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REVIEW 2 major objections 5 minor 48 references

Robustness of pairwise kinematic Sunyaev-Zel'dovich effect to optical-cluster-selection bias

T0 review · 2 major / 5 minor · reviewed 2026-08-07 · deepseek-v4-flash

Pith's one-line read This paper finds no significant optical-selection bias in pairwise kSZ measurements from hydrodynamical simulations, within roughly 16% for the kSZ signal, 10% for pairwise velocity, and 8% for optical depth.

desk verdict Clean simulation study with an honest null result on kSZ selection bias, but the random-slice lightcone may dilute the very projection effect it aims to test. read the letter →

arxiv 2505.14791 v2 pith:CJRBY6ZN submitted 2025-05-20 astro-ph.CO

classification astro-ph.CO
keywords pairwisekinematicSunyaev-Zel'dovicheffectopticalclusterselectionbiasrichnessvelocitydepthhydrodynamicalsimulationscylindricalgalaxycountsmatchedfilter
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

The paper asks whether optically selecting galaxy clusters—via a richness-like count of galaxies along the line of sight—biases the pairwise kinematic Sunyaev-Zel'dovich (kSZ) signal, and it finds no significant bias at current precision. The authors build an alternative richness from galaxy counts in cylinders that mimic photometric redshift projection, calibrate it to the observed mass-richness relation, and compare kSZ observables for richness-selected clusters against a mass-selected sample reweighted to the same mass distribution. Across a wide grid of galaxy selection criteria, the bias ratios for pairwise kSZ, pairwise velocity, and optical depth are consistent with unity within uncertainties of about 16%, 10%, and 8%, respectively. If correct, pairwise kSZ measurements from optically selected cluster samples—central to upcoming spectroscopic and CMB surveys—can be interpreted without a large selection-bias correction.

What carries the argument

The machinery is an alternative richness built from cylindrical galaxy counts. For every halo, the paper counts galaxies selected by stellar mass, age, and specific star formation rate inside a cylinder whose radius is about R200m and whose depth, 40-100 comoving Mpc/h, mimics photometric redshift uncertainty; this count is the richness, and the resulting mass-richness relation is required to match the observed survey-calibrated relation. The unbiased comparison is constructed by reweighting a mass-selected halo catalog to the richness-selected sample's mass probability distribution, and the two pairwise signals are compared with a matched filter that weights pair separations to optimize signal-to-noise, using a template and covariance from a larger simulation lightcone. Optical depth is handled separately by averaging binned per-cluster estimates with the same mass weights.

What would settle it

Run the same cylindrical-count selection on a continuous, non-sliced hydrodynamical simulation volume or a much larger lightcone, and check whether the bias ratios for pairwise kSZ, pairwise velocity, and optical depth move away from unity beyond the 16%, 10%, and 8% uncertainties.

Watch

Extended reading notes

Core claim

In a hydrodynamical simulation of a 5x5 degree sky patch, the paper constructs mock galaxy and cluster catalogs and assigns each halo an alternative richness equal to the number of bright and red galaxies inside a cylinder of radius about R200m and depth 40-100 comoving Mpc/h, matching the observed survey-calibrated mass-richness relation. It then measures pairwise kSZ, pairwise velocity, and optical depth for the richness-selected subsample and compares them with a reconstructed unbiased signal: a mass-selected catalog weighted to reproduce the richness-selected mass distribution. The ratios are consistent with one; the quoted median uncertainties are roughly 16% for the kSZ amplitude, 10% for pairwise velocity, and 8% for optical depth. The paper concludes that optical cluster selection does not create a detectable kSZ equivalent of the selection bias that affects weak lensing.

Load-bearing premise

The mock sky is stitched from separate depth slices, so it may break the long-range line-of-sight correlations that connect projected galaxy counts to cluster gas and velocities; if those correlations matter, the null result could be artificially clean.

Editorial extensions

If this is right

  • Pairwise kSZ analyses using optically selected clusters can proceed without applying a selection-bias correction at the precision of current and near-future measurements.
  • The cylindrical-count method with a survey-calibrated mass-richness relation is a workable mock for selection-bias studies across different galaxy-selection assumptions.
  • Selection bias does not affect kSZ, velocity, and optical depth in the same way it affects weak lensing, so the two probes may be combined without assuming a common projection bias.
  • The results hold for two different photometric aperture radii and across a broad grid of galaxy selection criteria, reinforcing the null conclusion.

