New constraints on cosmic anisotropy from galaxy clusters using an improved dipole fitting method

Abstract

In this work, we attempted to apply the dipole fitting (DF) method to galaxy clusters to search for cosmic anisotropic signals, and to construct a statistical isotropic analysis scheme for them. Compared to Type Ia supernova (SNe Ia), the galaxy clusters offer a significant advantage in terms of spatial distribution. This advantage makes the anisotropic signals obtained from them more reliable. From 313 galaxy clusters (Chandra + XMM-Newton), we find two preferred directions (l, b) = (${257.82^{\circ}}_{-52.88}^{+58.01}$, $-31.30{^{\circ}}_{-39.46}^{+35.92}$) and ($80.89{^{\circ}}_{-52.46}^{+60.97}$, $31.75{^{\circ}}_{-40.16}^{+35.19}$). The former to a direction where the universe is expanding at a faster rate than the surrounding area, while the latter to a slower rate of expansion. The corresponding magnitude of anisotropy is $|A|$ = 5.2 $\sim$ 5.4 $\times$ 10$^{-4}$. The results of statistical isotropy analyses give $\sim$1.0$σ$ confidence level. From the reanalyses based on the subsamples including Chandra, XMM-Newton, low reshift (LR, $z < 0.10$), high redshift (HR, $z > 0.10$) datasets, we find that the observation equipment and sample redshift can affect the preferred direction, anisotropic magnitude, and statistical significance of anisotropy. The XMM-Newton dataset gives a statistical significance of 2.26$σ$ (Mock) and 2.86$σ$ (Iso) which are much higher than that from Chandra and the total datasets. The magnitude of anisotropy $|A|$ from HR dataset is larger than that from LR dataset. Overall, our results indicate the presence of anisotropic signals in galaxy clusters, which must be taken seriously. Further test is still needed to better understand these signals.

Figures (12)

• Figure 1: Basic information of the galaxy cluster dataset. Redshift distribution (left panel) and location distribution (right panel) in the galactic coordinate system.
• Figure 2: $L_{X}-T$ diagrams (left panel) and the corresponding confidence contours (right panel) for different types datasets. Blue, red and green represent the results from Chandra, XMM-Newton, and Chandra + XMM-Newton datasets, respectively.
• Figure 3: $L_{X}-T$ diagrams (left panel) and the corresponding confidence contours (right panel) for different redshift datasets. Blue and red represent the results from LR and HR datasets, respectively.
• Figure 4: Confidence contours (1$\sigma$ and 2$\sigma$) of the correction parameters (l, b, A, and B) for different types datasets, including Chandra + XMM-N, Chandra and XMM-Newton.
• Figure 5: Constraints of dipole magnitude $A$ of different types datasets, including Chandra + XMM-N, Chandra and XMM-Newton. .