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arxiv: 2604.10061 · v1 · submitted 2026-04-11 · 🌀 gr-qc

Cosmological Parameters in f(T) Gravity: Theoretical and Observational Analysis

Pith reviewed 2026-05-10 16:31 UTC · model grok-4.3

classification 🌀 gr-qc
keywords f(T) gravityteleparallel gravitydynamical systemscosmological parametersMCMC constraintsBAO datacosmic expansion
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The pith

A torsion-based gravity model with chosen power-law terms reproduces the observed cosmic expansion history when its parameters satisfy stability conditions from dynamical analysis.

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

The paper studies an extension of teleparallel gravity by adopting the form f(T) = αT − β u^{-n} + γ u^m, with u defined as negative T divided by six. The cosmological equations are recast as an autonomous dynamical system whose critical points correspond to radiation-dominated, matter-dominated, and late-time accelerating phases. Stability analysis shows these points are stable when the exponents obey m less than one and n greater than negative one. Markov Chain Monte Carlo fitting to DESI DR2 baryon acoustic oscillation measurements combined with Hubble and Pantheon+SH0ES supernova data yields best-fit values m approximately 0.91 and n approximately 0.69, which lie inside the stable interval. The combined results indicate that this single function of torsion can drive the full sequence of cosmic epochs without separate dark-energy components.

Core claim

With the functional form f(T) = αT − βu^{-n} + γu^m, phase-space analysis identifies critical points for the radiation, matter, and dark-energy eras whose stability holds for m < 1 and n > −1. MCMC constraints from DESI DR2 BAO together with Hubble and Pantheon+SH0ES data return m = 0.91^{+0.07}_{-0.09} and n = 0.69^{+0.09}_{-0.08}, values inside the stable range, so that the model reproduces the observed cosmic expansion history.

What carries the argument

The autonomous system formed by rewriting the Friedmann equations of f(T) gravity, whose fixed points classify the evolutionary epochs and whose stability bounds are compared against MCMC-fitted parameter values.

If this is right

  • The model passes through stable radiation, matter, and accelerating phases in the required order.
  • Late-time acceleration is produced by the u^m term when m is positive but less than one.
  • The observationally preferred values of m and n automatically satisfy the stability criteria derived from the autonomous system.
  • No extra scalar field or cosmological constant is required to explain the current acceleration.

Where Pith is reading between the lines

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

  • If the functional form proves general, the same approach could be applied to growth-of-structure data to test whether the model remains consistent beyond background expansion.
  • The linkage of early and late behavior through a single torsion function might address why the dark-energy density becomes important only recently.
  • Tighter future bounds on the Hubble parameter could narrow the allowed window for n and m and reveal whether the stability window shrinks or survives.

Load-bearing premise

The chosen combination of linear, inverse-power, and positive-power terms in f(T) is general enough to capture the dynamics needed for a realistic cosmology.

What would settle it

An independent measurement of the expansion rate that forces the best-fit m above 1 or n below −1 while still matching the data would falsify the model's ability to remain stable across epochs.

Figures

Figures reproduced from arXiv: 2604.10061 by B. Mishra, Pratik P. Ray, S. A. Kadam, Suraj Kumar Behera.

Figure 1
Figure 1. Figure 1: Phase space diagram of the autonomous system showing the critical points [PITH_FULL_IMAGE:figures/full_fig_p006_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: The evolution of EoS parameters, density and deceleration parameter as functions of redshift with the [PITH_FULL_IMAGE:figures/full_fig_p007_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: A two-dimensional contour diagram derived from the observational [PITH_FULL_IMAGE:figures/full_fig_p009_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: A two-dimensional contour diagram derived from the Pantheon+SH0ES analysis, depicting best-fit [PITH_FULL_IMAGE:figures/full_fig_p010_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: A two-dimensional contour diagram derived from the DESI DR2 BAO analysis, depicting best-fit [PITH_FULL_IMAGE:figures/full_fig_p011_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: A two-dimensional contour diagram derived from the combined ( [PITH_FULL_IMAGE:figures/full_fig_p012_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: (i) Left panel: Redshift evolution of the Hubble parameter with corresponding error bars; (ii) Right panel: Distance modulus as a function of redshift including observational uncertainties. analysis, and a stable accelerating cosmological model is achieved by integrating torsion instead of curvature and f(T) form. The observational analysis strengthened this theoretical investigation by fitting the extract… view at source ↗
read the original abstract