Reading between the lines

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

  • Beyond the paper: the simulation lightcone is assembled from redshift slices whose thickness is comparable to the cylinder depth, so a continuous simulation volume might preserve more line-of-sight clustering and reveal a bias larger than the one reported.
  • Beyond the paper: at the higher precision expected from future surveys, a small residual bias below the 16% level could still matter for cosmological parameter constraints, so rerunning the same pipeline on larger simulations would set a tighter upper limit.
  • Beyond the paper: because pairwise kSZ is roughly a product of optical depth and pairwise velocity, biases in the two components might partially cancel; measuring their correlation directly in a larger sample would sharpen the interpretation.
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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 / 5 minor

Summary. This paper tests whether optical cluster selection, modeled by an alternative richness defined as galaxy counts in cylindrical volumes along the line of sight, biases the pairwise kinematic Sunyaev-Zel'dovich (kSZ) signal, the pairwise velocity, and the mean optical depth. Using the Magneticum Box2 5x5 deg^2 lightcone and a grid of galaxy-selection criteria that produce M-lambda relations consistent with DES-Y1, the authors assign mock richness to roughly 23,000 mock clusters at z=0.2-0.6, select a lambda>=5 sample, and compare its pairwise signals with a mass-selected sample reweighted to the same mass distribution. The bias ratio is estimated with a matched filter whose normalization cancels. The central finding is that all measured bias ratios are consistent with unity within statistical uncertainties of approximately 16%, 10%, and 8% for pairwise kSZ, pairwise velocity, and optical depth, respectively.

Significance. If the null result is robust, it is a timely and useful result for pairwise kSZ cosmology with optically selected cluster samples from upcoming surveys such as DESI, ACT, SO, and CMB-S4, since it would indicate that no large selection-bias correction is needed at current precision. The paper usefully extends the cylindrical-count selection-bias methodology of Wu et al. (2022) from weak lensing to kSZ and makes appropriate use of hydrodynamical simulations with ICM physics, which is necessary for modeling kSZ. The calibration of the mock M-lambda relation against DES-Y1 in the full sample and in four redshift bins is a strength, as is the systematic exploration of a wide range of galaxy-selection criteria. The matched-filter construction is carefully designed so that the filter normalization cancels in the ratio, and the bootstrap error estimation is appropriate. The main caveat is the random-slice construction of the lightcone, which the authors acknowledge but whose impact on the bias ratio they do not quantify; this is the primary reason the central claim is not yet fully supported.

