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Reproducible empirical evidence of cosmological-scale asymmetry in galaxy spin directions: comment on arXiv:2404.06617

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arXiv:2404.13864v1 Announce Type: new
Abstract: The distribution of the spin directions of galaxies has been a question in the past decade, with numerous Earth-based and space-based experiments showing that the distribution is not necessarily random. These experiments were based on different statistical methods, one of them was a simple and empirically verified open source $\chi^2$ method. Patel & Desmond (2024) proposed that previous experiments showing non-random distribution are flawed since they assume Gaussian distribution. To address that, they apply a new complex ad-hoc statistical method to several datasets, none of them except for one were used in the past to claim for a dipole axis. The new method showed that all datasets except for one exhibit isotropy. This paper discusses the soundness of the contention that Gaussian distribution cannot be assumed for galaxy spin directions. More importantly, simple empirical analyses show that the new statistical method is not fully responsive to asymmetry in the distribution of galaxy spin directions, and does not identify non-random distribution even in situations where a dipole axis clearly exists in the data, or when an artificial bias is added to the data to create an extremely non-random dataset. Results using Monte Carlo simulation show substantial differences between the results of the simulation and the results of the new statistical method. Code and data to reproduce the experiments are available, and released in a manner that is easily reproducible. Possible reasons leading to the results are also discussed. The claims that the actual results are different from the results reported in the papers are examined in an open and transparent manner. These claims are found to be inaccurate, as the previous literature results are fully reproducible. These findings further reinforce the need to study astrophysical or cosmological explanations for the non-random distribution.

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