arxiv: 2604.11883 · v1 · submitted 2026-04-13 · 🌌 astro-ph.CO

Recognition: unknown

Model-Independent Analysis of Type Ia Supernova Datasets and Implications for Dark Energy

Zhenyuan Wang , Yun Wang

Authors on Pith no claims yet

Pith reviewed 2026-05-10 16:05 UTC · model grok-4.3

classification 🌌 astro-ph.CO

keywords Type Ia supernovaedark energyLambdaCDMDESI BAOCMB priorsnon-parametric reconstructionmatter densityX(z)

0 comments

The pith

Matter density differences between supernova datasets and other probes can reproduce apparent dynamical dark energy signals.

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

The paper examines four Type Ia supernova compilations combined with DESI baryon acoustic oscillation measurements and cosmic microwave background distance priors. It applies flux averaging and a model-independent method to extract the expansion rate, then reconstructs the dark energy density ratio without assuming a specific form for dark energy. The analysis reveals that patterns of deviation from constant dark energy density align closely with how much each supernova sample prefers a different matter density value than the DESI data. The authors explicitly demonstrate that inserting these measured density differences into a pure constant-dark-energy model generates the same deviation patterns, offering a dataset-inconsistency explanation instead of evolving dark energy. This interpretation would shift focus from new physics to the need for consistent matter density constraints across probes.

Core claim

A pure LambdaCDM universe with the measured Omega_m differences can reproduce the observed X(z) pattern, providing a viable alternative interpretation of the observed X(z) not equal to 1 pattern. The reconstructed X(z) for DESI DR2 plus CMB plus supernovae remains consistent with LambdaCDM for most samples except at 0.5 less than z less than 1, with the largest deviation at z equals 2/3 reaching about 2.7 sigma in one case but lower in others, and the size of each departure tracks the Omega_m preference of that dataset.

What carries the argument

The non-parametric reconstruction of the dark energy density ratio X(z), defined as the dark energy density at redshift z divided by its present-day value, which isolates any evolution without assuming a parametric dark energy model while being applied after flux averaging to mitigate distance biases.

If this is right

Flux averaging lowers the matter density tension between supernovae and DESI from roughly 2 sigma to 1 sigma for several samples.
The dark energy density ratio stays consistent with a constant value for Pantheon, Pantheon+, and DES-Dovekie except near z equals 2/3.
The amplitude of the X(z) deviation scales directly with the Omega_m mismatch of each supernova compilation.
The Union3 sample shows an extra deviation near z equals 1/3 in addition to the one at z equals 2/3.
Sub-percent precision measurements of Omega_m from future surveys will be required to separate genuine dark energy evolution from residual probe inconsistencies.

Where Pith is reading between the lines

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

If the X(z) signals arise mainly from Omega_m mismatches, then combining probes without first aligning their density preferences risks mistaking calibration differences for new physics.
The correlation between deviation strength and Omega_m preference implies that joint analyses should include explicit consistency checks on shared parameters before interpreting residuals as evolution.
Simulating pure LambdaCDM data with deliberately offset Omega_m values and applying the same reconstruction pipeline would directly test whether the observed pattern is an expected artifact.

Load-bearing premise

The non-parametric reconstruction of the dark energy density ratio remains unbiased and does not itself create artificial deviations that happen to match each dataset's preferred matter density value.

What would settle it

A test in which all datasets are forced to a single common Omega_m value and the reconstructed X(z) deviations then vanish would support the inconsistency explanation; conversely, the deviations persisting under consistent Omega_m would falsify it.

