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POWER OF OBSERVATIONAL HUBBLE PARAMETER DATA: A FIGURE OF MERIT EXPLORATION

机译:观测性哈勃参数数据的力量:功绩探索图

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We use simulated Hubble parameter data in the redshift range 0 ≤ z ≤ 2 to explore the role and power of observational H(z) data in constraining cosmological parameters of the ΛCDM model. The error model of the simulated data is empirically constructed from available measurements and scales linearly as z increases. By comparing the median figures of merit calculated from simulated data sets with that of current Type Ia supernova (SNIa) data, we find that as many as 64 further independent measurements of H(z) are needed to match the parameter constraining power of SNIa. If the error of H(z) could be lowered to 3%, the same number of future measurements would be needed, but then the redshift coverage would only be required to reach z = 1. We also show that accurate measurements of the Hubble constant H 0 can be used as priors to increase the H(z) data's figure of merit.
机译:我们在0≤z≤2的红移范围内使用模拟的哈勃参数数据来探索观测H(z)数据在约束ΛCDM模型的宇宙学参数中的作用和功效。模拟数据的误差模型是根据可用的测量结果凭经验构建的,并随着z的增加而线性缩放。通过比较从模拟数据集计算得到的品质因数中位数与当前Ia型超新星(SNIa)数据的中位数,我们发现需要多达64个H(z)的独立测量值才能匹配SNIa的参数约束能力。如果H(z)的误差可以降低到3%,则需要进行相同数量的未来测量,但是仅需要红移覆盖范围即可达到z =1。我们还证明了哈勃常数的精确测量H 0可以用作提高H(z)数据品质因数的先验条件。

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