{
  "abstract": "We present the data reduction and transient detection pipeline for the Wide-field Infrared Transient Explorer (WINTER) surveyor and report its on-sky performance. The WINTER camera utilizes cost-effective InGaAs sensors as alternatives to traditional IR sensors, and is mounted on a dedicated 1-m robotic telescope at Palomar Observatory. The WINTER camera has six detectors producing a combined field-of-view of 1.2 sq. deg. equipped with y, J, and shortened-H bands. WINTER saw first light in June 2023 and has been operating robotically since. The WINTER data processing pipeline ($\\texttt{winterdrp}$) has been implemented within the broader framework $\\texttt{mirar}$: a modular, open-source $\\texttt{python}$ package developed for realtime processing of images from time-domain surveys. $\\texttt{winterdrp}$ performs end-to-end data processing implementing data reduction and image subtraction to go from raw dithered WINTER images to transient alerts in the $\\texttt{avro}$ format, which are then sent to $\\texttt{SkyPortal}$ for vetting and follow-up. During a year of observations in 2024, WINTER achieved J-band median 5-$σ$ depths ranging from $18.1-18.8$ mag (AB) on its six detectors in 960 second integrations as part of its survey, with an astrometric accuracy of $\\approx0.2$ arcsec (a fifth of a pixel) and a detector-performance limited photometric accuracy ranging from $\\approx0.09-0.18$ mag for its six detectors. We present early science results from WINTER, which include the identification of a stellar merger in M31, dust-enshrouded outbursting young stellar objects and classical novae in the Galactic plane, NIR followup of known supernovae, and multi-messenger follow-up of neutrinos, gravitational waves, fast X-ray transients and gamma-ray bursts.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.10675",
  "author_total": 21,
  "authors": [
    {
      "name": "Viraj Karambelkar"
    },
    {
      "name": "Robert Stein"
    },
    {
      "name": "Danielle Frostig"
    },
    {
      "name": "Saarah Hall"
    },
    {
      "name": "Mansi M. Kasliwal"
    },
    {
      "name": "Tomás Ahumada"
    },
    {
      "name": "Michael W. Coughlin"
    },
    {
      "name": "Thomas Culino"
    },
    {
      "name": "Kishalay De"
    },
    {
      "name": "Sulekha Kishore"
    },
    {
      "name": "Theophile Jegou du Laz"
    },
    {
      "name": "Nathan P. Lourie"
    },
    {
      "name": "Geoffrey Mo"
    },
    {
      "name": "Tanishk Mohan"
    },
    {
      "name": "Sam Rose"
    },
    {
      "name": "Benjamin R. Roulston"
    },
    {
      "name": "Aditya Pawan Saikia"
    },
    {
      "name": "Mallika Sheshadri"
    },
    {
      "name": "Robert A. Simcoe"
    },
    {
      "name": "Jamie Soon"
    },
    {
      "name": "Aswin Suresh"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/4mvq90gnv7wbt.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.10675",
  "fulltext_url": null,
  "id": "4mvq90gnv7wbt",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.10675",
  "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"
    ],
    [
      "openalex",
      "3105|Astronomy and Astrophysical Research"
    ]
  ],
  "openalex": "W7212252289",
  "pdf_url": "https://arxiv.org/pdf/2609.10675",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-09",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/4mvq90gnv7wbt.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:20:26Z",
      "native_id": "2609.10675",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.10675"
    }
  ],
  "subjects": [
    {
      "field": "astronomy",
      "origin": "arxiv:astro-ph.IM",
      "subfield": "instrumentation-methods"
    }
  ],
  "title": "A data processing pipeline for the WINTER near-infrared surveyor using the $\\texttt{mirar}$ framework",
  "title_text": "A data processing pipeline for the WINTER near-infrared surveyor using the mirar framework",
  "type": "preprint",
  "updated_at": "2026-10-30T12:20:26Z",
  "url": "https://research.draconitic.com/paper/4mvq90gnv7wbt",
  "venue": "arXiv",
  "versions": []
}