Pith. sign in

REVIEW 3 major objections 5 minor 1 cited by

Calibrating DESI's 100,000-galaxy peculiar-velocity sample with type Ia supernovae yields H0 = 73.7 ± 1.1 km/s/Mpc, with a statistical error smaller than any previous Hubble-constant sample.

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 →

Challenge this review Re-run · record.json Download PDF Read on arXiv ↗

T0 review · deepseek-v4-flash

2026-08-03 18:48 UTC pith:YBYRE5EZ

load-bearing objection Careful, transparent calibration of the largest PV sample to date gives H0 = 73.7 ± 1.1 but inherits the SH0ES zero-point; worth a serious referee. the 3 major comments →

arxiv 2512.03232 v2 pith:YBYRE5EZ submitted 2025-12-02 astro-ph.CO

The DESI DR1 Peculiar Velocity Survey: global zero-point and H₀ constraints

A. Carr , C. Howlett , A. J. Amsellem , Tamara M. Davis , K. Said , D. Parkinson , A. Palmese , J. Aguilar
show 50 more authors
S. Ahlen J. Bautista S. BenZvi D. Bianchi C. Blake D. Brooks T. Claybaugh A. Cuceu A. de la Macorra P. Doel K. Douglass S. Ferraro J. E. Forero-Romero E. Gazta\~naga S. Gontcho A Gontcho G. Gutierrez H. K. Herrera-Alcantar K. Honscheid D. Huterer M. Ishak R. Joyce A. G. Kim D. Kirkby A. Kremin O. Lahav C. Lamman M. Landriau L. Le Guillou M. E. Levi M. Manera A. Meisner R. Miquel J. Moustakas S. Nadathur W. J. Percival F. Prada I. P\'erez-R\`afols F. Qin C. Ross G. Rossi E. Sanchez D. Schlegel H. Seo D. Sprayberry G. Tarl\'e R. J. Turner B. A. Weaver P. Zarrouk R. Zhou H. Zou
This is my paper
classification astro-ph.CO
keywords cosmologyHubble constantpeculiar velocitiesFundamental PlaneTully-Fisher relationtype Ia supernovaegalaxy groupsdistance ladder
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

The pith

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

The paper attempts to establish that the DESI DR1 peculiar-velocity sample—more than 100,000 Fundamental Plane and Tully-Fisher galaxy distances—can be zero-pointed against external distance calibrators to yield a competitive Hubble constant. Its baseline calibration against type Ia supernovae gives H0 = 73.7 ± 0.06 (stat) ± 1.1 (syst) km/s/Mpc, a statistical uncertainty lower than any previous H0 sample. The key move is to use galaxy group catalogs to more than double the number of calibrator overlaps. The authors also show that a surface-brightness-fluctuation calibration gives a consistent H0, and that the main limitation is the systematic floor inherited from the distance-ladder calibrators.

Core claim

Using the DESI DR1 Fundamental Plane and Tully-Fisher distances—roughly 104,000 galaxies—the authors measure the global zero-point by matching to external calibrators, chiefly type Ia supernovae lying in the same galaxy groups. The zero-point shift in log-distance ratio is η_zp = 0.139 ± 0.007, applied to the full PV sample; the resulting Hubble diagram gives H0 = 73.7 ± 0.06 (stat) ± 1.1 (syst) km/s/Mpc. Calibration via surface brightness fluctuations gives 74.1 ± 1.1 km/s/Mpc, consistent with the supernova value. The paper claims this is the lowest statistical H0 uncertainty achieved to date, with the systematic error dominated by the external calibrators' distance-ladder uncertainties rat

What carries the argument

The central objects are the Fundamental Plane (an empirical relation between elliptical-galaxy size, velocity dispersion, and surface brightness) and the Tully-Fisher relation (spiral-galaxy rotation speed versus luminosity), both of which yield relative distances. The argument is carried by a group-based zero-point: galaxies from several external group catalogs are merged so that any galaxy sharing a group with a calibrated distance can serve as a calibrator, increasing the calibrator overlap roughly tenfold. This enables a global zero-point η_zp = ⟨η_PV⟩ − ⟨η_cal⟩ computed with a full covariance matrix, including the zero-point uncertainty as a block; the relation Δμ = −5η links the two di

Load-bearing premise

The result hinges on a correction that shifts the mean distance of galaxies in groups back to the full-sample mean; the physical mechanism behind this offset is unconfirmed, and removing the correction is the second-largest systematic in the analysis.

What would settle it

Build the zero-point using only the galaxies that directly host type Ia supernovae, without group matching, and compare H0; if the difference exceeds the quoted systematic, the group correction is not fully understood. Alternatively, re-run with a deeper, DESI-native group catalog: if the correction vanishes, it was a selection artifact.

