Asimov manages the full lifecycle of a gravitational-wave parameter estimation campaign — from constructing individual job configurations, to submitting them to a compute cluster, monitoring progress, and gathering results — all via a reproducible, version-controlled configuration.
It is designed to scale from a single event to an entire observing run’s worth of detections without additional complexity for the analyst.
Software updates
My team and I published GWTC-4.0 — identifying 128 new gravitational-wave events during LIGO's fourth observing run and more than doubling the all-time total to 218 detected collisions.
Using LIGO's open data and asimov, I re-analysed gravitational-wave candidates from O1, O2, and O3 that the standard catalogues missed, but which the community identified, using reproducible techniques from the LVK.
If you’re looking to try out asimov on your own laptop or workstation you’ll quickly run into a bit of a limitation: asimov, and the codes it works with, are designed to run on a large computing cluster. However, we can get around this by installing a lightweight version of the software used on clusters on your own machine before we try to run asimov.
I’m very pleased to announce that the first release of the 0.4 development and review cycle for asimov!
I remember as a child religiously reading the Argos catalogue; probably sometimes looking for Christmas presents, but often just looking at how many things you could possibly buy from one shop. As I got older I started to wonder how on earth they managed to put such a large catalogue together. Five years after the first detection of a gravitational wave signal, I have a little insight into just how hard the latter process is, and a little more appreciation for how much the Universe has to offer.
The latest release of asimov is now available from our gitlab server, as well as being available on pypi.