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A comparison of weak-lensing masses and X-ray properties of galaxy clusters

2007· article· en· W2004199221 on OpenAlexaffabout
Henk Hoekstra

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsPhysicsAstrophysicsWeak gravitational lensingVelocity dispersionCluster (spacecraft)GalaxyRedshiftGalaxy clusterPower lawPhotometric redshiftAstronomyStatistics

Abstract

fetched live from OpenAlex

We present measurements of the masses of 20 X-ray luminous clusters of galaxies at intermediate redshifts, determined from a weak lensing analysis of deep archival R-band data obtained using the Canada-France-Hawaii-Telescope. Compared to previous work, our analysis accounts for a number of effects that are typically ignored, but can lead to small biases, or incorrect error estimates. We derive masses that are essentially model independent and find that they agree well with measurements of the velocity dispersion of cluster galaxies and with the results of X-ray studies. Assuming a power law between the lensing mass and the X-ray temperature, M_2500 T^alpha, we find a best fit slope of alpha=1.34^{+0.30}_{-0.28}. This slope agrees with self-similar cluster models and studies based on X-ray data alone. For a cluster with a temperature of kT=5keV we obtain a mass M_{2500}=(1.4+-0.2)\times 10^{14}h^{-1}Msun in fair agreement with recent Chandra and XMM studies.

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 score0.024
Threshold uncertainty score0.472

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 head0.013
GPT teacher head0.221
Teacher spread0.208 · 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

Citations192
Published2007
Admission routes2
Has abstractyes

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