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Future gravitational-wave standard sirens will be able to distinguish whether cosmic acceleration is driven by horizon entropy production (GREA) or by a cosmological constant (ΛCDM), according to forecast analyses with current and mock data

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2026-08-02 19:28 UTC pith:27M4HWMD

load-bearing objection Solid Bayesian constraint-and-forecast paper on GREA; the GW forecast is conditional on a compressed-CMB approximation the paper itself flags, so read the headline numbers with caution. the 2 major comments →

arxiv 2603.01934 v2 pith:27M4HWMD submitted 2026-03-02 astro-ph.CO

Current and future constraints on the expansion history of the GREA model

Irene Graziotti , Chiara De Leo , Matteo Martinelli This is my paper
classification astro-ph.CO
keywords entropic accelerationGREAcosmic accelerationdark energyBayesian model comparisongravitational wave standard sirenscosmological horizon thermodynamicsexpansion history
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.

This paper asks whether the General Relativistic Entropic Acceleration (GREA) model—in which cosmic acceleration emerges from entropy production at the cosmological horizon rather than from a cosmological constant—can survive contact with current and future data. Using current BAO, supernova, cosmic-chronometer, and compressed CMB measurements, it finds that ΛCDM is statistically preferred whenever CMB information is included, while GREA remains competitive for low-redshift datasets. It then constructs a modified GREA with an extra dark-energy component that recovers ΛCDM as a limit, and shows that this extra parameter is strongly degenerate with the model's horizon parameter. Forecasts with simulated data from future radio, optical, and gravitational-wave surveys indicate that standard-siren distance measurements will sharply discriminate between the entropic and dark-energy scenarios, favoring the true model whether it is GREA or ΛCDM. The paper's central bet is that third-generation gravitational-wave detectors will settle the question.

Core claim

The central claim is that future multi-probe observations, especially gravitational-wave standard sirens—merging neutron stars whose distance is measured directly by gravitational waves and whose redshift is identified through a host galaxy—will provide sufficient sensitivity to identify GREA as the preferred model when it is the true cosmology, and to disfavor it when ΛCDM is true. This claim rests on a forecast: mock data generated from GREA, analyzed within GREA, ΛCDM, and modified GREA, yield Bayes factors of ΔlogZ≈−8 relative to ΛCDM when standard-siren data are included, while mock data from ΛCDM yield ΔlogZ≈−12 against GREA. The discriminating power comes from the luminosity distance–

What carries the argument

The geometric horizon parameter √(-k)η0—the dimensionless product of spatial curvature and present conformal time—controls the GREA background. The entropy-driven term in the Friedmann equation, sinh(2τ)/[(-k)^{3/2}V_c], normalized by the comoving volume V_c, drives late-time acceleration; the modified model adds a constant dark-energy density Ωde that allows a continuous interpolation to ΛCDM. Bayesian evidence computed by nested sampling supplies the model comparison, with the luminosity distance DL(z) acting as the observable most sensitive to the difference.

Load-bearing premise

In Section 3.1, the paper assumes the early-universe expansion history of GREA is identical to ΛCDM, which justifies applying compressed CMB information and analytic fits for the drag and decoupling redshifts (Eqs. 14 and 17); if the entropic term alters the sound horizon or recombination, the CMB calibration underlying the central ΔlogZ values would shift.

What would settle it

If a full CMB likelihood including perturbation evolution were computed within GREA's actual early-time expansion and the resulting sound-horizon calibration changed the current ΔlogZ values, or if a future sample of a few hundred standard sirens measured DL(z) to sub-percent precision and matched ΛCDM while excluding the GREA prediction with √(-k)η0 ≈ 3.6 at more than 3σ, the paper's central forecast would be contradicted.

