REVIEW 6 minor 75 references
Volume-limited HETDEX [OII] samples at z≤0.48 match flat ΛCDM mocks, with host halo masses log(M0)≈11.9–12.3 that rise weakly with luminosity.
Reviewed by Pith at T0; open to challenge. T0 means a machine referee read the full paper against a public rubric. the ladder, T0–T4 →
T0 review · grok-4.5
2026-07-13 06:35 UTC pith:VVK6UNIR
load-bearing objection Solid first clustering release of high-density HETDEX [OII] volume-limited samples that match Planck-ΛCDM mocks; foundation paper, not a growth-rate result yet.
HETDEX [OII] galaxies at z le 0.48: Volume-limited samples and their power spectra
The pith
A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.
Core claim
The monopole and quadrupole power spectra of three volume-limited HETDEX [OII] samples agree with Uchuu-based mocks under flat ΛCDM Planck parameters at all wavenumbers 0.01<k<0.7 h Mpc−1. The power-spectrum amplitudes are consistent with a characteristic host-halo mass log(M0 [h−1M⊙])≈11.9–12.3 that scales weakly with [OII] luminosity as M0∝La with a=0.37±0.10; the best-fit mocks place about 13 percent of the galaxies in subhalos.
What carries the argument
A single-parameter log-normal halo occupation distribution (central occupation ∝ exp[−(log Mh/M0)2/(2σlogM2)], σlogM fixed at 0.6 and Fg set to match the observed number density) applied to Uchuu halo and subhalo catalogs; the free parameter M0 is fit to the measured monopole via a Sellentin–Heavens likelihood.
Load-bearing premise
The model freezes the width of the log-normal occupation function at 0.6 by hand and uses the remaining free parameter only to match number density, so the claim that this simple form is enough rests on that fixed width remaining adequate for every luminosity bin and redshift.
What would settle it
A re-fit of the same monopoles with σlogM left free (or with a standard step-function plus satellite HOD) that yields statistically unacceptable residuals, or a direct measurement of the satellite fraction that differs significantly from the mock value of ~13 percent.
If this is right
- The same samples can be used for forthcoming redshift-space-distortion analyses that constrain the late-time growth rate without photometric pre-selection systematics.
- Linear bias values b1~0.8–0.9 are now available for three luminosity bins and can be inserted into halo-model or cross-correlation forecasts with weak lensing and CMB lensing.
- The high number densities make the catalogs competitive for void statistics and for cross-correlations with external low-redshift probes.
- The measured M0–L slope supplies a concrete target for semi-analytic or hydrodynamical models of star-forming galaxies at z≤0.48.
Where Pith is reading between the lines
- Because luminosity and redshift are correlated by construction in volume-limited bins, any future growth-rate measurement will need an explicit joint model of luminosity evolution and time evolution to avoid absorbing one into the other.
- The success of a pure log-normal HOD without a high-mass step function already suggests that [OII] selection at these redshifts is closer to a star-formation-rate threshold than to a stellar-mass threshold; that distinction can be tested by stacking the same galaxies on continuum mass estimates.
- If the ~13 percent subhalo fraction holds under more flexible HODs, satellite kinematics will contribute a non-negligible fraction of the small-scale quadrupole and should be forward-modelled rather than treated as a free nuisance.
Editorial analysis
A structured set of objections, weighed in public.
Referee Report
Summary. This paper constructs volume-limited samples of emission-line-selected [OII] galaxies from HETDEX PDR1 at z ≤ 0.48 in three luminosity bins across the Spring and Fall fields (N_gal from ~11k to ~65k; n-bar ≃ (2–5) imes10^{-3} h^3 Mpc^{-3}). Using a CIC-assigned FFT Yamamoto estimator with shot-noise subtraction, it measures monopole and quadrupole power spectra that agree with Uchuu mocks (Planck flat ΛCDM) at all 0.01 < k < 0.7 h Mpc^{-1}. A log-normal HOD (Eq. 11) with fixed σ_logM = 0.6 and F_g set to match n-bar yields best-fit characteristic halo masses log(M_0 [h^{-1} M_⊙]) ≃ 11.9–12.3 and a weak luminosity slope M_0 ∝ L^a with a = 0.37 ± 0.10; the mocks further imply ~13% of galaxies occupy subhalos. The samples are presented as the foundation for forthcoming RSD, galaxy–halo, and cross-correlation analyses.
