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The present. study suggests that more massive GC's are more likely to have a arger degree of LUEAS owing to their formation from eas clouds developed. from. merging between a larger number of dillerent gaseous regions with dillerent metallicities.
The present study suggests that more massive GCs are more likely to have a larger degree of HEAS owing to their formation from gas clouds developed from merging between a larger number of different gaseous regions with different metallicities.
The ow-mass GC's can be formed from single gas clouds so that hey are likely to have noflittle LIENS.
The low-mass GCs can be formed from single gas clouds so that they are likely to have no/little HEAS.
The present. study hus suggests that the origin of LLEZAS in some Galactic GC's can be closely associated with LEAS of ISM in their host chvarls.
The present study thus suggests that the origin of HEAS in some Galactic GCs can be closely associated with HEAS of ISM in their host dwarfs.
The laree metallicity spread: of various elements and »xossible age variation in « Cen (e.g..Sollima et al.
The large metallicity spread of various elements and possible age variation in $\omega$ Cen (e.g., Sollima et al.
2005) can » consistent. with the stripped nucleus scenario.
2005) can be consistent with the stripped nucleus scenario.
However. his does not necessarily mean that all of the Galactic GC's with LUEAS (ee. NGC 2419. M22. and Ferzan. 5) were ormed from stripped nuclei of dwarfs.
However, this does not necessarily mean that all of the Galactic GCs with HEAS (e.g., NGC 2419, M22, and Terzan 5) were formed from stripped nuclei of dwarfs.
A CC with cistinet wo peaks in the Fe/L] distributions of the stars might well » consistent. with GC merging with diferent Fe/1l] (e.g. Drünns Ixroupa 2011: BY11).
A GC with distinct two peaks in the [Fe/H] distributions of the stars might well be consistent with GC merging with different [Fe/H] (e.g., Brünns Kroupa 2011; BY11).
A GC with a smaller degree of EAS vet no clear bimodal Ee/L] distribution might well orm from massive gas clumps of the host dwarf and then be stripped from the dwarf without sinking into the center (i.e.. without becoming the stellar nucleus) to finally become the Galactic halo GC.
A GC with a smaller degree of HEAS yet no clear bimodal [Fe/H] distribution might well form from massive gas clumps of the host dwarf and then be stripped from the dwarf without sinking into the center (i.e., without becoming the stellar nucleus) to finally become the Galactic halo GC.
We lastly suggest that nucleation. GC merging. and merging of gas clouds with dillerent ο can be all promising mechanisms for the formation of the Galactic GCs with dillerent degrees of HEXD.
We lastly suggest that nucleation, GC merging, and merging of gas clouds with different [Fe/H] can be all promising mechanisms for the formation of the Galactic GCs with different degrees of HEAD.
lam grateful to the anonymous referee for constructive and useful comments that improved this paper.
I am grateful to the anonymous referee for constructive and useful comments that improved this paper.
be thermal emission from X-ray gas in the cluster.
be thermal emission from X-ray gas in the cluster.
For the X-rays to be cluster emission, we would expect a smooth and relatively isotropic distribution.
For the X-rays to be cluster emission, we would expect a smooth and relatively isotropic distribution.
The cluster center is not well-constrained.
The cluster center is not well-constrained.
It was estimated to lie ~20" east of 2270.1 by ?..
It was estimated to lie $\sim 20$ east of 270.1 by \citet{2009ApJ...695..724H}.
The current dataset has insufficient observed counts (22.8+5.6, 0.3-8 keV) to constrain the spatial distribution of the diffuse emission.
The current dataset has insufficient observed counts $\pm$ 5.6, 0.3-8 keV) to constrain the spatial distribution of the diffuse emission.
However the existence of an excess of counts around 2270.1, and the lack of a similar excess to the east suggest that the quasar may lie close to the center of the cluster.