Watch this falsifier. Get emailed when new claim-graph text bears on it.

If this is right

  • The statistical uncertainty on H0 drops to 0.06 km/s/Mpc, so any further precision gains must come from reducing calibration systematics, not from adding more peculiar-velocity galaxies.
  • If future DESI releases can overlap with Cepheid or tip-of-the-red-giant-branch calibrators, the group-based approach could produce a percent-level H0 from a shorter distance ladder independent of supernovae.
  • The consistency between the supernova and surface-brightness-fluctuation zero-points (0.139 versus 0.134, differing by 0.005) suggests the Cepheid-calibrated distance scale anchors the DESI sample robustly.
  • The low-redshift (z < 0.01) disagreement between DESI and the calibrators means future analyses must either model local volume effects or continue to exclude that region from zero-point fits.

Where Pith is reading between the lines

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

  • If the group correction (δFP ≈ −0.057 mag) is indeed a selection effect from shallower external group catalogs, a DESI-native group catalog should make the correction vanish; this is directly testable in the next data release.
  • The z < 0.01 discrepancy could be turned into a probe of local large-scale structure: a peculiar-velocity sample this size may map the local velocity field in detail, converting a nuisance into a measurement.
  • The method's dependence on supernova calibration means it cannot settle the Hubble tension by itself, but a future two-rung DESI ladder calibrated directly to Cepheids or the tip of the red giant branch would provide a largely independent check on both the supernova distance ladder and the cosmic-microwave-background-inferred H0.

Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

3 major / 5 minor

Summary. This paper calibrates the zero-point of the DESI DR1 Fundamental Plane and Tully-Fisher peculiar-velocity distance sample. Using a galaxy-group catalog to expand the overlap with external distance anchors, the authors align the TF and FP samples, correct a statistically significant offset between grouped and ungrouped FP galaxies (δFP, Eq. 1), apply a similar group correction for SN hosts (δSN, §5.5), and compute a global zero-point relative to SH0ES/Pantheon+ SNe Ia. The calibrated sample yields H0 = 73.7 ± 0.06 (stat) ± 1.1 (syst) km/s/Mpc, consistent with an SBF-based calibration (74.1 ± 1.1). The paper reports extensive systematics tests, with the largest shifts coming from the z>0.01 calibrator cut and the group corrections.

Significance. If the zero-point methodology holds, this work demonstrates that a >100,000-galaxy PV sample reaches a statistical precision well below the systematic floor, and it provides a consistency check of the SH0ES/Pantheon+ distance ladder through an independent set of distance tracers. The transparent use of the full SN covariance matrix and the detailed systematics budget are commendable. However, the H0 value is not an independent Hubble constant: the zero-point is defined by matching to SNe Ia that carry the SH0ES calibration, so the central value will track SH0ES by construction. The scientific value lies in the calibration infrastructure and the SBF/maser cross-checks, not in a new local H0 measurement.

major comments (3)
  1. [§4.1, §5.5, Eq. (12)] The central zero-point rests on the group-selection corrections δFP = −0.057 ± 0.010 mag (Eq. 1) and δSN (§5.5), whose physical origin is explicitly unconfirmed (§7). The systematics tests in §6.1.5 remove these corrections, but all variants share the same grouping scheme and correction philosophy; removing a correction is not equivalent to an independent calibration. I request a direct-match-only zero-point (using only galaxies with direct SN/SBF matches, no group-expanded distances) as a cross-check, and explicit propagation of the δFP and δSN uncertainties into the covariance matrix of Eq. (12). The current matrix includes σ_ηzp and σ_δη but not the uncertainties in the group corrections themselves.
  2. [Abstract, §3.1, §6.3] Because the zero-point is defined by aligning DESI distances to SH0ES/Pantheon+ SNe Ia, the resulting H0 inherits the entire three-rung calibration and will track the SH0ES value by construction. The paper discloses this clearly in §6.3, but the abstract and title present 'H0 constraints' without this caveat. I recommend reframing the primary result as a calibration of the DESI PV zero-point with an H0 consistency check, and stating in the abstract that the H0 value is not an independent measurement of the Hubble constant.
  3. [§5.5, §6.1.4] The z>0.01 calibrator cut is the largest systematic in Fig. 10, yet its justification is qualitative: low-redshift SN residuals are attributed to peculiar velocities and volume scattering, while the DESI PV residuals in the same region are described as 'in the opposite direction.' The binary test that removes the cut is useful, but it does not establish that the cut is not absorbing a real redshift-dependent offset. I ask for a sensitivity scan of the cut redshift (e.g., 0.008, 0.012, 0.015) and, if feasible, a joint model of the low-z calibration offset.
minor comments (5)
  1. [§3.3] 'tip of the red giant branch (TRBG)' should be 'TRGB'; the acronym is correct elsewhere.
  2. [§5.4] 'between FP and T' should be 'FP and TF'.
  3. [§5.5/Fig. 7] The text says the average difference is 0.139±0.007, but the caption reads 'PV G′ SN G′: 0.139+/-0.007'; please make the notation consistent.
  4. [Abstract] The claim of 'lower statistical uncertainty than any previously used to measure H0' is technically true but potentially misleading; consider emphasizing that the total uncertainty is dominated by calibrator systematics.
  5. [Data Availability] The Zenodo DOI is a placeholder; please provide the final DOI or a clear statement that it will be activated upon acceptance.