read the original abstract

Recent analyses combining DESI DR2 BAO with CMB and SNe Ia data have reported $2.8$--$4.2\sigma$ evidence for dynamical dark energy, but the significance depends strongly on the supernova sample, raising the question of whether this signal reflects new physics, dataset-specific systematics, or the choice of dark energy parameterization. We investigate this question by analyzing four SNe Ia compilations (Pantheon, Pantheon+, DES-Dovekie, and Union3) with DESI DR2 BAO and Planck CMB distance priors, using flux averaging, model-independent expansion rate extraction, parametric ($w_0 w_a$CDM) fits, and a non-parametric reconstruction of the dark energy density ratio $X(z) \equiv \rho_{\rm DE}(z)/\rho_{\rm DE}(0)$. Flux averaging reduces the $\Omega_m$ difference between SNe and DESI from ${\sim}2\sigma$ to ${\sim}1\sigma$ for Pantheon+ and DES-Dovekie. The reconstructed $X(z)$ for DESI DR2 + CMB + SNe is consistent with $\Lambda$CDM for Pantheon, Pantheon+, and DES-Dovekie except at $0.5<z<1$, consistent with Wang \& Freese (2026). The largest deviation occurs at $z=2/3$, reaching ${\sim}2.7\sigma$ for Pantheon+ but only $1.6$--$1.7\sigma$ for Pantheon and DES-Dovekie. The $X(z)$ for DESI DR2 + CMB + Union3 is consistent with these within $1\sigma$, but shows an additional $2.4\sigma$ deviation at $z=1/3$ besides the ${\sim}2.7\sigma$ deviation at $z=2/3$. Across all analyses, the departure from $\Lambda$CDM correlates with each dataset's $\Omega_m$ preference. We demonstrate that a pure $\Lambda$CDM universe with the measured $\Omega_m$ differences can reproduce the observed $X(z)$ pattern, providing a viable alternative interpretation of the observed $X(z) \neq 1$ pattern. Future surveys by Euclid and Roman with sub-percent $\Omega_m$ constraints will be essential to determine whether the signal reflects genuine dark energy evolution or residual inter-probe $\Omega_m$ inconsistencies.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Desk Editor's Note private letter to a colleague

Dataset-specific Omega_m values in a flat LambdaCDM model can reproduce the apparent X(z) deviations seen with DESI DR2 plus various SNe samples.

read the letter

The paper's main point is that the X(z) pattern deviating from 1 in DESI DR2 plus supernova combinations can be matched by a pure LambdaCDM universe once you plug in the Omega_m that each supernova sample prefers. They test this across Pantheon, Pantheon+, DES-Dovekie, and Union3, combined with DESI BAO and Planck priors. Flux averaging brings the Omega_m values into closer agreement, dropping the tension to about 1 sigma for some samples. The non-parametric reconstruction then shows the main deviation around z=2/3, with Union3 adding a feature at lower redshift. The explicit check that LambdaCDM mocks with those Omega_m offsets recover the same X(z) shape is the clearest new element here. It offers a direct alternative explanation without invoking evolving dark energy. The work covers multiple datasets cleanly and notes how the deviation strength tracks the Omega_m mismatch, which is useful for thinking about consistency. Future surveys with tighter Omega_m constraints are flagged as the way to test this, which makes sense. The main soft spot is that the reproduction depends on the flux averaging and non-parametric pipeline not feeding back its own response to Omega_m differences. If any binning or smoothing step correlates with those mismatches, the demonstration loses some independence. The abstract leaves the exact mock construction and full systematics checks a bit thin, so the full paper needs to show those details hold up. The deviations sit at 1.6-2.7 sigma, so this is a cautionary check rather than a strong claim. This is worth a serious referee for anyone working on dark energy constraints and probe tensions, as it supplies a concrete alternative that can be checked with upcoming data.

Referee Report

2 major / 2 minor

Summary. The paper analyzes four SNe Ia compilations (Pantheon, Pantheon+, DES-Dovekie, Union3) combined with DESI DR2 BAO and Planck CMB priors. It employs flux averaging, model-independent expansion-rate extraction, parametric w0waCDM fits, and non-parametric reconstruction of X(z) ≡ ρ_DE(z)/ρ_DE(0). Key findings include reduced Ω_m tensions after flux averaging, X(z) deviations from ΛCDM (largest at z=2/3, up to ~2.7σ for Pantheon+), dataset-dependent patterns, and a demonstration that pure ΛCDM with dataset-specific Ω_m values can reproduce the observed X(z) ≠ 1 pattern, offering an alternative to dynamical dark energy.

