{
  "abstract": "Box least squares (BLS) is a robust but computationally expensive method to search for transits in photometric data. Reducing its computational cost is especially relevant when scanning large datasets or conducting transit injection and recovery simulations. Greatly Expedited Revamp of BLS (GERBLS) is a software algorithm designed to substantially speed up a BLS search. It offers O ( n log n ) runtime scaling as opposed to O ( n ² ) for native brute-force BLS. GERBLS is based on a divide-and-conquer FFA that minimizes mathematically redundant operations during phase-folding. It can automatically downsample the input data at longer tested periods and yield a BLS period resolution that is close to optimal for transiting planets on circular orbits. GERBLS typically outperforms an efficient CPU-based brute-force BLS implementation by at least 10–100 times in total runtime, with a relative speedup of 600× demonstrated for a dataset consisting of 10 ⁵ observations.",
  "abstract_shown": true,
  "affiliations": [
    "Penn State",
    "Department of Astrophysical Sciences, Princeton University, 4 Ivy Lane, Princeton, NJ 08544, USA",
    "University of Florida"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 5,
  "authors": [
    {
      "affs": [
        0,
        1
      ],
      "name": "Kristo Ment",
      "orcid": "0000-0001-5847-9147"
    },
    {
      "affs": [
        0
      ],
      "name": "Eric B. Ford",
      "orcid": "0000-0001-6545-639X"
    },
    {
      "affs": [
        0
      ],
      "name": "Suvrath Mahadevan",
      "orcid": "0000-0001-9596-7983"
    },
    {
      "affs": [
        0
      ],
      "name": "Rachel B. Fernandes",
      "orcid": "0000-0002-3853-7327"
    },
    {
      "affs": [
        0,
        2
      ],
      "name": "Andrew Hotnisky",
      "orcid": "0009-0000-1825-4306"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/3jgenpm6e6r17.bib",
  "cited_by": 0,
  "doi": "10.3847/1538-3881/aea0c8",
  "fulltext_url": null,
  "id": "3jgenpm6e6r17",
  "issns": [
    "0004-6256",
    "1538-3881"
  ],
  "landing_url": "https://iopscience.iop.org/article/10.3847/1538-3881/aea0c8",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "3103|Stellar, planetary, and galactic studies"
    ]
  ],
  "openalex": "W7220674479",
  "pdf_url": "https://iopscience.iop.org/article/10.3847/1538-3881/aea0c8/pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-06",
  "publisher": "American Astronomical Society",
  "ris": "https://research.draconitic.com/paper/3jgenpm6e6r17.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:18:14Z",
      "native_id": "10.3847/1538-3881/aea0c8",
      "source": "crossref",
      "url": "https://iopscience.iop.org/article/10.3847/1538-3881/aea0c8"
    }
  ],
  "subjects": [
    {
      "field": "astronomy",
      "origin": "openalex:3103|Stellar, planetary, and galactic studies",
      "subfield": "stellar"
    }
  ],
  "title": "GERBLS—A Rapid Box Least Squares Algorithm for Exoplanet Detection That Scales Well for Large Datasets",
  "title_text": "GERBLS—A Rapid Box Least Squares Algorithm for Exoplanet Detection That Scales Well for Large Datasets",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:18:14Z",
  "url": "https://research.draconitic.com/paper/3jgenpm6e6r17",
  "venue": "The Astronomical Journal",
  "versions": []
}