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

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If this is right

  • If GREA is the true cosmology, future gravitational-wave standard sirens will recover its parameters and disfavor ΛCDM strongly, with ΔlogZ around −8.
  • If ΛCDM is the true cosmology, GREA will be strongly disfavored, while modified GREA will fit reasonably but be penalized for its extra parameter.
  • Current compressed CMB information is the main driver of ΛCDM's statistical preference; without it, GREA remains competitive at low redshift.
  • The dark-energy parameter Ωde in modified GREA is so degenerate with √(-k)η0 that current data alone cannot separate entropic from dark-energy-driven acceleration; only absolute distance measurements break this degeneracy.
  • For the same datasets, GREA infers a present-day expansion rate H(0) systematically higher than ΛCDM, shifting toward values measured by local probes.

Where Pith is reading between the lines

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

  • The forecast's discriminating power may be optimistic because the mock data are generated from the same background-only theory code; a full perturbation analysis could change predictions, as the paper itself lists as future work.
  • If the entropic term alters recombination or the sound horizon, the compressed CMB calibration that drives the current ΔlogZ values would shift, potentially changing the model ranking; the paper adopts the early-universe equality with ΛCDM as an approximation but does not test it.
  • The same standard-siren sample used for model comparison could directly constrain √(-k)η0, turning a discrete model choice into a continuous parameter measurement.
  • A future preference for modified GREA over both pure GREA and ΛCDM would indicate that both entropic and dark-energy contributions are present—a mixed scenario not evaluated in the current analysis.

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

2 major / 4 minor

Summary. This paper constrains the GREA (General Relativistic Entropic Acceleration) model and a phenomenological extension (GREA MOD, with an additional dark-energy component Ωde) using current BAO, SNIa, CC, and compressed CMB data, and forecasts the constraining power of future SKAO, LSST, and ET-like GW standard sirens. Current data are found to prefer ΛCDM when compressed CMB information is included, while GREA remains competitive for low-redshift-only combinations. Forecasts with GREA-based mocks indicate that future multi-probe data, especially GW standard sirens, would strongly discriminate GREA from ΛCDM; ΛCDM-based mocks show GREA is strongly disfavored while GREA MOD can mimic ΛCDM at the cost of an extra parameter.

Significance. If the results hold, the paper provides a useful, self-consistent Bayesian comparison of an entropic-acceleration scenario against ΛCDM, with a public numerical implementation and realistic mock forecasts. The main strengths are: validation of the GREA pipeline against earlier work (1σ agreement with Calderon et al.), use of nested sampling with Nautilus for evidence computation, a clearly defined ΛCDM limit for the modified model, and explicit forecasts that GW standard sirens can break degeneracies in the distance-redshift relation. The conclusion that current compressed-CMB data substantially disfavor GREA, while low-redshift data alone do not, is an informative and falsifiable statement. However, the central forecast claim is conditional on the GREA fiducial being the true cosmology and on the adequacy of the compressed CMB likelihood for this non-standard model.

