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REVIEW 2 major objections 4 minor 59 references

SPT-3G D1: Foreground-Robust Lensing Templates for Primordial Gravitational Wave Searches

T0 review · 2 major / 4 minor · reviewed 2026-08-07 · deepseek-v4-flash

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Pith's one-line read A lensing template made from a profile-hardened CMB lensing map plus a cosmic infrared background tracer removes about half the lensing B-mode power, with foreground bias under a tenth of the statistical uncertainty.

desk verdict Solid delensing paper with a real improvement in template efficiency; the foreground-robustness claim is undercut by in-sample Agora validation, but it deserves serious review. read the letter →

arxiv 2608.06343 v1 pith:HSSMSTOO submitted 2026-08-06 astro-ph.CO

Y. Nakato , W. L. K. Wu , Y. Omori , E. Anderes , A. J. Anderson , B. Ansarinejad , M. Archipley , L. Balkenhol
show 87 more authors
D. R. Barron P. S. Barry K. Benabed A. N. Bender B. A. Benson F. Bianchini L. E. Bleem S. Bocquet F. R. Bouchet E. Camphuis M. G. Campitiello J. E. Carlstrom J. Carron C. L. Chang P. M. Chichura A. Chokshi T.-L. Chou A. Coerver T. M. Crawford C. Daley T. de Haan K. R. Dibert M. A. Dobbs M. Doohan D. Dutcher C. Feng K. R. Ferguson N. C. Ferree K. Fichman A. Foster S. Galli A. E. Gambrel A. K. Gao F. Ge F. Guidi S. Guns N. W. Halverson E. Hivon G. P. Holder W. L. Holzapfel J. C. Hood A. Hryciuk N. Huang T. Jhaveri F. Kéruzoré A. R. Khalife L. Knox K. Kornoelje C.-L. Kuo K. Levy Y. Li A. E. Lowitz C. Lu G. P. Lynch T. J. Maccarone A. S. Maniyar E. S. Martsen F. Menanteau M. Millea J. Montgomery T. Natoli A. Ouellette Z. Pan P. Paschos K. A. Phadke K. Prabhu W. Quan S. Raghunathan M. Rahimi A. Rahlin C. L. Reichardt M. Rouble J. E. Ruhl A. C. Silva Oliveira A. Simpson J. A. Sobrin A. A. Stark J. Stephen C. Tandoi C. Trendafilova J. D. Vieira A. G. Vieregg A. Vitrier Y. Wan N. Whitehorn M. R. Young J. A. Zebrowski
This is my paper · ORCID
classification astro-ph.CO
keywords CMBlensingB-modepolarizationdelensingprimordialgravitationalwavesforegroundhardeningcosmicinfraredbackgroundtensor-to-scalarratioSPT-3G
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

This paper constructs a template for the lensing-induced B-mode polarization of the cosmic microwave background (CMB) and shows that it can be made both highly efficient and safe against extragalactic foreground contamination. The template combines a lensing-potential map reconstructed from South Pole Telescope polarization data with a cosmic infrared background (CIB) map from the Planck satellite, using a profile-hardened quadratic estimator that suppresses foreground-induced biases. The authors find that this combined template leaves about 48 percent of the lensing B-mode power on degree scales, the lowest residual yet achieved, while keeping foreground-induced bias below 10 percent of the statistical uncertainty. This matters because lensing B-modes are currently the dominant noise floor for searches for primordial gravitational waves: removing half the lensing power directly sharpens the tensor-to-scalar ratio constraint.

What carries the argument

The load-bearing object is the gradient-order lensing template $B^{\rm LT}_{\ell m} = \sum g^{\rm EB}_{\ell \ell' L} E^{\rm WF}_{\ell' m'} \phi^{\rm WF}_{L M}$, a harmonic-space convolution of Wiener-filtered CMB E-modes with a Wiener-filtered lensing-potential tracer. The tracer is a combined map whose scale-dependent weights are chosen to maximize its correlation with the true lensing potential, and whose CMB part is a profile-hardened GMV quadratic estimator that subtracts a nuisance 'source' field built from an assumed contaminant profile. The CIB map supplies an external tracer that stays well correlated with lensing at high multipoles where the CMB reconstruction becomes noise dominated. The efficiency metric is the residual lensing amplitude $A_{\rm lens}^{\rm res}(\ell) = 1-(\rho^B_\ell)^2$ when the Wiener filters are optimal, where $\rho^B_\ell$ is the correlation between the template and the true lensing B-mode field.

What would settle it

Recompute the GMVph-minus-polarization-only template difference bandpowers on several independent, deeper CMB maps; if the coherent offset exceeds 0.1$\sigma$ of the template's statistical uncertainty, the foreground-bias claim is falsified, while a null result within the quoted error keeps it.

