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Record W2011490256 · doi:10.1086/523619

The Milky Way Tomography with SDSS. I. Stellar Number Density Distribution

2008· article· en· W2011490256 on OpenAlexaff
Mario Jurić, Željko Ivezić, Alyson Brooks, Robert H. Lupton, David J. Schlegel, Douglas P. Finkbeiner, Nikhil Padmanabhan, Nicholas A. Bond, Branimir Sesar, Constance M. Rockosi, G. R. Knapp, James E. Gunn, T. Sumi, Donald P. Schneider, John C. Barentine, H. Brewington, J. Brinkmann, M. Fukugita, Michael Harvanek, S. J. Kleinman, J. Krzesiński, Dan Long, Eric H. Neilsen, A. Nitta, Stephanie A. Snedden, Donald G. York

Bibliographic record

VenueThe Astrophysical Journal · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsApache (Canada)
Fundersnot available
KeywordsPhysicsAstrophysicsMilky WayHaloSkyGalaxyThick diskStar countDwarf galaxySurface brightnessStarsAstronomy

Abstract

fetched live from OpenAlex

Using the photometric parallax method we estimate the distances to ~48 million stars detected by the Sloan Digital Sky Survey (SDSS) and map their three-dimensional number density distribution in the Galaxy. The currently available data sample the distance range from 100 pc to 20 kpc and cover 6500 deg 2 of sky, mostly at high Galactic latitudes (|b| > 25). These stellar number density maps allow an investigation of the Galactic structure with no a priori assumptions about the functional form of its components. The data show strong evidence for a Galaxy consisting of an oblate halo, a disk component, and a number of localized overdensities. The number density distribution of stars as traced by M dwarfs in the solar neighborhood ( D < 2 kpc) is well fit by two exponential disks (the thin and thick disk) with scale heights and lengths, bias corrected for an assumed 35% binary fraction, of H 1 = 300 pc and L 1 = 2600 pc, and H 2 = 900 pc and L 2 = 3600 pc, and local thick-to-thin disk density normalization ρ thick ( R ☉ )/ρ thin ( R ☉ ) = 12% . We use the stars near main-sequence turnoff to measure the shape of the Galactic halo. We find a strong preference for oblate halo models, with best-fit axis ratio c / a = 0.64, ρ H ∝ r −2.8 power-law profile, and the local halo-to-thin disk normalization of 0.5%. Based on a series of Monte Carlo simulations, we estimate the errors of derived model parameters not to be larger than ~20% for the disk scales and ~10% for the density normalization, with largest contributions to error coming from the uncertainty in calibration of the photometric parallax relation and poorly constrained binary fraction. While generally consistent with the above model, the measured density distribution shows a number of statistically significant localized deviations. In addition to known features, such as the Monoceros stream, we detect two overdensities in the thick disk region at cylindrical galactocentric radii and heights ( R,Z ) ∼ (6.5,1.5) kpc and ( R,Z ) ∼ (9.5,0.8) kpc and a remarkable density enhancement in the halo covering over 1000 deg 2 of sky toward the constellation of Virgo, at distances of ~6-20 kpc. Compared to counts in a region symmetric with respect to the l = 0° line and with the same Galactic latitude, the Virgo overdensity is responsible for a factor of 2 number density excess and may be a nearby tidal stream or a low-surface brightness dwarf galaxy merging with the Milky Way. The u − g color distribution of stars associated with it implies metallicity lower than that of thick disk stars and consistent with the halo metallicity distribution. After removal of the resolved overdensities, the remaining data are consistent with a smooth density distribution; we detect no evidence of further unresolved clumpy substructure at scales ranging from ~50 pc in the disk to ~1-2 kpc in the halo.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.007
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0150.021

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 head0.008
GPT teacher head0.201
Teacher spread0.193 · 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

Citations1,326
Published2008
Admission routes1
Has abstractyes

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