major comments (2)
  1. [Sec. 5.2, Table 1] The random-slice lightcone construction can artificially dilute the selection bias and therefore undermine the main null claim. The slice widths in Table 1 are 151-161 cMpc while the cylinder depths are 40-100 cMpc; because the cylinder extends +/-depth along the line of sight, a depth of 60 cMpc gives a total cylinder length of 120 cMpc, so for roughly 80% of clusters (2*60/151) part of the cylinder lies in an adjacent redshift slice where the galaxy distribution is uncorrelated with the cluster. This adds Poisson-like noise to the alternative richness, weakening the correlation between the richness residual and the kSZ/velocity residual at fixed mass and biasing the measured bias ratio toward unity. The reconstructed, mass-weighted sample does not contain this extra noise, so the statement in Sec. 5.2 that 'these limitations affect both the richness-selected and the reconstructed samples in the same way' is not correct for the bias ratio. I ask the authors to quantify this dilution, for example by comparing cylindrical richness measured in the full periodic box with richness measured in the sliced lightcone, or by validating against a continuously constructed lightcone, and to either correct the reported biases or present the result as an upper limit rather than a null detection.
  2. [Sec. 4.3, Appendix A] The bias ratio is estimated with a matched filter whose template is the total pairwise velocity profile. If the optical-selection bias is scale-dependent or changes sign across the pair-separation range, the filtered ratio can remain consistent with unity even when the unfiltered profiles differ. Figure 3 shows the profile comparison for only one galaxy selection; I recommend reporting the unfiltered bias ratio, or a binned-in-separation version, for at least the DES-Y1-consistent selections, so that the reader can verify that no scale-dependent bias is hidden by the matched filter.
minor comments (5)
  1. [Abstract, Sec. 5.1] The abstract reports uncertainty limits of approximately 16%, 10%, and 8%, while Sec. 5.1 states that for R_theta=2.7 arcmin the biases are consistent with unity above the levels of 19%, 11%, and 9% and that the median uncertainties across selections are 16%, 10%, and 8%. Please use a consistent definition of the quoted uncertainty.
  2. [Table 1, Sec. 4.1] Units are inconsistent: Table 1 lists slice depths and widths in cMpc, while the cylinder depth in Sec. 4.1 and Fig. 1 is given in h^-1 cMpc. Please specify whether the Table 1 values are h^-1 cMpc and use consistent notation throughout.
  3. [Sec. 4.3, Appendix A] The matched-filter template is derived from the 35x35 deg^2 lightcone based on Box0, which has different resolution and halo selection than the main Box2 lightcone. The authors state that the main result is insensitive to the template shape, but a quantitative test, such as recomputing the bias ratio with a different template shape, would strengthen this claim.
  4. [Fig. 5 caption] The phrase 'violin areas include both statistical errors and systematic errors within a set of proposed galaxy selections' is unclear; the violins appear to show the distribution of bias values across galaxy selections rather than a formal error budget. Please clarify the definition of the displayed width.
  5. [Sec. 5.2] The sentence about probing the tau-v independence 'down to a much lower mass' would benefit from a quantitative test or a reference, since the validity of the tau-v independence assumption is important for interpreting the kSZ bias as the product of the pairwise velocity and optical-depth biases.

Circularity Check

0 steps flagged · score 2.0 of 10

No significant circularity: the null bias result is an empirical simulation measurement, and the minor self-citations support the pipeline rather than the conclusion.

full rationale

The central claim is a measured simulation result, not a derived prediction: the bias is defined as the ratio of the pairwise signal in a richness-selected sample to a mass-reconstructed sample (Sec. 4.3), and the reconstructed sample is explicitly constructed to be unbiased, so a ratio consistent with unity is evidence rather than tautology. The matched-filter normalization cancels in the ratio, so the template cannot imprint the null. The main self-citations are not load-bearing for the null: Wu et al. (2022) supplies the cylindrical-count method, and Soergel et al. (2018) is invoked for the tau-v decorrelation assumption, which is used only for interpreting the relation among biases, while the kSZ, velocity, and optical-depth biases are each measured directly. The acknowledged Sec. 5.2 limitation that random slices 'could reduce large-scale structure correlations with the clusters' is a validity threat to the simulation test, not a circularity: it concerns whether the input lightcone contains the relevant large-scale correlations, not whether the output is assumed by the input. The paper calibrates richness to the external DES-Y1 M-lambda relation and measures kSZ observables from independent maps, so the central claim has independent content.

Assumptions & free parameters 5 free parameters · 7 assumptions · 0 invented entities

The central claim is a simulation-based null measurement. It rests on the fidelity of Magneticum, the cylindrical-count proxy for richness, the factorization assumption of the kSZ estimator, and the lightcone construction. Free parameters are mostly exploration grid choices; the matched-filter template is fitted but only affects weighting.

