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The impact of mergers on relaxed X-ray clusters – I. Dynamical evolution and emergent transient structures

2006· article· en· W2068618869 on OpenAlexafffund
Gregory B. Poole, Mark A. Fardal, Arif Babul, Ian G. McCarthy, Thomas Quinn, James Wadsley

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGamma-ray bursts and supernovae
Canadian institutionsMcMaster UniversityUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaDurham UniversityNational Aeronautics and Space AdministrationNational Science Foundation
KeywordsPhysicsAstrophysicsCluster (spacecraft)CentroidSurface brightnessGalaxy clusterGalaxyGeometry

Abstract

fetched live from OpenAlex

We report on the analysis of a suite of smoothed particle hydrodynamics simulations (incorporating cooling and star formation) of mergers involving idealized X-ray clusters whose initial conditions resemble relaxed clusters with cool compact cores observed by Chandra and XMM. The simulations sample the most-interesting, theoretically plausible, range of impact parameters and progenitor mass ratios. We find that all mergers evolve via a common progression. We illustrate this progression in the projected gas density, X-ray surface brightness, Sunyaev–Zel'dovich, temperature, and gas-entropy maps. Several different classes of transient ‘cold front’ like features can arise over the course of a merger. Each class is distinguished by a distinct morphological signature and physical cause. We find that all these classes are present in Chandra and XMM observations of merging systems and propose a naming scheme for these features: ‘comet-like’ tails, bridges, plumes, streams and edges. In none of the cases considered do the initial cool compact cores of the primary and the secondary get destroyed during the course of the mergers. Instead, the two remnant cores eventually combine to form a new core that, depending on the final mass of the remnant, can have a greater cooling efficiency than either of its progenitors. We quantify the evolving morphology of our mergers using centroid variance, power ratios and offset between the X-ray and the projected mass maps. We find that the centroid variance best captures the dynamical state of the cluster. It also provides an excellent indicator of how far the system is from virial and hydrostatic equilibrium. Placing the system at z= 0.1, we find that all easily identified observable traces of the secondary disappear from a simulated 50-ks Chandra image following the second pericentric passage. The system, however, takes an additional ∼2 Gyr to relax and virialize. Observationally, the only reliable indicator of a system in this state is the smoothness of its X-ray surface brightness isophotes, not temperature fluctuations. Temperature fluctuations at the level of ΔT/T∼ 20 per cent, can persist in the final systems well past the point of virialization, suggesting that the existence of temperature fluctuations, in and of themselves, does not necessarily indicate a disturbed or unrelaxed system.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.586
Threshold uncertainty score0.575

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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 head0.005
GPT teacher head0.207
Teacher spread0.203 · 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 designSimulation or modeling
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

Citations309
Published2006
Admission routes2
Has abstractyes

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