论文标题
螺旋星系的自旋均等III-带有3D随机步行模拟SDSS螺旋分布的偶极子分析
Spin Parity of Spiral Galaxies III -- Dipole Analysis of the Distribution of SDSS Spirals with 3D Random Walk Simulations
论文作者
论文摘要
观察尚未确定星系的自旋向量的分布是否真正随机。目前尚不清楚宇宙中涡度场的分布是否有大规模的对称性破坏。在这里,我们提出了一种评估观察到的自旋分布的偶极子d_ {max}的公式,其统计显着性sigma_ {d}可以通过3D随机步行(随机飞行)模拟的预期振幅来校准。 我们应用此公式来评估斯隆数字天空调查(SDSS)螺旋的分布中的偶极子分量。 Shamir(2017a)出版了SDSS DR8的螺旋星系目录,将其模式识别工具分类为顺时针和逆时针(分别为Z-Spiral和S-Spirals)。他发现其分布中显着的光度不对称性。我们已经确认该样本提供偶极子不对称,直至Sigma_ {d} = 4.00的水平。 但是,我们还发现该目录包含相同星系的大量多个条目。删除重复的条目后,样品数量大幅缩小至45%。对“清洁”目录观察到的实际偶极子不对称性很小,Sigma_ {d} = 0.29。我们得出的结论是,仅SDSS数据不支持当地宇宙中星系的自旋矢量分布中大规模对称性的存在。数据与随机分布兼容。
Observation has not yet determined whether the distribution of spin vectors of galaxies is truly random. It is unclear whether is there any large-scale symmetry-breaking in the distribution of the vorticity field in the universe. Here, we present a formulation to evaluate the dipole component D_{max} of the observed spin distribution, whose statistical significance sigma_{D} can be calibrated by the expected amplitude for 3D random walk (random flight) simulations. We apply this formulation to evaluate the dipole component in the distribution of Sloan Digital Sky Survey (SDSS) spirals. Shamir(2017a) published a catalog of spiral galaxies from the SDSS DR8, classifying them with his pattern recognition tool into clockwise and counterclockwise (Z-spiral and S-spirals, respectively). He found significant photometric asymmetry in their distribution. We have confirmed that this sample provides dipole asymmetry up to a level of sigma_{D}=4.00. However, we also found that the catalog contains a significant number of multiple entries of the same galaxies. After removing the duplicated entries, the number of samples shrunk considerably to 45%. The actual dipole asymmetry observed for the 'cleaned' catalog is quite modest, sigma_{D}=0.29. We conclude that SDSS data alone does not support the presence of a large-scale symmetry-breaking in the spin vector distribution of galaxies in the local universe. The data are compatible with a random distribution.