The immediate vicinity of an active supermassive black hole—with its event horizon, photon ring, accretion disk and relativistic jets—is an appropriate place to study physics under extreme conditions, particularly general relativity and magnetohydrodynamics. Observing the dynamics of such compact astrophysical objects provides insights into their inner workings, and the recent observations of M87* by the Event Horizon Telescope^1,2,3,4,5,6 using very-long-baseline interferometry techniques allows us to investigate the dynamical processes of M87* on timescales of days. Compared with most radio interferometers, very-long-baseline interferometry networks typically have fewer antennas and low signal-to-noise ratios. Furthermore, the source is variable, prohibiting integration over time to improve signal-to-noise ratio. Here, we present an imaging algorithm^7,8 that copes with the data scarcity and temporal evolution, while providing an uncertainty quantification. Our algorithm views the imaging task as a Bayesian inference problem of a time-varying brightness, exploits the correlation structure in time and reconstructs (2 + 1 + 1)-dimensional time-variable and spectrally resolved images. We apply this method to the Event Horizon Telescope observations of M87*⁹ and validate our approach on synthetic data. The time- and frequency-resolved reconstruction of M87* confirms variable structures on the emission ring and indicates extended and time-variable emission structures outside the ring itself.

活动超大质量黑洞的附近——有它的事件视界、光子环、吸积盘和相对论喷流——是研究极端条件下物理学的合适场所，特别是广义相对论和磁流体动力学。观察这种紧凑型天体物理物体的动力学可以深入了解它们的内部运作，以及最近由事件视界望远镜^{1、2、3、4、5、6}对 M87* 的观察使用超长基线干涉测量技术使我们能够在数天的时间尺度上研究 M87* 的动力学过程。与大多数无线电干涉仪相比，超长基线干涉测量网络通常具有更少的天线和低信噪比。此外，源是可变的，禁止随着时间的推移进行积分以提高信噪比。在这里，我们提出了一种成像算法^7,8应对数据稀缺和时间演变，同时提供不确定性量化。我们的算法将成像任务视为时变亮度的贝叶斯推理问题，利用时间相关性结构并重建 (2 + 1 + 1) 维时变和光谱解析图像。我们将此方法应用于 M87* ⁹的事件视界望远镜观测，并在合成数据上验证我们的方法。M87* 的时间和频率分辨重建证实了发射环上的可变结构，并指示了环外的扩展和时变发射结构。