major comments (2)
  1. [Sec. 3.1, Sec. 5.2.3, Tables 4-5] The current-data constraints and the GREA mock fiducial (Sec. 3.2) both rely on the compressed P-ACT likelihood and on the analytic fits for z_d and z_* (Eqs. 14 and 17), justified by the statement that GREA's high-redshift expansion history is identical to ΛCDM. While the entropic term in Eq. 5 is indeed negligible at z≳10, the compressed observable θ_* = r(z_*)/D_M(z_*) involves D_M(z_*), which integrates the full expansion history down to z=0 and therefore differs from ΛCDM by several percent at low z (Fig. 1). The paper itself concedes (§5.1.1) that the compressed likelihood 'does not represent the complete information contained in the full CMB power spectrum' and calls for a full likelihood and perturbation analysis. If a full CMB analysis shifted the GREA best-fit parameters in Table 6, the mock fiducial used for forecasts would change, and the ΔlogZ values in Tables 4 and 5 — whic
  2. [Sec. 5.1, Fig. 4, Table 6] The modified-GREA constraints are strongly prior-dependent: Fig. 4 shows that the posterior for Ωde changes substantially when the prior on √(-k)η0 is enlarged from [1,5] to [1,10], and the text states that 'enlarging the prior volume significantly affects the posterior distribution of Ωde.' The enlarged prior is then adopted for all modified-GREA analyses, but the corresponding Bayesian evidence (Table 3) is only reported for the enlarged prior. If the original prior were used, the ΔlogZ values for modified GREA could differ, which would affect the conclusion that the extra dark-energy component 'partially alleviates the tension' with ΛCDM. Please report the model evidence under both priors, or justify the enlarged prior on physical grounds rather than as a post-hoc response to the posterior's prior sensitivity.
minor comments (4)
  1. [General] There are several typos and formatting issues: 'fist valide' (Sec. 5), 'SLSt' (Sec. 5 intro), 'joit analysis' (Appendix B), 'continuousnuous' (Sec. 2.1), and the best-fit entries in Table 6 are typeset in a confused way (e.g., misplaced plus/minus offsets). These should be cleaned up.
  2. [Sec. 4.3 / Table 1] Table 1 lists a flat prior H0 ∈ [20,100] for all models. Since H(0) in GREA is derived from H0 and the entropic term, the extremely wide H0 prior can influence the prior volume entering the Bayesian evidence. A brief discussion of the sensitivity of ΔlogZ to the H0 prior width would be useful.
  3. [Sec. 3.2] The paper states that the GREA mock fiducial uses H(0)=70.11 km/s/Mpc but does not report the corresponding sampled H0 value. Reporting both would clarify the relation between H0 and H(0) for the fiducial model.
  4. [Fig. 1 / Fig. 2] The figures show ratios to ΛCDM but do not include error bars on the theoretical curves. Adding the data-point uncertainties in the legend or a small panel with residuals would improve readability.

Circularity Check

0 steps flagged

No significant circularity: the analysis tests an imported model against external data; forecasts are conditional consistency checks.

full rationale

The paper's derivation chain is self-contained as a parameter-constraint and forecast study. GREA is not derived here; Eqs. (1)-(7) are imported from prior work (Garcia-Bellido and Espinosa-Portales 2021; Arjona et al. 2022; Calderon et al. 2025), and the paper explicitly frames its contribution as testing this existing model against data (Secs. 1-2). The modified GREA (Eq. 8) is introduced as a phenomenological extension with the ΛCDM limit as a designed feature (Eq. 9), not as a prediction. Current-data constraints use external data (Pantheon+, DESI, CC, P-ACT); the compressed CMB likelihood and the Aizpuru et al. analytic fits for z_d and z_* are external, and Sec. 3.1 states the high-z equivalence assumption that justifies them—an approximation, not a reduction of the result to an input. The GREA fiducial mock parameters are the best-fit values from the current-data analysis (Sec. 3.2), and the forecast then tests whether the pipeline recovers that fiducial and whether model comparison discriminates. This is a standard consistency/forecast exercise, not a case of fitting a parameter and renaming it a prediction; the conclusion in Sec. 5.2.3 is explicitly conditional ('when it represents the true cosmological scenario'). No 'uniqueness theorem' or load-bearing self-citation chain is invoked; the consistency check against Calderon et al. within 1σ (Sec. 5.1) is an external benchmark. The acknowledged limitation that compressed CMB 'does not represent the complete information contained in the full CMB power spectrum' (Sec. 5.1.1) is a correctness/robustness caveat, not a circular step.