However the existence of an excess of counts around 270.1, and the lack of a similar excess to the east suggest that the quasar may lie close to the center of the cluster.
The extended emission has too few counts to constrain the spectral parameters.
The extended emission has too few counts to constrain the spectral parameters.
The hardness ratio HR=—0.09+0.22 indicates a temperature of ~4 keV in an APEC model but remains within 20 of a power-law spectrum with Γ~1.7, so we cannot rule out non-thermal emission.
The hardness ratio $-0.09\pm0.22$ indicates a temperature of $\sim 4$ keV in an APEC model but remains within $2 \sigma$ of a power-law spectrum with $\Gamma \sim 1.7$, so we cannot rule out non-thermal emission.
An APEC model was fitted, assuming abundance Z=0.5 Za and temperature 4 keV at the redshift of the source.
An APEC model was fitted, assuming abundance Z=0.5 $_{\bigodot}$ and temperature 4 keV at the redshift of the source.
With a grouping of 5 counts per bin to distribute them throughout the band, the spectrum looks reasonable, but the is too low to provide meaningful constraints.
With a grouping of 5 counts per bin to distribute them throughout the band, the spectrum looks reasonable, but the signal-to-noise is too low to provide meaningful constraints.
The fitted normalization yields a broad-band flux, F(0.3—8 kkeV)-(1.120.5)x10-14 erg cm? s! including a correction for the excluded sky area assuming isotropic emission.
The fitted normalization yields a broad-band flux, $-$ $(1.1 \pm 0.5) \times 10^{-14}$ erg $^{-2}$ $^{-1}$ including a correction for the excluded sky area assuming isotropic emission.
This translates to a broad-band X-ray luminosity ~2x10 erg s! for our assumed cosmology, consistent with the luminosity of a 4 keV cluster based on the low-redshift luminosity-temperature (L-T, «Rsoo) relation of ?..
This translates to a broad-band X-ray luminosity $\sim 2 \times 10^{44}$ erg $^{-1}$ for our assumed cosmology, consistent with the luminosity of a 4 keV cluster based on the low-redshift luminosity-temperature (L-T, $<$ $_{500}$ ) relation of \citet{2009A&A...498..361P}.
The few high-redshift (z> 1.4) clusters with X-ray measurements tend to be faint for their temperature based on a self-similar model for their evolution in comparison with similarly
The few high-redshift $z > 1.4$ ) clusters with X-ray measurements tend to be faint for their temperature based on a self-similar model for their evolution in comparison with similarly
fits, though the fits from both methods, presented in Table 1,, are completely consistent.
fits, though the fits from both methods, presented in Table \ref{Tab: Fits}, are completely consistent.
The correlation amplitude in our low redshift bin at z0.5 is in excellent agreement with the only other measurement at this redshift (?)..
The correlation amplitude in our low redshift bin at $z \approx 0.5$ is in excellent agreement with the only other measurement at this redshift \citep{gonzalez02}.
Our high redshift measurement, at z71. is the first to probe structure on the largest scales in the first half of Universe.
Our high redshift measurement, at $z \approx 1$, is the first to probe structure on the largest scales in the first half of Universe.
The space densities for these samples and the mean intercluster distances, d., are also presented in Table 1..
The space densities for these samples and the mean intercluster distances, $d_c$, are also presented in Table \ref{Tab: Fits}.
The relationship between clustering amplitude and d, predicted in a concordance cosmology, and observed in practice (?,andreferences therein),, is only weakly dependent on redshift.
The relationship between clustering amplitude and $d_c$ predicted in a concordance cosmology, and observed in practice \citep[and references therein]{bahcall03}, is only weakly dependent on redshift.
As shown in Figure 3,, the ISCS samples are quite consistent with the LCDM predictions between 0«z1.5 (hashed region) from ?..
As shown in Figure \ref{Fig: d_c}, the ISCS samples are quite consistent with the LCDM predictions between $0 < z < 1.5$ (hashed region) from \citet{younger05}.
