92 research outputs found
Finding Black Holes with Black Boxes -- Using Machine Learning to Identify Globular Clusters with Black Hole Subsystems
Machine learning is a powerful technique, becoming increasingly popular in
astrophysics. In this paper, we apply machine learning to more than a thousand
globular cluster (GC) models simulated as part of the 'MOCCA-Survey Database I'
project in order to correlate present-day observable properties with the
presence of a subsystem of stellar mass black holes (BHs). The machine learning
model is then applied to available observed parameters for Galactic GCs to
identify which of them that are most likely to be hosting a sizeable number of
BHs and reveal insights into what properties lead to the formation of BH
subsystems. With our machine learning model, we were able to shortlist 21
Galactic GCs that are most likely to contain a BH subsystem. We show that the
clusters shortlisted by the machine learning classifier include those in which
BH candidates have been observed (M22, M10 and NGC 3201) and that our results
line up well with independent simulations and previous studies that manually
compared simulated GC models with observed properties of Galactic GCs. These
results can be useful for observers searching for elusive stellar mass BH
candidates in GCs and further our understanding of the role BHs play in GC
evolution. In addition, we have released an online tool that allows one to get
predictions from our model after they input observable properties.Comment: 20 pages, 9 figures, 7 tables. Accepted for publication in MNRAS.
Source code available at
https://github.com/ammaraskar/black-holes-black-boxe
COCOA Code for Creating Mock Observations of Star Cluster Models
We introduce and present results from the COCOA (Cluster simulatiOn
Comparison with ObservAtions) code that has been developed to create idealized
mock photometric observations using results from numerical simulations of star
cluster evolution. COCOA is able to present the output of realistic numerical
simulations of star clusters carried out using Monte Carlo or \textit{N}-body
codes in a way that is useful for direct comparison with photometric
observations. In this paper, we describe the COCOA code and demonstrate its
different applications by utilizing globular cluster (GC) models simulated with
the MOCCA (MOnte Carlo Cluster simulAtor) code. COCOA is used to synthetically
observe these different GC models with optical telescopes, perform PSF
photometry and subsequently produce observed colour magnitude diagrams. We also
use COCOA to compare the results from synthetic observations of a cluster model
that has the same age and metallicity as the Galactic GC NGC 2808 with
observations of the same cluster carried out with a 2.2 meter optical
telescope. We find that COCOA can effectively simulate realistic observations
and recover photometric data. COCOA has numerous scientific applications that
maybe be helpful for both theoreticians and observers that work on star
clusters. Plans for further improving and developing the code are also
discussed in this paper.Comment: 18 pages, 12 figures, accepted for publication in MNRAS. Revised
manuscript has a new title, better quality figures and many other
improvements. COCOA can be downloaded from: https://github.com/abs2k12/COCOA
(comments are welcome
Cataclysmic variables in Globular clusters: First results on the analysis of the MOCCA simulations database
In this first investigation of the MOCCA database with respect to cataclysmic
variables, we found that for models with Kroupa initial distributions,
considering the standard value of the efficiency of the common-envelope phase
adopted in BSE, no single cataclysmic variable was formed only via binary
stellar evolution, i. e., in order to form them, strong dynamical interactions
have to take place. Our results also indicate that the population of
cataclysmic variables in globular clusters are, mainly, in the last stage of
their evolution and observational selection effects can change drastically the
expected number and properties of observed cataclysmic variables.Comment: 4 pages, 3 figures. Presented at the MODEST 16/Cosmic Lab conference
in Bologna, Italy, April 18-22 2016. To be pusblished in Mem. S. A. It.
Conference Serie
MOCCA Survey Database I: Dissolution of tidally filling star clusters harbouring BH subsystems
We investigate the dissolution process for dynamically evolving star clusters
embedded in an external tidal field by exploring the MOCCA Survey Database I,
with focus on the presence and evolution of a stellar-mass black hole
subsystem. We argue that the presence of a black hole subsystem can lead to the
dissolution of tidally filling star clusters and this can be regarded as a
third type of cluster dissolution mechanism (in addition to well-known
mechanisms connected with strong mass loss due to stellar evolution and mass
loss connected with the relaxation process). This third process is
characterized by abrupt cluster dissolution connected with the loss of
dynamical equilibrium. The abrupt dissolution is powered by strong energy
generation from a stellar-mass black hole subsystem accompanied by tidal
stripping. Additionally, we argue that such a mechanism should also work for
even tidally under-filling clusters with top-heavy initial mass function.
Observationally, star clusters which undergo dissolution powered by the third
mechanism would look as a 'dark cluster' i.e. composed of stellar mass black
holes surrounded by an expanding halo of luminous stars (Banerjee & Kroupa
2011), and they should be different from 'dark clusters' harbouring
intermediate mass black holes as discussed by Askar et al. (2017a). An
additional observational consequence of an operation of the third dissolution
mechanism should be a larger than expected abundance of free floating black
holes in the Galactic halo.Comment: 14 pages, 14 figures, accepted to MNRA
MOCCA-SURVEY database I. Accreting white dwarf binary systems in globular clusters -- IV. cataclysmic variables -- properties of bright and faint populations
We investigate here populations of cataclysmic variables (CVs) in a set of
288 globular cluster (GC) models evolved with the MOCCA code. This is by far
the largest sample of GC models ever analysed with respect to CVs. Contrary to
what has been argued for a long time, we found that dynamical destruction of
primordial CV progenitors is much stronger in GCs than dynamical formation of
CVs, and that dynamically formed CVs and CVs formed under no/weak influence of
dynamics have similar white dwarf mass distributions. In addition, we found
that, on average, the detectable CV population is predominantly composed of CVs
formed via typical common envelope phase (CEP) ( per cent), that
only per cent of all CVs in a GC is likely to be detectable, and
that core-collapsed models tend to have higher fractions of bright CVs than
non-core-collapsed ones. We also consistently show, for the first time, that
the properties of bright and faint CVs can be understood by means of the pre-CV
and CV formation rates, their properties at their formation times and cluster
half-mass relaxation times. Finally, we show that models following the initial
binary population proposed by Kroupa and set with low CEP efficiency better
reproduce the observed amount of CVs and CV candidates in NGC 6397, NGC 6752
and 47 Tuc. To progress with comparisons, the essential next step is to
properly characterize the candidates as CVs (e.g. by obtaining orbital periods
and mass ratios).Comment: 18 pages, 13 figures; accepted for publication in MNRA
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