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Record W4414254829 · doi:10.3847/1538-4357/adf743

Precise Parameters for Two LISA Sources

2025· article· en· W4414254829 on OpenAlexfundno aff
Manuel Barrientos, Mukremin Kilic, Warren R. Brown, Fatma Ben Daya, Antoine Bédard, T. B. Littenberg, Thomas Kupfer, Snehalata Sahu

Bibliographic record

VenueThe Astrophysical Journal · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicParticle physics theoretical and experimental studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaNASA Exoplanet Science InstituteNational Aeronautics and Space AdministrationNuclear Safety and Security CommissionSpace Telescope Science InstituteSmithsonian InstitutionNational Science Foundation
KeywordsSpectrographInterferometryAmplitudeHubble space telescopeSpace Telescope Imaging SpectrographSIGNAL (programming language)Primary (astronomy)Astronomical interferometerParameter space

Abstract

fetched live from OpenAlex

Abstract We present precise parameters for two compact double white dwarf (DWD) binaries, SDSS J232230.20+050942.0 (J2322+0509) and SDSS J063449.92+380352.2 (J0634+3803), with orbital periods of 20 and 26.5 minutes, respectively. These systems will serve as verification sources for the Laser Interferometer Space Antenna (LISA). To significantly improve the electromagnetic (EM) constraints on these two systems and the LISA detectability predictions, we conducted spectroscopic follow-up observations using Hubble Space Telescope/Space Telescope Imaging Spectrograph, Keck I/LRIS, and Keck II/Echellette Spectrograph and Imager. Our analysis significantly improves the temperature, surface gravity, and mass constraints for both primary and secondary components in J2322+0509, as well as dynamical properties such as radial velocities and orbital periods in both systems. For J2322+0509, we derive an updated inclination of i = 25 − 3.0 + 4.5 deg, while for J0634+3803, we obtain i = 43 − 5.6 + 7.0 deg. We assess the detectability of these sources using LDASOFT. Incorporating EM priors on inclination significantly enhances the gravitational-wave signal recovery, reducing uncertainties in amplitude by a factor of 2–4 and shortening the detection time by up to a few months. Our results underscore the importance of multimessenger observations in characterizing DWD binaries and maximizing LISA’s early scientific capabilities.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.283
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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