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Extended reading notes

Core claim

On the paper's own terms, the central result is that a lensing B-mode template built from a profile-hardened global-minimum-variance (GMVph) CMB lensing reconstruction combined with a CIB tracer is both the most efficient delensing template to date and effectively free of foreground bias. In the fiducial configuration the template achieves a residual lensing amplitude $A_{\rm lens}^{\rm res} \simeq 0.48$ averaged over $20 \leq \ell \leq 200$, meaning roughly half of the lensing B-mode power is removed; adding the CIB tracer improves the residual by about 20–25 percent relative to the CMB-reconstruction-only template. The paper further argues, from simulations with realistic non-Gaussian foregrounds and from data difference tests, that foreground-induced bias in the GMVph + CIB template is below 10 percent of the statistical uncertainty, with an average level near 0.05$\sigma$. Because the template spectra measured in data agree with the Gaussian simulation predictions, the authors take the simulation-derived delensing efficiency as a reliable forecast for real data.

Load-bearing premise

The load-bearing premise is that the single full-sky realization of non-Gaussian extragalactic foregrounds used in the paper's simulations—including the tSZ profile that defines the profile-hardened estimator—faithfully represents the real foreground sky's shape and its correlations with the lensing signal.

Editorial extensions

If this is right

  • The GMVph + CIB template removes about 52 percent of the degree-scale lensing B-mode power, leaving residual lensing at $A_{\rm lens}^{\rm res}\simeq 0.48$, so a directly delensed map retains barely half the lensing contamination.
  • Adding the CIB tracer to the CMB-only reconstruction improves delensing efficiency by about 20–25 percent across all estimator choices considered.
  • Foreground-induced bias in the baseline template sits below a tenth of the statistical uncertainty, so the template can be used without paying a foreground-bias penalty in near-term delensing analyses.
  • Delensing with this template on the current leading B-mode dataset would cut the lensing contribution to $\sigma(r)$ from about 0.005 to 0.0024, a roughly 29 percent reduction in the total uncertainty.
  • The validated pipeline—hardened CMB lensing reconstruction plus an external tracer—is the recipe for foreground-safe delensing in upcoming CMB experiments.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • If the real extragalactic foreground sky differs from the simulation model used to calibrate the hardening and the bias test—for instance in the tSZ profile shape or in correlations with the lensing signal—the sub-0.1$\sigma$ bias bound could be optimistic; this is the main residual risk and will be tested as deeper data accumulate.
  • The same hardened-plus-external-tracer combination should carry over to other CMB surveys with deeper polarization maps, where the polarization-only cross-check becomes a genuinely powerful null test.
  • Because the CIB tracer contributes high-multipole lensing modes that CMB reconstruction misses, adding further large-scale-structure tracers (deeper CIB maps, galaxy lensing) could push $A_{\rm lens}^{\rm res}$ below 0.4.
  • A decisive future check is a GMVph-minus-polarization-only difference measured on several independent patches with enough integration to reach sub-0.1$\sigma$ precision; a coherent non-zero difference would falsify the claimed foreground robustness.
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Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

2 major / 4 minor

Summary. This paper constructs CMB lensing B-mode templates for delensing primordial B-mode searches, using SPT-3G D1 E-mode maps and lensing-potential reconstructions (standard GMV, profile-hardened GMV, and polarization-only PP) combined with the Planck 545 GHz CIB map. The central result is A_lens^res = 0.48 over 20 <= ell <= 200 for the GMVph + CIB template, claimed to be the highest delensing efficiency to date, with foreground-induced bias below 10% of the template power-spectrum statistical uncertainty. The validation uses 500 Gaussian simulations and 10 Agora patches with realistic non-Gaussian foregrounds; data auto-spectra are consistent with Gaussian simulations with PTEs of 0.47-0.97.

Significance. If robust, this is a timely and important result for the BICEP/SPT delensing program. The paper's strengths are the realistic end-to-end pipeline, the explicit comparison of three estimators with different foreground immunities, the use of matched Agora realizations to isolate non-Gaussian foreground effects, and the detailed multipole-cut robustness tests. The PTEs from data-versus-simulation comparisons are healthy. The main weakness is that the headline foreground-robustness claim rests partly on an in-sample Agora validation and on a cross-spectrum quantity that is presented as a template-power-spectrum bias.

major comments (2)
  1. [Abstract and Sec. IV E (Fig. 9)] The claim that the GMVph + CIB template has residual foreground bias below 10% of the statistical uncertainty on the template power spectrum is not directly supported by the plotted quantity. Fig. 9 shows the Agora-versus-Gaussian difference in the template cross-spectrum with the input B field, C^{BLT B_in}, normalized by the standard deviation of the template auto-spectrum C^{BLT BLT}; the foreground bias in the template auto-spectrum itself could differ. Since the abstract and Section IV E quote the power-spectrum bias, please either report the Agora-based bias in C^{BLT BLT} for GMVph + CIB or restate the claim as applying to the cross-spectrum bias. The data PTE for the auto-spectrum in Fig. 5 is a different, though supportive, test.
  2. [Sec. III A 1 b and Sec. IV E] The foreground-bias validation is in-sample with respect to the foreground model. The GMVph hardening profile is defined using Agora's tSZ model, and the bias test uses 10 patches cut from the same single full-sky Agora realization. If the real tSZ profile, or the correlation between foregrounds and the lensing field, differs from Agora, the residual bias after hardening could exceed the quoted ~0.05 sigma average. The bottom panel of Fig. 8 provides an out-of-sample data check, but as the authors note, the difference error bars are large, so a bias of several tenths of a sigma in the template spectrum would not be excluded. I recommend adding sensitivity tests that vary the hardening profile or use an independent non-Gaussian foreground simulation, and in any case qualifying the Abstract and Conclusion to state that the sub-0.1 sigma bias is demonstrated under the Agora foreground model.
minor comments (4)
  1. [Sec. IV F] The sigma(r) forecast for BK18 is internally inconsistent. If the total sigma(r)=0.009 and the no-lensing sigma(r)=0.004, the lensing contribution in quadrature is sqrt(0.009^2 - 0.004^2) = 0.008, not 0.005; moreover, since A_lens^res is defined as a power ratio in Eq. (8), the delensed lensing sigma(r) should scale as sqrt(A_lens^res), not A_lens^res. Please redo this toy calculation and update the quoted 29% improvement.
  2. [Table I] The uncertainties on A_lens^res quoted in the text (0.021-0.025) are not shown in the table; including them would allow a proper comparison of the tracer variants.
  3. [Abstract and Sec. IV C] The phrase 'the highest delensing efficiency lensing template to date' should be supported by explicit A_lens values for the previous BICEP/SPTpol [8] and ACT DR6 [14] templates, rather than left as an unquantified claim.
  4. [Fig. 5 caption/labels] The PTE labels such as 'PTE (No CIB): 0.68 (+ CIB): 0.96' are ambiguous; please clearly separate the no-CIB and with-CIB cases.

