标题： 阿西莫夫：一种协调参数估计工作流的框架 显示英文标题

标题： Asimov: A framework for coordinating parameter estimation workflows

摘要： 自2015年首次探测到来自致密双星合并的引力波以来，先进LIGO和先进Virgo探测器的改进扩大了我们对这些信号的宇宙视野。最新观测运行（O3）的搜索已将探测到的信号数量增加到90个，每周大约1个。未来的观测运行预计会进一步增加这一数量。对信号的贝叶斯分析可以通过将预测的波形与观测数据进行比较，揭示合并黑洞和中子星的特性。探测信号数量的不断增加，已部署方法数量的增多以及波形模型的多样化，使得可以考虑的分析数量不断增长。Asimov是一个Python包，旨在简化并标准化为大量事件配置这些分析的过程。它已经在三个主要引力波目录出版物的分析开发中得到了应用。 显示英文摘要

摘要： Since the first detection in 2015 of gravitational waves from compact binary coalescence, improvements to the Advanced LIGO and Advanced Virgo detectors have expanded our view into the universe for these signals. Searches of the of the latest observing run (O3) have increased the number of detected signals to 90, at a rate of approximately 1 per week. Future observing runs are expected to increase this even further. Bayesian analysis of the signals can reveal the properties of the coalescing black holes and neutron stars by comparing predicted waveforms to the observed data. The proliferating number of detected signals, the increasing number of methods that have been deployed, and the variety of waveform models create an ever-expanding number of analyses that can be considered. Asimov is a python package which is designed to simplify and standardise the process of configuring these analyses for a large number of events. It has already been used in developing analyses in three major gravitational wave catalog publications.