14,083 research outputs found
Intracluster stellar population properties from N-body cosmological simulations -- I. Constraints at
We use a high resolution collisionless simulation of a Virgo--like cluster in
a CDM cosmology to determine the velocity and clustering properties of
the diffuse stellar component in the intracluster region at the present epoch.
The simulated cluster builds up hierarchically and tidal interactions between
member galaxies and the cluster potential produce a diffuse stellar component
free-flying in the intracluster medium. Here we adopt an empirical scheme to
identify tracers of the stellar component in the simulation and hence study its
properties. We find that at the intracluster stellar light is mostly
unrelaxed in velocity space and clustered in structures whose typical
clustering radii are about 50 kpc at R=400--500 kpc from the cluster center,
and predict the radial velocity distribution expected in spectroscopic
follow-up surveys. Finally, we compare the spatial clustering in the simulation
with the properties of the Virgo intracluster stellar population, as traced by
ongoing intracluster planetary nebulae surveys in Virgo. The preliminary
results indicate a substantial agreement with the observed clustering
properties of the diffuse stellar population in Virgo.Comment: 39 pages, 10 figures, 8 tables, in press on ApJ. Bad image quality
for some figures because resizing is neede
Local Subspace-Based Outlier Detection using Global Neighbourhoods
Outlier detection in high-dimensional data is a challenging yet important
task, as it has applications in, e.g., fraud detection and quality control.
State-of-the-art density-based algorithms perform well because they 1) take the
local neighbourhoods of data points into account and 2) consider feature
subspaces. In highly complex and high-dimensional data, however, existing
methods are likely to overlook important outliers because they do not
explicitly take into account that the data is often a mixture distribution of
multiple components.
We therefore introduce GLOSS, an algorithm that performs local subspace
outlier detection using global neighbourhoods. Experiments on synthetic data
demonstrate that GLOSS more accurately detects local outliers in mixed data
than its competitors. Moreover, experiments on real-world data show that our
approach identifies relevant outliers overlooked by existing methods,
confirming that one should keep an eye on the global perspective even when
doing local outlier detection.Comment: Short version accepted at IEEE BigData 201
The outer halo globular cluster system of M31 - II. Kinematics
We present a detailed kinematic analysis of the outer halo globular cluster
(GC) system of M31. Our basis for this is a set of new spectroscopic
observations for 78 clusters lying at projected distances between Rproj ~20-140
kpc from the M31 centre. These are largely drawn from the recent PAndAS
globular cluster catalogue; 63 of our targets have no previous velocity data.
Via a Bayesian maximum likelihood analysis we find that GCs with Rproj > 30 kpc
exhibit coherent rotation around the minor optical axis of M31, in the same
direction as more centrally- located GCs, but with a smaller amplitude of
86+/-17 km s-1. There is also evidence that the velocity dispersion of the
outer halo GC system decreases as a function of projected distance from the M31
centre, and that this relation can be well described by a power law of index ~
-0.5. The velocity dispersion profile of the outer halo GCs is quite similar to
that of the halo stars, at least out to the radius up to which there is
available information on the stellar kinematics. We detect and discuss various
velocity correlations amongst subgroups of GCs that lie on stellar debris
streams in the M31 halo. Many of these subgroups are dynamically cold,
exhibiting internal velocity dispersions consistent with zero. Simple Monte
Carlo experiments imply that such configurations are unlikely to form by
chance, adding weight to the notion that a significant fraction of the outer
halo GCs in M31 have been accreted alongside their parent dwarf galaxies. We
also estimate the M31 mass within 200 kpc via the Tracer Mass Estimator,
finding (1.2 - 1.6) +/- 0.2 10^{12}M_sun. This quantity is subject to
additional systematic effects due to various limitations of the data, and
assumptions built in into the TME. Finally, we discuss our results in the
context of formation scenarios for the M31 halo.Comment: 24 pages, 12 figures, 7 tables; Accepted for publication in MNRA
Divisive clustering of high dimensional data streams
Clustering streaming data is gaining importance as automatic data acquisition technologies are deployed in diverse applications. We propose a fully incremental projected divisive clustering method for high-dimensional data streams that is motivated by high density clustering. The method is capable of identifying clusters in arbitrary subspaces, estimating the number of clusters, and detecting changes in the data distribution which necessitate a revision of the model. The empirical evaluation of the proposed method on numerous real and simulated datasets shows that it is scalable in dimension and number of clusters, is robust to noisy and irrelevant features, and is capable of handling a variety of types of non-stationarity
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