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arXiv 1809.07142astro-ph.COgr-qc
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关于从Ia型超新星数据重建暗能量标量场的稳定性

On the Stability of Dark Energy Scalar Field Reconstruction from SNe Ia Data

A. I. Alikhanian National Science Laboratory (Yerevan Physics Institute)(阿·伊·阿里哈尼扬国家科学实验室(埃里温物理研究所));University of Illinois Urbana-Champaign(伊利诺伊大学厄巴纳-香槟分校)

Arpine Piloyan, Sergey Pavluchenko

AI总结:

研究从Ia型超新星数据重建暗能量标量场势的可能性及问题,用合成数据测试方法,发现数据分箱法有不确定性放大问题,还探讨了参数估计错误导致重建不稳定的情况。

摘要:

本文探讨了从Ia型超新星数据重建暗能量标量场势的可能性及过程中出现的问题。描述了方法并利用合成数据测试其极限与特征,讨论了误差传播相关问题。得出所选平滑方法(数据分箱)会引入巨大不确定性放大,限制了该方法实际应用,需其他替代方案。还探讨了‘重建的不稳定性’,即若错误估计\(\Omega_m\)和\(H_0\)参数可能重建出错误标量场,其他暗能量模型也可能有类似情况。

英文摘要:

The current paper addresses the possibility of Dark Energy scalar field potential reconstruction from SNe Ia data and the problems arising during the process. We describe the method and test its limits and features with use of synthetic data, as well as discuss several issues connected to error propagation. We conclude that the chosen smoothing method -- binning of the data -- introduces immense uncertainty amplification which limits the practical application of this method, leaving us with other alternatives. We also address the ``instability of the reconstruction'', an important effect when a false scalar field -- real or phantom -- could be reconstructed if the $Ω_m$ and $H_0$ parameters are wrongly estimated; a similar effect could be expected in other Dark Energy models as well.

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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