free parameters (5)
  • Cylindrical richness depth = 40 to 100 h^-1 cMpc (grid; typical DES value 50 cMpc)
    Chosen by hand to mimic photometric redshift uncertainty; the measured bias is averaged over this range, so the null result depends on this choice.
  • Galaxy selection thresholds (min stellar mass, min age, max sSFR) = min M* 9.8-10.2 log Msun at z=0.65; min age 0-6 Gyr; max log sSFR -15 to 0 yr^-1
    Explored grid; only selections consistent with DES-Y1 M-lambda are used for the headline result, so the result is conditional on this consistency cut.
  • Matched filter template parameters (broken power law) = A=0.49, x_b=409.79, alpha1=0.01, alpha2=-10.00
    Fitted to the pairwise velocity profile of the 35x35 deg2 Magneticum lightcone (Appendix A); used only to weight pair separations, but the fitted shape enters the reported bias ratios.
  • Aperture radius R_theta = 2.1 and 2.7 arcmin
    Chosen from median R200m of the mass-selected sample and compared with eROMaPPer R_lambda; results are quoted for both, with tau at 2.1 arcmin consistent within 1.34 sigma.
  • Mock M-lambda relation fit parameters a and b per selection = e.g., a=1.109 +/- 0.011, b=14.356 +/- 0.005 for one selection
    Fitted to mock richness to compare with DES-Y1 and to decide which galaxy selections are accepted; not directly the target observable, but enters the selection of the sample.
assumptions (7)
  • domain assumption Magneticum hydrodynamical simulations accurately model ICM gas, galaxy formation, and large-scale structure needed for kSZ and richness.
    The entire measurement is a simulation study; if the subgrid feedback or galaxy modeling is inaccurate, the bias estimate inherits the error. Invoked throughout Sec. 3.
  • domain assumption Galaxy counts in cylinders along the line of sight reproduce the relevant part of redMaPPer optical cluster selection bias.
    Alternative richness of Wu et al. (2022) is used because color-based richness is hard to simulate; the paper validates only the M-lambda relation against DES-Y1, not the full richness-kSZ correlation. Introduced in Sec. 4.1.
  • domain assumption The pairwise kSZ signal factorizes as mean optical depth times pairwise velocity, with negligible correlation between tau and |v_los|.
    Stated in Sec. 2.1 and relied on for interpreting P(kSZ) and for estimating tau; the paper notes Soergel et al. verified this at higher mass, but this work probes lower masses (Sec. 5.2).
  • domain assumption Clusters can be treated as centered on their central galaxies with the same velocity for richness assignment and kSZ measurement.
    Sec. 4.1 states the mock catalogs assume the same locations and velocities for clusters and central galaxies, ignoring centering offsets that are 'another effect to model'.
  • ad hoc to paper The 5x5 degree lightcone assembled from random redshift slices preserves the line-of-sight projection correlations that generate selection bias.
    Required for the null result to generalize; Sec. 5.2 acknowledges slice widths are comparable to cylinder depths, which could reduce large-scale structure correlations with clusters.
  • domain assumption Mean peculiar velocity in each optical-depth mass bin is zero and independent of mass, so a T_kSZ versus v regression recovers tau without bias.
    Assumed in Sec. 4.2; the authors verify mean velocities are consistent with zero in their bins.
  • domain assumption DES-Y1 M-lambda relation is the correct external benchmark for selecting realistic galaxy selections.
    Selections are restricted to those matching DES-Y1 within 2 sigma; if the DES relation is biased or the comparison redshift binning is wrong, accepted selections change. Sec. 4.1 and Fig. 4.

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Cite this review

Pith. "Pith review of Robustness of pairwise kinematic Sunyaev-Zel'dovich effect to optical-cluster-selection bias." pith.science (2026). https://pith.science/paper/CJRBY6ZN

@misc{pith2026250514791,
  author       = {Pith},
  title        = {Pith review of: Robustness of pairwise kinematic Sunyaev-Zel'dovich effect to optical-cluster-selection bias},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/CJRBY6ZN}},
  note         = {Machine review of arXiv:2505.14791}
}
read the original abstract

The pairwise kinematic Sunyaev-Zel'dovich(kSZ) effect measures both the pairwise motion between galaxy groups and clusters and the amount of gas within them, providing a tracer for cosmic growth. To interpret the cosmological information in the kSZ measurements, it is crucial to understand the optical-cluster-selection bias on the kSZ observables. Line-of-sight structures that contribute to both the optical observable (e.g. richness) and the cosmological signal can induce a correlation between these two quantities at a fixed cluster mass. The selection bias arising from this correlation is a key systematic effect for cosmological analyses. For cosmological observables such as cluster abundance and weak lensing, controlling this selection bias may help explain the tension between the DES-Y1 results and the Planck constraints. In order to test for a kSZ effect equivalent of such a bias, we adopted an alternative mock richness based on galaxy counts within cylindrical volumes along the line of sight. We applied the cylindrical count method to hydrodynamical simulations across a wide range of galaxy-selection criteria, assigning richness consistent with DES-Y1 to the mock clusters. When comparing optically selected clusters to mass-selected halos, we find no significant bias on pairwise kSZ signals, pairwise velocities, or optical depth within our uncertainty limits of approximately 16, 10, and 8 per cent, respectively.

