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Record W1966898222 · doi:10.1088/2041-8205/782/2/l24

FIRST RESULTS FROM THE DRAGONFLY TELEPHOTO ARRAY: THE APPARENT LACK OF A STELLAR HALO IN THE MASSIVE SPIRAL GALAXY M101

2014· article· en· W1966898222 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal Letters · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSurface brightnessBulgeSpiral galaxyHaloGalaxyMilky WayRADIUSStellar massDark matter halo

Abstract

fetched live from OpenAlex

We use a new telescope concept, the Dragonfly Telephoto Array, to study the low surface brightness outskirts of the spiral galaxy M101. The radial surface brightness profile is measured down to mu_g ~ 32 mag/arcsec^2, a depth that approaches the sensitivity of star count studies in the Local Group. We convert surface brightness to surface mass density using the radial g-r color profile. The mass density profile shows no significant upturn at large radius and is well-approximated by a simple bulge + disk model out to R = 70 kpc, corresponding to 18 disk scale lengths. Fitting a bulge + disk + halo model we find that the best-fitting halo mass M_halo ~ 1.7 x 10^8 M_sun. The total stellar mass of M101 is M_tot,* ~ 5.3 x 10^10 Msun, and we infer that the halo mass fraction f_halo = M_halo / M_tot,* ~ 0.003. This mass fraction is lower than that of the Milky Way (f_halo ~ 0.02) and M31 (f_halo ~ 0.04). All three galaxies fall below the f_halo - M_tot,* relation predicted by recent cosmological simulations that trace the light of disrupted satellites, with M101's halo mass a factor of ~10 below the median expectation. However, the predicted scatter in this relation is large, and more galaxies are needed to better quantify this possible tension with galaxy formation models. Dragonfly is well suited for this project: as integrated-light surface brightness is independent of distance, large numbers of galaxies can be studied in a uniform way.

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)0.001
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 score0.330
Threshold uncertainty score0.526

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.213
Teacher spread0.200 · 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

Citations122
Published2014
Admission routes1
Has abstractyes

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