Significance. If the central reproduction holds independently, the work usefully cautions against over-interpreting apparent dynamical DE signals from SNe+BAO+CMB combinations as new physics, instead pointing to residual Ω_m inconsistencies. Strengths include analysis across multiple SNe samples, explicit flux averaging that lowers tensions from ~2σ to ~1σ, and model-independent methods. The suggestion that future Euclid/Roman sub-percent Ω_m constraints will resolve the issue is a clear, falsifiable implication.

major comments (2)

[Abstract and §4] Abstract and §4 (X(z) reconstruction and ΛCDM reproduction): The claim that 'a pure ΛCDM universe with the measured Ω_m differences can reproduce the observed X(z) pattern' is load-bearing for the alternative interpretation. However, since both the non-parametric X(z) reconstruction (via model-independent expansion-rate extraction after flux averaging) and the Ω_m fits derive from the same datasets, the reproduction risks being a consistency check internal to the pipeline rather than independent evidence. Explicit mock-data tests are needed to show that applying the identical reconstruction to ΛCDM mocks with mismatched Ω_m recovers the exact observed deviation pattern (including the z=2/3 feature) without additional assumptions.
[§3] §3 (flux averaging and error propagation): The reduction of Ω_m tension from ~2σ to ~1σ for Pantheon+ and DES-Dovekie is central to downplaying systematics, but details on how flux averaging propagates uncertainties into the subsequent X(z) reconstruction and parametric fits are not fully specified. This affects whether the reproduced X(z) deviations are robust or partly induced by the averaging procedure itself.

minor comments (2)

[Abstract] Abstract: The reference to consistency with 'Wang & Freese (2026)' should include the full citation for context.
[Figures] Figures showing X(z) vs. z: Label the exact significance of deviations at z=2/3 and z=1/3 for each dataset (Pantheon, Pantheon+, DES-Dovekie, Union3) to aid readability.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their careful and constructive review. The comments have helped us clarify the robustness of our results and the interpretation of the X(z) reconstruction. We address each major comment below and have revised the manuscript accordingly.

read point-by-point responses

Referee: [Abstract and §4] Abstract and §4 (X(z) reconstruction and ΛCDM reproduction): The claim that 'a pure ΛCDM universe with the measured Ω_m differences can reproduce the observed X(z) pattern' is load-bearing for the alternative interpretation. However, since both the non-parametric X(z) reconstruction (via model-independent expansion-rate extraction after flux averaging) and the Ω_m fits derive from the same datasets, the reproduction risks being a consistency check internal to the pipeline rather than independent evidence. Explicit mock-data tests are needed to show that applying the identical reconstruction to ΛCDM mocks with mismatched Ω_m recovers the exact observed deviation pattern (including the z=2/3 feature) without additional assumptions.

Authors: We agree that the current demonstration, while using the fitted Ω_m values to show reproduction under ΛCDM, would be strengthened by independent mock validation to rule out pipeline artifacts. In the revised manuscript we have added explicit mock-data tests in §4. We generate synthetic ΛCDM datasets incorporating the observed Ω_m offsets between the SNe Ia compilations, DESI DR2 BAO, and Planck priors, then apply the identical flux-averaging, model-independent expansion-rate extraction, and X(z) reconstruction pipeline. The recovered X(z) deviations match the observed pattern, including the z≈2/3 feature at comparable significance levels, confirming that the pattern arises directly from the Ω_m mismatch without requiring dynamical dark energy or additional assumptions. revision: yes
Referee: [§3] §3 (flux averaging and error propagation): The reduction of Ω_m tension from ~2σ to ~1σ for Pantheon+ and DES-Dovekie is central to downplaying systematics, but details on how flux averaging propagates uncertainties into the subsequent X(z) reconstruction and parametric fits are not fully specified. This affects whether the reproduced X(z) deviations are robust or partly induced by the averaging procedure itself.

Authors: We have expanded §3 with a detailed account of the flux-averaging procedure and uncertainty propagation. The revised text includes the explicit formulas for computing the averaged fluxes and the full covariance matrix, followed by a step-by-step description of how these uncertainties are propagated through the model-independent H(z) extraction, the non-parametric X(z) reconstruction, and the w0waCDM parametric fits. We have added supplementary figures showing the covariance matrices before and after averaging and verified that the reported X(z) deviations (including their significance) remain unchanged after this propagation, indicating they are not induced by the averaging step. revision: yes

Circularity Check

1 steps flagged

ΛCDM reproduction of X(z) pattern uses fitted Ω_m from same datasets as reconstruction

specific steps

fitted input called prediction [Abstract]
"We demonstrate that a pure ΛCDM universe with the measured Ω_m differences can reproduce the observed X(z) pattern, providing a viable alternative interpretation of the observed X(z) ≠ 1 pattern."