Figures

Figures reproduced from arXiv: 2505.14791 by the authors.

Figure 1
Figure 1. The M − λ relation of halos in the Magneticum 5x5 deg2 lightcone, given a galaxy selection of M⋆ ≥ 109.8 M⊙, mean stellar age ≥ 4.2 Gyr, sSFR ≤ 10−15 yr−1 , and cylindrical depth of 60 h −1 cMpc. The relation fitted to λ ≥ 5 (dashed line) is consistent with DES-Y1 results within 1σ(To et al. 2021a, blue line and shaded region). Applying this correction to the lightcone could in itself introduce bias. Hence, we disab… view at source ↗
Figure 2
Figure 2. The mass distribution of the clusters with [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗
Figure 3
Figure 3. Comparing the pairwise signal of the “Richness-selected” and the “Reconstructed” sample of clusters. The “Richness [PITH_FULL_IMAGE:figures/full_fig_p006_3.png] view at source ↗
Figures from the paper (4 more)
Figure 4
Figure 4. Figure 4: The galaxy selection criteria explored to examine if the [PITH_FULL_IMAGE:figures/full_fig_p007_4.png]
Figure 5
Figure 5. Figure 5: Constraints on bias values based on smoothing scale [PITH_FULL_IMAGE:figures/full_fig_p008_5.png]
Figure 6
Figure 6. Figure 6: Constraints on bias values based on smoothing scale [PITH_FULL_IMAGE:figures/full_fig_p009_6.png]
Figure 7
Figure 7. Figure 7: The mass distributions in richness bins [5, 10, 20, 30, 45, 60, inf], given di [PITH_FULL_IMAGE:figures/full_fig_p010_7.png]

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Works this paper leans on

48 extracted references · 41 canonical work pages

  1. [1]

    2018, Physical Review D, 98, 043526

    Abbott, T., Abdalla, F., Alarcon, A., et al. 2018, Physical Review D, 98, 043526

  2. [2]

    2020, Physical Review D, 102, 023509

    Abbott, T., Aguena, M., Alarcon, A., et al. 2020, Physical Review D, 102, 023509

  3. [3]

    2018, Monthly Notices of the Royal Astro- nomical Society, 481, 2213

    Biffi, V ., Dolag, K., & Merloni, A. 2018, Monthly Notices of the Royal Astro- nomical Society, 481, 2213

  4. [4]

    2024, Monthly Notices of the Royal Astronomical Society, 534, 655 Article number, page 9 A&A proofs:manuscript no

    Bigwood, L., Amon, A., Schneider, A., et al. 2024, Monthly Notices of the Royal Astronomical Society, 534, 655 Article number, page 9 A&A proofs:manuscript no. main 12.5 13.0 13.5 14.0 14.5 15.0 0.0 0.5 1.0 1.5 2.0 2.5PDF M 9.8, log sSFR -15, Age 4.2, Depth=60 =5-10 =10-20 =20-30 =30-45 =45-60 =60-inf 12.5 13.0 13.5 14.0 14.5 15.0 0.0 0.5 1.0 1.5 2.0 2.5 ...

  5. [5]

    & Charlot, S

    Bruzual, G. & Charlot, S. 2003, MNRAS, 344, 1000

  6. [6]

    2017, Physical Review D, 96, 123529

    Calafut, V ., Bean, R., & Yu, B. 2017, Physical Review D, 96, 123529

  7. [7]

    2021, Physical Review D, 104, 043502

    Calafut, V ., Gallardo, P., Vavagiakis, E., et al. 2021, Physical Review D, 104, 043502

  8. [8]

    2022, Monthly Notices of the Royal Astronomical Society, 510, 5916

    Chen, Z., Zhang, P., Yang, X., & Zheng, Y . 2022, Monthly Notices of the Royal Astronomical Society, 510, 5916

Show all 48 references
  1. [9]

    E., Mead, A

    Chisari, N. E., Mead, A. J., Joudaki, S., et al. 2019, The Open Journal of Astro- physics, 2

  2. [10]

    S., et al

    Costanzi, M., Rozo, E., Rykoff, E. S., et al. 2018, Monthly Notices of the Royal Astronomical Society, 482, 490

