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Cosmic Voids and Large-Scale Structure Formation: A Pressure-Driven Gravity Approach

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  • Additional Information
    • Publication Date:
      2025
    • Collection:
      Middlesex University London: Figshare
    • Abstract:
      This thesis proposes a novel cosmological framework in which the large-scale structure of the universe - voids, filaments and sheets - emerges from pressure gradients in a relativistic superfluid vacuum. Abandoning the need for dark matter and dark energy, the Pressure-Driven Gravity (PDG) model derives gravitational effects from a compressible medium governed by a barotropic equation of state inspired by axion-like particle (ALP) field theory. We develop the theoretical underpinnings of PDG, present a relativistic extension compatible with the Tolman-Oppenheimer-Volkoff equation and derive structure formation criteria via a Jeans-like instability analysis. Numerical simulations using a modified GADGET-2 code are compared to observational data from SDSS, DESI, Planck, DES and SPT. Key observational tests - including void size distributions, two-point correlation functions, weak lensing spectra, BAO and CMB residuals - demonstrate consistency with cosmological data. Bayesian evidence is evaluated against ΛCDM, with sensitivity analyses on priors and model parameters. We address challenges including neutron star stability, CMB fine-tuning and the Hubble tension. Appendices include derivations of the Jeans scale and ALP parameter justifications. This work contributes a unified, testable alternative to standard cosmology with implications for cosmic structure formation, vacuum physics and the interpretation of high-precision data from upcoming surveys like Euclid and the Simons Observatory.
    • Accession Number:
      10.6084/m9.figshare.29825891.v2
    • Online Access:
      https://doi.org/10.6084/m9.figshare.29825891.v2
      https://figshare.com/articles/thesis/Cosmic_Voids_and_Large-Scale_Structure_Formation_A_Pressure-Driven_Gravity_Approach/29825891
    • Rights:
      CC BY 4.0
    • Accession Number:
      edsbas.D7C8DBCC