Significance. The work supplies a unique high-density, untargeted spectroscopic tracer set in the low-redshift regime most sensitive to late-time growth and dark-energy effects, complementary to continuum-selected surveys (GAMA, DESI BGS). Strengths that raise include the public HPSC2 catalog, open power-spectrum pipeline, KS-validated volume-limited cuts, Sellentin–Heavens likelihood accounting for finite mocks (N_s = 50), high PTEs for both multipoles, and the fact that the quadrupole is a genuine prediction (not fitted). The demonstration that a minimal HOD already reproduces the data to k = 0.7 h Mpc^{-1} makes the samples immediately usable for cosmology and galaxy-formation studies.
minor comments (6)
- Abstract/title and several headings contain residual LaTeX spacing artifacts (e.g., “V olume-limited”, “z≤0.48”). A global clean-up of the compiled PDF is needed before final production.
- Section 4.2 / Eq. (11): the choice σ_logM = 0.6 is stated as “neither too large nor too small”; a one-sentence justification referencing prior ELG HOD literature (or a brief sensitivity plot already performed for ±0.1) would help readers assess robustness without re-running the mocks.
- Section 5.2: the conversion of M_0 to linear bias b_1 ≃ 0.8–0.9 cites the halo-model reviews but does not specify the exact mass function or bias fitting formula used. Adding the reference (or a short appendix formula) would make the numbers fully reproducible.
- Figure 5 and Appendix A: the N_overlap sky maps and the quantitative effect of the weight on P_0(k) at high k are useful; a single sentence in the main text noting that the weight changes the monopole amplitude by only a few percent would improve accessibility.
- Table 1: the effective redshifts and volumes are clear, but a column (or footnote) listing the exact KS p-values obtained for the adopted (z_min, z_max) pairs would document the volume-limited criterion more transparently.
- Section 4.2: Spring Bin 4 uses 21 slightly overlapping sub-boxes (9 % of the simulation volume). A brief remark that the resulting covariance is therefore mildly underestimated (or a test with non-overlapping boxes) would complete the error-budget discussion.
Circularity Check
Ordinary HOD amplitude fit of M0; monopole amplitude is matched by construction while shape, quadrupole, and external Planck/Uchuu cosmology remain independent tests.
specific steps
-
fitted input called prediction
[Abstract; Section 5.2 Results; Eq. (11) and surrounding text]
"We find that the power spectrum amplitudes are consistent with a characteristic dark matter halo mass of log(M0 [h−1M⊙])≃11.9–12.3, with the halo mass showing a weak dependence on [OII] luminosity, M0∝La, increasing with a slope of a=0.37±0.10. ... By fixing σlogM=0.6 and the galaxy fraction, Fg, to match the observed number density of each sample, we reduced the HOD to have a single free parameter: the characteristic halo mass M0."
M0 is the sole free parameter adjusted to the monopole amplitudes of each luminosity bin; the quoted log(M0) values and the power-law slope a fitted to those values are therefore the direct numerical output of the fit, not an independent prediction. (The spectral shape across all k and the unused quadrupole remain non-circular consistency checks.)
full rationale
The paper's central results are volume-limited sample construction from HETDEX PDR1, FFT power-spectrum multipoles, and comparison to Uchuu mocks under fixed external Planck 2015 flat-ΛCDM parameters. The only free HOD parameter M0 is fitted solely to the monopole amplitude (Sellentin-Heavens likelihood on 7 k-bins); Fg is set to match the observed number density and σ_logM is fixed by hand at 0.6 (with a ±0.1 robustness check). Consequently the reported log(M0) values and the subsequent power-law slope a = 0.37 ± 0.10 are direct outputs of that fit rather than independent predictions. This is the ordinary level of any HOD amplitude analysis and does not rise to definitional circularity: the full k-dependence of the monopole, the quadrupole (never used in the fit), the subhalo fraction, and the agreement with an external N-body cosmology are genuine, non-forced tests. No self-definitional loop, no load-bearing self-citation uniqueness theorem, and no smuggled ansatz appear. Score 2 reflects only the mild fitted-input reporting of halo masses.