A key theoretically predictable cluster observable is the correlation function as a function of halo mass.
A key theoretically predictable cluster observable is the correlation function as a function of halo mass.
In simulations the halo mass,M»oo,, is defined as the mass inside the radius at which the mean overdensity is 200 times the critical density.
In simulations the halo mass, is defined as the mass inside the radius at which the mean overdensity is 200 times the critical density.
We compare our clustering results with the ? analysis of the ? high-resolution cosmological simulation, which had a 1500 bbox length, an individual particle mass of 1.8x10!!Mo, and a spectrum normalization of og=0.84.
We compare our clustering results with the \citet{younger05} analysis of the \citet{hopkins05} high–resolution cosmological simulation, which had a 1500 box length, an individual particle mass of $1.8 \times 10^{11} \msun$, and a power spectrum normalization of $\sigma_8 = 0.84$.
We infer that the powerISCS cluster sample has average log[M20/Mo] masses of ~ and ~13.8702 at zeg=0.53 and 0.97, respectively.
We infer that the ISCS cluster sample has average $\log [M_{\mbox{\scriptsize 200}}/M_\odot]$ masses of $\sim 13.9^{+0.3}_{-0.2}$ and $\sim 13.8^{+0.2}_{-0.3}$ at $z_{\mbox{\scriptsize eff}}=0.53$ and $0.97$, respectively.
Direct 13.903dynamical masses for the 10 z>1 clusters presented in E07 yield a largely consistent distribution of masses (Gonzalez iin prep).
Direct dynamical masses for the 10 $z>1$ clusters presented in E07 yield a largely consistent distribution of masses (Gonzalez in prep).
The observed constancy of ro for massive galaxy clusters out to z=1 is a robust confirmation of a key from numerical simulations, reflecting the relative constancy predictionof the mass hierarchy of clusters with redshift (?)..
The observed constancy of $r_0$ for massive galaxy clusters out to $z=1$ is a robust confirmation of a key prediction from numerical simulations, reflecting the relative constancy of the mass hierarchy of clusters with redshift \citep{younger05}.
That is, the N most massive clusters at one epoch roughly correspond to the N most massive clusters at a later epoch, and therefore have similar clustering.
That is, the N most massive clusters at one epoch roughly correspond to the N most massive clusters at a later epoch, and therefore have similar clustering.
In Figure 4 (?),, (???),, (??),, (?).. (????),, 4.. ?,, ? (?,picture,
In Figure \ref{Fig: theory and evolution} \citep{overzier03}, \citep{brown05,daddi04,daddi01}, \citep{farrah06, magliocchetti07}, \citep{blain04}. \citep{porciani04, croom05, myers06, coil07}, \ref{Fig: theory and evolution}. \citet{moustakas&somerville02},
dashed
\citet{fry96} \citep[dashed lines]{groth&peebles77},
As a consequence. the question of super-fast magnetosonic Jet formation from weakly magnetized disks is still open.
As a consequence, the question of super-fast magnetosonic jet formation from weakly magnetized disks is still open.
In this paper we address this issue using 2.5D numerical MHD simulations based on a mean field approximation.
In this paper we address this issue using 2.5D numerical MHD simulations based on a mean field approximation.
We explore the accretion-ejection processes from a quasi-standard accretion disk where the magnetization is very low (smaller than 107).
We explore the accretion-ejection processes from a quasi-standard accretion disk where the magnetization is very low (smaller than $10^{-3}$ ).
Since the magnetic field is low. we assume that turbulence triggered by the MRI is indeed present but that it provides mainly anomalous transport coefficients: a viscosity v, and a magnetic diffusivity vj,.
Since the magnetic field is low, we assume that turbulence triggered by the MRI is indeed present but that it provides mainly anomalous transport coefficients: a viscosity $\nu_\mathrm{v}$ and a magnetic diffusivity $\nu_\mathrm{m}$.