Circularity Check

1 steps flagged

Headline H0 is inherited from the SN calibrator rather than independently predicted: the zero-point is defined to match SH0ES/Pantheon+ distances, so the fitted H0 tracks the input ladder by construction.

specific steps
  1. fitted input called prediction [Sec. 5.5 (Eq. 10) and Sec. 6.3]
    "ηzp = ⟨η PV⟩G′ − ⟨η cal⟩G′. ... Since this distance ladder contains systematic uncertainties from all three rungs, our analysis cannot in principle give a H0 constraint tighter than the SH0ES measurement. ... For this reason, our H0 constraints are never tighter than those achieved from the calibrator by itself."

    The zero-point is defined as the weighted difference between the DESI PV sample and the SH0ES/Pantheon+ SN distances. Those SN distances already encode the SH0ES H0 (73.04 km/s/Mpc). After shifting the DESI sample by this zero-point, the H0 fit returns the calibrator's H0 up to small relative-distance weighting. The headline H0 = 73.7 ± 1.1 is therefore statistically forced by the input calibration rather than being an independent prediction from the DESI sample. The paper is transparent about this floor, but the numerical central value is still inherited by construction.

full rationale

The paper's central contribution is the zero-point calibration of the DESI FP/TF sample and the demonstration that a >100,000-galaxy PV sample can yield very small statistical uncertainties. The group-matching and selection-correction methodology are independent modeling steps. However, the headline H0 constraint itself is not independent of the SH0ES/Pantheon+ distance ladder: Eq. (10) defines the zero-point as the difference between DESI and SN-calibrator distances, and the paper explicitly acknowledges that the H0 constraint cannot be tighter than the calibrator's own H0 and that the systematic uncertainty is approximately equal to the SH0ES total uncertainty. Thus the central numerical result reduces, by construction, to the input SN calibration. The group corrections (δFP, δSN) are internally estimated and tested, so they are systematic modeling choices rather than circular predictions, but the main H0 value is a calibrated inheritance rather than an independent measurement. This is disclosed, so the circularity is partial rather than hidden, scoring 6.

Axiom & Free-Parameter Ledger

6 free parameters · 7 axioms · 0 invented entities

The measurement rests on well-established distance-ladder assumptions plus two ad hoc corrections (FP group offset and low-z cut) whose physical origins are not fully confirmed. The TF/FP relation coefficients are external inputs from companion papers. No new physical entities are introduced.

free parameters (6)
  • FP group-selection correction δFP = -0.057 ± 0.010 mag (converted to η)
    Weighted mean offset between FP galaxies in groups and the full FP sample (§4.1, Eq. 1); applied to make grouped FP mean representative. The physical mechanism is unconfirmed.
  • SN-host group correction δSN = consistent with 0 (weighted mean difference applied)
    Difference between grouped PV η and full PV η for groups containing SNe (§5.5); p = 0.05, applied as a correction despite being consistent with zero.
  • TF-FP alignment offset δη = 0.0051 ± 0.0041
    Measured offset used to align TF to FP (§5.4); adds a covariance block to the DESI covariance matrix.
  • TF relation slope/intercept (a, b) = not quoted in this paper
    Taken from Douglass et al. (in prep.); needed to convert rotation velocity to absolute magnitude (Eq. 2).
  • FP relation coefficients (a, b, c) = not quoted in this paper
    Taken from Ross et al. (in prep.); needed to convert velocity dispersion and surface brightness to effective radius (Eq. 7).
  • q0 in free-fit case = -0.56 +0.01/-0.02
    Constraint on deceleration parameter when allowed free; heavily influenced by the DES Y5 prior and not used for the fiducial H0 result.
axioms (7)
  • domain assumption TF and FP relations are standard candles/rulers with no significant redshift evolution over the fitted range.
    Invoked in §5.3, where the zero-point process enforces no evolution of η or Δμ across redshift bins.
  • domain assumption All galaxies within a galaxy group are at the same distance.
    Used throughout §4 to expand the calibrator sample by matching group members; the paper notes this breaks down at very low redshift for large clusters.
  • domain assumption The SH0ES/Pantheon+ SN covariance matrix fully captures the statistical and systematic uncertainties of the distance ladder.
    Stated in §3.1 and used as the irreducible uncertainty floor; the paper explicitly notes H0 cannot be tighter than SH0ES.
  • ad hoc to paper The low-redshift (z < 0.01) disagreement between DESI PV and calibrators is due to peculiar-velocity and volume-scattering effects, justifying the redshift cut.
    Discussed in §5.5 and §6.1.4; this cut is the largest systematic test in Fig. 10, yet it is applied to the fiducial zero-point.
  • domain assumption The 2M++/pvhub velocity-field reconstruction adequately corrects redshifts for large-scale coherent motions when fitting H0.
    Used in §6 to convert to the Hubble-diagram frame z_HD; the paper argues this is best practice for H0 fits.
  • domain assumption Fiducial flat ΛCDM with Ωm = 0.3151 is adequate for converting redshifts to distances at z < 0.1.
    Adopted in §5.3; the paper argues the choice has no significant effect at these low redshifts.
  • ad hoc to paper The group-selection corrections δFP and δSN remove the bias introduced by the shallower group catalogs.
    Applied in §4.1 and §5.5; §7 states the source of the mechanism is not confirmed, making this an unverified correction.

