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  1. Home
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Browsing by Author "Tiwari, Prabhakar"

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    Superhorizon perturbations: A possible explanation of the hubble–lemaître tension and the large-scale anisotropy of the universe
    (IOP Publishing, 2022) Tiwari, Prabhakar; Kothari, Rahul; Jain, Pankaj
    Current cosmological observations point to a serious discrepancy between the observed Hubble parameter obtained using direct versus cosmic microwave background radiation measurements. Besides this so-called Hubble– Lemaî tre tension, we also find considerable evidence in diverse cosmological observables that indicate violation of the cosmological principle. In this paper, we suggest that both these discrepancies are related and can be explained by invoking superhorizon perturbations in the universe. We implement this by considering a single superhorizon mode and showing that it leads to both a dipole in large-scale structures and a shift in the Hubble–Lemaî tre parameter. Furthermore, the shift is found to be independent of redshift up to a certain distance. This is nicely consistent with the data.
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    Superhorizon Perturbations: A Possible Explanation of the Hubble–Lemaître Tension and the Large-scale Anisotropy of the Universe.
    (The American Astronomical Society., 2022) Tiwari, Prabhakar; Kothari, Rahul; Jain, Pankaj
    Current cosmological observations point to a serious discrepancy between the observed Hubble parameter obtained using direct versus cosmic microwave background radiation measurements. Besides this so-called Hubble– Lemaître tension, we also find considerable evidence in diverse cosmological observables that indicate violation of the cosmological principle. In this paper, we suggest that both these discrepancies are related and can be explained by invoking superhorizon perturbations in the universe. We implement this by considering a single superhorizon mode and showing that it leads to both a dipole in large-scale structures and a shift in the Hubble–Lemaître parameter. Furthermore, the shift is found to be independent of redshift up to a certain distance. This is nicely consistent with the data.

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