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arXiv 1901.02540astro-ph.CO
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J-PAS:从重子声学振荡和红移空间畸变对相互作用暗能量的预测

J-PAS: forecasts on interacting dark energy from baryon acoustic oscillations and redshift-space distortions

A. A. Costa, R. J. F. Marcondes, R. G. Landim, E. Abdalla, L. R. Abramo, H. S. Xavier, A. A. Orsi, N. Chandrachani Devi, A. J. Cenarro, D. Cristobal-Hornillos, … 展开作者

A. A. Costa, R. J. F. Marcondes, R. G. Landim, E. Abdalla, L. R. Abramo, H. S. Xavier, A. A. Orsi, N. Chandrachani Devi, A. J. Cenarro, D. Cristobal-Hornillos, R. A. Dupke, A. Ederoclite, A. Marin-Franch, C. M. Oliveira, H. Vazquez Ramio, K. Taylor, J. Varela

摘要:

我们估计的约束功率的J-PAS相互作用的暗能量宇宙学的参数。该调查预计将绘制数百万个发光的红色星系,发射线星系和类星体在北半球天空数千平方度的区域内,精确的光度红移测量。对DESI和欧几里得调查的预测也进行了评估,并与J-PAS进行了比较。与Fisher矩阵的方法,我们发现,J-PAS可以把约束的相互作用参数相媲美,从DESI,与约$0.02$的绝对不确定性,当相互作用项是成比例的暗物质的能量密度,几乎一样好,约$0.01$,当相互作用是成比例的暗能量密度。对于暗能量的状态方程,J-PAS的约束在两种情况下稍好一些(不确定度$0.04$ - $0.05$与基准值$-1$周围的$0.05$ - $0.07$)。这两个调查都落后于欧几里德,但紧随其后,在所有考虑的具体情况下施加了可比的限制。

英文摘要:

We estimate the constraining power of J-PAS for parameters of an interacting dark energy cosmology. The survey is expected to map several millions of luminous red galaxies, emission line galaxies and quasars in an area of thousands of square degrees in the northern sky with precise photometric redshift measurements. Forecasts for the DESI and Euclid surveys are also evaluated and compared to J-PAS. With the Fisher matrix approach, we find that J-PAS can place constraints on the interaction parameter comparable to those from DESI, with an absolute uncertainty of about $0.02$, when the interaction term is proportional to the dark matter energy density, and almost as good, of about $0.01$, when the interaction is proportional to the dark energy density. For the equation of state of dark energy, the constraints from J-PAS are slightly better in the two cases (uncertainties $0.04$ - $0.05$ against $0.05$ - $0.07$ around the fiducial value $-1$). Both surveys stay behind Euclid but follow it closely, imposing comparable constraints in all specific cases considered.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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