On the other hand. we do not expect to observe any MRI feature (such as channel flows for instance) in our simulatior because of the presence of explicit viscosity and magnetic diffusivity effects.
On the other hand, we do not expect to observe any MRI feature (such as channel flows for instance) in our simulation because of the presence of explicit viscosity and magnetic diffusivity effects.
While measurements of the turbulent viscosity in MRI induced turbulence have been extensively reported in the literature. it is only very recently that such a work has been done for the turbulent magnetic diffusivity (??)..
While measurements of the turbulent viscosity in MRI induced turbulence have been extensively reported in the literature, it is only very recently that such a work has been done for the turbulent magnetic diffusivity \citep{Lesur:2009bf, Guan:2009gd}.
In particular ? showed that the turbulent magnetic diffusion scales like a resistivity tensor with dominant diagonal terms.
In particular \citet{Lesur:2009bf} showed that the turbulent magnetic diffusion scales like a resistivity tensor with dominant diagonal terms.
Also. as a first approximation. an isotropic value can be safely used.
Also, as a first approximation, an isotropic value can be safely used.
Finally. the effective Prandtl number Pm=vv given by the ratio of turbulent viscosity and diffusivity. has been found to be of order unity.
Finally, the effective Prandtl number $ \mathcal{P}_\mathrm{m} = \nu_\mathrm{v}/\nu_\mathrm{m}$, given by the ratio of turbulent viscosity and diffusivity, has been found to be of order unity.
The mean field approximation has been successfully employed in a number of semi-analytical (e.g.2220202)22222 and numerical applications (e.g.222222)222221 related to the study of magnetizec aceretion-ejection flows.
The mean field approximation has been successfully employed in a number of semi-analytical \citep[e.g.][]{1995A&A...295..807F, 1995ApJ...444..848L, 2000A&A...353.1115C, 2001ApJ...553..158O, 2008ApJ...677.1221R} and numerical applications \citep[e.g.][]{2002ApJ...581..988C, 2003ApJ...589..397K, 2003A&A...398..825V, 2006A&A...460....1M, 2007A&A...469..811Z, 2009MNRAS.399.1802R} related to the study of magnetized accretion-ejection flows.
Beside having a precise control of the diffusive and transport phenomena. the numerical experiments based on this approach provide laminar flow solutions which can be compared to semi-analytical models.
Beside having a precise control of the diffusive and transport phenomena, the numerical experiments based on this approach provide laminar flow solutions which can be compared to semi-analytical models.
In section 2. we describe the numerical nethod used. the boundary and initial conditions.
In section 2, we describe the numerical method used, the boundary and initial conditions.
Section 3 is devoted to the description and discussion of the results obtained.
Section 3 is devoted to the description and discussion of the results obtained.
Surprisingly. super-fast jets are indeed obtained from a finite disk region and remain stable for a time span never previously achieved in the literature.
Surprisingly, super-fast jets are indeed obtained from a finite disk region and remain stable for a time span never previously achieved in the literature.
Section + summarizes our findings and. in a companion paper (Murphy et al..
Section 4 summarizes our findings and, in a companion paper (Murphy et al.,
1n prep). we will examine the long standing issue of the magnetic field redistribution within the disk on long (aceretion) time scales.
in prep), we will examine the long standing issue of the magnetic field redistribution within the disk on long (accretion) time scales.
The full visco-resistive MHD equations in axial symmetry are evolved in time using the publicly available numerical code PLUTO (?)..
The full visco-resistive MHD equations in axial symmetry are evolved in time using the publicly available numerical code PLUTO \citep{2007ApJS..170..228M}.
The solved equations are: the continuity equation the conservation of momentum equation the induction equation the conservation of energy equation where $2-puVOo+L.. and Ly is the local cooling term (see below).
