Collaborative Research: Spectral Synthesis for Broad Absorption Line Quasars - Feedback and Physics for Everyone

黑洞存在于大多数大星系的中心。对星系演化的研究表明，黑洞和星系是一起演化的。这种演化需要黑洞和星系之间的相互作用，例如，从黑洞中冒出的风可以与星系中的气体相互作用。在这个项目中，一种名为SimBAL的新型计算机代码将用于研究类星体风。SimBAL使用机器学习技术来分析类星体发出的光。SimBAL方法将用于研究两个大型类星体样本，以测量类星体风的特性，并了解类星体风的能量是否足以影响宿主星系的演化。作为该项目的一部分，SimBAL代码将准备向公众发布，以便任何人都可以使用它。这项研究将涉及本科生，包括代表性不足的学生。研究人员还将向本科生讲授数据分析课程，并开发工具来评估本学期数据素养的提高。黑洞存在于大多数大星系的中心。对星系演化的研究表明，黑洞和星系是一起演化的。这种演化需要黑洞和星系之间的相互作用，例如，从黑洞中冒出的风可以与星系中的气体相互作用。在这个项目中，一种名为SimBAL的新型计算机代码将用于研究类星体风。SimBAL使用机器学习技术来分析大约10%的类星体光谱中的吸收线。SimBAL方法将用于研究两个大的互补类星体样本。风的特性，如速度、量和风的位置将被测量。首要目标是确定风是如何加速的，以及风的能量是否足以影响宿主星系的演化。作为该项目的一部分，SimBAL代码将准备向公众发布，以便任何人都可以使用它。这项研究将涉及本科生，包括代表性不足的学生。研究人员还将向本科生讲授数据分析课程，并开发工具来评估本学期数据素养的提高。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Black holes exist in the centers of most large galaxies. Studies of galaxy evolution show that black holes and galaxies evolve together. This evolution requires interactions between the black hole and the galaxy, for example, winds emerging from the black hole can interact with the gas in the galaxy. In this project, a novel computer code called SimBAL will be used to study quasar winds. SimBAL uses machine learning techniques to analyze the light emitted by the quasar. The SimBAL method will be used to study two large samples of quasars to measure the properties of quasar winds and to learn whether the winds are energetic enough to influence the evolution of the host galaxy. As part of this project, the SimBAL code will be prepared to be released to the public so that anyone can use it. The research will involve undergraduate students, including under-represented students. The investigators will also teach courses in data analytics to undergraduates and will develop tools to evaluate gains in data literacy during the semester.Black holes exist in the centers of most large galaxies. Studies of galaxy evolution show that black holes and galaxies evolve together. This evolution requires interactions between the black hole and the galaxy, for example, winds emerging from the black hole can interact with the gas in the galaxy. In this project, a novel computer code called SimBAL will be used to study quasar winds. SimBAL uses machine learning techniques to analyze the absorption lines found in about 10% of quasar spectra. The SimBAL method will be used to study two large and complementary samples of quasars. The properties of the winds, such as the velocity, the amount, and the location of the winds will be measured. The overarching goals are to determine how the winds are accelerated, and whether the winds are energetic enough to influence the evolution of the host galaxy. As part of this project, the SimBAL code will be prepared to be released to the public so that anyone can use it. The research will involve undergraduate students, including under-represented students. The investigators will also teach courses in data analytics to undergraduates and will develop tools to evaluate gains in data literacy during the semester.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.