eROSITA’s Window into the X-ray-Transient Sky: AGN Accretion in the Era of Big Data

关于活动星系核（AGN）的燃料机制，仍然存在一些悬而未决的问题：活动星系核的平均占空比是多少？最内层吸积流的结构和形态是什么？这种流动如何取决于全球吸积速率？最近的光学和x射线观测已经提供了诱人的线索：罕见的吸积开启/关闭事件，以及由于穿越离散团块而导致的视线柱密度变化。然而，由于观测到的事件数量少，进展受到限制。我们将使用eROSITA x射线望远镜编制一个新的、扩展的超过1e6AGN的x射线监测变异性统计数据库。我们将使用机器学习来识别AGN中发生的新的变化状态和变化模糊事件，从而提高目前已知事件的数量。累积的吸积点火/熄灭事件的统计数据将揭示AGN的占空比，我们预期的多波长运动将监测吸积盘、BLR和x射线日冕在AGN点火期间的演变。我们还将监测大约800个Seyferts的云蚀事件，确定云的物理性质，并使用这些事件的累积统计数据来确定云的分布和物理来源。我们还将测量大约60000 AGN的变异性振幅，作为质量和红移的函数。最后，我们将监测大约1600个耀变体的快速x射线变化，并与同期费米- lat数据相关联，以测试所有正常状态下的单区和多区发射模型，而不仅仅是在爆发期间。eROSITA将产生唯一的数据库（在可预见的未来），将x射线监测与目标AGN的统计显著样本相结合，从而产生唯一的新瞬态事件的大量x射线识别。我们的工作将产生第一个基于x射线观测的AGN占空比估计，测试统一方案，并限制AGN点火事件中吸积流演变的速度。我们还将限制块状物质的分布和观测到的遮挡跃迁率，帮助我们理解x射线/光学类型不匹配。我们还将了解在塞弗茨的x射线变率机制是否随着红移而演变。我们的耀变体子集将有助于区分当前各种耀变体发射模型。我们的工作也为21世纪20年代中期的更多大数据研究奠定了基础，这些研究也将使用机器学习对瞬态进行分类。我们的合作结合了AGN和黑洞双星的时间和光谱方面的互补专业知识，以及跨多个带通的高红移AGN大样本。为了加强合作，该项目的新博士生将是双边的，由两国共同指导。

Open questions persist regarding the fueling mechanisms in Active Galactic Nuclei (AGN): What is the average AGN duty cycle? What is the structure and morphology of the innermost accretion flow? How does that flow depend on global accretion rate? Recent optical and X-ray observations have yielded tantalizing clues: rare accretion turn-on/turn off events and variations in line-of-sight columndensities due to transiting discrete clumps. However, progress has been limited by the low number of observed events.We will use the eROSITA X-ray telescope to compile a new, expanded X-ray monitoring variability statistics database for more than 1e6AGN. We will use machine learning to identify new changing-state and changing-obscuration events in AGN as they occur, boosting the currently small number of known events. The accumulated statistics on accretion ignition/quenching events will reveal AGN duty cycles, and our expected multi-wavelength campaigns will monitor how the accretion disk, BLR, and X-ray corona evolve during AGN ignition. We will also monitor about 800 Seyferts for cloud eclipse events, determine clouds' physical properties, and use the accumulated statistics on such events to determine the distribution and physical origin of clouds. We will also measure variability amplitudes in about 60000 AGN as function of mass and redshift. Finally, we will monitor rapid X-ray variability in about 1600 blazars and correlate with contemporaneous Fermi-LAT data to test single- and multi-zone emission models at all normal states, not just during outbursts.eROSITA will yield the only database (for the foreseeable future) combining X-ray monitoring with a statistically significant sample oftarget AGN, and thus the only bulk X-ray identification of new transient events. Our work will yield the first X-ray observation-based estimate for AGN duty cycles, test unification schemes, and constrain how quickly the accretion flow can evolve in AGN ignition events. We will also constrain the distribution of clumpy matter and the rate of observed obscuration transitions, helping us understand X-ray/optical type mismatches. We will also learn if the X-ray variability mechanism in Seyferts evolves with redshift. Our blazar variability subset will help distinguish various current blazar emission models. Our work also sets the stage for additional Big Dataresearch in the mid 2020s that also use machine learning to classify transients.Our collaboration combines complementary expertise spanning timing and spectroscopy of both AGN and Black Hole Binaries and large samples of high-redshift AGN across multiple bandpasses. To cement the collaboration, new PhD students in this project will be bilateral, with joint supervisors from both countries.