The solved equations are: the continuity equation the conservation of momentum equation the induction equation the conservation of energy equation where $S=-\rho\vec{u} \nabla \Phi_\mathrm{G} + L_\mathrm{c}$, and $L_\mathrm{c}$ is the local cooling term (see below).
The total energy density is defined as and the total pressure (thermal and magnetic) is The equations are written and solved in dimensionless form. thus without jig coefficients.
The total energy density is defined as and the total pressure (thermal and magnetic) is The equations are written and solved in dimensionless form, thus without $\mu_0$ coefficients.
The equation of state is the ideal gas equation.
The equation of state is the ideal gas equation.
Here. p is the mass density. wthe velocity. P the eas pressure. B the magnetic field. bx;=—GM/V2+ is the gravitational potential of the central mass. J=VxB is the current density.v,, the magnetic diffusivity and y=5/3 is the ratio of specific heats.
Here, $\rho$ is the mass density, $\vec{u}$the velocity, $P$ the gas pressure, $\vec{B}$ the magnetic field, $\Phi_\mathrm{G} = - GM / \sqrt{r^2 + z^2} $ is the gravitational potential of the central mass, $\vec{J}=\nabla \times \vec{B}$ is the current $\nu_\mathrm{m}$ the magnetic diffusivity and $\gamma = 5/3$ is the ratio of specific heats.
The viscous stress tensor T is defined as where 7. is the dynamic viscosity.
The viscous stress tensor ${\overline {\overline {\vec T}}}$ is defined as where $\eta_\mathrm{v}$ is the dynamic viscosity.
See Appendix Appendix for the expression of the tensor components.
See Appendix \ref{AddNumCond} for the expression of the tensor components.
As_ is customary. the kinematic viscosity is defined as v,=7./p.
As is customary, the kinematic viscosity is defined as $\nu_\mathrm{v} = \eta_\mathrm{v}/\rho$.
As stressed. above. we follow a mean field approach where the turbulence is crudely modeled by mere transport coefficients: a viscosity νν and a magnetic diffusivity vj.
As stressed above, we follow a mean field approach where the turbulence is crudely modeled by mere transport coefficients: a viscosity $\nu_\mathrm{v}$ and a magnetic diffusivity $\nu_\mathrm{m}$.
Consistently with this approximation. a? alpha prescription is then employed.
Consistently with this approximation, a \citet{1973A&A....24..337S} alpha prescription is then employed.
This assumes that the viscosity is proportional to the heightscale of the disk. /. and some characteristic velocity. in this case the sound speed. ος. namely We assume that the disk is not flat. but will have initially à constant aspect ratio ο=A/rc/VgOL.
This assumes that the viscosity is proportional to the heightscale of the disk, $h$, and some characteristic velocity, in this case the sound speed, $c_\mathrm{s}$, namely We assume that the disk is not flat, but will have initially a constant aspect ratio $\varepsilon= h/r= c_\mathrm{s}/V_\mathrm{K}= 0.1$.
As at initial condition for the alpha accretion disk. we take the perturbative solution of the steady-state disk equations found in?) and the references therein.
As an initial condition for the alpha accretion disk, we take the perturbative solution of the steady-state disk equations found in \citet{2009A&A...508.1117Z} and the references therein.
The disk is 1n. hydrostatic equilibrium and accretion is driven by the viscous stress tensor alone.
The disk is in hydrostatic equilibrium and accretion is driven by the viscous stress tensor alone.
This particular solution provides reasonable vertical anc radial profiles of all quantities that are suitable for à SAD (see Appendix AppendixA: for more details).
This particular solution provides reasonable vertical and radial profiles of all quantities that are suitable for a SAD (see Appendix \ref{AddNumCond} for more details).
A not so well knowr bias of the alpha preseription in 2D flows is that. below a critical value found to be aiy~0.685. there is a backflow or the disk midplane (2)..
