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Record W2909449638 · doi:10.3847/2041-8213/ab0e8c

Still Missing Dark Matter: KCWI High-resolution Stellar Kinematics of NGC1052-DF2

2019· article· en· W2909449638 on OpenAlexaff
Shany Danieli, Pieter van Dokkum, Charlie Conroy, Roberto Abraham, Aaron J. Romanowsky

Bibliographic record

VenueThe Astrophysical Journal Letters · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsCanadian Institute for Theoretical AstrophysicsUniversity of Toronto
Fundersnot available
KeywordsPhysicsGlobular clusterVelocity dispersionAstrophysicsGalaxyStellar kinematicsRADIUSStellar massDark matter haloDark matterStarsHaloStar formationMilky Way

Abstract

fetched live from OpenAlex

Abstract The velocity dispersion of the ultra diffuse galaxy NGC1052-DF2 was found to be km s −1 , much lower than expected from the stellar mass–halo mass relation and nearly identical to the expected value from the stellar mass alone. This result was based on the radial velocities of 10 luminous globular clusters that were assumed to be associated with the galaxy. A more precise measurement is possible from high-resolution spectroscopy of the diffuse stellar light. Here we present an integrated spectrum of the diffuse light of NGC1052-DF2 obtained with the Keck Cosmic Web Imager (KCWI), with an instrumental resolution of σ instr ≈ 12 km s −1 . The systemic velocity of the galaxy is v sys = 1805 ± 1.1 km s −1 , in very good agreement with the average velocity of the globular clusters ( km s −1 ). There is no evidence for rotation within the KCWI field of view. We find a stellar velocity dispersion of km s −1 , consistent with the dispersion that was derived from the globular clusters. The implied dynamical mass within the half-light radius r 1/2 = 2.7 kpc is M dyn = (1.3 ± 0.8) × 10 8 M ⊙ , similar to the stellar mass within that radius ( M stars = (1.0 ± 0.2) × 10 8 M ⊙ ). With this confirmation of the low velocity dispersion of NGC1052-DF2, the most urgent question is whether this “missing dark matter problem” is unique to this galaxy or applies more widely.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.469
Threshold uncertainty score0.728

Codex and Gemma teacher scores by category

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

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 head0.006
GPT teacher head0.196
Teacher spread0.191 · 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 teacher head, 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

Citations147
Published2019
Admission routes1
Has abstractyes

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