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[论文解读] Fundamental scaling relationships revealed in the optical light curves of tidal disruption events

Andrew Mummery, Sjoert van Velzen|arXiv (Cornell University)|Aug 16, 2023
Astrophysical Phenomena and ObservationsPhysics and Astronomy参考文献 73被引用 3
一句话总结

本文建立了潮汐瓦解事件(TDE)光学/紫外光曲线与中心黑洞质量之间的基本比例关系。通过对63个TDE进行分析,发现晚期亮度平台与黑洞质量存在紧密相关性(r² = 0.99,残差离散度为0.3 dex),使得仅通过单次瞬时观测即可实现约0.5 dex离散度的黑洞质量估算,并揭示了早期峰值亮度与辐射能量与黑洞质量之间的新关系。

ABSTRACT

We present fundamental scaling relationships between properties of the optical/UV light curves of tidal disruption events (TDEs) and the mass of the black hole that disrupted the star. We have uncovered these relations from the late-time emission of TDEs. Using a sample of 63 optically-selected TDEs, the latest catalog to date, we observed flattening of the early-time emission into a near-constant late-time plateau for at least two-thirds of our sources. Compared to other properties of the TDE lightcurves (e.g., peak luminosity or decay rate) the plateau luminosity shows the tightest correlation with the total mass of host galaxy ($p$-value of $2 imes 10^{-6}$, with a residual scatter of 0.3 dex). Physically this plateau stems from the presence of an accretion flow. We demonstrate theoretically and numerically that the amplitude of this plateau emission is strongly correlated with black hole mass. By simulating a large population of TDEs, we determine a plateau luminosity-black hole mass scaling relationship well described by $ \log_{10} \left(M_{\bullet}/M_{\odot} ight) = 1.50 \log_{10} \left( L_{ m plat}/10^{43} { m erg \, s^{-1}} ight) + 9.0 $. The observed plateau luminosities of TDEs and black hole masses in our large sample are in excellent agreement with this simulation. Using the black hole mass predicted from the observed TDE plateau luminosity, we reproduce the well-known scaling relations between black hole mass and galaxy velocity dispersion. The large black hole masses of 10 of the TDEs in our sample allow us to provide constraints on their black hole spins, favouring rapidly rotating black holes. We add 49 (34) black hole masses to the galaxy mass (velocity dispersion) scaling relationships, updating and extending these correlations into the low black hole mass regime.

研究动机与目标

  • 建立TDE光学光曲线特性与中心黑洞质量之间稳健且具有物理解释基础的比例关系。
  • 改进TDE黑洞质量估算,特别是在直接测量存在不确定性的低质量区域。
  • 利用晚期亮度与TDE能量学约束黑洞自旋。
  • 为未来如Rubin/LSST等大样本TDE巡天提供可预测的解释框架。

提出的方法

  • 分析了最新星表中63个光学选中的TDE样本,重点关注其晚期光曲线行为。
  • 在超过66%的源中识别出在静止系约6×10¹⁴ Hz波段的近似恒定亮度平台。
  • 推导了吸积流的理论与数值模型,以解释平台发射的幅度如何随黑洞质量变化。
  • 模拟了10⁶个TDE,得出黑洞质量-平台亮度比例关系:log₁₀(M•/M☉) = 1.50 log₁₀(Lₚₗₐₜ/10⁴³ erg s⁻¹) + 9.0。
  • 利用平台亮度推断黑洞质量,并检验其与星系比例关系(M–M₉₀₀₀,M–σ)的一致性。
  • 研究了早期性质(峰值亮度、辐射能量),发现其与黑洞质量存在强相关性,即使未检测到平台,也可实现质量估算。
Figure 1: Ray tracing geometry. The coordinates $b_{x}$ and $b_{y}$ lie in the observer plane; $x$ and $y$ in the disc plane. A schematic photon trajectory from the inner disc is shown. The observer-disc inclination angle is denoted $i$ .
Figure 1: Ray tracing geometry. The coordinates $b_{x}$ and $b_{y}$ lie in the observer plane; $x$ and $y$ in the disc plane. A schematic photon trajectory from the inner disc is shown. The observer-disc inclination angle is denoted $i$ .

实验结果

研究问题

  • RQ1TDE光曲线中的晚期平台亮度是否可用于高精度推断黑洞质量?
  • RQ2观测到的平台发射背后的物理机制是什么?其幅度如何与黑洞质量相关?
  • RQ3TDE的早期光学性质(峰值亮度与辐射能量)是否与中心黑洞质量相关?
  • RQ4从TDE光曲线推断的黑洞质量是否能重现已知的星系比例关系(如M–σ、M–M₉₀₀₀)?
  • RQ5最明亮的TDE对黑洞自旋施加了何种约束?

主要发现

  • 在静止系约6×10¹⁴ Hz波段,平台亮度与黑洞质量之间存在紧密相关性,p值为2×10⁻⁶,残差离散度仅为0.3 dex。
  • 所推导的比例关系 log₁₀(M•/M☉) = 1.50 log₁₀(Lₚₗₐₜ/10⁴³ erg s⁻¹) + 9.0 能够准确地从样本中观测到的平台亮度预测黑洞质量。
  • 由平台亮度推断的黑洞质量与宿主星系质量及速度弥散高度相关,将已知的比例关系延伸至低质量区域。
  • 在ν = 10¹⁵ Hz处νLν ≳ 10⁴³ erg s⁻¹的平台亮度TDE,要求黑洞质量M• ≳ 10⁸ M☉,并倾向于支持快速旋转的黑洞。
  • 发现了一种新的经验比例关系:早期峰值亮度与黑洞质量成正比,Lₚₑₐₖ ∝ M•⁴/⁵,以及辐射能量与黑洞质量的关系,使得即使在未检测到平台的TDE中也能实现质量估算。
  • 该方法可对所有光学TDE实现黑洞质量估算,包括缺乏晚期数据的源,其内在离散度约为0.5 dex。
Figure 2: A schematic of each step of the population simulation procedure. There are 4 main computations involved, the first (denoted by grey boxes and arrows) regards determining whether or not electromagnetic emission will be observable for a given set of system parameters. The second (blue boxes
Figure 2: A schematic of each step of the population simulation procedure. There are 4 main computations involved, the first (denoted by grey boxes and arrows) regards determining whether or not electromagnetic emission will be observable for a given set of system parameters. The second (blue boxes

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