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Parametric and nonparametric methods hint dark energy evolution

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arxiv 2111.08289 v3 pith:YFYT56XV submitted 2021-11-16 astro-ph.CO gr-qc

classification astro-ph.COgr-qc
keywords darkenergydataequationevolutionfoundfunctionshint
verification ladder T0 review T1 audit T2 compute T3 formal
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We study dark energy through the viewpoints of parametric and nonparametric analyses of late-time cosmological data. We consider four Hubble parameter priors reflecting the Hubble tension and make use of two phenomenological functions, namely, a normalized dark energy density and a compactified dark energy equation of state. We predict the shape of both functions and present new constraints on the dark energy equation of state. The results hint at dark energy evolution regardless of the choice of the method and of the priors. The fact that similar evolutions for the dark energy densities are found through drastically different approaches suggests that the features found in this paper are driven by the data, and are not artifact of the reconstruction methods applied.

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Cited by 4 Pith papers

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

  1. Alleviating the Hubble Tension with Smooth Sign-Switching Dark Energy: Full CMB Constraints with DESI and PantheonPlus

    astro-ph.CO 2026-07 conditional novelty 6.0 of 10

    Smooth ECDM dark energy remains compatible with Planck+ACT+SPT, DESI DR2 and Pantheon+/SH0ES while alleviating the Hubble tension through a controlled late-time density transition.

  2. Background-level reconstruction of scalar-field potentials from dark-energy histories and comparison with analytic potential families

    astro-ph.CO 2026-03 conditional novelty 5.5 of 10

    A background reconstruction maps prescribed ρ_de(z) histories to V(φ) and ranks analytic potentials by Bayesian evidence, with exponential preferred for CPL and shifted-tanh for sign-switching targets.

  3. Cosmo-Learn: code for learning cosmology using different methods and mock data

    astro-ph.CO 2025-08 conditional novelty 5.0 of 10

    An open-source toolkit that simulates late-universe cosmological observations and benchmarks MCMC, genetic algorithms, Gaussian processes, Bayesian ridge regression, and neural networks in one pipeline.

  4. Evidence of dynamical dark energy found via the DESI DR2 Lyman$\alpha$ forest

    astro-ph.CO 2025-10 unverdicted novelty 4.0 of 10

    Fitting seven dark-energy parameterizations to DESI DR2 Lyman-alpha BAO plus CMB, galaxy BAO, and three supernova samples yields 2–2.5σ hints of evolving dark energy (w0>−1, wa<0) that weaken below 2σ when supernovae ...

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