Axiom & Free-Parameter Ledger
free parameters (3)
- M0 (characteristic halo mass per luminosity bin) =
log(M0/h−1M⊙) ≈ 11.94–12.32 depending on bin/field
- σ_logM (HOD width) =
0.6 (fixed)
- Fg (galaxy fraction) =
0.37–0.64 depending on bin
axioms (4)
- domain assumption Flat ΛCDM cosmology with Planck 2015/2018 parameters (Ωm=0.3089, σ8=0.8159, etc.) correctly describes the matter power spectrum at z≤0.48.
- domain assumption A log-normal central occupation (Geach et al. 2012 form without the error-function term) plus subhalo population is an adequate description of [OII] galaxy occupation.
- ad hoc to paper Two-sample KS p>0.05 between data and random redshift distributions guarantees a sufficiently volume-limited sample for clustering analysis.
- domain assumption Sparse IFU sampling (fill factor ~1/4.6) does not introduce significant window-function bias once the grid cell is larger than the IFU separation.
read the original abstract
The catalog from the Hobby-Eberly Telescope Dark Energy Experiment (HETDEX) Public Data Release 1 (PDR1) contains half a million emission-line-selected [OII] galaxies spread across $540~\mathrm{deg}^2$ at $z \le 0.48$ from HETDEX's unprecedented untargeted spectroscopic survey. In this paper, we construct volume-limited samples from PDR1 in three luminosity bins across the two main fields: "Spring'' and "Fall''. The numbers of galaxies in the bins range from 11,354 to 64,794 and number densities, $\bar{n}\simeq (2-5)\times10^{-3}~h^3~\mathrm{Mpc}^{-3}$, are higher than those of typical cosmological spectroscopic surveys of emission-line galaxies by a factor of five to ten. The monopole and quadrupole power spectra derived from these samples are in excellent agreement with the mock power spectra from the Uchuu simulation based on a flat $\Lambda$CDM model and the cosmological parameters from the Planck cosmic microwave background data, at all wavenumbers used for the measurement ($0.01<k<0.7~h~\mathrm{Mpc}^{-1}$). We find that the power spectrum amplitudes are consistent with a characteristic dark matter halo mass of $\log(M_0~[h^{-1}M_{\odot}])\simeq 11.9$-$12.3$, with the halo mass showing a weak dependence on [OII] luminosity, $M_0\propto L^a$, increasing with a slope of $a = 0.37\pm0.10$. The best-fit mock suggests that approximately 13 percent of the [OII] galaxies in our sample reside in subhalos. The new, high-density tracers of the underlying matter distribution presented in this paper provide precise measurements of clustering in a low-redshift regime sensitive to the late-time growth of structures. These samples will form the basis for forthcoming analyses of the redshift-space distortion effect, galaxy-halo connection, and cross-correlations with external low-redshift probes.
Figures
Reference graph
Works this paper leans on
-
[1]
