The distribution of spin directions of $\sim6.4\cdot10^4$ SDSS spiral galaxies with spectra was examined, and compared to the distribution of $\sim3.3\cdot10^4$ Pan-STARRS galaxies. The analysis shows a statistically significant asymmetry between the number of SDSS galaxies with opposite spin directions, and the magnitude and direction of the asymmetry changes with the direction of observation and with the redshift. The redshift dependence shows that the distribution of the spin direction of SDSS galaxies becomes more asymmetric as the redshift gets higher. Fitting the distribution of the galaxy spin directions to a quadrupole alignment provides fitness with statistical significance >5$\sigma$, which grows to >8$\sigma$ when just galaxies with z>0.15 are used. Similar analysis with Pan-STARRS galaxies provides dipole and quadrupole alignments nearly identical to the analysis of SDSS galaxies, showing that the source of the asymmetry is not necessarily a certain unknown flaw in a specific telescope system. While these observations are clearly provocative, there is no known error that could exhibit itself in such form. The data analysis process is fully automatic, and uses deterministic and symmetric algorithms with defined rules. It does not involve either manual analysis that can lead to human perceptual bias, or machine learning that can capture human biases or other subtle differences that are difficult to identify due to the complex nature of machine learning processes. Also, an error in the galaxy annotation process is expected to show consistent bias in all parts of the sky, rather than change with the direction of observation to form a clear and definable pattern.

中文翻译：

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SDSS 和 Pan-STARRS 中星系自旋方向的模式显示奇偶校验和多极点

研究了具有光谱的$\sim6.4\cdot10^4$ SDSS螺旋星系的自旋方向分布，并与$\sim3.3\cdot10^4$泛星星系的分布进行了比较。分析表明，自旋方向相反的SDSS星系数量之间存在统计上显着的不对称性，并且不对称性的大小和方向随着观测方向和红移而变化。红移相关性表明，随着红移变高，SDSS 星系的自旋方向分布变得更加不对称。将星系自旋方向的分布拟合为四极对齐提供了具有统计显着性 >5$\sigma$ 的适应度，当仅使用 z>0.15 的星系时，其增长到 >8$\sigma$。Pan-STARRS 星系的类似分析提供了与 SDSS 星系分析几乎相同的偶极子和四极子排列，表明不对称的来源不一定是特定望远镜系统中的某个未知缺陷。虽然这些观察结果显然具有挑衅性，但没有已知的错误可以以这种形式表现出来。数据分析过程是全自动的，并使用具有定义规则的确定性和对称算法。它不涉及可能导致人类感知偏见的手动分析，也不涉及可以捕捉人类偏见或其他由于机器学习过程的复杂性而难以识别的细微差异的机器学习。此外，星系注释过程中的错误预计会在天空的所有部分显示一致的偏差，