PROBING PRIMORDIAL NON-GAUSSIANITY WITH WEAK-LENSING MINKOWSKI FUNCTIONALS

PROBING PRIMORDIAL NON-GAUSSIANITY WITH WEAK-LENSING MINKOWSKI FUNCTIONALS
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DOI:
10.1088/0004-637x/760/1/45
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发表时间:
2012-04
期刊:
The Astrophysical Journal
影响因子:
--
通讯作者:
M. Shirasaki;N. Yoshida;T. Hamana;T. Nishimichi
M. Shirasaki;N. Yoshida;T. Hamana;T. Nishimichi
中科院分区:
其他
文献类型:
--
作者:
M. Shirasaki;N. Yoshida;T. Hamana;T. Nishimichi

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相似文献

研究了弱引力透镜会聚映射的Minkowski泛函中包含的宇宙学信息。我们发现,MF提供了强有力的约束本地型原始非高斯参数fNL。我们运行一组宇宙学N体模拟,并对弱透镜进行光线追踪模拟,以生成fNL = −100,0和100的25 ° 2视场的100个独立收敛图。我们利用Fisher分析研究了暗能量状态方程参数w和涨落幅度σ8等宇宙学参数的简并性。我们使用完全非线性协方差矩阵评估1000射线跟踪模拟。对于即将到来的宽场观测,例如来自斯巴鲁Hyper Suprime-Cam调查的那些,其建议的调查区域为1500 deg 2,原始非高斯性可以通过弱透镜MF被限制在fNL = 80和w = 0.036的水平。如果简单地按有效测量区域缩放,使用大型综合巡天望远镜进行20,000度2的透镜测量将产生fNL = 25和w = 0.013的约束。我们表明,这些限制可以进一步改善使用源星系在多个红移箱的层析成像方法。
We study the cosmological information contained in the Minkowski functionals (MFs) of weak gravitational lensing convergence maps. We show that the MFs provide strong constraints on the local-type primordial non-Gaussianity parameter fNL. We run a set of cosmological N-body simulations and perform ray-tracing simulations of weak lensing to generate 100 independent convergence maps of a 25 deg2 field of view for fNL = −100, 0 and 100. We perform a Fisher analysis to study the degeneracy among other cosmological parameters such as the dark energy equation of state parameter w and the fluctuation amplitude σ8. We use fully nonlinear covariance matrices evaluated from 1000 ray-tracing simulations. For upcoming wide-field observations such as those from the Subaru Hyper Suprime-Cam survey with a proposed survey area of 1500 deg2, the primordial non-Gaussianity can be constrained with a level of fNL ∼ 80 and w ∼ 0.036 by weak-lensing MFs. If simply scaled by the effective survey area, a 20,000 deg2 lensing survey using the Large Synoptic Survey Telescope will yield constraints of fNL ∼ 25 and w ∼ 0.013. We show that these constraints can be further improved by a tomographic method using source galaxies in multiple redshift bins.