Abdalla, E., Abell´ an, G. F., Aboubrahim, A., et al. 2022, Journal of High Energy Astrophysics, 34, 49, doi: 10.1016/j.jheap.2022.04.002 Abdul Karim, M., Aguilar, J., Ahlen, S., et al. 2025, PhRvD, 112, 083515, doi: 10.1103/tr6y-kpc6
-
[2]
Hopkins, A. M. 2021a, MNRAS, 503, 59, doi: 10.1093/mnras/stab409
-
[3]
2020, MNRAS, 497, 581, doi: 10.1093/mnras/staa1956
Comparat, J. 2020, MNRAS, 497, 581, doi: 10.1093/mnras/staa1956
-
[4]
2017, MNRAS, 470, 2617, doi: 10.1093/mnras/stx721
Alam, S., Ata, M., Bailey, S., et al. 2017, MNRAS, 470, 2617, doi: 10.1093/mnras/stx721
-
[5]
2021b, PhRvD, 103, 083533, doi: 10.1103/PhysRevD.103.083533 20
Alam, S., Aubert, M., Avila, S., et al. 2021b, PhRvD, 103, 083533, doi: 10.1103/PhysRevD.103.083533 20
-
[6]
Anderson, T. W. 2003, An Introduction to Multivariate Statistical Analysis, 3rd edn. (Hoboken, NJ: Wiley-Interscience)
2003
-
[7]
Asgari, M., Mead, A. J., & Heymans, C. 2023, The Open Journal of Astrophysics, 6, 39, doi: 10.21105/astro.2303.08752
-
[8]
2023, MNRAS, 519, 1648, doi: 10.1093/mnras/stac3514
Aung, H., Nagai, D., Klypin, A., et al. 2023, MNRAS, 519, 1648, doi: 10.1093/mnras/stac3514
-
[9]
Avila, S., Gonzalez-Perez, V., Mohammad, F. G., et al. 2020, MNRAS, 499, 5486, doi: 10.1093/mnras/staa2951
-
[10]
Behroozi, P., Wechsler, R. H., Hearin, A. P., & Conroy, C. 2019, MNRAS, 488, 3143, doi: 10.1093/mnras/stz1182
-
[11]
Behroozi, P. S., Conroy, C., & Wechsler, R. H. 2010, ApJ, 717, 379, doi: 10.1088/0004-637X/717/1/379
-
[12]
Bianchi, D., Gil-Mar´ ın, H., Ruggeri, R., & Percival, W. J. 2015, MNRAS, 453, L11, doi: 10.1093/mnrasl/slv090
-
[13]
Blake, C., Kazin, E. A., Beutler, F., et al. 2011, MNRAS, 418, 1707, doi: 10.1111/j.1365-2966.2011.19592.x
-
[14]
2013, JCAP, 2013, 030, doi: 10.1088/1475-7516/2013/12/030
Chiang, C.-T., Wullstein, P., Jeong, D., et al. 2013, JCAP, 2013, 030, doi: 10.1088/1475-7516/2013/12/030
-
[15]
Ciardullo, R., Gronwall, C., Adams, J. J., et al. 2013, ApJ, 769, 83, doi: 10.1088/0004-637X/769/1/83
-
[16]
2026, A&A Rv, 34, 1, doi: 10.1007/s00159-026-00166-x
Contarini, S., Verza, G., & Pisani, A. 2026, A&A Rv, 34, 1, doi: 10.1007/s00159-026-00166-x
-
[17]
2002, PhR, 372, 1, doi: 10.1016/S0370-1573(02)00276-4
Cooray, A., & Sheth, R. 2002, PhR, 372, 1, doi: 10.1016/S0370-1573(02)00276-4
-
[18]
2023, PhRvD, 108, 123519, doi: 10.1103/PhysRevD.108.123519
Dalal, R., Li, X., Nicola, A., et al. 2023, PhRvD, 108, 123519, doi: 10.1103/PhysRevD.108.123519
-
[19]
Davis, D., Gebhardt, K., Cooper, E. M., et al. 2023, ApJ, 946, 86, doi: 10.3847/1538-4357/acb0ca de Mattia, A., Ruhlmann-Kleider, V., Raichoor, A., et al. 2021, MNRAS, 501, 5616, doi: 10.1093/mnras/staa3891
-
[20]
2007, ApJL, 671, L101, doi: 10.1086/524950 DES Collaboration, Abbott, T
