论文标题
二进制黑洞数值相对性波形的初始数据和偏心降低工具包
Initial Data and Eccentricity Reduction Toolkit for Binary Black Hole Numerical Relativity Waveforms
论文作者
论文摘要
描述准二元黑洞合并的数值相对性波形的产生需要高质量的初始数据,并且迭代降低了剩余偏心率的算法。迄今为止,这些工具仍然是封闭的源,或者在阻止其在高性能计算平台中使用的商业软件中。为了解决这些限制,并确保更广泛的数值相对性社区可以访问这些工具,在本文中,我们提供了所有必需的元素,以在超级计算机平台中产生高质量的数值相对性模拟,即:开源参数文件:为数值模拟黑洞旋转的黑洞二进制文件,并具有不对称的质量 - 比纳里奥;开源$ \ texttt {python} $工具可生成高质量的初始数据,以用于在准圆形轨道上旋转黑洞二进制文件的数值相对性模拟;开源$ \ texttt {python} $用于减少偏心的工具,无论是独立软件,都将其部署在$ \ texttt {einstein toolkit} $的软件基础架构中。在数值相对论在研究和解释引力波源的解释中,该开源工具包填补了文献中的关键空隙。作为我们社区建设努力的一部分,为了简化和加速这些资源的使用,我们提供的教程逐步描述了如何获取和使用这些开源数值相对论工具。
The production of numerical relativity waveforms that describe quasicircular binary black hole mergers requires high-quality initial data, and an algorithm to iteratively reduce residual eccentricity. To date, these tools remain closed source, or in commercial software that prevents their use in high performance computing platforms. To address these limitations, and to ensure that the broader numerical relativity community has access to these tools, herein we provide all the required elements to produce high-quality numerical relativity simulations in supercomputer platforms, namely: open source parameter files to numerical simulate spinning black hole binaries with asymmetric mass-ratios; open source $\texttt{Python}$ tools to produce high-quality initial data for numerical relativity simulations of spinning black hole binaries on quasi-circular orbits; open source $\texttt{Python}$ tools for eccentricity reduction, both as stand-alone software and deployed in the $\texttt{Einstein Toolkit}$'s software infrastructure. This open source toolkit fills in a critical void in the literature at a time when numerical relativity has an ever increasing role in the study and interpretation of gravitational wave sources. As part of our community building efforts, and to streamline and accelerate the use of these resources, we provide tutorials that describe, step by step, how to obtain and use these open source numerical relativity tools.