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Record W2141385023 · doi:10.1093/mnras/sts076

The Millennium Run Observatory: first light

2012· article· en· W2141385023 on OpenAlexaff
Roderik Overzier, Gerard Lemson, Raúl E. Angulo, E. Bertin, J. Blaizot, Bruno Henriques, Gabriel-Dominique Marleau, Simon D. M. White

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGalaxies: Formation, Evolution, Phenomena
Canadian institutionsMcGill University
Fundersnot available
KeywordsPhysicsObservatoryGalaxyAstrophysicsGalaxy formation and evolutionDark matterAstronomyVirtual observatory

Abstract

fetched live from OpenAlex

Simulations of galaxy evolution aim to capture our current understanding as well as to make predictions for testing by future experiments. Simulations and observations are often compared in an indirect fashion: physical quantities are estimated from the observational data and compared to models. However, many applications can benefit from a more direct approach, where the observing process is also simulated, so that the models are seen fully from the observer’s perspective. To facilitate this, we have developed the Millennium Run Observatory (MRObs), a theoretical virtual observatory which uses virtual telescopes to ‘observe’ semi-analytic galaxy formation simulations based on the suite of Millennium Run (MR) dark matter simulations. The MRObs produces data that can be processed and analysed using the standard observational software packages developed for real observations. At present, we produce images in 40 filters covering the rest-frame ultraviolet to infrared for two stellar population synthesis models, for three different models of absorption by the intergalactic medium, and in two cosmologies (Wilkinson Microwave Anisotropy Probe year 1 and 7). Galaxy distributions for a large number of mock light cones can be ‘observed’ using models of major ground- and space-based telescopes. The data include light cone catalogues linked to structural properties of galaxies, pre-observation model images, mock telescope images and Source Extractor products that can all be traced back to the higher level dark matter, semi-analytic galaxy and light cone catalogues available in the MR data base. Here, we describe our methods and announce a first public release of simulated observations that emulate a large number of extragalactic surveys [e.g. Sloan Digital Sky Survey, Canada-France-Hawaii Telescope Legacy Survey (CFHT-LS), Great Observatories Origins Deep Survey (GOODS), GOODS/Early Release Science (ERS), Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey (CANDELS) and Hubble Ultra Deep Field (HUDF)]. The MRObs browser, an online tool, further facilitates exploration of the simulated data. We demonstrate the benefits of a direct approach through a number of example applications: (1) deep galaxy number counts in the CANDELS survey; (2) observed properties of galaxy clusters; (3) structural parameters of galaxies; and (4) identification of dropout galaxies. The MRObs enhances the range of questions that can be asked of semi-analytic models, allowing observers and theorists to work towards each other with virtually complete freedom of where to meet.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.002

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 head0.188
Teacher spread0.180 · 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

Citations60
Published2012
Admission routes1
Has abstractyes

Explore more

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