发表机构
Faculty of Science, Mohammed V University in Rabat（拉巴特穆罕默德五世大学理学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究利用机器学习分析B形变Reissner–Nordström–AdS黑洞，发现其具有范德瓦尔斯热力学行为，并通过M87*和Sgr A*观测数据约束参数，研究其光学阴影。
AI 中文摘要
利用机器学习技术，我们在受弦论中非对易几何启发的扩展时空导数框架下研究Reissner–Nordström–AdS黑洞，其中形变参数与NS-NS B场的倒数相关。我们将这些解称为B形变Reissner–Nordström–AdS黑洞。具体而言，我们考察了此类弦论形变AdS黑洞的热力学与光学行为。借助高级数值计算，我们首先通过计算描述P-V临界性与焦耳-汤姆逊膨胀特征的普适比率，考察相应的热力学范德瓦尔斯行为。应用这些数值结果，我们为全连接神经网络构建可靠的训练数据，以判定此类弦论黑洞构型是否展现热力学范德瓦尔斯特性。具体地，我们揭示出全连接且训练好的神经网络能准确检测范德瓦尔斯行为。在事件视界望远镜国际合作组织报告的观测数据支持下，我们利用机器学习方法研究此类B形变Reissner–Nordström–AdS黑洞的光学阴影。为提供经过验证的模型，我们利用M87*和Sgr A*黑洞的经验数据约束相关参数，包括弦论参数B。
英文摘要
Using machine learning techniques, we study the Reissner--Nordström--AdS black holes in the framework of extended space-time derivatives inspired by non-commutative geometry in string theory where the deformation parameters are related to the inverse of the NS-NS B-field. We refer to these solutions as B-deformed Reissner--Nordström--AdS black holes. Precisely, we examine the thermodynamic and the optical behaviors of such stringy deformed AdS black holes. Exploiting advanced numerical computations, we first examine the corresponding thermodynamic Van der Waals behaviors by calculating the universal ratios describing the P-V criticality and the Joule-Thomson expansion features. Applying such numerical results, we construct reliable training data for a fully connected neural network being developed to determine whether such stringy black hole configurations exhibit thermodynamic Van der Waals aspects. Concretely, we reveal that the fully connected and trained neural network accurately detects Van der Waals behaviors. Supported by the observational data reported by the Event Horizon Telescope international collaborations, we investigate the optical shadows of such B-deformed Reissner--Nordström--AdS black holes using machine learning methods. In order to provide corroborated models, we constraint the involved parameters including the stringy one B by making use of M87* and Sgr A* black hole empirical data.
Comments22 pages, 11 figures, 6 tables, Latex, Authors are listed in alphabetical order. Comments are welcome