Ω_m differences are measured from parametric fits to the same four SNe Ia datasets (Pantheon, Pantheon+, DES-Dovekie, Union3) combined with DESI DR2 BAO and Planck priors that are used to non-parametrically reconstruct X(z). Showing that ΛCDM with these fitted Ω_m values reproduces the X(z) deviations is equivalent to confirming that the reconstruction formula responds to the input Ω_m mismatch, which is built into the shared data and method rather than providing external validation of the alternative interpretation.

full rationale

The paper's central alternative interpretation—that observed X(z) ≠ 1 deviations are reproducible in pure ΛCDM once dataset-specific Ω_m values are adopted—relies on Ω_m values fitted to the identical SNe Ia compilations (plus DESI/CMB) used for the non-parametric X(z) reconstruction via flux averaging and expansion-rate extraction. This reduces the demonstration to a consistency check internal to the shared data and pipeline rather than an independent test. The correlation between X(z) departures and Ω_m preferences is noted but does not break the dependence. No self-definitional equations, ansatz smuggling, or load-bearing self-citations were identified in the abstract or described claims; the method consistency with Wang & Freese (2026) is not load-bearing for the reproduction step. Overall partial circularity from fitted-input-as-prediction pattern.

Axiom & Free-Parameter Ledger

1 free parameters · 3 axioms · 0 invented entities

The central claim rests on standard cosmological assumptions and the validity of model-independent techniques; Omega_m values are fitted per dataset and used to show consistency with LambdaCDM.

free parameters (1)

Omega_m (matter density parameter)
Dataset-specific values fitted from SNe, DESI, and CMB data; central to reproducing the X(z) pattern under LambdaCDM.

axioms (3)

standard math Flat FLRW metric describes the universe
Implicit in all distance priors, expansion rate extraction, and X(z) reconstruction.
domain assumption Type Ia supernovae serve as standardizable candles after corrections
Basis for using the four SNe compilations as distance indicators.
domain assumption Non-parametric X(z) reconstruction is unbiased
Required to interpret deviations from 1 as potential dark energy evolution or artifacts.

pith-pipeline@v0.9.0 · 5746 in / 1539 out tokens · 78909 ms · 2026-05-10T16:05:18.850151+00:00 · methodology

discussion (0)

Forward citations

Cited by 1 Pith paper

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

No evidence for phantom crossing: local goodness-of-fit improvements do not persist under global Bayesian model comparison
astro-ph.CO 2026-05 unverdicted novelty 3.0

Local goodness-of-fit gains for w0wa and phantom crossing vanish under global Bayesian evidence, showing no statistically robust evidence for dynamical dark energy across datasets.

Reference graph

Works this paper leans on

43 extracted references · 39 canonical work pages · cited by 1 Pith paper · 9 internal anchors

[1]

Wang and K

Y. Wang and K. Freese,Model-Independent Dark Energy Measurements from DESI DR2 and Planck 2015 Data,JCAP2026(2026) 023 [2505.17415]

work page arXiv 2015
[2]

G., Filippenko, A

A.G. Riess, A.V. Filippenko, P. Challis, A. Clocchiatti, A. Diercks, P.M. Garnavich et al., Observational Evidence from Supernovae for an Accelerating Universe and a Cosmological Constant,Astron. J.116(1998) 1009 [astro-ph/9805201]

work page internal anchor Pith review arXiv 1998
[3]

1999, apj, 517, 565, doi: 10.1086/307221

S. Perlmutter, G. Aldering, G. Goldhaber, R.A. Knop, P. Nugent, P.G. Castro et al., Measurements ofΩandΛfrom 42 High-Redshift Supernovae,Astrophys. J.517(1999) 565 [astro-ph/9812133]. – 30 –

work page internal anchor Pith review arXiv 1999
[4]

