SGNAX unifies snax and omicron in one Python-native pipeline and reproduces production trigger populations while exposing a low-frequency SNR amplitude error in snax.
SGN: A python framework for stream-processing pipelines
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abstract
We present the Stream Graph Navigator (SGN), a lightweight Python framework for building streaming data applications. In SGN, stream-processing pipelines are built by connecting computational components into directed acyclic graphs that run within an event loop. The time-series extension of the SGN library, SGN-TS, introduces signal processing methods to handle time series data. Together, SGN and SGN-TS provide the foundation for SGNL, a matched-filtering gravitational-wave search pipeline, and are being adopted by multiple projects across the low-latency gravitational-wave data analysis infrastructure as an extensible and maintainable framework for future gravitational-wave observations.
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astro-ph.IM 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
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SGNAX: a unified matched-filter and excess-power pipeline for gravitational-wave detector characterization
SGNAX unifies snax and omicron in one Python-native pipeline and reproduces production trigger populations while exposing a low-frequency SNR amplitude error in snax.