pith-pipeline@v1.3.0-alltime-deepseek · 25954 in / 12315 out tokens · 114064 ms · 2026-08-03T18:48:58.176171+00:00 · methodology

0 comments
read the original abstract

The Dark Energy Spectroscopic Instrument (DESI) in its first Data Release (DR1) already provides more than 100,000 galaxies with relative distance measurements. The primary purpose of this paper is to perform the calibration of the zero-point for the DESI Fundamental Plane and Tully-Fisher relations, which allows us to measure the Hubble constant, $H_0$. This sample has a lower statistical uncertainty than any previously used to measure $H_0$, and we investigate the systematic uncertainties in absolute calibration that could limit the accuracy of that measurement. We improve upon the DESI Early Data Release Fundamental Plane $H_0$ measurement by a) using a group catalog to increase the number of calibrator galaxies and b) investigating alternative calibrators in the nearby Universe. Our baseline measurement calibrates to the SH0ES/Pantheon+ type Ia supernovae, and finds $H_0=73.7\pm 0.06\;(\text{stat.})\pm 1.1\;(\text{syst.})$ km s$^{-1}$ Mpc$^{-1}$. Calibrating to surface brightness fluctuation (SBF) distances yields a similar $H_0$. We explore measurements using other calibrators, but these are currently less precise since the overlap with DESI peculiar velocity tracers is much smaller. In future data releases with an even larger peculiar velocity sample, we plan to calibrate directly to Cepheids and the tip of the red giant branch, which will enable the uncertainty to decrease towards a percent-level measurement of $H_0$. This will provide an alternative to supernovae as the Hubble flow sample for $H_0$ measurements.

Figures

Figures reproduced from arXiv: 2512.03232 by A. Carr, A. Cuceu, A. de la Macorra, A. G. Kim, A. J. Amsellem, A. Kremin, A. Meisner, A. Palmese, B. A. Weaver, C. Blake, C. Howlett, C. Lamman, C. Ross, D. Bianchi, D. Brooks, D. Huterer, D. Kirkby, D. Parkinson, D. Schlegel, D. Sprayberry, E. Gazta\~naga, E. Sanchez, F. Prada, F. Qin, G. Gutierrez, G. Rossi, G. Tarl\'e, H. K. Herrera-Alcantar, H. Seo, H. Zou, I. P\'erez-R\`afols, J. Aguilar, J. Bautista, J. E. Forero-Romero, J. Moustakas, K. Douglass, K. Honscheid, K. Said, L. Le Guillou, M. E. Levi, M. Ishak, M. Landriau, M. Manera, O. Lahav, P. Doel, P. Zarrouk, R. Joyce, R. J. Turner, R. Miquel, R. Zhou, S. Ahlen, S. BenZvi, S. Ferraro, S. Gontcho A Gontcho, S. Nadathur, Tamara M. Davis, T. Claybaugh, W. J. Percival.