Circularity Check

1 steps flagged · score 3.0 of 10

In-sample Agora validation supports the foreground-robustness claim: the GMVph hardening profile and the foreground-bias test share the same Agora tSZ model, though data-based PP difference tests provide independent support.

  1. other [Sec. III A 1 b (GMVph hardening profile) and Sec. IV E (foreground bias)]
    "The GMVph reconstruction used in this work follows the implementation described in O26, where the lensing estimator is hardened using a profile matching a modified tSZ power spectrum profile from Agora[19]... We next assess the impact of non-Gaussian foregrounds on the lensing templates using Agora simulations, which include extragalactic foregrounds such as the tSZ/kSZ effects, CIB, and radio sources, which are realistically correlated with the large-scale structure responsible for CMB lensing."

    The GMVph estimator's hardening profile is taken from the Agora tSZ model, and the headline foreground-bias result (residual bias below 0.1 sigma, Fig. 9) is measured on Agora simulations containing that same tSZ model. The simulation test therefore validates the estimator against its own assumed contaminant profile; it cannot detect a mismatch between the Agora tSZ profile and the real foreground sky. The paper acknowledges this limitation in Sec. III A 1 c ('relies on an assumed foreground profile... if the true contaminants differ from the assumed model'). The GMVph-PP data difference tests provide an independent, though statistically limited, out-of-sample check, so the circularity is partial rather than complete.

full rationale

The central delensing-efficiency result, A_lens^res approx 0.48, is not circular: it is computed from Gaussian simulations with known input lensing fields using standard template formalism (Eqs. 3, 8, 10), and the data auto-spectra agree with those simulations. The circularity concern is limited to the foreground-robustness claim. The hardening kernel is defined from the Agora tSZ profile (via O26), and the main validation of foreground bias uses Agora simulations with the same tSZ model, making that validation in-sample with respect to the assumed contaminant profile. The paper's own caveat that hardening cannot remove biases if the true foregrounds differ from the assumed model, plus the independent GMVph-PP data difference tests (Fig. 8) and the small number of Agora realizations, justify a moderate score rather than a high one. No equation-level reduction or fitted-parameter-renamed-as-prediction is present in the A_lens^res derivation.

Assumptions & free parameters 3 free parameters · 5 assumptions · 0 invented entities

The analysis introduces no new physical entities. It relies on standard CMB lensing formalism, a fitted CIB-lensing model, and simulation-based validation. The main external inputs are the SPT-3G QE lensing maps from the companion paper O26 (in prep) and the Planck CIB map.

free parameters (3)
  • CIB auto-spectrum amplitude A and slope b (plus shot-noise constant C) = not quoted in the paper; fitted to the mean 545 GHz CIB auto-spectra over 8 high-latitude patches
    Used as C_CIB*CIB in the tracer-combination weights (Eqs. 12-14) and in generating CIB noise realizations (Sec. III B 1-2). If misestimated, the optimal Wiener filter and the template auto-spectrum would shift.
  • CIB-lensing linear bias parameter = not quoted in the paper; fitted to the cross-spectrum of the Planck 545 GHz CIB map with the SPT-3G PP lensing map
    Sets C_CIB*kappa in the tracer weights and the CIB signal part of simulations (Eq. 25). The paper checks agreement with a Planck PR4 cross-spectrum fit to within about 1%.
  • White-noise level for N_flat in the C^-1 filter = 5/sqrt(2) microK-arcmin
    Chosen to match the noise power in the filtered maps at ell about 3000 (Sec. III C 3). It enters the Wiener-filtered E-modes and thus the template amplitude.
assumptions (5)
  • domain assumption Gradient-order lensing template using lensed (not unlensed) E-modes accurately describes lensing B-modes at SPT-3G noise levels (Eq. 3).
    Invoked in Sec. II A and justified by reference [13]; higher-order lensing terms are argued to cancel when lensed E-modes are used.
  • domain assumption The CIB is a valid tracer of the lensing potential, with a redshift kernel peaking near z~2, modeled by a single-SED with z_c=2, sigma_z=2 and the Limber approximation.
    Sec. III B 1; used to compute C_CIB*kappa. If the CIB-lensing correlation model is wrong, the combined tracer weights and the simulated CIB fields are biased.
  • domain assumption Extragalactic foregrounds are largely unpolarized, so the polarization-only (PP) lensing estimator is essentially free of foreground bias and can serve as a reference.
    Sec. III A 1 c, citing references [34,35]. This is load-bearing for the GMVph versus PP difference tests that establish foreground robustness.
  • standard math Planck 2018 TTTEEE lowE lensing cosmology is the fiducial model for unlensed and lensed CMB spectra.
    Stated at the end of Sec. I; used in CAMB theory spectra for Wiener filters and lensing power spectra.
  • domain assumption Restricting template spectra to ell <= 500 avoids bias from B-modes that overlap with the EB lensing reconstruction.
    Sec. IV, citing references [36-39]. If this bias were not fully removed, the template power and A_lens^res could be affected.

