hit-count/inverse-variance weight distributions that likely drive both auto suppression and cross nulls (Sec. 2; interpretation in Secs. 4.1–4.2, 4.4; discussion in Sec. 5).
Recommendation: In Sec. 2, add an explicit, actionable DS/DN definition: (i) how DS and DN are constructed in the DR6.02 daytime archive (time/az/scan criteria vs precomputed region labels); (ii) the exact masks used for TT and for QE (including apodization type/scale); (iii) $f_{\rm sky}$(DS), $f_{\rm sky}$(DN), and $f_{\rm sky}$(overlap) (or an overlap fraction); and (iv) basic weight/depth statistics (e.g., median/percentiles of inverse-variance weights or an effective $\mu{\rm K}$-arcmin depth proxy) for each region at 150 GHz. Include a footprint/weight map figure or a compact table. Then, in Secs. 4.1–4.2, state explicitly whether DS and DN are treated as disjoint for the analysis and what overlap is expected to contribute to DS$\times$DN cross-power for a common CMB sky with uncorrelated noise.
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Key elements of the map-making and pseudo–$C_\ell$ pipeline are under-specified, making it difficult to assess whether DS/DN differences arise from calibration, beam/transfer-function differences, filtering, weighting, or noise modeling. The text indicates “same pipeline choices” but does not document beam/transfer deconvolution, mode-coupling correction, mapmaking filters/cuts, or whether calibration/transfer functions are shared or independently derived per region (Secs. 2, 3.1–3.2).
Recommendation: Expand Sec. 2 and Sec. 3.1 with a concise but complete “analysis configuration” description: (i) beam treatment (per-split vs common beam, deconvolution choice, beam uncertainty); (ii) transfer function/filtering description (time-domain filtering scales, map-domain filtering, any $\ell$-dependent response corrections); (iii) pseudo–$C_\ell$ details (mask apodization, mode-coupling matrix treatment, binning/weighting, any noise-bias subtraction for TT autos); and (iv) calibration procedure (absolute and relative) and whether DS/DN inherit a common calibration. Where these are inherited from published ACT DR6 pipelines (e.g., Naess et al. 2020; Qu et al. 2024; Madhavacheril et al. 2024), cite the exact configuration/section and list any deviations relevant to DS/DN.
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The magnitude and $\ell$-dependence of the TT suppression ($R^{TT}\sim0.3$) is so extreme that the paper needs a more quantitative decomposition into plausible causes (relative gain, transfer-function mismatch, beam differences, noise bias/weighting effects). Currently Sec. 5 lists possible contributors but does not demonstrate whether any are numerically capable of producing a factor $\sim3$ change in TT power (Secs. 4.1, 5).
Recommendation: Strengthen Sec. 5 with quantitative “sanity checks” tied to the presented spectra: (i) test a pure multiplicative calibration model ($C_\ell\propto g^2$): $R^{TT}\approx0.3$ implies $g\approx0.55$—state whether such a relative gain is plausible under DR6 daytime calibration; (ii) examine $\ell$-dependence of $R_b^{TT}$ to distinguish calibration-like (flat) vs transfer-function-like (tilted) behavior, and relate this to any known daytime filtering/atmospheric differences; (iii) estimate DS and DN noise levels using high-$\ell$ TT, difference maps, or jackknife products, and show how noise/weighting would bias auto bandpowers; and (iv) explicitly clarify what “beam-corrected TT” means here (Figure captions and Sec. 3.1), including whether DS and DN beams differ. Even back-of-the-envelope bounds would materially improve interpretability.
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The QE lensing reconstruction and the exact content of the plotted/archived $\kappa\kappa$ spectra are not described with enough specificity to interpret $R^\kappa\approx0.85$. It is unclear whether the $\kappa\kappa$ bandpowers used for ratios are raw, $N^{(0)}$-subtracted, $N^{(1)}$-corrected, Monte-Carlo-corrected, and/or normalized identically between DS and DN; given the stated $N^{(0)}$ dominance, region-dependent noise differences could explain much of the effect, but the analysis does not quantify this (Secs. 3.2–3.4, 4.2, 5).