Figure 1
Figure 1. Figure 1: Example of how we combine group catalogs to discover calibrators that are in the same group as DESI PV galaxies. Taking Lim group 2dFGRS 949 (orange circles in the left panel) as the initial group that contains one of our DESI PV galaxies (step 3), the SDSS group (green circles) was found to overlap (step 4), and then 2dFGRS 4889 was linked (step 6). The final group is defined as all galaxies discovered in… view at source ↗
Figure 2
Figure 2. Figure 2: Distributions of TF distance indicators in groups (green) and in the full sample (gray). There is no evidence of a difference between the populations. ies, in Figures 2 and 3. The use of ∆µ is expanded upon in Sec. 5, but it can be viewed simply as distance for this test. Basically, ∆µ represents the apparent brightness (in magnitudes) compared to the prediction from a cos￾mological model, so a positive va… view at source ↗
Figure 4
Figure 4. Figure 4: The difference between FP and TF η in each group containing at least one of each type of galaxy. Indi￾vidual η differences are in pink, and the binned, weighted averages are in black. There is no significant trend with redshift. The black dashed line shows the average differ￾ence/offset [PITH_FULL_IMAGE:figures/full_fig_p009_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: “Hubble Diagram” in η, which shows Hubble residuals as a function of redshift. We expect it to be flat in z, and centered on 0 when we use the same fiducial cosmology as was used to generate the catalogs. model to convert z to D, so a model must be assumed to calculate η for FP, as well as to find µmodel and there￾fore ∆µ for TF. For this model, we choose flat ΛCDM with the DESI fiducial Ωm = 0.3151 (Planc… view at source ↗
Figure 6
Figure 6. Figure 6: Comparison of the distributions of all DESI PV η (gray) and of the galaxies in groups with SNe (pink). The means (dashed lines) disagree by < 1σ, but the K–S test still shows some evidence that they are different distributions. 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 zCMB 0.2 0.1 0.0 0.1 0.2 0.3 0.4 0.5 PV SN only FP only TF both PV G0 SN G0: 0.139+/-0.007 [PITH_FULL_IMAGE:figures/full_fig_p011_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: The difference between the log-distance ratio given by DESI and Pantheon+ SNe Ia for individual groups (for visualization only). The average difference between the two is the zero-point (gray dashed line). We shift the DESI PV sample to match the SN. groups containing SNe versus all galaxies are less clear ( [PITH_FULL_IMAGE:figures/full_fig_p011_7.png] view at source ↗
Figure 9
Figure 9. Figure 9: Alternative calibrators compared to the DESI log-distance ratio Hubble Diagram. The white-outlined cir￾cles represent each calibrator, and the DESI PV values (pink circles, squares) are displayed on the SN zero-point for com￾parison [PITH_FULL_IMAGE:figures/full_fig_p012_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: Whisker plot of all systematic tests. Each point corresponds to a single change to the fiducial zero-pointing and H0 fitting pipeline. The black point, gray-shaded region and gray dashed line all represent the fiducial measurement, and each color corresponds to the systematic group described in Sections 6.1.1 to 6.1.5. The weighted standard deviation of all tests results in σH0 (syst.) = 0.29 km s−1 Mpc−1… view at source ↗
Figure 11
Figure 11. Figure 11: Comparison of H0 constraints from each choice of calibrator and from the literature. Each DESI DR1 measurement comes from the combined FP and TF relations calibrated by each of the calibrators shown above the dotted line. For each measurement, we show the total uncertainty (blue) and highlight the systematic component (orange). The blue shaded region corresponds to the fiducial measurement for comparison … view at source ↗
Figure 12
Figure 12. Figure 12: Hubble diagram displaying the DESI distance moduli (faint blue points) with our fiducial best fit using the SN Ia zero-point with fixed q0 (grey line), with the SN+SBF and SH0ES results also shown for comparison (orange dashed and red dotted line, respectively). The binned data (blue squares) were calculated from the DESI covariance matrix built to fit H0. For each calibrator type, we provide an approxima… view at source ↗
Figure 13
Figure 13. Figure 13: Posteriors on cosmological parameters from the DESI PV sample zero-pointed to SNe Ia (blue) compared with the fiducial SH0ES result (orange) for which q0 was fixed to −0.55. relying on only two masers is apparent. The SNe Ia and SBF were all calibrated from Cepheids (which were cal￾ibrated using masers) and all show good consistency, as expected. The combination of SNe Ia and SBF that is allowed from bein… view at source ↗

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. The DESI DR1 Peculiar Velocity Survey: growth rate measurements from the maximum likelihood fields method

    astro-ph.CO 2025-12 accept novelty 5.0

    DESI DR1 peculiar velocity data yields fσ8(z_eff=0.07) = 0.450 ± 0.055, consistent with Planck ΛCDM and GR growth index γ = 0.58 ± 0.11.