  3. [11]

    2021, Physical Review D, 103, 043522

    Costanzi, M., Saro, A., Bocquet, S., et al. 2021, Physical Review D, 103, 043522

  4. [12]

    2022, Monthly Notices of the Royal Astronomical Society, 513, 2252 De Bernardis, F., Aiola, S., Vavagiakis, E., et al

    Coulton, W., Feldman, S., Maamari, K., et al. 2022, Monthly Notices of the Royal Astronomical Society, 513, 2252 De Bernardis, F., Aiola, S., Vavagiakis, E., et al. 2017, Journal of Cosmology and Astroparticle Physics, 2017, 008 DESI Collaboration, Abdul-Karim, M., Adame, A. G...

  5. [13]

    2024, MNRAS, 536, 572

    Ding, J., Dalal, R., Sunayama, T., et al. 2024, MNRAS, 536, 572

  6. [14]

    2009, Monthly Notices of the Royal Astronomical Society, 399, 497

    Dolag, K., Borgani, S., Murante, G., & Springel, V . 2009, Monthly Notices of the Royal Astronomical Society, 399, 497

  7. [15]

    K., Roncarelli, M., & Moscardini, L

    Dolag, K., Hansen, F. K., Roncarelli, M., & Moscardini, L. 2005, Monthly No- tices of the Royal Astronomical Society, 363, 29

  8. [16]

    2016, Monthly Notices of the Royal Astronomical Society, 463, 1797

    Dolag, K., Komatsu, E., & Sunyaev, R. 2016, Monthly Notices of the Royal Astronomical Society, 463, 1797

  9. [17]

    M., et al

    Dolag, K., Remus, R.-S., Valenzuela, L. M., et al. 2025, ArXiv e-prints [arXiv:2504.01061]

  10. [18]

    G., Juszkiewicz, R., Feldman, H

    Ferreira, P. G., Juszkiewicz, R., Feldman, H. A., Davis, M., & Jaffe, A. H. 1999, The Astrophysical Journal, 515, L1

  11. [19]

    Gallardo, P. A. 2019, https://doi.org/10.7298/kj4t-8e29

  12. [20]

    R., et al

    Hadzhiyska, B., Ferraro, S., Guachalla, B. R., et al. 2024, ArXiv e-prints [arXiv:2407.07152]

  13. [21]

    E., Aubourg, E., et al

    Hand, N., Addison, G. E., Aubourg, E., et al. 2012, Physical Review Letters, 109, 041101

  14. [22]

    2014, Monthly Notices of the Royal Astronomical Society, 442, 2304

    Hirschmann, M., Dolag, K., Saro, A., et al. 2014, Monthly Notices of the Royal Astronomical Society, 442, 2304

  15. [23]

    2024, Astronomy & Astrophysics, 688, A210

    Kluge, M., Comparat, J., Liu, A., et al. 2024, Astronomy & Astrophysics, 688, A210

  16. [24]

    M., Dunkley, J., et al

    Komatsu, E., Smith, K. M., Dunkley, J., et al. 2011, The Astrophysical Journal Supplement Series, 192, 18

  17. [25]

    2013, arXiv, arXiv:1308.0847

    Levi, M., Bebek, C., Beers, T., et al. 2013, arXiv, arXiv:1308.0847

  18. [26]

    2024, The Astrophysical Journal Supplement Series, 271, 30

    Li, S., Zheng, Y ., Chen, Z., Xu, H., & Yang, X. 2024, The Astrophysical Journal Supplement Series, 271, 30

  19. [27]

    2025, Astronomy & Astrophysics, 694, A207

    Marini, I., Popesso, P., Dolag, K., et al. 2025, Astronomy & Astrophysics, 694, A207

  20. [28]

    2024, Astronomy & Astrophysics, 689, A7

    Marini, I., Popesso, P., Lamer, G., et al. 2024, Astronomy & Astrophysics, 689, A7

  21. [29]

    G., Amon, A., Schaye, J., et al

    McCarthy, I. G., Amon, A., Schaye, J., et al. 2024, ArXiv e-prints [arXiv:2410.19905]

  22. [30]