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Cite this review

Pith. "Pith review of SPT-3G D1: Foreground-Robust Lensing Templates for Primordial Gravitational Wave Searches." pith.science (2026). https://pith.science/paper/HSSMSTOO

@misc{pith2026260806343,
  author       = {Pith},
  title        = {Pith review of: SPT-3G D1: Foreground-Robust Lensing Templates for Primordial Gravitational Wave Searches},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/HSSMSTOO}},
  note         = {Machine review of arXiv:2608.06343}
}
abstract

Gravitational lensing of the cosmic microwave background (CMB) generates B-mode polarization that acts as a source of contamination to searches for B modes generated by primordial gravitational waves (PGWs). The strongest constraint on PGW B modes is already significantly limited by lensing B modes, as shown in the most recent BICEP result. In this work, we present CMB lensing B-mode templates constructed using SPT-3G and Planck data, which characterize the lensing B modes and can be used to improve PGW B-mode searches. We use SPT-3G data from the 2019 and 2020 observing seasons for the E modes and the CMB-reconstructed lensing potential, and a cosmic infrared background (CIB) map from Planck as an external lensing tracer. To test for extragalactic foreground biases in the lensing template, we consider CMB lensing reconstruction variants with different levels of foreground immunity: the standard and profile-hardened global minimum variance (GMV) quadratic estimators, and a polarization-only quadratic estimator. We validate the template construction using Gaussian simulations and Agora simulations with realistic non-Gaussian foregrounds. From simulations, we find that foreground-induced biases are strongly suppressed for the template constructed with the profile-hardened GMV + CIB tracer, with residual bias below 10% of the statistical uncertainty on the template power spectrum. Data difference tests on this template similarly show no evidence for significant foreground contamination. This foreground-immune lensing template achieves delensed residual BB power of $A_{\rm lens}^{\rm res} \simeq 0.48$ averaged over $20 \leq \ell \leq 200$, the highest delensing efficiency lensing template to date. These results demonstrate and validate a method to construct foreground-robust lensing templates which will be used in upcoming delensed PGW B-mode analyses of BICEP data.

Figures

Figures reproduced from arXiv: 2608.06343 by the authors.

Figure 1
Figure 1. FIG. 1. The GMVph lensing convergence [PITH_FULL_IMAGE:figures/full_fig_p007_1.png] view at source ↗
Figure 3
Figure 3. FIG. 3. The [PITH_FULL_IMAGE:figures/full_fig_p008_3.png] view at source ↗
Figure 4
Figure 4. FIG. 4. The lensing template map from data, constructed using PP (top right), GMVph (bottom right), and GMVph + CIB [PITH_FULL_IMAGE:figures/full_fig_p013_4.png] view at source ↗
Figures from the paper (6 more)
Figure 5
Figure 5. Figure 5: FIG. 5. The lensing template auto-spectra from data (lighter colored points), compared to the Gaussian-simulation mean [PITH_FULL_IMAGE:figures/full_fig_p014_5.png]
Figure 6
Figure 6. Figure 6: FIG. 6. Residual lensing amplitude [PITH_FULL_IMAGE:figures/full_fig_p014_6.png]
Figure 7
Figure 7. Figure 7: FIG. 7. Difference ∆ [PITH_FULL_IMAGE:figures/full_fig_p015_7.png]
Figure 8
Figure 8. Figure 8: FIG. 8. Gaussian-simulation mean subtracted differences in [PITH_FULL_IMAGE:figures/full_fig_p016_8.png]
Figure 9
Figure 9. Figure 9: FIG. 9. Foreground-induced bias in the lensing template, [PITH_FULL_IMAGE:figures/full_fig_p017_9.png]
Figure 10
Figure 10. Figure 10: FIG. 10. The power spectra of the lensing templates from [PITH_FULL_IMAGE:figures/full_fig_p019_10.png]

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Works this paper leans on

59 extracted references · 45 canonical work pages

  1. [1]

    5 GNILC is designed to separate Galactic thermal dust emission from CIB anisotropies by exploiting both their spectral and spatial differences

