The paper describes a neural network architecture, based on **normalizing flows** alone, that is able to generate posteriors on the **full** $D = 15$ dimensional parameter space of quasi-circular binary inspirals, using input data surrounding the first observed GW event, **GW150914**, from multiple gravitational-wave detectors.
Demo script (Python) of particle swarm optimization (PSO) partly translated from [SDMBIGDAT19](https://github.com/mohanty-sd/SDMBIGDAT19) (MATLAB).
模型选择 (model selection) 是统计推断专题里一个很重要的话题。此文是于 2021.1.19 在 ITP-CAS 为 Journal Club 准备的一个整理与调研。算是自己对 model selection 在个人在当前理解程度上的一个记录。
An interactive gravitational wave simulation ([LIGO-G2001983-v3](https://dcc.ligo.org/LIGO-G2001983)) in JavaScript created by [Graham Woan](https://dcc.ligo.org/cgi-bin/private/DocDB/ListBy?authorid=234), suitable for talks etc on spinning NSs and BBHs.
Python Script to plot cumulative GW Events until the end of O3a and Public Alerts in O3b