Reference graph

Works this paper leans on

50 extracted references · 3 canonical work pages · cited by 1 Pith paper

  1. [1]

    S., Rizzi, L., Tully, R

    Anand, G. S., Rizzi, L., Tully, R. B., et al. 2021, AJ, 162, 80, doi: 10.3847/1538-3881/ac0440

    doi:10.3847/1538-3881/ac0440 2021

  2. [2]

    2019, Astrophys

    Ashton, G., et al. 2019, Astrophys. J. Suppl., 241, 27, doi: 10.3847/1538-4365/ab06fc Bautista et al., J. in prep

    doi:10.3847/1538-4365/ab06fc 2019

  3. [3]

    C., Ferrarese, L., Onken, C

    Bentz, M. C., Ferrarese, L., Onken, C. A., Peterson, B. M., & Valluri, M. 2019, ApJ, 885, 161, doi: 10.3847/1538-4357/ab48fb 20Carr et al

    work page doi:10.3847/1538-4357/ab48fb 2019

  4. [4]

    M., Macri, L

    Bhardwaj, A., Kanbur, S. M., Macri, L. M., et al. 2016, AJ, 151, 88, doi: 10.3847/0004-6256/151/4/88

    doi:10.3847/0004-6256/151/4/88 2016

  5. [5]

    P., Cantiello, M., Mei, S., et al

    Blakeslee, J. P., Cantiello, M., Mei, S., et al. 2010, ApJ, 724, 657, doi: 10.1088/0004-637X/724/1/657

    doi:10.1088/0004-637x/724/1/657 2010

  6. [6]

    G., Casertano, S., et al

    Breuval, L., Riess, A. G., Casertano, S., et al. 2024, ApJ, 973, 30, doi: 10.3847/1538-4357/ad630e

    doi:10.3847/1538-4357/ad630e 2024

  7. [7]

    2022, ApJ, 938, 110, doi: 10.3847/1538-4357/ac8e04

    Brout, D., Scolnic, D., Popovic, B., et al. 2022, ApJ, 938, 110, doi: 10.3847/1538-4357/ac8e04

    doi:10.3847/1538-4357/ac8e04 2022

  8. [8]

    P., Ferrarese, L., et al

    Cantiello, M., Blakeslee, J. P., Ferrarese, L., et al. 2018, ApJ, 856, 126, doi: 10.3847/1538-4357/aab043

    doi:10.3847/1538-4357/aab043 2018

  9. [9]

    M., Scolnic, D., et al

    Carr, A., Davis, T. M., Scolnic, D., et al. 2022, PASA, 39, e046, doi: 10.1017/pasa.2022.41

    doi:10.1017/pasa.2022.41 2022

  10. [10]

    J., Lavaux, G., & Hudson, M

    Carrick, J., Turnbull, S. J., Lavaux, G., & Hudson, M. J. 2015, MNRAS, 450, 317, doi: 10.1093/mnras/stv547

    doi:10.1093/mnras/stv547 2015

  11. [11]

    M., Hinton, S

    Davis, T. M., Hinton, S. R., Howlett, C., & Calcino, J. 2019, MNRAS, 490, 2948, doi: 10.1093/mnras/stz2652 DES Collaboration, Abbott, T. M. C., Acevedo, M., et al. 2024, ApJL, 973, L14, doi: 10.3847/2041-8213/ad6f9f DESI Collaboration, Aghamousa, A., Aguilar, J., et al. 2016a, arXiv e-prints, arXiv:1611.00037, doi: 10.48550/arXiv.1611.00037 DESI Collabora...

    Pith/arXiv arXiv doi:10.48550/arxiv.1611.00037 2019

  12. [12]

    J., Lang, D., et al

    Dey, A., Schlegel, D. J., Lang, D., et al. 2019, AJ, 157, 168, doi: 10.3847/1538-3881/ab089d

    doi:10.3847/1538-3881/ab089d 2019

  13. [13]

    1987, ApJ, 313, 59, doi: 10.1086/164948

    Djorgovski, S., & Davis, M. 1987, ApJ, 313, 59, doi: 10.1086/164948

    doi:10.1086/164948 1987

  14. [14]

    2025, arXiv e-prints, arXiv:2507.11765, doi: 10.48550/arXiv.2507.11765 Douglass et al., K

    Douglass, K., BenZvi, S., Uberoi, N., et al. 2025, arXiv e-prints, arXiv:2507.11765, doi: 10.48550/arXiv.2507.11765 Douglass et al., K. in prep

    Pith/arXiv arXiv doi:10.48550/arxiv.2507.11765 2025

  15. [15]

    1987, ApJ, 313, 42, doi: 10.1086/164947

    Dressler, A., Lynden-Bell, D., Burstein, D., et al. 1987, ApJ, 313, 42, doi: 10.1086/164947

    doi:10.1086/164947 1987

  16. [16]

    L., Madore, B

    Freedman, W. L., Madore, B. F., Gibson, B. K., et al. 2001, ApJ, 553, 47, doi: 10.1086/320638

    doi:10.1086/320638 2001

  17. [17]

    L., Madore, B

    Freedman, W. L., Madore, B. F., Hatt, D., et al. 2019, ApJ, 882, 34, doi: 10.3847/1538-4357/ab2f73

    doi:10.3847/1538-4357/ab2f73 2019

  18. [18]