Deng, X.-F., He, J.-Z., & Jiang, P. 2007, ApJL, 671, L101, doi: 10.1086/524950 DES Collaboration, Abbott, T. M. C., Aguena, M., et al. 2026, arXiv e-prints, arXiv:2602.10065, doi: 10.48550/arXiv.2602.10065
doi:10.1086/524950 2007
-
[21]
2018, Physics Reports, 733, 1, doi: 10.1016/j.physrep.2017.12.002 Dong-P´ aez, C
Desjacques, V., Jeong, D., & Schmidt, F. 2018, Physics Reports, 733, 1, doi: 10.1016/j.physrep.2017.12.002 Dong-P´ aez, C. A., Smith, A., Szewciw, A. O., et al. 2024, MNRAS, 528, 7236, doi: 10.1093/mnras/stae062
-
[22]
Driver, S. P., Hill, D. T., Kelvin, L. S., et al. 2011, MNRAS, 413, 971, doi: 10.1111/j.1365-2966.2010.18188.x Euclid Collaboration, Mellier, Y., Abdurro’uf, et al. 2025, A&A, 697, A1, doi: 10.1051/0004-6361/202450810
-
[23]
J., Cole, S., Norberg, P., et al
Farrow, D. J., Cole, S., Norberg, P., et al. 2015, MNRAS, 454, 2120, doi: 10.1093/mnras/stv2075
-
[24]
2026, ApJ, 1002, 90, doi: 10.3847/1538-4357/ae592a
Favole, G., Kitaura, F.-S., Hadzhiyska, B., et al. 2026, ApJ, 1002, 90, doi: 10.3847/1538-4357/ae592a
-
[25]
Favole, G., Rodr´ ıguez-Torres, S. A., Comparat, J., et al. 2017, MNRAS, 472, 550, doi: 10.1093/mnras/stx1980
-
[26]
2016, MNRAS, 461, 3421, doi: 10.1093/mnras/stw1483
Favole, G., Comparat, J., Prada, F., et al. 2016, MNRAS, 461, 3421, doi: 10.1093/mnras/stw1483
-
[27]
Feldman, H. A., Kaiser, N., & Peacock, J. A. 1994, ApJ, 426, 23, doi: 10.1086/174036
doi:10.1086/174036 1994
-
[28]
Gao, H., Jing, Y. P., Gui, S., et al. 2023, ApJ, 954, 207, doi: 10.3847/1538-4357/ace90a
-
[29]
Geach, J. E., Sobral, D., Hickox, R. C., et al. 2012, MNRAS, 426, 679, doi: 10.1111/j.1365-2966.2012.21725.x
-
[30]
2021, ApJ, 923, 217, doi: 10.3847/1538-4357/ac2e03
Gebhardt, K., Mentuch Cooper, E., Ciardullo, R., et al. 2021, ApJ, 923, 217, doi: 10.3847/1538-4357/ac2e03
-
[31]
2018, MNRAS, 474, 4024, doi: 10.1093/mnras/stx2807
Gonzalez-Perez, V., Comparat, J., Norberg, P., et al. 2018, MNRAS, 474, 4024, doi: 10.1093/mnras/stx2807
-
[32]
Hahn, C., Wilson, M. J., Ruiz-Macias, O., et al. 2023, AJ, 165, 253, doi: 10.3847/1538-3881/accff8
-
[33]
2017, JCAP, 2017, 002, doi: 10.1088/1475-7516/2017/07/002
Hand, N., Li, Y., Slepian, Z., & Seljak, U. 2017, JCAP, 2017, 002, doi: 10.1088/1475-7516/2017/07/002
-
[34]
Hill, G. J., Lee, H., MacQueen, P. J., et al. 2021, AJ, 162, 298, doi: 10.3847/1538-3881/ac2c02
-
[35]
W., & Eastwood, J
Hockney, R. W., & Eastwood, J. W. 1988, Computer simulation using particles (CRC Press)
1988
-
[36]
Ishiyama, T., Prada, F., Klypin, A. A., et al. 2021, MNRAS, 506, 4210, doi: 10.1093/mnras/stab1755
-
[37]
1997, ApJ, 484, 560, doi: 10.1086/304372 Jim´ enez, E., Padilla, N., Contreras, S., et al
Jain, B., & Seljak, U. 1997, ApJ, 484, 560, doi: 10.1086/304372 Jim´ enez, E., Padilla, N., Contreras, S., et al. 2021, MNRAS, 506, 3155, doi: 10.1093/mnras/stab1819
doi:10.1086/304372 1997
-
[38]
Jing, Y. P. 2005, ApJ, 620, 559, doi: 10.1086/427087
doi:10.1086/427087 2005