Axiom & Free-Parameter Ledger

6 free parameters · 4 axioms · 1 invented entities

The paper adds one free parameter (Ωde) and relies on the GREA theory from prior work plus the early-time equivalence assumption for CMB compression. No new particles or forces are proposed beyond the existing entropic term.

free parameters (6)
  • H0 = varies by dataset (e.g. 69-71 km/s/Mpc)
    Sampled with U[20,100]; in GREA acts as normalization, physical H(0) is derived.
  • Omega_b h^2 = ~0.022
    Gaussian prior from BBN or uniform when CMB compressed data used.
  • Omega_c h^2 = ~0.12
    Sampled with U[0.05,0.5].
  • M_B = -19.2435 +/- 0.0373 (prior)
    Gaussian prior from SH0ES to break H0-MB degeneracy.
  • sqrt(-k) eta_0 = ~3.5-4.0 (GREA), ~7 (GREA MOD)
    Flat prior [1,5] for GREA, [1,10] for GREA MOD; central geometric parameter of the model.
  • Omega_de h^2 = ~0-0.7 depending on dataset
    Flat prior [0,1] in modified GREA; extra phenomenological dark-energy component.
axioms (4)
  • domain assumption GREA modified Friedmann equation (Eq. 5) and entropic force tensor f_mu_nu from Garcia-Bellido & Espinosa-Portales (2021).
    The whole analysis assumes the GREA framework is a valid description of late-time acceleration; not derived here.
  • domain assumption Early-time expansion history of GREA is identical to ΛCDM, justifying the use of ΛCDM-calibrated analytic fits for z_d and z_* (Eqs. 14, 17) and compressed CMB likelihood.
    Stated in §3.1 but not quantitatively verified; load-bearing for the CMB-based model comparison.
  • standard math Datasets are statistically independent and likelihoods are Gaussian.
    Standard assumption in cosmological parameter inference.
  • domain assumption Mock noise models, SNR>8 threshold, inclination cut at 18 degrees, and merger rate R(z) follow the cited population studies.
    Assumptions for forecast realism; affect expected constraining power.
invented entities (1)
  • Omega_de dark energy component in modified GREA no independent evidence
    purpose: Phenomenological extra component to interpolate between GREA and ΛCDM expansion histories.
    Introduced ad hoc in this paper; constrained only by the fitted data, no independent prediction.

pith-pipeline@v1.3.0-alltime-deepseek · 23749 in / 11354 out tokens · 99603 ms · 2026-08-02T19:28:36.734857+00:00 · methodology

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Cite this review

Pith. "Pith review of Current and future constraints on the expansion history of the GREA model." pith.science (2026). https://pith.science/paper/27M4HWMD

@misc{pith2026260301934,
  author       = {Pith},
  title        = {Pith review of: Current and future constraints on the expansion history of the GREA model},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/27M4HWMD}},
  note         = {Machine review of arXiv:2603.01934}
}
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read the original abstract

In this work, we investigate the General Relativistic Entropic Acceleration (GREA) framework, in which late-time acceleration emerges from entropy production associated with the cosmological horizon, and compare its performance with the standard $\Lambda$CDM description of the Universe. We first confront GREA with current background observations, including baryon acoustic oscillations, type Ia supernovae, compressed CMB information, and cosmic chronometers, with particular emphasis on the geometric horizon parameter $\sqrt{-k}\eta_0$. We then introduce a phenomenological extension of the theory by allowing for an additional dark energy component, $\Omega_{de}$, enabling the recovery of a $\Lambda$CDM-like expansion history as a limiting case. We perform a Bayesian parameter inference and model comparison analysis using both current data and mock datasets representative of future surveys, including SKAO, LSST, and ET. While current data statistically prefer $\Lambda$CDM when compressed CMB information is included, GREA remains competitive for low-redshift combinations. Forecasts indicate that gravitational wave standard sirens are expected to enhance the ability to discriminate between entropic-driven and dark-energy-driven expansion scenarios, and to identify the underlying cosmological model favored by the data.

Figures

Figures reproduced from arXiv: 2603.01934 by Chiara De Leo, Irene Graziotti, Matteo Martinelli.

