Rotating Globular Clusters

Bianchini, P.; Varri, Anna Lisa; Bertin, G.; Zocchi, Alice

doi:10.1088/0004-637x/772/1/67

Cited by 112 publications

(200 citation statements)

References 68 publications

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“…The position of a cluster in the diagram is often compared to the relation between V rot max /σ 0 and expected for oblate rotators viewed "edge-on" (Binney 2005;Cappellari et al 2007). Assuming an average ellipticity of ∼ 0.9 for M13 (see above), and estimating V rot max /σ 0 0.4 ± 0.1 from the values of Table 2 for the whole sample (and bearing in mind inclination effects), we find that M13 is in good agreement with the expected relation for an isotropic oblate rotator (comparing for example with figures from Bianchini et al 2013;Kacharov et al 2014). This suggests that the flattening is consistent with being caused by internal rotation.…”

Section: Global Rotation Of M13supporting

confidence: 81%

“…Note that the White & Shawl (1987) work is based on optical data, while Chen & Chen (2010) is based on the spatial distribution of 2MASS point sources 6 Kadla et al (1976) also suggest that the cluster may be slightly prolate in the very central parts (radii less than 0.7 arcmin), but these results should be considered uncertain due to the small number of stars contributing to the light in these regions (see discussions in Lupton et al 1987). 7 For detailed examples of the connection between rotation and flattening in the GCs ω Cen and 47 Tuc, see Bianchini et al (2013).…”

Section: Global Rotation Of M13mentioning

confidence: 99%

“…A simple and commonly used tool to estimate the importance of rotation in shaping the morphology of GCs is to place them in the V rot max /σ 0 vs. diagram, where V rot max /σ 0 is the ratio of the observed maximum of the line-of-sight rotation profile to the central line-of-sight velocity dispersion and is the (global) ellipticity. We note that this approach is no substitute to detailed dynamical modelling, because it only compares global quantities while rotation and ellipticity can vary significantly with radius as the anisotropy parameter changes, and the position of a cluster in the V rot max /σ 0 vs. diagram is also sensitive to inclination effects (see discussion in Bianchini et al 2013). The position of a cluster in the diagram is often compared to the relation between V rot max /σ 0 and expected for oblate rotators viewed "edge-on" (Binney 2005;Cappellari et al 2007).…”

Section: Global Rotation Of M13mentioning

confidence: 99%

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Differences in the rotational properties of multiple stellar populations in M13: a faster rotation for the ‘extreme’ chemical subpopulation

Cordero

Hénault-Brunet

Pilachowski

et al. 2016

Mon. Not. R. Astron. Soc.

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We use radial velocities from spectra of giants obtained with the WIYN telescope, coupled with existing chemical abundance measurements of Na and O for the same stars, to probe the presence of kinematic differences among the multiple populations of the globular cluster (GC) M13. To characterise the kinematics of various chemical subsamples, we introduce a method using Bayesian inference along with an MCMC algorithm to fit a six-parameter kinematic model (including rotation) to these subsamples. We find that the so-called "extreme" population (Na-enhanced and extremely O-depleted) exhibits faster rotation around the centre of the cluster than the other cluster stars, in particular when compared to the dominant "intermediate" population (moderately Na-enhanced and O-depleted). The most likely difference between the rotational amplitude of this extreme population and that of the intermediate population is found to be ∼ 4 km s −1 , with a 98.4% probability that the rotational amplitude of the extreme population is larger than that of the intermediate population. We argue that the observed difference in rotational amplitudes, obtained when splitting subsamples according to their chemistry, is not a product of the long-term dynamical evolution of the cluster, but more likely a surviving feature imprinted early in the formation history of this GC and its multiple populations. We also find an agreement (within uncertainties) in the inferred position angle of the rotation axis of the different subpopulations considered. We discuss the constraints that these results may place on various formation scenarios.

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Section: Global Rotation Of M13supporting

confidence: 81%

Section: Global Rotation Of M13mentioning

confidence: 99%

Section: Global Rotation Of M13mentioning

confidence: 99%

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Differences in the rotational properties of multiple stellar populations in M13: a faster rotation for the ‘extreme’ chemical subpopulation

Cordero

Hénault-Brunet

Pilachowski

et al. 2016

Mon. Not. R. Astron. Soc.