    2023, AJ, 165, 144, doi: 10.3847/1538-3881/acb212

    Guy, J., Bailey, S., Kremin, A., et al. 2023, AJ, 165, 144, doi: 10.3847/1538-3881/acb212

    doi:10.3847/1538-3881/acb212 2023

  19. [19]

    J., Ruiz-Macias, O., et al

    Hahn, C., Wilson, M. J., Ruiz-Macias, O., et al. 2023, AJ, 165, 253, doi: 10.3847/1538-3881/accff8

    doi:10.3847/1538-3881/accff8 2023

  20. [20]

    R., et al

    Howlett, C., Said, K., Lucey, J. R., et al. 2022, MNRAS, 515, 953, doi: 10.1093/mnras/stac1681

    doi:10.1093/mnras/stac1681 2022

  21. [21]

    B., Blakeslee, J

    Jensen, J. B., Blakeslee, J. P., Ma, C.-P., et al. 2021, ApJS, 255, 21, doi: 10.3847/1538-4365/ac01e7

    doi:10.3847/1538-4365/ac01e7 2021

  22. [22]

    D., Riess, A

    Kenworthy, W. D., Riess, A. G., Scolnic, D., et al. 2022, ApJ, 935, 83, doi: 10.3847/1538-4357/ac80bd

    work page doi:10.3847/1538-4357/ac80bd 2022

  23. [23]

    2024, joshspeagle/dynesty: v2.1.4, v2.1.4 Zenodo, doi: 10.5281/zenodo.12537467

    Koposov, S., Speagle, J., Barbary, K., et al. 2024, joshspeagle/dynesty: v2.1.4, v2.1.4 Zenodo, doi: 10.5281/zenodo.12537467

    doi:10.5281/zenodo.12537467 2024

  24. [24]

    B., Eftekharzadeh, S., et al

    Kourkchi, E., Tully, R. B., Eftekharzadeh, S., et al. 2020, ApJ, 902, 145, doi: 10.3847/1538-4357/abb66b Lai et al., Y. in prep. L´ eget, P.-F., Pruzhinskaya, M. V., Ciulli, A., et al. 2018, A&A, 615, A162, doi: 10.1051/0004-6361/201832932

    doi:10.3847/1538-4357/abb66b 2020

  25. [25]

    H., Mo, H

    Lim, S. H., Mo, H. J., Lu, Y., Wang, H., & Yang, X. 2017, MNRAS, 470, 2982, doi: 10.1093/mnras/stx1462

    doi:10.1093/mnras/stx1462 2017

  26. [26]

    N., Doel, P., Gutierrez, G., et al

    Miller, T. N., Doel, P., Gutierrez, G., et al. 2024, AJ, 168, 95, doi: 10.3847/1538-3881/ad45fe

    doi:10.3847/1538-3881/ad45fe 2024

  27. [27]

    2023, ApJS, 269, 3, doi: 10.3847/1538-4365/acfaa2 Nguyen et al., A

    Moustakas, J., Lang, D., Dey, A., et al. 2023, ApJS, 269, 3, doi: 10.3847/1538-4365/acfaa2 Nguyen et al., A. in prep

    doi:10.3847/1538-4365/acfaa2 2023

  28. [28]

    W., Braatz, J

    Pesce, D. W., Braatz, J. A., Reid, M. J., et al. 2020, ApJL, 891, L1, doi: 10.3847/2041-8213/ab75f0

    doi:10.3847/2041-8213/ab75f0 2020

  29. [29]

    R., Kenworthy, W

    Peterson, E. R., Kenworthy, W. D., Scolnic, D., et al. 2022, ApJ, 938, 112, doi: 10.3847/1538-4357/ac4698

    doi:10.3847/1538-4357/ac4698 2022

  30. [30]

    R., Carreres, B., Carr, A., et al

    Peterson, E. R., Carreres, B., Carr, A., et al. 2025, ApJ, 980, 21, doi: 10.3847/1538-4357/ada285 Planck Collaboration, Aghanim, N., Akrami, Y., et al. 2020, A&A, 641, A6, doi: 10.1051/0004-6361/201833910

    work page doi:10.3847/1538-4357/ada285 2025

  31. [31]

    2024, AJ, 168, 245, doi: 10.3847/1538-3881/ad76a4

    Poppett, C., Tyas, L., Aguilar, J., et al. 2024, AJ, 168, 245, doi: 10.3847/1538-3881/ad76a4

    doi:10.3847/1538-3881/ad76a4 2024

  32. [32]

    H., Flannery, B

    Press, W. H., Flannery, B. P., & Teukolsky, S. A. 1986, Numerical recipes. The art of scientific computing Qin et al., F. in prep

    1986

  33. [33]

    J., Pesce, D

    Reid, M. J., Pesce, D. W., & Riess, A. G. 2019, ApJL, 886, L27, doi: 10.3847/2041-8213/ab552d

    doi:10.3847/2041-8213/ab552d 2019

  34. [34]