Figure 1
Figure 1. Figure 1: — Comparison between ΛCDM model (black dashed lines) and GREA framework for different values of the parameter √ −kη0. Top left: Hubble expansion rate H(z) normalized to ΛCDM, compared with cosmic chronometers data. Top right: transverse comoving distance DM(z)/rd, normalized to ΛCDM, with BAO measurements shown as data points. Bottom left: BAO distance DH(z)/rd normalized to ΛCDM, with corresponding BAO da… view at source ↗
Figure 2
Figure 2. Figure 2: — Comparison between ΛCDM model (black dashed lines), GREA (red dashed lines) and modified GREA for different values of the parameter Ωdeh 2 . Top left: Hubble expansion rate H(z) normalized to ΛCDM, compared with cosmic chronometers data. Top right: transverse comoving distance DM(z)/rd, normalized to ΛCDM, with BAO measurements shown as data points. Bottom left: BAO distance DH(z)/rd normalized to ΛCDM, … view at source ↗
Figure 3
Figure 3. Figure 3: — Left panel: posterior distribution of H0, H(0) and Ωm from DESI+P-ACT+CC+Pantheon+ obtained with ΛCDM (red) and GREA (blue). Right panel: posterior distribution of √ −kη0, α and ΩGREA from DESI+P-ACT+CC+Pantheon+ (pink) and DESI+CC+Pantheon+ (green) obtained with GREA theory. 5.1.1. Bayesian model comparison In addition to parameter estimation, we perform a Bayesian model comparison among the three compe… view at source ↗
Figure 4
Figure 4. Figure 4: — Posterior distribution of H(0), Ωm and Ωde from DESI+P-ACT+CC+Pantheon+ obtained with modified GREA. In the orange case we use a flat prior on √ −kη0 between [1.0; 5.0], in the purple case we use a flat prior on √ −kη0 between [1.0; 10.0], allowing for the ΛCDM limit. (GREA SKAO+LSST, GREA SKAO+LSST+ET). In particular, we focus on mock gravitational wave standard siren data, which directly probe the lumi… view at source ↗
Figure 5
Figure 5. Figure 5: — Left: posterior distribution of GREA parameters from GREA SKAO+LSST (pink), GREA SKAO+LSST+ET (blue) obtained with GREA. The dashed lines correspond to the parameters value that we used to generate the mock datasets. Right: posterior distribution of ΛCDM parameter from GREA SKAO+LSST (yellow), GREA SKAO+LSST+ET (green) obtained with ΛCDM analysis. The dashed lines correspond to the parameters values that… view at source ↗
Figure 6
Figure 6. Figure 6: — Left panel: Posterior distribution of modified GREA parameter from GREA SKAO+LSST+ET. The dashed lines correspond to the parameters value that we used to generate the mock datasets. Right panel: Luminosity distance, DL(z) predicted by ΛCDM (black line), GREA (dashed red line) and modified GREA for different values of Ωdeh 2 . the luminosity distance-redshift relation. The physical origin of this behavior… view at source ↗
Figure 7
Figure 7. Figure 7: — Posterior distribution of GREA and modified GREA parameter from ΛCDM SKAO+LSST (pink and green), ΛCDM SKAO+LSST+ET (cyan and purple). The dashed lines correspond to the parameters value that we used to generate the mock datasets. 6. CONCLUSIONS In this work, we investigated the General Relativistic Entropic Acceleration (GREA) framework as an alternative to the cosmological constant (Λ) for explaining la… view at source ↗

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Forward citations

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Reference graph

Works this paper leans on

8 extracted references · 2 linked inside Pith · cited by 2 Pith papers

  1. [3]

    doi:10.1088/1475-7516/2020/12/019. D. E. Holz and S. A. Hughes. Using gravitational-wave standard sirens.Astrophys. J., 629:15–22, 2005. doi:10.1086/431341. H. Jeffreys.The Theory of Probability. Oxford Classic Texts in the Physical Sciences. 1939. ISBN 978-0-19-850368-2, 978-0-19-853193-7. J. U. Lange. nautilus: boosting Bayesian importance nested sampli...

