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arXiv 1601.01758astro-ph.CO
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我们对宇宙学了解多少

What do we know about cosmography

Ming-Jian Zhang, Hong Li, Jun-Qing Xia

备注：
12 pages, 10 figures, 1 table, accepted by EPJC
发表信息：
Eur. Phys. J. C (2017) 77:434
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摘要：

在本文中，我们研究宇宙学问题使用的偏差方差权衡。我们发现z-红移和$y=z/(1+z)$ -红移都可以给出一个小的偏差估计。这意味着宇宙学可以更准确地描述超新星数据。最小化风险，它表明，宇宙学到第二阶是最好的近似。通过对未来观测数据的预测，我们发现未来的超新星和红移漂移可以显著改善这一约束，从而有可能解决宇宙学问题。我们还利用宇宙学对暗能量$w(z)$的减速参数和状态方程的价值。我们发现，超新星宇宙学不能给出稳定的估计。然而，我们获得了许多有用的信息，如宇宙学倾向于一个复杂的暗能量与不同的$w(z)$，和衍生物$dw/dz<0$低红移。宇宙学有助于建立暗能量模型。

英文摘要：

In the present paper, we investigate the cosmographic problem using the bias-variance trade-off. We find that both the z-redshift and the $y=z/(1+z)$-redshift can present a small bias estimation. It means that the cosmography can describe the supernova data more accurately. Minimizing risk, it suggests that cosmography up to the second order is the best approximation. Forecasting the constraint from future measurements, we find that future supernova and redshift drift can significantly improve the constraint, thus having the potential to solve the cosmographic problem. We also exploit the values of cosmography on the deceleration parameter and equation of state of dark energy $w(z)$. We find that supernova cosmography cannot give stable estimations on them. However, much useful information was obtained, such as that the cosmography favors a complicated dark energy with varying $w(z)$, and the derivative $dw/dz<0$ for low redshift. The cosmography is helpful to model the dark energy.

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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