    G., Macri, L

    Riess, A. G., Macri, L. M., Hoffmann, S. L., et al. 2016, ApJ, 826, 56, doi: 10.3847/0004-637X/826/1/56

    doi:10.3847/0004-637x/826/1/56 2016

  35. [35]

    G., Yuan, W., Macri, L

    Riess, A. G., Yuan, W., Macri, L. M., et al. 2022, ApJL, 934, L7, doi: 10.3847/2041-8213/ac5c5b Ross et al., C. in prep

    doi:10.3847/2041-8213/ac5c5b 2022

  36. [36]

    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

    doi:10.1093/mnras/staf700 2025

  37. [37]

    A., et al

    Saulder, C., Howlett, C., Douglass, K. A., et al. 2023, MNRAS, 525, 1106, doi: 10.1093/mnras/stad2200 DESI PV Survey DR1: zero-point andH 0 21

    doi:10.1093/mnras/stad2200 2023

  38. [38]

    F., Kirkby, D., Schlegel, D

    Schlafly, E. F., Kirkby, D., Schlegel, D. J., et al. 2023, AJ, 166, 259, doi: 10.3847/1538-3881/ad0832

    doi:10.3847/1538-3881/ad0832 2023

  39. [39]

    2022, ApJ, 938, 113, doi: 10.3847/1538-4357/ac8b7a

    Scolnic, D., Brout, D., Carr, A., et al. 2022, ApJ, 938, 113, doi: 10.3847/1538-4357/ac8b7a

    doi:10.3847/1538-4357/ac8b7a 2022

  40. [40]

    G., Murakami, Y

    Scolnic, D., Riess, A. G., Murakami, Y. S., et al. 2025, ApJL, 979, L9, doi: 10.3847/2041-8213/ada0bd

    doi:10.3847/2041-8213/ada0bd 2025

  41. [41]

    H., Fagrelius, P., Fanning, K., et al

    Silber, J. H., Fagrelius, P., Fanning, K., et al. 2023, AJ, 165, 9, doi: 10.3847/1538-3881/ac9ab1

    doi:10.3847/1538-3881/ac9ab1 2023

  42. [42]

    2004, in American Institute of Physics Conference Series, Vol

    Skilling, J. 2004, in American Institute of Physics Conference Series, Vol. 735, Bayesian Inference and Maximum Entropy Methods in Science and Engineering: 24th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, ed. R. Fischer, R. Preuss, & U. V. Toussaint (AIP), 395–405, doi: 10.1063/1.1835238

    doi:10.1063/1.1835238 2004

  43. [43]

    2006, Bayesian Analysis, 1, 833 , doi: 10.1214/06-BA127

    Skilling, J. 2006, Bayesian Analysis, 1, 833 , doi: 10.1214/06-BA127

    doi:10.1214/06-ba127 2006

  44. [44]

    Speagle, J. S. 2020, Monthly Notices of the Royal Astronomical Society, 493, 3132, doi: 10.1093/mnras/staa278

    doi:10.1093/mnras/staa278 2020

  45. [45]

    E., de Jaeger, T., Boruah, S

    Stahl, B. E., de Jaeger, T., Boruah, S. S., et al. 2021, MNRAS, 505, 2349, doi: 10.1093/mnras/stab1446

    doi:10.1093/mnras/stab1446 2021

  46. [46]

    2025, arXiv e-prints, arXiv:2509.09665, doi: 10.48550/arXiv.2509.09665

    Stiskalek, R., Desmond, H., Tsaprazi, E., et al. 2025, arXiv e-prints, arXiv:2509.09665, doi: 10.48550/arXiv.2509.09665

    Pith/arXiv arXiv doi:10.48550/arxiv.2509.09665 2025

  47. [47]

    L., Dressler, A., Blakeslee, J

    Tonry, J. L., Dressler, A., Blakeslee, J. P., et al. 2001, ApJ, 546, 681, doi: 10.1086/318301

    doi:10.1086/318301 2001

  48. [48]

    B., & Fisher, J

    Tully, R. B., & Fisher, J. R. 1977, A&A, 54, 661

    1977

  49. [49]

    B., Rizzi, L., Shaya, E

    Tully, R. B., Rizzi, L., Shaya, E. J., et al. 2009, AJ, 138, 323, doi: 10.1088/0004-6256/138/2/323

    doi:10.1088/0004-6256/138/2/323 2009

  50. [50]

    B., Kourkchi, E., Courtois, H

    Tully, R. B., Kourkchi, E., Courtois, H. M., et al. 2023, ApJ, 944, 94, doi: 10.3847/1538-4357/ac94d8 Turner et al., R. in prep

    doi:10.3847/1538-4357/ac94d8 2023