{
  "abstract": "Large spectroscopic surveys require robust pipelines capable of inferring stellar parameters over a wide range of the Hertzsprung-Russell (HR) diagram from data of varying quality. SDSS-V is one such survey, where the data from the lower-resolution, optical BOSS spectrograph will provide a large dataset covering a wide range of Galactic stellar populations. To better analyze these data, we present BOSS-CLAM, a generative, forward modeling pipeline for inferring effective temperature ($T_\\mathrm{eff}$), surface gravity ($\\log g$), metallicity ($[\\mathrm{Fe/H}]$), and $α-$abundance ($[α/\\mathrm{M}]$) from continuum-normalized BOSS spectra. BOSS-CLAM maps stellar labels to Non-negative Matrix Factorization (NMF) basis vector weights via a polynomial mapping jointly optimized with the spectral decomposition, which provides a more flexible framework for working with the lower-resolution BOSS data. Additionally, training labels are drawn from four complementary sources (ASPCAP, BOSS-MINESweeper, wide binaries, and a hot star validation sample), which enables coverage from cool M dwarfs through hot OB stars, and across a wide range of metallicity. We infer parameters for 1,708,214 BOSS spectra, with a recommended clean catalog of 915,514 sources. Validation against open and globular clusters demonstrates homogeneous, accurate abundances across a wide range of metallicity. Wide binary tests yield abundance uncertainties of $σ_{[\\mathrm{Fe/H}]} \\approx 0.15$ dex and $σ_{[α/\\mathrm{M}]} \\approx 0.06$ dex at SNR = 10. Finally, we demonstrate that the BOSS-CLAM catalog recovers known chemical structure of the Milky Way disk and is well-suited for Galactic archaeology, chemical tagging, and stellar population modeling. The pipeline, trained model, and catalog are publicly released as part of SDSS-V DR20.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2607.22822",
  "author_total": 16,
  "authors": [
    {
      "name": "Ilija Medan"
    },
    {
      "name": "Andrew R. Casey"
    },
    {
      "name": "Alexander P. Ji"
    },
    {
      "name": "Jonah M. Otto"
    },
    {
      "name": "Kayvon Sharifi"
    },
    {
      "name": "Zachary Way"
    },
    {
      "name": "Madeleine McKenzie"
    },
    {
      "name": "Natalie R. Myers"
    },
    {
      "name": "Keivan G. Stassun"
    },
    {
      "name": "Peter J. Smith"
    },
    {
      "name": "Andrew Tkachenko"
    },
    {
      "name": "Vedant Chandra"
    },
    {
      "name": "Michael R. Blanton"
    },
    {
      "name": "Peter M. Frinchaboy"
    },
    {
      "name": "Guy S. Stringfellow"
    },
    {
      "name": "Sean Morrison"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/6a7gb07qbecg0.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2607.22822",
  "fulltext_url": null,
  "id": "6a7gb07qbecg0",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2607.22822",
  "language": null,
  "licence": "CC-BY-NC-ND-4.0",
  "licence_label": "CC BY-NC-ND 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "astro-ph.GA"
    ],
    [
      "arxiv",
      "astro-ph.IM"
    ],
    [
      "arxiv",
      "astro-ph.SR"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://arxiv.org/pdf/2607.22822",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-08",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/6a7gb07qbecg0.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:20:12Z",
      "native_id": "2607.22822",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2607.22822"
    }
  ],
  "subjects": [
    {
      "field": "astronomy",
      "origin": "arxiv:astro-ph.GA",
      "subfield": "galaxies"
    },
    {
      "field": "astronomy",
      "origin": "arxiv:astro-ph.IM",
      "subfield": "instrumentation-methods"
    },
    {
      "field": "astronomy",
      "origin": "arxiv:astro-ph.SR",
      "subfield": "stellar"
    }
  ],
  "title": "BOSS-CLAM: Utilizing a Constrained Linear Absorption Model to Infer Stellar Parameters from BOSS Spectra",
  "title_text": "BOSS-CLAM: Utilizing a Constrained Linear Absorption Model to Infer Stellar Parameters from BOSS Spectra",
  "type": "preprint",
  "updated_at": "2026-10-30T12:20:12Z",
  "url": "https://research.draconitic.com/paper/6a7gb07qbecg0",
  "venue": "arXiv",
  "versions": []
}