    545 GHz Planck CIB Map and Model Fitting For the externalϕtracer, we use the 545 GHzPlanck CIB map constructed using the GNILC component sep- aration method [21]. 5 GNILC is designed to separate Galactic thermal dust emission from CIB anisotropies by exploiting both their spectral and spatial differences. Be- cause Galactic dust and the CIB have similar s...

    work page

  2. [2]

    We obtain these auto- and cross-spectra by fitting to the measured CIB auto-spectrum and CIB-κcross-spectrum, as discussed in the previous section

    CIB Simulations To generate simulated CIB realizations that have the appropriate correlation with the input lensing field, we follow the procedure used in [8], which requires an auto- spectrum of the CIB map and cross-spectum between the CIB map and the lensing field. We obtain these auto- and cross-spectra by fitting to the measured CIB auto-spectrum and...

    work page

  3. [3]

    The inverse-variance filtering on the in- put polarizationQ/Umaps are performed using theC −1 approach, commonly employed in CMB lensing analy- ses [e.g., 15, 51, 52]

    Wiener-FilteredEMap We form theE WF input to theBtemplate by multi- plying the inverse-variance-filteredE ℓm, ¯E, by the signal varianceC EE ℓ . The inverse-variance filtering on the in- put polarizationQ/Umaps are performed using theC −1 approach, commonly employed in CMB lensing analy- ses [e.g., 15, 51, 52]. In brief, the total varianceCof the input ma...

    work page

  4. [4]

    In particular, unlike in the mid- ℓmap set, not all modes below angular multipoles of ℓ≈300 are filtered away

    SPT-3G Low-ℓMap Set forEModes The SPT-3G D1 low-ℓmap set is designed to preserve large-scale polarization modes relevant for degree-scale B-mode analyses [2]. In particular, unlike in the mid- ℓmap set, not all modes below angular multipoles of ℓ≈300 are filtered away. Since more than 50% of the lensingBmodes on degree scales (20≤ℓ≤200) are sourced byEmod...

    work page

  5. [5]

    The input skies are identical to the set used in O26 in order for the lens- ingBtemplate to trace the input lensingBmodes

    SPT-3G Low-ℓMap SetQ/USimulations We create 500 signal simulations by mock-observing simulated lensed CMB skies identically as real data maps at 95 and 150 GHz of the low-ℓmap set. The input skies are identical to the set used in O26 in order for the lens- ingBtemplate to trace the input lensingBmodes. To form a complete mock sky, we add to the mock-obser...

    work page

  6. [6]

    J., Barreiro, R

    Planck Collaboration, Akrami, Y., Arroja, F., Ashdown, M., Aumont, J., Baccigalupi, C., Ballardini, M., Ban- day, A. J., Barreiro, R. B., Bartolo, N., Basak, S., Ben- abed, K., Bernard, J.-P., Bersanelli, M., Bielewicz, P., Bock, J. J., Bond, J. R., Borrill, J., Bouchet, F. R., Boulanger, F., Bucher, M., Burigana, C., Butler, R. C., Calabrese, E., Cardoso...

    work page 2020

  7. [7]

    BICEP/Keck Collaboration, Improved Constraints on Primordial Gravitational Waves using Planck, WMAP, 20 and BICEP/Keck Observations through the 2018 Ob- serving Season, Physical Review Letters127, 151301 (2021)

    work page 2021

  8. [8]

    SPT-3G Collaboration, SPT-3G D1: Constraints on In- flationary Gravitational Waves with Two Years of SPT- 3G Data, Physical Review D112, 123520 (2025)

    work page 2025

Show all 59 references
  1. [9]

    Adachi, T

    POLARBEAR Collaboration, S. Adachi, T. Adkins, M. A. O. Aguilar Fa´ undez, K. S. Arnold, C. Baccigalupi, D. Barron, S. Chapman, K. Cheung, Y. Chinone, K. T. Crowley, T. Elleflot, J. Errard, G. Fabbian, C. Feng, T. Fujino, N. Galitzki, N. W. Halverson, M. Hasegawa, M. Hazumi, H...

    2022

  2. [10]

    P. A. R. Ade, M. Amiri, S. J. Benton, A. S. Bergman, R. Bihary, J. J. Bock, J. R. Bond, J. A. Bonetti, S. A. Bryan, H. C. Chiang, C. R. Contaldi, O. Dor´ e, A. J. Duivenvoorden, H. K. Eriksen, M. Farhang, J. P. Fil- ippini, A. A. Fraisse, K. Freese, M. Galloway, A. E. Gambrel,...

    2022

  3. [11]

    Tristram, A

    M. Tristram, A. J. Banday, K. M. G´ orski, R. Keski- talo, C. R. Lawrence, K. J. Andersen, R. B. Barreiro, J. Borrill, L. P. L. Colombo, H. K. Eriksen, R. Fernandez- Cobos, T. S. Kisner, E. Mart ´ ınez-Gonz´ alez, B. Partridge, D. Scott, T. L. Svalheim, and I. K. Wehus, Improv...

    2022

  4. [12]

    Manzotti, K

    A. Manzotti, K. T. Story, W. L. K. Wu, J. E. Auster- mann, J. A. Beall, A. N. Bender, B. A. Benson, L. E. Bleem, J. J. Bock, J. E. Carlstrom, C. L. Chang, H. C. Chiang, H.-M. Cho, R. Citron, A. Conley, T. M. Craw- 21 ford, A. T. Crites, T. de Haan, M. A. Dobbs, S. Dodel- son, ...