A not so well known bias of the alpha prescription in 2D flows is that, below a critical value found to be $\alpha_\mathrm{crit} \sim 0.685$, there is a backflow on the disk midplane \citep{1984SvA....28...50U}.
This is certainly unphysical and arises caly from the functional form of the stress tensor used to mimic turbulence.
This is certainly unphysical and arises only from the functional form of the stress tensor used to mimic turbulence.
In order to circumvent this bias. we used e,=0.97.
In order to circumvent this bias, we used $\alpha_\mathrm{v}=0.9$.
. Consistently with the recent ? results. we assume that the effective magnetic Prandtl number μι=v/v 1s of order unity: for simplicity we set P,,=2/3 in all simulations.
Consistently with the recent \citet{Lesur:2009bf} results, we assume that the effective magnetic Prandtl number $\mathcal{P}_\mathrm{m} = \nu_\mathrm{v}/\nu_\mathrm{m}$ is of order unity: for simplicity we set $\mathcal{P}_\mathrm{m} = 2/3$ in all simulations.
Again. we stress that this ts a strong simplification of highly complex phenomena but also an unavoidable price to pay if one seeks for long term evolution of global systems. such as aceretion disks and their related jets.
Again, we stress that this is a strong simplification of highly complex phenomena but also an unavoidable price to pay if one seeks for long term evolution of global systems, such as accretion disks and their related jets.
With a constant £. the viscosity and resistivity will follow the same radial and vertical profiles.
With a constant $\mathcal{P}_\mathrm{m}$ , the viscosity and resistivity will follow the same radial and vertical profiles.
They decrease smoothly with height until they become negligible. allowing a transition to a magnetized "corona" in
They decrease smoothly with height until they become negligible, allowing a transition to a magnetized “corona” in
The planar components of the Galactic tidal acceleration are accurately approximated by the epicvcle: model for all objects moving on nearly circular orbits at the solar racius(Jiang&‘Tremaine2010:Wineetal.1990:etal. 2POO4):: where 4d is the OortOs constant. and Q is the rotation frequeney.
The planar components of the Galactic tidal acceleration are accurately approximated by the epicycle model for all objects moving on nearly circular orbits at the solar \citep{jia,kin,maol}: : where $A$ is the OortÕs constant, and $\Omega$ is the rotation frequency.
“Phe vertical component of acceleration. to à good approximation for small vertical velocities at the plane. is harmonie(Alakaroyvetal.2004)... and. therefore. tends. to compress very wide binaries.
The vertical component of acceleration, to a good approximation for small vertical velocities at the plane, is \citep{maol}, and, therefore, tends to compress very wide binaries.
It is sullicient to consider the stability problem restricted to the planar case. ignoring the vertical dimension.
It is sufficient to consider the stability problem restricted to the planar case, ignoring the vertical dimension.
All integrations were performed with the well-tested Mercury code (Chambers&Migliorini1997). by adding the tidal acceleration components in the user-defined external acceleration. subroutine.
All integrations were performed with the well-tested Mercury code \citep{cha} by adding the tidal acceleration components in the user-defined external acceleration subroutine.
In the units adopted. in he Mercury. code. the assumed. parameters were 4:40.=119-107% 7 and 20=15-101" qd1.
In the units adopted in the Mercury code, the assumed parameters were $4 A \Omega=1.19\cdot 10^{-20}$ $^{-2}$ and $2\Omega=1.5\cdot10^{-10}$ $^{-1}$.
Ne used the Dulirsch-Stoer option of integration and set the integration step to 200 d. The companion was considered ejectedwhen he distance from the primary exceeded 900 000 AU.
We used the Bulirsch-Stoer option of integration and set the integration step to 200 d. The companion was considered ejectedwhen the distance from the primary exceeded 900 000 AU.
the number of stars and the central densities are lower than for real clusters.
the number of stars and the central densities are lower than for real clusters.
Increasing both quantities would increase the relaxation time. which in turn would increase the evolutionary times.
