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The fractal structure of the universe: Correlations of galaxies and clusters and the average mass density

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  • Pietronero, L.

Abstract

It is shown that the use of the function ζ(r) for the analysis of statistical correlations for galaxies and clusters is conceptually incorrect. This is due to the fact that ζ(r) provides a correct characterization of correlations only for systems for which an intrinsic and unique average density can be defined independently of the position and size of the sample volume considered. This is the case for liquids but it is manifestly not the case for the large scale structures in the universe. A reinterpretation of the data with the appropriate correlation functions naturally resolves a number of puzzling features of the previous interpretation, like, for example, the amplitude mismatch for ζ(r) of galaxies and clusters. The correct correlation analysis strongly supports the existence of a single fractal (self-similar) structure extending from the galaxy scale up to the present limits of observation. This picture is now fully consistent with the existence of clusters and voids of very large sizes as well as with large scale anomalous velocities. In addition the present observational data do not support the existence of a length-scale above which the distribution of matter becomes homogeneous. This fact poses serious doubts about the current determinations of “a fair sample” from which one deduces the average mass density and the cosmological density parameter Ω.

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  • Pietronero, L., 1987. "The fractal structure of the universe: Correlations of galaxies and clusters and the average mass density," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 144(2), pages 257-284.
  • Handle: RePEc:eee:phsmap:v:144:y:1987:i:2:p:257-284
    DOI: 10.1016/0378-4371(87)90191-9
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    1. Schramm, W.F., 1985. "WIC prenatal participation and its relationship to newborn Medicaid costs in Missouri: A cost/benefit analysis," American Journal of Public Health, American Public Health Association, vol. 75(8), pages 851-857.
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    Cited by:

    1. Dickau, Jonathan J., 2009. "Fractal cosmology," Chaos, Solitons & Fractals, Elsevier, vol. 41(4), pages 2103-2105.
    2. Puetz, Stephen J. & Prokoph, Andreas & Borchardt, Glenn & Mason, Edward W., 2014. "Evidence of synchronous, decadal to billion year cycles in geological, genetic, and astronomical events," Chaos, Solitons & Fractals, Elsevier, vol. 62, pages 55-75.
    3. Kantelhardt, Jan W & Eduardo Roman, H & Greiner, Martin, 1995. "Discrete wavelet approach to multifractality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 220(3), pages 219-238.
    4. Vlad, Marcel Ovidiu, 1994. "Non-Markovian approach for anomalous diffusion with infinite memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 208(2), pages 167-176.
    5. Puetz, Stephen J., 2022. "The infinitely fractal universe paradigm and consupponibility," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    6. Calabrese, Armando & Capece, Guendalina & Costa, Roberta & Di Pillo, Francesca & Giuffrida, Stefania, 2018. "A ‘power law’ based method to reduce size-related bias in indicators of knowledge performance: An application to university research assessment," Journal of Informetrics, Elsevier, vol. 12(4), pages 1263-1281.
    7. Aerts, Diederik & Czachor, Marek & Kuna, Maciej, 2016. "Crystallization of space: Space-time fractals from fractal arithmetic," Chaos, Solitons & Fractals, Elsevier, vol. 83(C), pages 201-211.
    8. Momin Mukherjee, 2017. "A Review of Research Design," Post-Print hal-01592483, HAL.

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