The $f(T)$ gravity is one of the extensions of teleparallel equivalent of general relativity, in which more general functions of the torsion scalar $T$ can be described. With the proposed functional form of $f(T) = \alpha T - \beta u^{-n} + \gamma u^m$, where $u = (-T/6)$, we have analyzed the cosmological parameters using dynamical system analysis and cosmological datasets. The dynamical behavior of this model is analyzed with phase-space analysis by transforming the cosmological equations into an autonomous system. Critical points are identified, and their stability conditions examined, enabling the classifications of the early and late-time evolutionary phases of the Universe. The stability conditions are further demonstrated by phase-portrait diagrams that highlight transitions between radiation, matter, and dark-energy-dominated epochs. Then we used the Markov Chain Monte Carlo statistical technique to constrain the model parameters with the recent observational dataset, such as DESI DR2 BAO, and its combination with the Hubble and Pantheon+SH0ES data. The best-fit values for the model parameters were obtained by data analysis, $m \equiv 0.91^{+0.07}_{-0.09}$ and $n \equiv 0.69^{+0.09}_{-0.08}$, and are well within the stability range obtained ($m<1\land n>-1$) through dynamical system analysis. The combined theoretical and observational analysis shows that the proposed $f(T)$ gravity model successfully reproduces the observed cosmic expansion history of the Universe.

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.

Referee Report

2 major / 2 minor

Summary. The manuscript proposes the specific f(T) form f(T) = αT − βu^{-n} + γu^m (u = −T/6), converts the background cosmological equations to an autonomous dynamical system, identifies critical points and derives stability conditions m < 1 and n > −1 that permit a radiation → matter → dark-energy sequence, presents phase portraits confirming the transitions, and performs MCMC parameter estimation on DESI DR2 BAO combined with Hubble and Pantheon+SH0ES data, obtaining best-fit values m = 0.91^{+0.07}_{-0.09}, n = 0.69^{+0.09}_{-0.08} that lie inside the stability window, thereby claiming the model reproduces the observed expansion history.

Significance. If the derivations are correct, the work supplies a concrete, observationally viable f(T) model whose parameters are simultaneously constrained by data and shown to satisfy analytically derived stability requirements for the full cosmic sequence. The explicit consistency check between the MCMC posterior and the pre-data stability bounds, together with the use of recent DESI DR2 data, constitutes a clear strength of the combined theoretical–observational approach.

major comments (2)
  1. [Dynamical system analysis] Dynamical system analysis: the autonomous system obtained from the Friedmann and torsion equations, the coordinates of the critical points, and the Jacobian matrix whose eigenvalues yield the stability conditions m < 1 and n > −1 are not displayed. Without these explicit expressions it is impossible to reproduce the phase portraits or to confirm that the reported best-fit values lie in the stable region by direct substitution rather than by assertion.
  2. [MCMC constraints] Observational analysis: the explicit likelihood function, the precise combination of DESI DR2 BAO + Hubble + Pantheon+SH0ES, and any priors or nuisance parameters employed in the MCMC are not stated. This information is load-bearing for verifying that the quoted best-fit values and uncertainties for m and n are correctly derived and that no post-hoc data selection affects the conclusion that they satisfy m < 1, n > −1.
minor comments (2)
  1. [Introduction] The notation u = −T/6 is introduced without a brief reminder of its relation to the torsion scalar in the teleparallel framework; adding one sentence would improve readability for readers outside the immediate subfield.
  2. [Phase portraits] Figure captions for the phase portraits should explicitly label the axes in terms of the autonomous variables and indicate which critical points correspond to radiation, matter, and dark-energy domination.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the careful reading and constructive comments on our manuscript. We address each major comment below and have revised the manuscript to incorporate the requested details for improved reproducibility.

