{
  "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.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2607.03575",
  "author_total": 14,
  "authors": [
    {
      "name": "Yun-Jing Huang"
    },
    {
      "name": "Olivia Godwin"
    },
    {
      "name": "Chad Hanna"
    },
    {
      "name": "James Kennington"
    },
    {
      "name": "Jameson Rollins"
    },
    {
      "name": "Max Melching"
    },
    {
      "name": "Nathanael E Sovitzky"
    },
    {
      "name": "Aaron Viets"
    },
    {
      "name": "Madeline Wade"
    },
    {
      "name": "Zach Yarbrough"
    },
    {
      "name": "Yu-Kuang Chu"
    },
    {
      "name": "William Wyatt Phillips"
    },
    {
      "name": "Surabhi Sachdev"
    },
    {
      "name": "Rhiannon Udall"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/85e2mpdqfdrnb.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2607.03575",
  "fulltext_url": null,
  "id": "85e2mpdqfdrnb",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2607.03575",
  "language": null,
  "licence": "LicenseRef-arXiv-nonexclusive-1.0",
  "licence_label": "arXiv licence",
  "licence_source": "article",
  "licence_url": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "astro-ph.IM"
    ],
    [
      "arxiv",
      "gr-qc"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://arxiv.org/pdf/2607.03575",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-14",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/85e2mpdqfdrnb.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:21:25Z",
      "native_id": "2607.03575",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2607.03575"
    }
  ],
  "subjects": [
    {
      "field": "astronomy",
      "origin": "arxiv:astro-ph.IM",
      "subfield": "instrumentation-methods"
    },
    {
      "field": "physics",
      "origin": "arxiv:gr-qc",
      "subfield": "gravitation"
    }
  ],
  "title": "SGN: A python framework for stream-processing pipelines",
  "title_text": "SGN: A python framework for stream-processing pipelines",
  "type": "preprint",
  "updated_at": "2026-10-30T12:21:25Z",
  "url": "https://research.draconitic.com/paper/85e2mpdqfdrnb",
  "venue": "arXiv",
  "versions": []
}