论文标题
丽莎数据挑战
The LISA Data Challenges
论文作者
论文摘要
未来的空间重力波检测器LISA将通过聆听Millihertz宇宙来提供丰富而信息密集的数据。测得的时间序列将包含数以万计的可检测的银河二进制物的烙印，每年几十个超级质量的黑洞合并事件，数十恒星的黑洞，甚至可能成千上万的极端质量比率灵感。最重要的是，我们希望检测到随机引力波背景和爆发的存在。寻找和表征许多这样的来源是一项艰巨而尚未解决的任务。 LISA数据挑战（LDCS）是解决这个令人兴奋的问题的开放和协作努力。刚刚发布了一个新的模拟数据集，即绰号Sangria，目的是用理想化的仪器噪声来解决温和的源混乱。本演讲将描述最不发达国家策略，展示可用的数据集和分析工具，并讨论未来准备LISA数据分析的努力。
The future space-based gravitational-wave detector LISA will deliver rich and information-dense data by listening to the milliHertz Universe. The measured time series will contain the imprint of tens of thousands of detectable Galactic binaries constantly emitting, tens of supermassive black hole merger events per year, tens of stellar-origin black holes, and possibly thousands of extreme mass-ratio inspirals. On top of that, we expect to detect the presence of stochastic gravitational wave backgrounds and bursts. Finding and characterizing many such sources is a vast and unsolved task. The LISA Data Challenges (LDCs) are an open and collaborative effort to tackle this exciting problem. A new simulated data set, nicknamed Sangria, has just been released with the purpose of tackling mild source confusion with idealized instrumental noise. This presentation will describe the LDC strategy, showcase the available datasets and analysis tools, and discuss future efforts to prepare LISA data analysis.