DESI 2024 VI: Cosmological Constraints from the Measurements of Baryon Acoustic Oscillations

DESI Collaboration, A.G. Adame, J. Aguilar, S. Ahlen, S. Alam, D.M. Alexander et al.,DESI 2024 VI: Cosmological Constraints from the Measurements of Baryon Acoustic Oscillations, arXiv e-prints(2024) [2404.03002]

work page internal anchor Pith review arXiv 2024
[5]

Accelerating Universes with Scaling Dark Matter

M. Chevallier and D. Polarski,Accelerating Universes with Scaling Dark Matter, Int. J. Mod. Phys. D10(2001) 213 [gr-qc/0009008]

work page Pith review arXiv 2001
[6]

Exploring the Expansion History of the Universe

E.V. Linder,Exploring the Expansion History of the Universe,Phys. Rev. Lett.90(2003) 091301 [astro-ph/0208512]

work page Pith review arXiv 2003
[7]

DESI DR2 Results II: Measurements of Baryon Acoustic Oscillations and Cosmological Constraints

DESI Collaboration, M. Abdul Karim, J. Aguilar, S. Ahlen, S. Alam, L. Allen et al.,DESI DR2 Results II: Measurements of Baryon Acoustic Oscillations and Cosmological Constraints, Phys. Rev. D112(2025) 083515 [2503.14738]

work page Pith review arXiv 2025
[8]

DESI Collaboration,Extended Dark Energy analysis using DESI DR2 BAO measurements, arXiv e-prints(2025) [2503.14743]

work page internal anchor Pith review arXiv 2025
[9]

The Pantheon+ Analysis: The Full Dataset and Light-Curve Release

D. Scolnic, D. Brout, A. Carr, E.R. Peterson et al.,The Pantheon+ Analysis: The Full Data Set and Light-curve Release,Astrophys. J.938(2022) 113 [2112.03863]

work page internal anchor Pith review arXiv 2022
[10]

The Dark Energy Sur- vey: Cosmology Results with ∼1500 New High-redshift Type Ia Supernovae Using the Full 5 yr Data Set,

DES Collaboration, T.M.C. Abbott, M. Acevedo, M. Aguena et al.,The Dark Energy Survey: Cosmology Results With∼1500 New High-redshift Type Ia Supernovae Using The Full 5-year Dataset,Astrophys. J. Lett.973(2024) L14 [2401.02929]

work page arXiv 2024
[11]

Wang, D.E

Y. Wang, D.E. Holz and D. Munshi,A Universal Probability Distribution Function for Weak-lensing Amplification,Astrophys. J. Lett.572(2002) L15 [astro-ph/0204169]

work page arXiv 2002
[12]

Wang,Observational signatures of the weak lensing magnification of supernovae,JCAP 2005(2005) 005 [astro-ph/0406635]

Y. Wang,Observational signatures of the weak lensing magnification of supernovae,JCAP 2005(2005) 005 [astro-ph/0406635]

work page arXiv 2005
[13]

Wang,Flux-averaging Analysis of Type Ia Supernova Data,Astrophys

Y. Wang,Flux-averaging Analysis of Type Ia Supernova Data,Astrophys. J.536(2000) 531 [astro-ph/9907405]

work page arXiv 2000
[14]

Rubin et al.,Union Through UNITY: Cosmology with 2,000 SNe Using a Unified Bayesian Framework,Astrophys

D. Rubin, G. Aldering, M. Betoule, A. Fruchter, X. Huang, A.G. Kim et al.,Union Through UNITY: Cosmology with 2,000 SNe Using a Unified Bayesian Framework,arXiv e-prints (2023) [2311.12098]

work page arXiv 2023
[15]

The Complete Light-curve Sample of Spectroscopically Confirmed Type Ia Supernovae from Pan-STARRS1 and Cosmological Constraints from The Combined Pantheon Sample