    2014, The Astrophys- ical Journal, 808, 47

    Mueller, E.-M., de Bernardis, F., Bean, R., & Niemack, M. 2014, The Astrophys- ical Journal, 808, 47

  23. [31]

    Mueller, E.-M., de Bernardis, F., Bean, R., & Niemack, M. D. 2015, Physical Review D, 92, 063501

  24. [32]

    B., et al

    Myles, J., Gruen, D., Mantz, A. B., et al. 2021, Monthly Notices of the Royal Astronomical Society, 505, 33

  25. [33]

    2021, Astronomy and Astrophysics, 653, A135

    Orlowski-Scherer, J., Di Mascolo, L., Bhandarkar, T., et al. 2021, Astronomy and Astrophysics, 653, A135

  26. [34]

    S., Rozo, E., Busha, M

    Rykoff, E. S., Rozo, E., Busha, M. T., et al. 2014, The Astrophysical Journal, 785, 104

  27. [35]

    S., Rozo, E., Hollowood, D., et al

    Rykoff, E. S., Rozo, E., Hollowood, D., et al. 2016, The Astrophysical Journal Supplement Series, 224, 1

  28. [36]

    P., Sánchez-Blázquez, P., Bender, R., et al

    Saglia, R. P., Sánchez-Blázquez, P., Bender, R., et al. 2010, Astronomy & Astro- physics, 524, A6

  29. [37]

    N., Wu, H.-Y ., Rozo, E., et al

    Salcedo, A. N., Wu, H.-Y ., Rozo, E., et al. 2024, Physical Review Letters, 133, 221002

  30. [38]

    2023, Physical Review D, 107, 042004

    Schiappucci, E., Bianchini, F., Aguena, M., et al. 2023, Physical Review D, 107, 042004

  31. [39]

    T., et al

    Soergel, B., Flender, S., Story, K. T., et al. 2016, Monthly Notices of the Royal Astronomical Society, 461, 3172

  32. [40]

    2018, Monthly Notices of the Royal Astronomical Society, 478, 5320

    Soergel, B., Saro, A., Giannantonio, T., Efstathiou, G., & Dolag, K. 2018, Monthly Notices of the Royal Astronomical Society, 478, 5320

  33. [41]

    D., Tormen, G., & Kauffmann, G

    Springel, V ., White, S. D., Tormen, G., & Kauffmann, G. 2001, Monthly Notices of the Royal Astronomical Society, 328, 726

  34. [42]

    2020, Monthly Notices of the Royal Astronomical Society, 496, 4468 Article number, page 10 Y .-H

    Sunayama, T., Park, Y ., Takada, M., et al. 2020, Monthly Notices of the Royal Astronomical Society, 496, 4468 Article number, page 10 Y .-H. Hsu et al.: Robustness of Pairwise Kinematic SZ Effect to Optical Cluster Selection Bias

  35. [43]

    Sunyaev, R. A. & Zeldovich, Y . B. 1980, Monthly Notices of the Royal Astro- nomical Society, 190, 413

  36. [44]

    2024, Journal of Cosmology and As- troparticle Physics, 2024, 037

    To, C.-H., Pandey, S., Krause, E., et al. 2024, Journal of Cosmology and As- troparticle Physics, 2024, 037

  37. [45]

    2022, Monthly Notices of the Royal Astronomical Society, 515, 4471

    Wu, H.-Y ., Costanzi, M., To, C.-H., et al. 2022, Monthly Notices of the Royal Astronomical Society, 515, 4471

  38. [46]

    L., et al

    Zhang, Y ., Jeltema, T., Hollowood, D. L., et al. 2019, Monthly Notices of the Royal Astronomical Society, 487, 2578

  39. [47]

    2022, MNRAS, 523, 1994

    Zhang, Z., Wu, H.-Y ., Zhang, Y ., et al. 2022, MNRAS, 523, 1994

  40. [48]

    2021, Monthly Notices of the Royal Astronomical Society, 507, 4852 Article number, page 11 A&A proofs:manuscript no

    Zubeldia, I., Rotti, A., Chluba, J., & Battye, R. 2021, Monthly Notices of the Royal Astronomical Society, 507, 4852 Article number, page 11 A&A proofs:manuscript no. main Appendix A: Matched filter We employ the matched filter approach to combine the pairwise kSZ signal over ...

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