read point-by-point responses
  1. Referee: [Dynamical system analysis] Dynamical system analysis: the autonomous system obtained from the Friedmann and torsion equations, the coordinates of the critical points, and the Jacobian matrix whose eigenvalues yield the stability conditions m < 1 and n > −1 are not displayed. Without these explicit expressions it is impossible to reproduce the phase portraits or to confirm that the reported best-fit values lie in the stable region by direct substitution rather than by assertion.

    Authors: We agree that the explicit autonomous system, critical point coordinates, and Jacobian matrix were omitted from the original submission, which limits independent verification. In the revised manuscript we have added a new subsection that derives the autonomous system from the Friedmann and torsion equations, lists all critical points with their coordinates, and presents the full Jacobian matrix. The eigenvalues are computed explicitly, confirming the stability conditions m < 1 and n > −1. We also substitute the MCMC best-fit values (m = 0.91, n = 0.69) directly into these conditions and report the result, together with updated phase portraits that reference the new expressions. revision: yes

  2. Referee: [MCMC constraints] Observational analysis: the explicit likelihood function, the precise combination of DESI DR2 BAO + Hubble + Pantheon+SH0ES, and any priors or nuisance parameters employed in the MCMC are not stated. This information is load-bearing for verifying that the quoted best-fit values and uncertainties for m and n are correctly derived and that no post-hoc data selection affects the conclusion that they satisfy m < 1, n > −1.

    Authors: We acknowledge that the MCMC methodology was not described in sufficient detail. The revised manuscript now includes the explicit likelihood function, the precise dataset combination (DESI DR2 BAO together with Hubble and Pantheon+SH0ES), the priors on all parameters (including m and n), and any nuisance parameters. We confirm that no post-hoc data selection was performed and that the posterior samples satisfy the stability window m < 1, n > −1 derived from the dynamical analysis. revision: yes

Circularity Check

0 steps flagged

No significant circularity; derivation uses independent dynamical analysis and external data

full rationale

The paper selects a functional form for f(T), converts the Friedmann equations into an autonomous dynamical system, derives stability conditions (m < 1, n > -1) from the critical-point analysis, and separately performs MCMC fitting to external datasets (DESI DR2 BAO, Hubble, Pantheon+SH0ES). The best-fit parameters lie inside the previously derived stability region and the phase portraits recover the expected radiation-matter-DE sequence. Neither the stability bounds nor the expansion history are obtained by re-expressing the fitted values; the dynamical-system results are obtained prior to and independently of the data fit. No self-citation chain, self-definitional step, or fitted-input-renamed-as-prediction is present. The analysis is therefore self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

3 free parameters · 2 axioms · 0 invented entities

The central claim rests on the assumption that the chosen f(T) ansatz is physically motivated and that standard FLRW cosmology plus teleparallel equivalence holds. No new particles or forces are postulated.

free parameters (3)
  • m
    Exponent in the positive-power term; fitted to data and required to satisfy m < 1 for stability.
  • n
    Exponent in the negative-power term; fitted to data and required to satisfy n > −1 for stability.
  • α, β, γ
    Overall scaling coefficients whose values are implicitly absorbed into the normalization of the Hubble parameter during fitting.
axioms (2)
  • domain assumption The universe is described by a flat FLRW metric and the torsion scalar T is the only gravitational degree of freedom.
    Standard assumption in f(T) cosmology invoked throughout the dynamical-system analysis.
  • standard math The matter content is perfect fluid with standard equation-of-state parameters for radiation and dust.
    Used to close the autonomous system of equations.

pith-pipeline@v0.9.0 · 5587 in / 1520 out tokens · 39525 ms · 2026-05-10T16:31:17.371570+00:00 · methodology

discussion (0)

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Reference graph

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