    2017

  5. [13]

    Kusaka, J

    A. Kusaka, J. Appel, T. Essinger-Hileman, J. A. Beall, L. E. Campusano, H.-M. Cho, S. K. Choi, K. Crowley, J. W. Fowler, P. Gallardo, M. Hasselfield, G. Hilton, S.- P. P. Ho, K. Irwin, N. Jarosik, M. D. Niemack, G. W. Nixon, M. Nolta, L. A. P. Jr., G. A. Palma, L. Parker, S. R...

  6. [14]

    BICEP/Keck and SPTpol Collaborations, A Demonstra- tion of Improved Constraints on Primordial Gravita- tional Waves with Delensing, Physical Review D103, 10.1103/physrevd.103.022004 (2021)

    2021 doi

  7. [15]

    Grav- itational Lensing, Astronomy and Astrophysics641, A8 (2020)

    Planck Collaboration, Planck 2018 Results: VIII. Grav- itational Lensing, Astronomy and Astrophysics641, A8 (2020)

    2020

  8. [16]

    POLARBEAR Collaboration, Internal Delensing of Cos- mic Microwave Background Polarization B-modes with the POLARBEAR Experiment, Physical Review Letters 124, 10.1103/physrevlett.124.131301 (2020)

    2020 doi

  9. [17]

    K. M. Smith, D. Hanson, M. LoVerde, C. M. Hirata, and O. Zahn, Delensing CMB Polarization with Exter- nal Datasets, Journal of Cosmology and Astroparticle Physics2012(6), 14

  10. [18]

    B. Yu, J. C. Hill, and B. D. Sherwin, Multitracer CMB Delensing Maps from Planck and WISE Data, Physical Review D96, 10.1103/physrevd.96.123511 (2017)

    2017 doi

  11. [19]

    Baleato Lizancos, A

    A. Baleato Lizancos, A. Challinor, and J. Carron, Lim- itations of CMB B-mode Template Delensing, Physical Review D103, 10.1103/physrevd.103.023518 (2021)

    2021 doi

  12. [20]

    Hertig, A

    E. Hertig, A. B. Lizancos, F. J. Qu, J. R. Bond, E. Cal- abrese, A. Challinor, M. J. Devlin, J. Dunkley, T. Louis, M. S. Madhavacheril, T. Namikawa, L. A. Page, N. Se- hgal, B. Sherwin, C. Sif´ on, S. T. Staggs, and E. J. Wol- lack, The Atacama Cosmology Telescope: B-mode De- ...

    2026

  13. [21]

    Omori and SPT-3G Collaboration, SPT-3G D1: Quadratic-Estimator Lensing Reconstruction and Cos- mology,in prep.(2026)

    Y. Omori and SPT-3G Collaboration, SPT-3G D1: Quadratic-Estimator Lensing Reconstruction and Cos- mology,in prep.(2026)

    2026

  14. [22]

    Aghanim, Y

    Planck Collaboration, N. Aghanim, Y. Akrami, M. Ash- down, J. Aumont, C. Baccigalupi, M. Ballardini, A. J. Banday, R. B. Barreiro, N. Bartolo, S. Basak, R. Battye, K. Benabed, J.-P. Bernard, M. Bersanelli, P. Bielewicz, J. J. Bock, J. R. Bond, J. Borrill, F. R. Bouchet, F. Bou...

    2020 arXiv

  15. [23]

    Lewis and A

    A. Lewis and A. Challinor, Weak Gravitational Lensing of the CMB, Physics Reports429, 1 (2006)

    2006

  16. [24]

    Hu and T

    W. Hu and T. Okamoto, Mass Reconstruction with Cos- mic Microwave Background Polarization, The Astrophys- ical Journal574, 566 (2002)

    2002

  17. [25]

    Omori, Agora: Multicomponent Simulation for Cross- Survey Science, Monthly Notices of the Royal Astronom- ical Society530, 5030 (2024)

    Y. Omori, Agora: Multicomponent Simulation for Cross- Survey Science, Monthly Notices of the Royal Astronom- ical Society530, 5030 (2024)

    2024

  18. [26]

    W. Quan, E. Camphuis, C. Daley, N. Huang, Y. Omori, F. Guidi, and SPT-3G Collaboration, SPT-3G D1: Maps of the Millimeter-Wave Sky from 2019 and 2020 Observa- tions of the SPT-3G Main Field, arXiv e-prints (2026), arXiv:2603.20163 [astro-ph.CO]

    2026

  19. [27]

    Disentangling Galactic Dust Emission and Cos- mic Infrared Background Anisotropies, Astronomy and Astrophysics596(2016)

    Planck Collaboration, Planck Intermediate Results XL VIII. Disentangling Galactic Dust Emission and Cos- mic Infrared Background Anisotropies, Astronomy and Astrophysics596(2016)

    2016

  20. [28]

    K. M. Gorski, E. Hivon, A. J. Banday, B. D. Wan- delt, F. K. Hansen, M. Reinecke, and M. Bartelmann, HEALPix: A Framework for High-Resolution Discretiza- tion and Fast Analysis of Data Distributed on the Sphere, The Astrophysical Journal622, 759–771 (2005)