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“…1 The simulations have no central intermediate mass black hole and internal rotation is not considered (note however that internal rotation is observed in several GCs, e.g. Bianchini et al 2013;Fabricius et al 2014;Kacharov et al 2014;Lardo et al 2015). Five different independent realisations of the same simulation are available, and we will use them to analyse stochastic effects.…”

Section: Simulations Of Globular Clustersmentioning

confidence: 99%

Understanding the central kinematics of globular clusters with simulated integrated-light IFU observations

Bianchini

Norris

Ven

et al. 2015

Mon. Not. R. Astron. Soc.

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The detection of intermediate mass black holes in the centres of globular clusters is highly controversial, as complementary observational methods often deliver significantly different results. In order to understand these discrepancies, we develop a procedure to simulate integral field unit (IFU) observations of globular clusters: Simulating IFU Star Cluster Observations (SISCO). The input of our software are realistic dynamical models of globular clusters that are then converted in a spectral data cube. We apply SISCO to Monte Carlo cluster simulations from Downing et al. (2010), with a realistic number of stars and concentrations. Using independent realisations of a given simulation we are able to quantify the stochasticity intrinsic to the problem of observing a partially resolved stellar population with integrated-light spectroscopy. We show that the luminosity-weighted IFU observations can be strongly biased by the presence of a few bright stars that introduce a scatter in the velocity dispersion measurements up to 40% around the expected value, preventing any sound assessment of the central kinematic and a sensible interpretation of the presence/absence of an intermediate mass black hole. Moreover, we illustrate that, in our mock IFU observations, the average kinematic tracer has a mass of 0.75 M , only slightly lower than the mass of the typical stars examined in studies of resolved line-of-sight velocities of giant stars. Finally, in order to recover unbiased kinematic measurements we test different masking techniques that allow us to remove the spaxels dominated by bright stars, bringing the scatter down to a level of only a few percent. The application of SISCO will allow to investigate state-of-the-art simulations as realistic observations.

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“…Besides an elongated shape owing to residual pressure-tensor anisotropy that was left over by the merger or lingering rotation, in the case of off-axis mergers, the clues are probably subtle and difficult to parameterize. Moreover, deviations from spherical symmetry in clusters are actually observed (White & Shawl 1987;Chen & Chen 2010) but there is currently limited consensus as to their explanation because rotation and tidal effects may result in elongated profiles without the need for a merger (Davoust 1986;Bertin & Varri 2008;Varri & Bertin 2009, 2012Bianchini et al 2013;Vesperini et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Merged or monolithic? Using machine-learning to reconstruct the dynamical history of simulated star clusters

Pasquato

Chung

2016

A&A

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Context. Machine-learning (ML) solves problems by learning patterns from data with limited or no human guidance. In astronomy, ML is mainly applied to large observational datasets, e.g. for morphological galaxy classification. Aims. We apply ML to gravitational N-body simulations of star clusters that are either formed by merging two progenitors or evolved in isolation, planning to later identify globular clusters (GCs) that may have a history of merging from observational data. Methods. We create mock-observations from simulated GCs, from which we measure a set of parameters (also called features in the machine-learning field). After carrying out dimensionality reduction on the feature space, the resulting datapoints are fed in to various classification algorithms. Using repeated random subsampling validation, we check whether the groups identified by the algorithms correspond to the underlying physical distinction between mergers and monolithically evolved simulations.Results. The three algorithms we considered (C5.0 trees, k-nearest neighbour, and support-vector machines) all achieve a test misclassification rate of about 10% without parameter tuning, with support-vector machines slightly outperforming the others. The first principal component of feature space correlates with cluster concentration. If we exclude it from the regression, the performance of the algorithms is only slightly reduced.

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Rotating Globular Clusters

Cited by 112 publications

References 68 publications

Differences in the rotational properties of multiple stellar populations in M13: a faster rotation for the ‘extreme’ chemical subpopulation

Differences in the rotational properties of multiple stellar populations in M13: a faster rotation for the ‘extreme’ chemical subpopulation

Understanding the central kinematics of globular clusters with simulated integrated-light IFU observations

Merged or monolithic? Using machine-learning to reconstruct the dynamical history of simulated star clusters

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