BOOM and Babamul: a real-time, multi-survey, optical alert broker system operating at scale
Theophile Jegou du Laz, Michael W. Coughlin, Peter Bachant, Jacob E. Simones, Thomas Culino, Antoine Le Calloch, Sushant Sharma Chaudhary, Xander J. Hall, Tyler Barna, Daniel Warshofsky, Matthew Graham, Mansi M. Kasliwal, Ashish Mahabal, Joshua S. Bloom, Antonella Palmese

TL;DR
The paper introduces BOOM, a high-throughput, real-time alert broker system for astronomical surveys, and discusses its development and capabilities for upcoming large-scale sky surveys like LSST.
Contribution
It presents a scalable, efficient, Rust-based framework for real-time processing of astronomical alerts, building on previous systems and preparing for LSST's data volume.
Findings
BOOM achieves 7 times higher throughput than previous ZTF systems.
The system maintains feature parity with existing alert brokers.
Demonstrated real-time processing with custom filters.
Abstract
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; - alerts per night) with an eye towards Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST; 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…
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