Kavli Affiliate: Peter Graham
| First 5 Authors: Theophile Jegou du Laz, Theophile Jegou du Laz, , ,

| Summary:
With the arrival of ever higher throughput wide-field surveys and a multitude of multi-messenger and multi-wavelength instruments to complement them, software capable of harnessing these associated data streams is urgently required. To meet these needs, a number of community supported alert brokers have been built, currently focused on processing of Zwicky Transient Facility (ZTF; $sim 10^5$-$10^6$ alerts per night) with an eye towards Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST; $sim 2 times 10^7$ alerts per night). Building upon the system that successfully ran in production for ZTF’s first seven years of operation, we introduce BOOM (Burst & Outburst Observations Monitor), an analysis framework focused on real-time, joint brokering of these alert streams. BOOM harnesses the performance of a Rust-based software stack relying on a non-relational MongoDB database combined with a Valkey in-memory processing queue and a Kafka cluster for message sharing. With this system, we demonstrate feature parity with the existing ZTF system with a throughput $sim 8 times$ higher. We describe the workflow that enables the real-time processing as well as the results with custom filters we have built to demonstrate the system’s capabilities. In conclusion, we present the development roadmap for both BOOM and Babamul – the public-facing LSST alert broker built atop BOOM – as we begin the Rubin era.
| Search Query: arXiv Query: search_query=au:”Graham Peter”&id_list=&start=0&max_results=3
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