论文标题

从EHT观测值的黑洞SGR A*电荷的上限

An Upper Limit on the Charge of the Black Hole Sgr A* from EHT Observations

论文作者

Ghosh, Sushant G., Afrin, Misba

论文摘要

事件视野望远镜(EHT)最近发布了超大质量黑洞SGR A*显示角阴影直径$ d_ {sh} = 48.7 \ pm 7 \,μ$ as as and Schwarzschild shadow $δ= = = = = -0.08^{+0.09} _ { - 0.09}〜\ text {(vlti)}, - 0.04^{+0.09} _ { - 0.10}〜\ text {(keck)} $使用黑洞质量$ m = 4.0^{+1.11} {+1.11} {+1.11} _ $ 0.6} $ 10^6 m, SGR A*的EHT图像与Kerr Black Hole的预期外观一致,结果直接证明了银河系中心的超质量黑洞。在这里,我们使用SGR A*的EHT观察结果来研究其收费的约束,借助Kerr样黑洞,注意三种领先的旋转模型,即Kerr-Newman-Newman,Horndeski和毛茸茸的黑洞。对这些类似Kerr的黑洞的超级质量黑洞Sgr A*建模,我们观察到,Sgr A*的EHT结果与Kerr-Newman和Horndeski黑洞的参数空间更严格,而不是M87*的EHT结果。系统的偏见分析表明,未来EHT实验的观察结果对黑洞SGR A*的电荷更为精确。因此,在EHT约束参数空间的大量区域中,Kerr样黑洞和Kerr黑洞是不可见的。我们的偏见分析证实了这一主张。

The Event Horizon Telescope (EHT) recently released an image of the supermassive black hole Sgr A* showing an angular shadow diameter $d_{sh}= 48.7 \pm 7\,μ$as and Schwarzschild shadow deviation $δ= -0.08^{+0.09}_{-0.09}~\text{(VLTI)},-0.04^{+0.09}_{-0.10}~\text{(Keck)}$ using a black hole mass $M = 4.0^{+1.1}_{-0.6} \times 10^6 M_\odot $. The EHT image of Sgr A* is consistent with a Kerr black hole's expected appearance, and the results directly prove the existence of a supermassive black hole at the center of the Milky Way. Here, we use the EHT observational results for Sgr A* to investigate the constraints on its charge with the aid of Kerr-like black holes, paying attention to three leading rotating models, namely Kerr--Newman, Horndeski, and hairy black holes. Modeling the supermassive black hole Sgr A* as these Kerr-like black holes, we observe that the EHT results of Sgr A* place more strict upper limits on the parameter space of Kerr--Newman and Horndeski black holes than those placed by the EHT results for M87*. A systematic bias analysis reveals that, observational results of future EHT experiments place more precise limits on the charge of black hole Sgr A*. Thus, the Kerr-like black holes and Kerr black holes are indiscernible in a substantial region of the EHT-constrained parameter space; the claim is substantiated by our bias analysis.

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