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Record W4293138498 · doi:10.3847/1538-4357/aca5f8

DESI Observations of the Andromeda Galaxy: Revealing the Immigration History of Our Nearest Neighbor

2023· article· en· W4293138498 on OpenAlexafffund
Arjun Dey, Joan Najita, S. E. Koposov, J. Josephy-Zack, Gabriel Maxemin, Eric F. Bell, C. Poppett, Ekta Patel, Leandro Beraldo e Silva, Anand Raichoor, David J. Schlegel, Dustin Lang, Aaron Meisner, Adam D. Myers, J. Aguilar, S. P. Ahlen, Carlos Allende Prieto, D. Brooks, Andrew P. Cooper, Kyle Dawson, Axel de la Macorra, P. Doel, Andreu Font-Ribera, J. García-Bellido, Satya Gontcho A Gontcho, J. Guy, K. Honscheid, R. Kehoe, Theodore Kisner, Anthony Kremin, Martin Landriau, L. Le Guillou, M. E. Levi, Ting S. Li, R. Miquel, John Moustakas, Jundan Nie, N. Palanque‐Delabrouille, Francisco Prada, Edward F. Schlafly, R. M. Sharples, G. Tarlé, Yuan-Sen Ting, Luke Tyas, Monica Valluri, Risa H. Wechsler, Hu Zou

Bibliographic record

VenueThe Astrophysical Journal · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversity of TorontoPerimeter InstituteUniversity of Waterloo
FundersDivision of Astronomical SciencesScience and Technology Facilities CouncilCanadian Space AgencyHigh Energy PhysicsSmithsonian Astrophysical ObservatoryRadcliffe Institute for Advanced Study, Harvard UniversityOffice of ScienceCommissariat à l'Énergie Atomique et aux Énergies AlternativesAspen Center for PhysicsHarvard UniversitySimons FoundationNational Science FoundationEuropean Space AgencyNational Aeronautics and Space AdministrationNuclear Safety and Security CommissionGordon and Betty Moore FoundationU.S. Department of EnergySmithsonian InstitutionConsejo Nacional de Ciencia y TecnologíaMinisterio de Ciencia e InnovaciónJohn Simon Guggenheim Memorial Foundation
KeywordsPhysicsAndromedaAndromeda GalaxyAstronomyAstrophysicsGalaxyk-nearest neighbors algorithmMilky WayArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract We present Dark Energy Spectroscopic Instrument (DESI) observations of the inner halo of M31, which reveal the kinematics of a recent merger—a galactic immigration event—in exquisite detail. Of the 11,416 sources studied in 3.75 hr of on-sky exposure time, 7438 are M31 sources with well-measured radial velocities. The observations reveal intricate coherent kinematic structure in the positions and velocities of individual stars: streams, wedges, and chevrons. While hints of coherent structures have been previously detected in M31, this is the first time they have been seen with such detail and clarity in a galaxy beyond the Milky Way. We find clear kinematic evidence for shell structures in the Giant Stellar Stream, the Northeast Shelf, and Western Shelf regions. The kinematics are remarkably similar to the predictions of dynamical models constructed to explain the spatial morphology of the inner halo. The results are consistent with the interpretation that much of the substructure in the inner halo of M31 is produced by a single galactic immigration event 1–2 Gyr ago. Significant numbers of metal-rich stars ([Fe/H] > − 0.5) are present in all of the detected substructures, suggesting that the immigrating galaxy had an extended star formation history. We also investigate the ability of the shells and Giant Stellar Stream to constrain the gravitational potential of M31, and estimate the mass within a projected radius of 125 kpc to be log 10 M NFW ( < 125 kpc ) / M ⊙ = 11.80 − 0.10 + 0.12 . The results herald a new era in our ability to study stars on a galactic scale and the immigration histories of galaxies.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.033
GPT teacher head0.235
Teacher spread0.201 · 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 designObservational
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

Citations53
Published2023
Admission routes2
Has abstractyes

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