-
[39]
2013, ApJ, 768, 51, doi: 10.1088/0004-637X/768/1/51
Kajisawa, M., Shioya, Y., Aida, Y., et al. 2013, ApJ, 768, 51, doi: 10.1088/0004-637X/768/1/51
-
[40]
Kennicutt, R. C., & Evans, N. J. 2012, ARA&A, 50, 531, doi: 10.1146/annurev-astro-081811-125610
-
[41]
Kennicutt, Jr., R. C. 1998, ApJ, 498, 541, doi: 10.1086/305588
doi:10.1086/305588 1998
-
[42]
A., Sobral, D., Mobasher, B., et al
Khostovan, A. A., Sobral, D., Mobasher, B., et al. 2018, MNRAS, 478, 2999, doi: 10.1093/mnras/sty925
-
[43]
Kravtsov, A. V., Berlind, A. A., Wechsler, R. H., et al. 2004, ApJ, 609, 35, doi: 10.1086/420959
doi:10.1086/420959 2004
-
[44]
Liske, J., Baldry, I. K., Driver, S. P., et al. 2015, MNRAS, 452, 2087, doi: 10.1093/mnras/stv1436 Mentuch Cooper, E., Gebhardt, K., Davis, D., et al. 2023, ApJ, 943, 177, doi: 10.3847/1538-4357/aca962 Mentuch Cooper, E., Gebhardt, K., Davis, D., et al. 2026, ApJS, 284, 67, doi: 10.3847/1538-4365/ae6068
-
[45]
Mo, H. J., & White, S. D. M. 1996, MNRAS, 282, 347, doi: 10.1093/mnras/282.2.347
-
[46]
2023, PhRvL, 131, 111001, doi: 10.1103/PhysRevLett.131.111001 21
Nguyen, N.-M., Huterer, D., & Wen, Y. 2023, PhRvL, 131, 111001, doi: 10.1103/PhysRevLett.131.111001 21
-
[47]
Norberg, P., Baugh, C. M., Hawkins, E., et al. 2001, MNRAS, 328, 64, doi: 10.1046/j.1365-8711.2001.04839.x
-
[48]
2021, PASJ, 73, 1186, doi: 10.1093/pasj/psab068
Okumura, T., Hayashi, M., Chiu, I.-N., et al. 2021, PASJ, 73, 1186, doi: 10.1093/pasj/psab068
-
[49]
2023, MNRAS, 525, 3879, doi: 10.1093/mnras/stad2401
Oogi, T., Ishiyama, T., Prada, F., et al. 2023, MNRAS, 525, 3879, doi: 10.1093/mnras/stad2401
-
[50]
2025, A&A, 697, A226, doi: 10.1051/0004-6361/202453086
Chaves-Montero, J. 2025, A&A, 697, A226, doi: 10.1051/0004-6361/202453086
-
[51]
Ortega-Martinez, S., Angulo, R. E., Contreras, S., et al. 2026, arXiv e-prints, arXiv:2604.19449, doi: 10.48550/arXiv.2604.19449
-
[52]
2023, MNRAS, 519, 1771, doi: 10.1093/mnras/stac3582
Osato, K., & Okumura, T. 2023, MNRAS, 519, 1771, doi: 10.1093/mnras/stac3582
-
[53]
Pakmor, R., Springel, V., Coles, J. P., et al. 2023, MNRAS, 524, 2539, doi: 10.1093/mnras/stad2027
-
[54]
J., Friedrich, O., Sellentin, E., & Heavens, A
Percival, W. J., Friedrich, O., Sellentin, E., & Heavens, A. 2022, MNRAS, 510, 3207, doi: 10.1093/mnras/stab3540
-
[55]
Philcox, O. H. E., & Ivanov, M. M. 2022, PhRvD, 105, 043517, doi: 10.1103/PhysRevD.105.043517 Planck Collaboration, Ade, P. A. R., Aghanim, N., et al. 2016, A&A, 594, A13, doi: 10.1051/0004-6361/201525830 Planck Collaboration, Aghanim, N., Akrami, Y., et al. 2020, A&A, 641, A6, doi: 10.1051/0004-6361/201833910
-
[56]
2023, arXiv e-prints, arXiv:2304.11911, doi: 10.48550/arXiv.2304.11911
Prada, F., Behroozi, P., Ishiyama, T., Klypin, A., & P´ erez, E. 2023, arXiv e-prints, arXiv:2304.11911, doi: 10.48550/arXiv.2304.11911