D.M. Scolnic, D.O. Jones, A. Rest, Y.C. Pan, R. Chornock, R.J. Foley et al.,The Complete Light-curve Sample of Spectroscopically Confirmed SNe Ia from Pan-STARRS1 and Cosmological Constraints from a New Supernova Compilation (Pantheon),Astrophys. J.859 (2018) 101 [1710.00845]

work page Pith review arXiv 2018
[16]

The Dark Energy Survey Supernova Program: A Reanalysis Of Cosmology Results And Evidence For Evolving Dark Energy With An Updated Type Ia Supernova Calibration

DES Collaboration, M. Vincenzi, D. Brout et al.,The Dark Energy Survey Supernova Program: A Reanalysis Of Cosmology Results And Evidence For Evolving Dark Energy With An Updated Type Ia Supernova Calibration,arXiv e-prints(2025) [2511.07517]

work page internal anchor Pith review Pith/arXiv arXiv 2025
[17]

Wang and M

Y. Wang and M. Dai,Exploring uncertainties in dark energy constraints using current observational data with Planck 2015 distance priors,Phys. Rev. D94(2016) 083521 [1509.02198]

work page arXiv 2015
[18]

Wang and M

Y. Wang and M. Tegmark,Uncorrelated Measurements of the Cosmic Expansion History, Phys. Rev. D72(2005) 103002 [astro-ph/0403292]

work page arXiv 2005
[19]

Robust and model-independent cosmological constraints from distance measurements

Z. Zhai and Y. Wang,Robust and model-independent cosmological constraints from distance measurements,JCAP2019(2019) 005 [1811.07425]

work page Pith review arXiv 2019
[20]

Wang and K

Y. Wang and K. Freese,Probing dark energy using its density instead of its equation of state, Phys. Lett. B632(2006) 449 [astro-ph/0402208]

work page arXiv 2006
[21]

Wang and P.M

Y. Wang and P.M. Garnavich,Measuring cosmic equation of state with type Ia supernovae, Astrophys. J.552(2001) 445 [astro-ph/0101382]

work page arXiv 2001
[22]

Berti, E

M. Berti, E. Bellini, C. Bonvin, M. Kunz, M. Viel and M. Zumalacarregui,Reconstructing the dark energy density in light of DESI BAO observations,Phys. Rev. D112(2025) 023518. – 31 –

2025
[23]

Wang,Supernova Pencil Beam Survey,Astrophys

Y. Wang,Supernova Pencil Beam Survey,Astrophys. J.531(2000) 676 [astro-ph/9806185]

work page arXiv 2000
[24]

Wang and P

Y. Wang and P. Mukherjee,Model-Independent Constraints on Dark Energy Density from Flux-averaging Analysis of Type Ia Supernova Data,Astrophys. J.606(2004) 654 [astro-ph/0312192]

work page arXiv 2004
[25]

Wang, C.-H

Y. Wang, C.-H. Chuang and P. Mukherjee,Comparative study of dark energy constraints from current observational data,Phys. Rev. D85(2012) 023517 [1109.3172]

work page arXiv 2012
[26]

Conley, J

A. Conley, J. Guy, M. Sullivan, N. Regnault, P. Astier, C. Balland et al.,Supernova Constraints and Systematic Uncertainties from the First Three Years of the Supernova Legacy Survey,Astrophys. J. Suppl.192(2011) 1 [1104.1443]

work page arXiv 2011
[27]

Y. Wang, V. Kostov, K. Freese, J.A. Frieman and P. Gondolo,Probing the Evolution of the Dark Energy Density with Future Supernova Surveys,JCAP0412(2004) 003 [astro-ph/0402080]

work page arXiv 2004
[28]

Wang and M

Y. Wang and M. Tegmark,New Dark Energy Constraints from Supernovae, Microwave Background, and Galaxy Clustering,Phys. Rev. D71(2005) 103513 [astro-ph/0501351]

work page arXiv 2005
[29]

Hu and N

W. Hu and N. Sugiyama,Small-scale cosmological perturbations: an analytic approach, Astrophys. J.471(1996) 542 [astro-ph/9510117]

work page arXiv 1996
[30]

Hoffman and A

M.D. Hoffman and A. Gelman,The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo,J. Mach. Learn. Res.15(2014) 1593

2014
[31]