Increasing both quantities would increase the relaxation time, which in turn would increase the evolutionary times.
Including the presence of binaries could change not only the timescales but also the nature of the core contraction and expansion.
Including the presence of binaries could change not only the timescales but also the nature of the core contraction and expansion.
Also. our analysis comes from images with a limited amount of signal to noise (a combination of number of stars and fiducial distance).
Also, our analysis comes from images with a limited amount of signal to noise (a combination of number of stars and fiducial distance).
It is likely that the comparisons would be more meaningful using images with a larger number of stars.
It is likely that the comparisons would be more meaningful using images with a larger number of stars.
These issues have to be kept in mind when comparing to observed globular clusters.
These issues have to be kept in mind when comparing to observed globular clusters.
Despite the idealizations in the models. the span of r./7r; and central slope values seems to generally agree between our models and observed clusters.
Despite the idealizations in the models, the span of $r_c/r_h$ and central slope values seems to generally agree between our models and observed clusters.
We note that the agreement between the two models that have undergone core-collapse and the observed clusters that are suspect of having undergone the same process Is very good.
We note that the agreement between the two models that have undergone core-collapse and the observed clusters that are suspect of having undergone the same process is very good.
Having simulations with a larger number of stars would allow to analyze snapshots closer in time to fully explore the process of core-collapse.
Having simulations with a larger number of stars would allow to analyze snapshots closer in time to fully explore the process of core-collapse.
There are some areas of Figs 6 and 7 containing observed clusters that our models do not populate.
There are some areas of Figs 6 and 7 containing observed clusters that our models do not populate.
As mentioned in section ??.. a variety of heating mechanisms have been proposed for star clusters in recent years.
As mentioned in section \ref{intro}, a variety of heating mechanisms have been proposed for star clusters in recent years.
Some of them. like mass loss or white dwarf kicks should affect most clusters: while others like tidal shocking or primordial binaries depend on the structure and evolution history of each cluster.
Some of them, like mass loss or white dwarf kicks should affect most clusters; while others like tidal shocking or primordial binaries depend on the structure and evolution history of each cluster.
A combination of including some of these heating mechanisms and starting from a larger variety of configurations (a larger range of initial Wo) would likely produce a better agreement between models and observations.
A combination of including some of these heating mechanisms and starting from a larger variety of configurations (a larger range of initial $W_0$ ) would likely produce a better agreement between models and observations.
Our results are in contrast with those of Vesperini&Trenti(2010) since they find a number of models that present central shallow cusps without containing black holes.
Our results are in contrast with those of \citet{ves10} since they find a number of models that present central shallow cusps without containing black holes.
We think the reason for the difference between their result and ours Hes on a combination of two things: on one hand. their models contain about of the number of stars our models have.
We think the reason for the difference between their result and ours lies on a combination of two things: on one hand, their models contain about of the number of stars our models have.
On the other hand. they count main sequence stars. which we find to be detected with a large degree of incompleteness 1n realistic analysis. particularly 1n the center of rich clusters.
On the other hand, they count main sequence stars, which we find to be detected with a large degree of incompleteness in realistic analysis, particularly in the center of rich clusters.
Thus. we are tracing a different subset of stars when measuring density profiles.
Thus, we are tracing a different subset of stars when measuring density profiles.
We believe that the lower numbers of stars in their models produces noisier profiles that in turn can show shallow cusps due to fluctuations in the photometric points.
We believe that the lower numbers of stars in their models produces noisier profiles that in turn can show shallow cusps due to fluctuations in the photometric points.
This is illustrated by the fact that as soon as they use more particles (64K runs with combined snapshots). their central slopes before core-collapse times converge to shallower values consistent with the ones we find for models without black holes.
This is illustrated by the fact that as soon as they use more particles (64K runs with combined snapshots), their central slopes before core-collapse times converge to shallower values consistent with the ones we find for models without black holes.