-
[57]
J., Hang, Q., Farren, G., et al
Qu, F. J., Hang, Q., Farren, G., et al. 2025, PhRvD, 111, 103503, doi: 10.1103/PhysRevD.111.103503
-
[58]
Ramsey, L. W., Adams, M. T., Barnes, T. G., et al. 1998, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 3352, Advanced Technology Optical/IR Telescopes VI, ed. L. M. Stepp, 34–42, doi: 10.1117/12.319287
-
[59]
2025, MNRAS, 539, 3627, doi: 10.1093/mnras/staf700
Said, K., Howlett, C., Davis, T., et al. 2025, MNRAS, 539, 3627, doi: 10.1093/mnras/staf700
-
[60]
2015, PhRvD, 92, 083532, doi: 10.1103/PhysRevD.92.083532
Scoccimarro, R. 2015, PhRvD, 92, 083532, doi: 10.1103/PhysRevD.92.083532
-
[61]
Sellentin, E., & Heavens, A. F. 2016, MNRAS, 456, L132, doi: 10.1093/mnrasl/slv190
-
[62]
Springel, V., White, S. D. M., Jenkins, A., et al. 2005, Nature, 435, 629, doi: 10.1038/nature03597
-
[63]
2012, MNRAS, 423, 2617, doi: 10.1111/j.1365-2966.2012.21063.x
Tadaki, K.-i., Kodama, T., Ota, K., et al. 2012, MNRAS, 423, 2617, doi: 10.1111/j.1365-2966.2012.21063.x
-
[64]
Takada, M., Ellis, R. S., Chiba, M., et al. 2014, PASJ, 66, R1, doi: 10.1093/pasj/pst019
-
[65]
Tegmark, M., Blanton, M. R., Strauss, M. A., et al. 2004, ApJ, 606, 702, doi: 10.1086/382125
doi:10.1086/382125 2004
-
[66]
2014, A&A, 566, A1, doi: 10.1051/0004-6361/201423585
Tempel, E., Tamm, A., Gramann, M., et al. 2014, A&A, 566, A1, doi: 10.1051/0004-6361/201423585
-
[67]
Tinker, J. L., Robertson, B. E., Kravtsov, A. V., et al. 2010, ApJ, 724, 878, doi: 10.1088/0004-637X/724/2/878
-
[68]
Vale, A., & Ostriker, J. P. 2004, MNRAS, 353, 189, doi: 10.1111/j.1365-2966.2004.08059.x
-
[69]
2024, JCAP, 2024, 044, doi: 10.1088/1475-7516/2024/09/044
Wang, Y., & Yu, Y. 2024, JCAP, 2024, 044, doi: 10.1088/1475-7516/2024/09/044
-
[70]
2022, ApJ, 928, 1, doi: 10.3847/1538-4357/ac4973
Wang, Y., Zhai, Z., Alavi, A., et al. 2022, ApJ, 928, 1, doi: 10.3847/1538-4357/ac4973
-
[71]
H., St¨ olzner, B., Asgari, M., et al
Wright, A. H., St¨ olzner, B., Asgari, M., et al. 2025, A&A, 703, A158, doi: 10.1051/0004-6361/202554908
-
[72]
Yamamoto, K., Nakamichi, M., Kamino, A., Bassett, B. A., & Nishioka, H. 2006, PASJ, 58, 93, doi: 10.1093/pasj/58.1.93
-
[73]
Yuan, S., Wechsler, R. H., Wang, Y., et al. 2025, MNRAS, 538, 1216, doi: 10.1093/mnras/staf368
-
[74]
Zehavi, I., Blanton, M. R., Frieman, J. A., et al. 2002, ApJ, 571, 172, doi: 10.1086/339893
doi:10.1086/339893 2002
-
[75]
Zheng, Z., Berlind, A. A., Weinberg, D. H., et al. 2005, ApJ, 633, 791, doi: 10.1086/466510 22 160180200220240 R.A.[deg] 46 48 50 52 54 56Dec.[deg] N1 = 59195 N2 = 4562 N3 = 461 N4 = 42 N5 = 13 5101520253035 R.A.[deg] 2 1 0 1 2 Dec.[deg] N1 = 25386 N2 = 1885 N3 = 129 N4 = 3 Figure 15.Sky distribution ofN overlap for Spring Bin 4 and Fall Bin 4 in the pane...
doi:10.1086/466510 2005
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.