    doi:10.1088/1475-7516/2020/12/019 2020

  2. [1968]

    doi:10.1070/PU1968v011n03ABEH003927. I. Zlatev, L.-M. Wang, and P. J. Steinhardt. Quintessence, cosmic coincidence, and the cosmological constant.Phys. Rev. Lett., 82:896–899, 1999. doi:10.1103/PhysRevLett.82.896. 21 APPENDIX In this appendix we provide the numerical details for the current observational datsets employed to constrain the ΛCDM, GREA and mo...

    doi:10.1070/pu1968v011n03abeh003927 1999

  3. [2009]

    coincidence problem

    ISSN 0883-4237. doi:10.1214/09-sts284. D. Scolnic et al. The Pantheon+ Analysis: The Full Data Set and Light-curve Release.Astrophys. J., 938(2):113, 2022. doi:10.3847/1538-4357/ac8b7a. D. M. Scolnic et al. The Complete Light-curve Sample of Spectroscopically Confirmed SNe Ia from Pan-STARRS1 and Cosmological Constraints from the Combined Pantheon Sample....

    doi:10.1214/09-sts284 2022

  4. [2010]

    doi:10.1088/0004-637X/709/2/1420. A. Heavens. Statistical techniques in cosmology. 6 2009. doi:10.48550/arXiv.0906.0664. N. B. Hogg, M. Martinelli, and S. Nesseris. Constraints on the distance duality relation with standard sirens.JCAP, 12:019,

    Pith/arXiv arXiv doi:10.48550/arxiv.0906.0664 2009

  5. [2016]

    doi:10.1088/1475-7516/2016/05/014. M. Moresco et al. Unveiling the Universe with emerging cosmological probes.Living Rev. Rel., 25(1):6, 2022. doi:10.1007/s41114-022-00040-z. S. Nesseris and J. Garcia-Bellido. Is the Jeffreys’ scale a reliable tool for Bayesian model comparison in cosmology?JCAP, 08: 036, 2013. doi:10.1088/1475-7516/2013/08/036. S. Nissan...

    Pith/arXiv arXiv doi:10.48550/arxiv.2507.07093 2016

  6. [2020]

    doi:10.1017/pasa.2019.51. S. Bahamonde, C. G. B¨ ohmer, S. Carloni, E. J. Copeland, W. Fang, and N. Tamanini. Dynamical systems applied to cosmology: dark energy and modified gravity.Phys. Rept., 775-777:1–122, 2018. doi:10.1016/j.physrep.2018.09.001. F. B. Bianco et al. Optimization of the Observing Cadence for the Rubin Observatory Legacy Survey of Spac...

    doi:10.48550/arxiv.2509.21491 2019

  7. [2022]

    We assume that the measures ofH(z) are uncorrelated and we assume a diagonal covariance matrix

    and are reported in Table 7, in units of km s −1 Mpc−1. We assume that the measures ofH(z) are uncorrelated and we assume a diagonal covariance matrix. Redshift (z)H(z)σ H 0.07 69.0 19.6 0.09 69.0 12.0 0.12 68.6 26.2 0.17 83.0 8.0 0.179 75.0 4.0 0.199 75.0 5.0 0.2 72.9 29.6 0.27 77.0 14.0 0.28 88.8 36.6 0.35 82.7 8.4 0.352 83.0 14.0 0.3802 83.0 13.5 0.4 9...

    2022

  8. [2025]

    doi:10.1088/1475-7516/2025/11/062. G. Mangano, G. Miele, S. Pastor, T. Pinto, O. Pisanti, and P. D. Serpico. Relic neutrino decoupling including flavor oscillations. Nucl. Phys. B, 729:221–234, 2005. doi:10.1016/j.nuclphysb.2005.09.041. M. Martinelli, F. Scarcella, N. B. Hogg, B. J. Kavanagh, D. Gaggero, and P. Fleury. Dancing in the dark: detecting a pop...

    doi:10.1088/1475-7516/2025/11/062 2025