Tests of the Kerr Hypothesis with MAXI J1803-298 Using Different RELXILL_NK Flavors
Jie Liao, M. Ghasemi-Nodehi, Lang Cui, Ashutosh Tripathi, Yong-Feng Huang, Xiang Liu
arXiv:2404.06020v1 Announce Type: new
Abstract: Iron line spectroscopy has been one of the leading methods not only for measuring the spins of accreting black holes but also for testing fundamental physics. Basing on such a method, we present an analysis of a dataset observed simultaneously by NuSTAR and NICER for the black hole binary candidate MAXI J1803-298, which shows prominent relativistic reflection features. Various relxill_nk flavors are utilized to test the Kerr black hole hypothesis. The results obtained from our analysis provide stringent constraints on Johannsen deformation parameter $alpha_{13}$ with the highest precise to date, namely $alpha_{13}=0.023^{+0.071}_{-0.038}$ from relxillD_nk and $alpha_{13}=0.006^{+0.045}_{-0.022}$ from relxillion_nk respectively in 3-$sigma$ credible lever, where Johannsen metric reduces to Kerr metric when $alpha_{13}$ vanishes. Furthermore, we investigate the best model-fit results using Akaike Information Criterion and assess its systematic uncertainties.arXiv:2404.06020v1 Announce Type: new
Abstract: Iron line spectroscopy has been one of the leading methods not only for measuring the spins of accreting black holes but also for testing fundamental physics. Basing on such a method, we present an analysis of a dataset observed simultaneously by NuSTAR and NICER for the black hole binary candidate MAXI J1803-298, which shows prominent relativistic reflection features. Various relxill_nk flavors are utilized to test the Kerr black hole hypothesis. The results obtained from our analysis provide stringent constraints on Johannsen deformation parameter $alpha_{13}$ with the highest precise to date, namely $alpha_{13}=0.023^{+0.071}_{-0.038}$ from relxillD_nk and $alpha_{13}=0.006^{+0.045}_{-0.022}$ from relxillion_nk respectively in 3-$sigma$ credible lever, where Johannsen metric reduces to Kerr metric when $alpha_{13}$ vanishes. Furthermore, we investigate the best model-fit results using Akaike Information Criterion and assess its systematic uncertainties.