标题： 利用星系团的重子声波振荡测量距离-红移关系 显示英文标题

标题： Measuring the distance-redshift relation with the baryon acoustic oscillations of galaxy clusters

摘要： 我们分析了迄今为止最大的星系团光谱样本，并从重子声波振荡的角度提供了距离-红shift关系的观测限制。 本研究中考虑的星系团样本是从斯隆数字巡天（Sloan Digital Sky Survey）在三个中值redshift，$z=0.2$、$z=0.3$和$z=0.5$处提取的。这三个样本分别包含$12910$、$42215$和$11816$个天体对象。我们检测到了这三个样本的重子声波振荡峰值。 得到的距离限制为：$r_s/D_V(z=0.2)=0.18 \pm 0.01$、$r_s/D_V(z=0.3)=0.124 \pm 0.004$和$r_s/D_V(z=0.5)=0.080 \pm 0.002$。 结合这些测量结果，我们获得了宇宙学参数的稳健限制。 我们的结果与标准的$\Lambda$冷暗物质模型一致。 具体而言，我们在一个$\Lambda$CDM模型中限制哈勃常数，$H_0 = 64_{-9}^{+14} \, \mathrm{km} \, \mathrm{s}^{-1}\mathrm{Mpc}^{-1}$，曲率能量密度，在$o\Lambda$CDM背景下，$\Omega_K = -0.015_{-0.36}^{+0.34}$，最后在$ow$CDM情况下暗能量状态方程的参数，$w = -1.01_{-0.44}^{+0.44}$。 这是首次利用星系团重子声波振荡峰值来限制距离-红移关系。 显示英文摘要

摘要： We analyse the largest spectroscopic samples of galaxy clusters to date, and provide observational constraints on the distance-redshift relation from baryon acoustic oscillations. The cluster samples considered in this work have been extracted from the Sloan Digital Sky Survey at three median redshifts, $z=0.2$, $z=0.3$, and $z=0.5$. The number of objects is $12910$, $42215$, and $11816$, respectively. We detect the peak of baryon acoustic oscillations for all the three samples. The derived distance constraints are: $r_s/D_V(z=0.2)=0.18 \pm 0.01$, $r_s/D_V(z=0.3)=0.124 \pm 0.004$ and $r_s/D_V(z=0.5)=0.080 \pm 0.002$. Combining these measurements, we obtain robust constraints on cosmological parameters. Our results are in agreement with the standard $\Lambda$ cold dark matter model. Specifically, we constrain the Hubble constant in a $\Lambda$CDM model, $H_0 = 64_{-9}^{+14} \, \mathrm{km} \, \mathrm{s}^{-1}\mathrm{Mpc}^{-1}$, the density of curvature energy, in the $o\Lambda$CDM context, $\Omega_K = -0.015_{-0.36}^{+0.34}$, and finally the parameter of the dark energy equation of state in the $ow$CDM case, $w = -1.01_{-0.44}^{+0.44}$. This is the first time the distance-redshift relation has been constrained using only the peak of baryon acoustic oscillations of galaxy clusters.