    2005

  21. [29]

    Zonca, L

    A. Zonca, L. Singer, D. Lenz, M. Reinecke, C. Rosset, E. Hivon, and K. Gorski, healpy: Equal Area Pixeliza- tion and Spherical Harmonics Transforms for Data on the Sphere in Python, Journal of Open Source Software 4, 1298 (2019)

    2019

  22. [30]

    Raghunathan and Y

    S. Raghunathan and Y. Omori, A Cross-Internal Linear Combination Approach to Probe the Secondary CMB Anisotropies: Kinematic Sunyaev-Zel’dovich Effect and 22 CMB Lensing, The Astrophysical Journal954, 83 (2023)

    2023

  23. [31]

    Okamoto and W

    T. Okamoto and W. Hu, Cosmic Microwave Background Lensing Reconstruction on the Full Sky, Physical Review D67, 10.1103/physrevd.67.083002 (2003)

    2003 doi

  24. [32]

    C. M. Hirata and U. Seljak, Reconstruction of Lens- ing from the Cosmic Microwave Background Polariza- tion, Physical Review D68, 10.1103/physrevd.68.083002 (2003)

    2003 doi

  25. [34]

    S. J. Osborne, D. Hanson, and O. Dor´ e, Extragalactic Foreground Contamination in Temperature-Based CMB Lens Reconstruction, Journal of Cosmology and As- troparticle Physics2014(03), 24

  26. [36]

    Teng, C.-L

    W.-H. Teng, C.-L. Kuo, and J.-H. P. Wu, Cosmic Microwave Background Delensing Revisited: Resid- ual Biases and a Simple Fix, arXiv e-prints (2011), arXiv:1102.5729 [astro-ph.CO]

    2011 arXiv

  27. [37]

    van Engelen, S

    A. van Engelen, S. Bhattacharya, N. Sehgal, G. P. Holder, O. Zahn, and D. Nagai, CMB Lensing Power Spectrum Biases from Galaxies and Clusters using High- Angular Resolution Temperature Maps, The Astrophys- ical Journal786, 13 (2014)

    2014

  28. [38]

    Namikawa, D

    T. Namikawa, D. Hanson, and R. Takahashi, Bias- Hardened CMB Lensing, Monthly Notices of the Royal Astronomical Society431, 609 (2013)

    2013

  29. [39]

    Sailer, E

    N. Sailer, E. Schaan, and S. Ferraro, Lower Bias, Lower Noise CMB Lensing with Foreground-Hardened Estimators, Physical Review D102, 10.1103/phys- revd.102.063517 (2020)

    2020 doi

  30. [40]

    Feng and G

    C. Feng and G. Holder, Polarization of the Cosmic Infrared Background Fluctuations, The Astrophysical Journal897, 140 (2020)

    2020

  31. [41]

    Khabibullin, S

    I. Khabibullin, S. Komarov, E. Churazov, and A. Schekochihin, Polarization of Sunyaev–Zel’dovich Sig- nal due to Electron Pressure Anisotropy in Galaxy Clus- ters, Monthly Notices of the Royal Astronomical Society 474, 2389–2400 (2017)

    2017

  32. [42]

    Carron and A

    J. Carron and A. Lewis, Maximum a Posteriori CMB Lensing Reconstruction, Physical Review D96, 10.1103/physrevd.96.063510 (2017)

    2017 doi

  33. [43]

    D. Han, N. Sehgal, A. MacInnis, A. van Engelen, B. D. Sherwin, M. S. Madhavacheril, S. Aiola, N. Battaglia, J. A. Beall, D. T. Becker, E. Calabrese, S. K. Choi, O. Darwish, E. V. Denison, M. J. Devlin, J. Dunk- ley, S. Ferraro, A. E. Fox, M. Hasselfield, J. C. Hill, G. C. Hilt...

  34. [44]

    Carron, A

    J. Carron, A. Lewis, and A. Challinor, Internal Delensing of Planck CMB Temperature and Polarization, Journal of Cosmology and Astroparticle Physics2017(5), 035, arXiv:1701.01712 [astro-ph.CO]

    arXiv

  35. [45]

    Baleato Lizancos, A

    A. Baleato Lizancos, A. Challinor, and J. Carron, Impact of Internal-Delensing Biases on Searches for Primordial B-modes of CMB Polarisation, Journal of Cosmology and Astroparticle Physics2021(3), 016, arXiv:2007.01622 [astro-ph.CO]

    2007 arXiv

  36. [46]

    Puget, A

    J.-L. Puget, A. Abergel, J.-P. Bernard, F. Boulanger, W. B. Burton, F.-X. Desert, and D. Hartmann, Tenta- tive Detection of a Cosmic Far-Infrared Background with COBE, Astronomy and Astrophysics308, L5 (1996)

    1996

  37. [47]

    D. J. Fixsen, E. Dwek, J. C. Mather, C. L. Bennett, and R. A. Shafer, The Spectrum of the Extragalactic Far-Infrared Background from the COBE FIRAS Ob- servations, The Astrophysical Journal508, 123 (1998), arXiv:astro-ph/9803021