Recommendation: In Sec. 3.2 (or a dedicated subsection), specify: (i) QE estimator type (temperature-only TT), the L range for $\kappa$ bandpowers, and $\ell$ cuts for gradient/small-scale legs; (ii) filtering applied before QE (including any inpainting, mean-field subtraction, or mask treatment); (iii) the normalization method (analytic vs simulation-based) and whether it is common to DS/DN; and (iv) precisely which bias terms are removed ($N^{(0)}$, $N^{(1)}$, any MC corrections) in the $\kappa\kappa$ spectra used in Sec. 4.2 and Appendix A. Then, add a short quantitative diagnostic: compare estimated $N^{(0)}_L$ (or an effective QE noise level) between DS and DN and show whether the observed $R^\kappa$ can be explained primarily by reconstruction noise differences rather than changes in the true lensing signal.
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The statistical framing over-emphasizes a $\chi^2$-like quantity (Eq. 5; $\chi^2\approx5168$ for 10 bins) while explicitly neglecting bin–bin covariance, and the jackknife error model (4 temporal splits, delete-one) is not sufficiently explained to justify extremely small quoted uncertainties on weighted-mean ratios. As written, readers may misinterpret the $\chi^2$ and sub-permil errors as formal significances (Secs. 3.3, 4.2, Table 1, Appendix B; also affects TT in Sec. 4.1).
Recommendation: Revise Sec. 3.3 and Sec. 4.2 to (i) clearly define what is jackknifed (the bandpowers, the ratios, or a combined estimator) and how 4 temporal splits enter the cross/auto constructions; (ii) provide a reality check uncertainty summary that does not rely solely on potentially misestimated per-bin $\sigma$ (e.g., report per-bin pulls, unweighted mean$\pm$RMS across bins, and/or a bin-bootstrap as a descriptive measure); and (iii) either estimate an approximate covariance for $R_b^\kappa$ (from ACT simulations, analytic mode-counting, or even a nearest-neighbor model) and recompute a generalized $\chi^2$ with an interpretable p-value, or explicitly demote Eq. (5) to a “severity index” and stop presenting it in a way that resembles a formal $\chi^2$ test. Update Eq. (5) typesetting accordingly (see very minor issues).
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Cross-spectrum ‘null tests’ (DS$\times$DN TT and $\kappa$ cross) are interpreted as consistency checks, but if DS and DN have negligible overlap, near-zero cross-power is largely guaranteed and does not strongly constrain shared systematics; conversely, if overlap exists, a near-null cross could indicate deeper calibration/transfer inconsistencies. The manuscript does not connect the observed cross suppression to an explicit overlap/geometry expectation (Secs. 4.1–4.2, 4.4).
Recommendation: After quantifying DS/DN overlap (Major Issue 1), add to Sec. 4.1–4.2 a simple expectation for cross-power: e.g., predict the DS$\times$DN TT cross amplitude (or cross/auto ratio) for a common CMB signal under the measured masks/weights, assuming uncorrelated noise. Then interpret the observed DS$\times$DN cross bandpowers relative to that expectation. If overlap is near zero, state explicitly that the cross is a weak systematic diagnostic and mainly confirms disjointness; if overlap is non-negligible, discuss what classes of systematics could drive an anomalously small cross.
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Presentation and data-product interpretability: several key figures and captions do not clearly specify units, normalization conventions ($C_\ell$ vs $D_\ell$; beam/transfer deconvolved or not), and uncertainty visualization; additionally, the mapping between plotted curves and specific archived arrays/files is not always explicit. This is particularly problematic where order-of-magnitude statements are made (e.g., $\kappa$ cross vs auto levels) and where the paper aims to be a reusable diagnostic using archived .npz products (Figures 1, 3, 4, 5, 7; Secs. 4.1–4.4; Appendix A).
Recommendation: For each relevant figure (esp. Figures 1, 3, 4, 5, 7), add: (i) explicit y-axis units and whether spectra are $C_\ell$, $D_\ell$, or an internal pipeline normalization; (ii) whether beam/transfer corrections and any noise/bias subtractions are applied; (iii) visible jackknife/simulation error bars or shaded bands on ratio and cross panels, with reference lines (0 or 1); and (iv) captions that define DS/DN/AA and point to the exact .npz filename(s) and array keys corresponding to each plotted series. If the $\kappa$ plots use a nonstandard normalization, state it prominently in the caption and/or add a companion panel in conventional units if feasible.