Getting parallel bilby production-ready for LIGO’s fourth observing run

The Third Observing Run of the LIGO-VIRGO-KAGRA Collaboration (LVK), O3, ended on March 31, 2020, bringing the total number of gravitational-wave (GW) events to more than 90. LVK’s Fourth Observing Run will start towards the end of 2022 and is estimated to provide over 150 GW events. Inferring the astrophysics of these candidates is a cornerstone of GW astronomy. In inference, observed data is modeled with parameterized GW signals to understand the objects that generated the GW. However, some GW models are very complex and take a long time to compute. To make it possible to use these complex models, Parallel Bilby makes it possible to use multiple computers to help study the observed data. Using multiple computers, Parallel bilby can reduce the time for computation from 15 years to a few days!

Due to Parallel Bilby being the only software tool that allows the LVK to use the very complex GW models, the LVK required the immediate release of Parallel Bilby for analysis in O3 (a few days after its inception)! Hence, various development practices to ensure code quality and readability were sacrificed to achieve the functional requirements of Parallel Bilby. These sacrifices allowed the small team of Parallel Bilby developers to build and release the first version of the software quickly. However, due to the poor code quality, lack of unit-tests (UT), and end-to-end tests (E2E), maintenance and further development of Parallel Bilby has become challenging.

In 2021, ADACS developers Conrad Chan, David Liptai, and Tiger Hu stepped in to restructure Parallel Bilby. With their technical knowledge, they essentially re-wrote Parallel Bilby using state-of-art software engineering design principles.

Their work has instilled good development practices within the (currently small) development team and made the software more accessible to new developers. Their refactoring and the addition of tests have provided a firmer foundation for future development, which may enable us to make further optimizations to Parallel Bilby.

A. Vajpeyi

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