    1998 arXiv

  38. [48]

    F. McCarthy, Large-Scale Galactic-Dust-Cleaned Cosmic Infrared Background Maps from Planck PR4 and HI4PI with pyilc, arXiv e-prints , arXiv:2405.13470 (2024), arXiv:2405.13470 [astro-ph.CO]

    2024 arXiv

  39. [49]

    SPTpol Collaboration, Detection of B-mode Polarization in the Cosmic Microwave Background with Data from the South Pole Telescope, Physical Review Letters111, 10.1103/physrevlett.111.141301 (2013)

    2013 doi

  40. [50]

    G. P. Holder, M. P. Viero, O. Zahn, K. A. Aird, B. A. Benson, S. Bhattacharya, L. E. Bleem, J. Bock, M. Brod- win, J. E. Carlstrom, C. L. Chang, H.-M. Cho, A. Con- ley, T. M. Crawford, A. T. Crites, T. de Haan, M. A. Dobbs, J. Dudley, E. M. George, N. W. Halverson, W. L. Holza...

    2013

  41. [51]

    The Gravitational Lensing-Infrared Background Correlation, Astronomy and Astrophysics571, A18 (2014)

    Planck Collaboration, Planck 2013 Results: XVIII. The Gravitational Lensing-Infrared Background Correlation, Astronomy and Astrophysics571, A18 (2014)

    2014

  42. [52]

    ACT Collaboration, The Atacama Cosmology Telescope: Lensing of CMB Temperature and Polarization Derived from Cosmic Infrared Background Cross-Correlation, The Astrophysical Journal808, 7 (2015)

    2015

  43. [53]

    D. Lenz, O. Dor´ e, and G. Lagache, Large-scale Maps of the Cosmic Infrared Background from Planck, The Astro- physical Journal883, 75 (2019), arXiv:1905.00426 [astro- ph.CO]

    2019 arXiv

  44. [54]

    Belkner, J

    S. Belkner, J. Carron, L. Legrand, C. Umilt` a, C. Pryke, C. Bischoff, and CMB-S4 Collaboration, CMB-S4: It- erative Internal Delensing and r Constraints, The As- trophysical Journal964, 148 (2024), arXiv:2310.06729 [astro-ph.CO]

    2024 arXiv

  45. [55]

    N. R. Hall, R. Keisler, L. Knox, C. L. Reichardt, P. A. R. Ade, K. A. Aird, B. A. Benson, L. E. Bleem, J. E. Carl- strom, C. L. Chang, H.-M. Cho, T. M. Crawford, A. T. Crites, T. de Haan, M. A. Dobbs, E. M. George, N. W. Halverson, G. P. Holder, W. L. Holzapfel, J. D. Hrubes, ...

    2010

  46. [56]

    Lewis, A

    A. Lewis, A. Challinor, and A. Lasenby, Efficient Com- putation of CMB Anisotropies in Closed FR W Models, The Astrophysical Journal538, 473 (2000), arXiv:astro- ph/9911177 [astro-ph]

    2000

  47. [57]

    Z. Pan, F. Bianchini, W. L. K. Wu, P. A. R. Ade, Z. Ahmed, E. Anderes, A. J. Anderson, B. Ansarine- jad, M. Archipley, K. Aylor, L. Balkenhol, P. S. Barry, R. Basu Thakur, K. Benabed, A. N. Bender, B. A. Ben- son, L. E. Bleem, F. R. Bouchet, L. Bryant, K. Byrum, E. Camphuis, J...

    2023 arXiv

  48. [58]

    W. L. K. Wu, L. M. Mocanu, P. A. R. Ade, A. J. An- derson, J. E. Austermann, J. S. Avva, J. A. Beall, A. N. Bender, B. A. Benson, F. Bianchini, L. E. Bleem, J. E. Carlstrom, C. L. Chang, H. C. Chiang, R. Citron, C. Cor- bett Moran, T. M. Crawford, A. T. Crites, T. de Haan, M. ...

    2019 arXiv

  49. [59]

    Baleato Lizancos, A

    A. Baleato Lizancos, A. Challinor, B. D. Sherwin, and T. Namikawa, Delensing the CMB with the Cosmic In- frared Background: the Impact of Foregrounds, Monthly Notices of the Royal Astronomical Society514, 5786 (2022), arXiv:2102.01045 [astro-ph.CO]

    2022 arXiv

  50. [61]

    Abril-Cabezas, S

    I. Abril-Cabezas, S. Adachi, P. Ade, A. E. Adler, P. Agrawal, J. Aguirre, S. Aiola, T. Alford, A. Ali, D. Alonso, M. A. Alvarez, R. An, M. Aravena, K. Arnold, P. Ashton, F. Astori, Z. Atkins, J. Austermann, S. Azzoni, C. Baccigalupi, D. Baker, R. Balafendiev, A. Baleato Lizanc...

  51. [1500]

    BelowLof 200, the model predicts more CIB power than is measured from the spectra, which reduces the modeled correlation between the CIB and the true κ. We do not modify the model to improve the fit below Lof 200 because (1) we do not use them in our fiducial setting, and (2) ...

Pith tools

Reviewed August 7, 2026 · model on record in the stance chip above.