We propose a simple, analytic dual-cone accretion model for horizon scale images of the cores of Low-Luminosity Active Galactic Nuclei (LLAGN), including those observed by the Event Horizon Telescope (EHT). Our underlying model is of synchrotron emission from an axisymmetric, magnetized plasma, which is constrained to flow within two oppositely oriented cones that are aligned with the black hole's spin axis. We show that this model can accurately reproduce images for a variety of time-averaged general relativistic magnetohydrodynamic (GRMHD) simulations, that it accurately recovers both the black hole and emission parameters from these simulations, and that it is sufficiently efficient to be used to measure these parameters in a Bayesian inference framework with radio interferometric data. We show that non-trivial topologies in the source image can result in non-trivial multi-modal solutions when applied to observations from a sparse array, such as the EHT 2017 observations of M87${}^*$. The presence of these degeneracies underscores the importance of employing Bayesian techniques that adequately sample the posterior space for the interpretation of EHT measurements. We fit our model to the EHT observations of M87${}^*$ and find a 95% Highest Posterior Density Interval (HPDI) for the mass-to-distance ratio of $θ_g\in(2.84,3.75)\,μ{\rm as}$, and give an inclination of $θ_{\rm o}\in(11^\circ,24^\circ)$. These new measurements are consistent with mass measurements from the EHT and stellar dynamical estimates (e.g., Gebhardt et al. 2011; EHTC et al. 2019a,b; Liepold et al. 2023), and with the spin axis inclination inferred from properties of the M87${}^*$ jet (e.g., Walker et al. 2018).
Joint Bayesian Source and Lens Reconstruction for Multi-messenger Binary Black Holes
The Chinese University of Hong Kong（香港中文大学）；Kapteyn Astronomical Institute, University of Groningen（格罗宁根大学卡普坦天文研究所）；University of Portsmouth（朴茨茅斯大学）；Université Catholique de Louvain（天主教鲁汶大学）；Royal Observatory of Belgium（比利时皇家天文台）
Spin Constraints on 4U 1630-47 via combined Continuum Fitting and Reflection methods: a comparative study using Frequentist and Bayesian statistics
Fudan University（复旦大学）；Eberhard-Karls Universität Tübingen（蒂宾根大学）；University of Oxford（牛津大学）；New Uzbekistan University（新乌兹别克斯坦大学）；University of Warwick（华威大学）；Max Planck Institute for Extraterrestrial Physics（马克斯·普朗克地外物理学研究所）
Testing black hole space-times with the S2 star orbit: a Bayesian comparison
Instituto de Ciencias Nucleares, Universidad Nacional Autónoma de México（墨西哥国立自治大学核科学研究所）；DAMTP, Centre for Mathematical Sciences, University of Cambridge（剑桥大学数学科学中心应用数学与理论物理系）；Instituto de Astronomía, Universidad Nacional Autónoma de México（墨西哥国立自治大学天文研究所）
Inferring Black Hole Properties from Astronomical Multivariate Time Series with Bayesian Attentive Neural Processes
Kavli Institute for Particle Astrophysics and Cosmology（卡弗里粒子天体物理与宇宙学研究所）；Stanford University（斯坦福大学）；SLAC National Accelerator Laboratory（SLAC国家加速器实验室）；Flatiron Institute（熨斗研究所）；Columbia University（哥伦比亚大学）；Princeton University（普林斯顿大学）；New York University（纽约大学）；Carnegie Mellon University（卡内基梅隆大学）；University of Illinois at Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）
Optimizing Optical Searches for Supermassive Black Hole Binaries in AGN Light Curves: Fourier versus Bayesian Periodicity Detection
Vanderbilt University（范德堡大学）；Wake Forest University（维克森林大学）；Center for Interdisciplinary Exploration and Research in Astrophysics (CIERA)（天体物理跨学科探索与研究中心）；Northwestern University（西北大学）