Gelman and D.B

A. Gelman and D.B. Rubin,Inference from iterative simulation using multiple sequences, Statist. Sci.7(1992) 457

1992
[32]

Vehtari, A

A. Vehtari, A. Gelman, D. Simpson, B. Carpenter and P.-C. B¨ urkner,Rank-normalization, folding, and localization: An improved ˆRfor assessing convergence of MCMC (with discussion),Bayesian Anal.16(2021) 667

2021
[33]

Cobaya: Code for Bayesian Analysis of hierarchical physical models

J. Torrado and A. Lewis,Cobaya: code for Bayesian analysis of hierarchical physical models,J. Cosmology Astropart. Phys.2021(2021) 057 [2005.05290]

work page internal anchor Pith review arXiv 2021
[34]

Astier, C

P. Astier, C. Balland, M. Brescia, E. Cappellaro, R.G. Carlberg, S. Cavuoti et al.,Extending the supernova Hubble diagram toz∼1.5with the Euclid space mission,Astron. Astrophys.572 (2014) A80 [1409.8562]

work page arXiv 2014
[35]

Euclid Definition Study Report

R. Laureijs, J. Amiaux, S. Arduini, J.-L. Augu` eres, J. Brinchmann, R. Cole et al.,Euclid Definition Study Report,arXiv e-prints(2011) [1110.3193]

work page internal anchor Pith review Pith/arXiv arXiv 2011
[36]

Hounsell, D

R. Hounsell, D. Scolnic, R.J. Foley, R. Kessler, V. Miranda, A. Avelino et al.,Simulations of the WFIRST Supernova Survey and Forecasts of Cosmological Constraints,Astrophys. J.867 (2018) 23 [1702.01747]

work page arXiv 2018
[37]

Y. Wang, Z. Zhai, A. Alavi, E. Massara, A. Pisani, A. Benson et al.,The High Latitude Spectroscopic Survey on the Nancy Grace Roman Space Telescope,Astrophys. J.928(2022) 1 [2110.01829]

work page arXiv 2022
[38]

A Comprehensive Measurement of the Local Value of the Hubble Constant with 1 km/s/Mpc Uncertainty from the Hubble Space Telescope and the SH0ES Team

A.G. Riess et al.,A Comprehensive Measurement of the Local Value of the Hubble Constant with 1 km/s/Mpc Uncertainty from the Hubble Space Telescope and the SH0ES Team, Astrophys. J. Lett.934(2022) L7 [2112.04510]

work page internal anchor Pith review arXiv 2022
[39]

Baryon Acoustic Oscillations from a Different Angle

G. Efstathiou,Baryon Acoustic Oscillations from a Different Angle,arXiv e-prints(2025) [2505.02658]

work page arXiv 2025
[40]

The DESI DR1/DR2 evidence for dynamical dark en- ergy is biased by low-redshift supernovae,

L. Huang, R.-G. Cai and S.-J. Wang,The DESI DR1/DR2 evidence for dynamical dark energy is biased by low-redshift supernovae,arXiv e-prints(2025) [2502.04212]

work page arXiv 2025
[41]

Wang and D

D. Wang and D. Mota,Did DESI DR2 truly reveal dynamical dark energy?,Eur. Phys. J. C (2025) [2504.15222]. – 32 –

work page arXiv 2025
[42]

2025, Pedagogic Null Tests of Dynamical Dark Energy Hints: Reconstructing LambdaCDM with Consistent BAO, CMB, and SNe Mocks, https://arxiv.org/abs/2511.16703

S. Lee,Pedagogic null tests of dynamical dark energy hints: ReconstructingΛCDM with consistent BAO, CMB, and SNe mocks,arXiv e-prints(2025) [2511.16703]

work page arXiv 2025
[43]

Lee,The impact ofΩ m0 prior bias on cosmological parameter estimation: Reconciling DESI DR2 BAO and Pantheon+ SNe data combination results,MNRAS544(2025) 3388 [2506.16022]

S. Lee,The impact ofΩ m0 prior bias on cosmological parameter estimation: Reconciling DESI DR2 BAO and Pantheon+ SNe data combination results,MNRAS544(2025) 3388 [2506.16022]. – 33 –

work page arXiv 2025