BOOM and Babamul: a real-time, multi-survey, optical alert broker system operating at scale
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arXiv
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| Autori principali: | , , , , , , , , , , , , , , , , , , , |
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| Natura: | Preprint |
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2025
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| _version_ | 1866911653824561152 |
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| author | Laz, Theophile Jegou du Coughlin, Michael W. Bachant, Peter Simones, Jacob E. Culino, Thomas Calloch, Antoine Le Chaudhary, Sushant Sharma Hall, Xander J. Barna, Tyler Warshofsky, Daniel Graham, Matthew Kasliwal, Mansi M. Mahabal, Ashish Bloom, Joshua S. Palmese, Antonella Masci, Frank J. Groom, Steven L. Dekany, Richard Riddle, Reed L. Helou, George |
| author_facet | Laz, Theophile Jegou du Coughlin, Michael W. Bachant, Peter Simones, Jacob E. Culino, Thomas Calloch, Antoine Le Chaudhary, Sushant Sharma Hall, Xander J. Barna, Tyler Warshofsky, Daniel Graham, Matthew Kasliwal, Mansi M. Mahabal, Ashish Bloom, Joshua S. Palmese, Antonella Masci, Frank J. Groom, Steven L. Dekany, Richard Riddle, Reed L. Helou, George |
| contents | 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 $\sim 7 \times$ 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_00164 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | BOOM and Babamul: a real-time, multi-survey, optical alert broker system operating at scale Laz, Theophile Jegou du Coughlin, Michael W. Bachant, Peter Simones, Jacob E. Culino, Thomas Calloch, Antoine Le Chaudhary, Sushant Sharma Hall, Xander J. Barna, Tyler Warshofsky, Daniel Graham, Matthew Kasliwal, Mansi M. Mahabal, Ashish Bloom, Joshua S. Palmese, Antonella Masci, Frank J. Groom, Steven L. Dekany, Richard Riddle, Reed L. Helou, George Instrumentation and Methods for Astrophysics 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 $\sim 7 \times$ 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. |
| title | BOOM and Babamul: a real-time, multi-survey, optical alert broker system operating at scale |
| topic | Instrumentation and Methods for Astrophysics |
| url | https://arxiv.org/abs/2511.00164 |