Datasets:
ReadingTimeMachine
/
rtm-sgt-ocr-v1

Dataset card Data Studio Files Community
2
source
stringlengths
1
2.05k
⌀
target
stringlengths
1
11.7k
At redshift 2. this quantity is given by where p,, is the average matter density. and. as before. V(Al.z)=6,DI2)mCAL)].
At redshift $z$, this quantity is given by where $\bar\rho_m$ is the average matter density, and, as before, $\nu(M,z)\equiv\delta_c/[D(z)\sigma(M)]$.
The critical overdensity of collapse of a halo is denoted by 0... (2) is the growth function of density perturbations. and (A7) is the rms value of density perturbations at the comoving scale corresponding to mass A.
The critical overdensity of collapse of a halo is denoted by $\delta_c$, $D(z)$ is the growth function of density perturbations, and $\sigma(M)$ is the rms value of density perturbations at the comoving scale corresponding to mass $M$.
In a region with overdensity ὁ and linear size /?. the mass function is enhanced.
In a region with overdensity $\delta$ and linear size $R$, the mass function is enhanced.
This enhancement can be calculated using the excursion set formalism (?)..
This enhancement can be calculated using the excursion set formalism \citep{1991ApJ...379..440B}.
The resulting mass function is again given by Equation (I9)). except that now the quantity v(A/.z) is defined as where op is the rms value of density perturbations at comoving scale 77.
The resulting mass function is again given by Equation \ref{ps-mf}) ), except that now the quantity $\nu(M,z)$ is defined as where $\sigma_R$ is the rms value of density perturbations at comoving scale $R$.
Closely following 2.. we can write where Nios(AZ.z)dM is the destruction rate at redshift = of haloes of mass between Al and dA. (
Closely following \citet{1994PASJ...46..427S}, we can write where $\dot N_\mathrm{dest}(M,z)dM$ is the destruction rate at redshift $z$ of haloes of mass between $M$ and $dM$. (
The halo formation rate is detined as the number density of haloes formed per unit time from mergers of lower mass haloes.
The halo formation rate is defined as the number density of haloes formed per unit time from mergers of lower mass haloes.
Similarly the halo destruction rate is detined as the number density of haloes destroyed per unit time due to mergers with other haloes.)
Similarly the halo destruction rate is defined as the number density of haloes destroyed per unit time due to mergers with other haloes.)
Here. an overdot denotes the time derivative.
Here, an overdot denotes the time derivative.
We can write the destruction rate as and the formation rate as where QUM.AL.2) is the probability that a halo of mass Al merges with another halo to result in a halo of mass Al’ per unit time. and (QV.ΛΙ.2) that an halo of mass AJ forming at redshift + has a progenitor of mass Al’.
We can write the destruction rate as and the formation rate as where $\tilde Q(M,M^\prime,z)$ is the probability that a halo of mass $M$ merges with another halo to result in a halo of mass $M^\prime$ per unit time, and $Q(M^\prime,M,z)$ that an halo of mass $M$ forming at redshift $z$ has a progenitor of mass $M^\prime$.
The threshold mass Aui is introduced at this stage to avoid divergence.
The threshold mass $M_\mathrm{min}$ is introduced at this stage to avoid divergence.
This gives We now assume that ó has no characteristic mass scale so that OCAL2)=AL“oz).
This gives We now assume that $\phi$ has no characteristic mass scale so that $\phi(M,z)=M^\alpha\tilde\phi(z)$.
This gives But since the left hand side of Equation (263) is a function of time alone(through theredshift). the right hand sideof this equation also has to be independent of mass.
This gives But since the left hand side of Equation \ref{phi1}) ) is a function of time alone(through theredshift), the right hand sideof this equation also has to be independent of mass.
In particular. we can then set AZ=Ai, in this equation. giving us Now. in the case of the overdense region that we are considering here. we have
In particular, we can then set $M=M_\mathrm{min}$ in this equation, giving us Now, in the case of the overdense region that we are considering here, we have
L4tkms! ffor maser sources. compared to 1.1] ffor other sources). indicating that the high density gas surrounding the protostellar cores traced by ammonia emission is dynamically linked to the collisional processes associated with the maser emission.
1.4 for maser sources, compared to 1.1 for other sources), indicating that the high density gas surrounding the protostellar cores traced by ammonia emission is dynamically linked to the collisional processes associated with the maser emission.
In this section we will compare the derived ammonia and dust properties to identify correlations and anti-correlations in the data and to check for inconsistencies between the different tracers.
In this section we will compare the derived ammonia and dust properties to identify correlations and anti-correlations in the data and to check for inconsistencies between the different tracers.
In Section 2.3. we derived the kinetic temperatures and NH; column densities which are the most readily available quantities we have at hand to compare with quantities derived from the dust emission.
In Section \ref{sec:parameters} we derived the kinetic temperatures and $_3$ column densities which are the most readily available quantities we have at hand to compare with quantities derived from the dust emission.
In the next section we will describe how the dust temperatures were determined and estimate the H» column densities.
In the next section we will describe how the dust temperatures were determined and estimate the $_2$ column densities.
In an earlier paper (?)) we presented observations of submillimetre emission which tracing the distribution of warm «dust.
In an earlier paper \citealt{Morgan2008}) ) we presented observations of submillimetre emission which tracing the distribution of warm dust.
Spectral energy distributions (SEDs) were determined by fitting grevbody functions to the measured submillimetre fluxes and mid- and far-infrared fluxes.
Spectral energy distributions (SEDs) were determined by fitting greybody functions to the measured submillimetre fluxes and mid- and far-infrared fluxes.
Fits were presented for all sources for which good quality data was available.
Fits were presented for all sources for which good quality data was available.
The H» column density associated with each SFO object detected by ? may be calculated using where S, is the 850 fflux density. © is the solid angle associated with the aperture used to observe each core in 2.. j( = 2.3 is the mean molecular weight. mj is the mass of a hydrogen atom. αι. is the dust opacity per unit mass at 850 (0.02 cm? g |. following 21) and BG) is the Planck function. evaluated at dust temperature 7,4.
The $_2$ column density associated with each SFO object detected by \citet{Morgan2008} may be calculated using where $S_{\nu}$ is the 850 flux density, $\Omega$ is the solid angle associated with the aperture used to observe each core in \citet{Morgan2008}, $\mu$ = 2.3 is the mean molecular weight, $\mathrm{m_H}$ is the mass of a hydrogen atom, $\kappa_{\nu}$ is the dust opacity per unit mass at 850 (0.02 $^2$ $^{-1}$ following \citet{Morgan2008}) ) and $\mathrm{B}_{\nu}(T_\mathrm{d})$ is the Planck function, evaluated at dust temperature $T_\mathrm{d}$.
Resulting values of H» column density are presented in the tinal column of Table ??..
Resulting values of $_{2}$ column density are presented in the final column of Table \ref{tbl:Detections}.
In Fig.
In Fig.
3 we present two scatter plots comparing the temperatures (upper panel) and column densities (lower panel) derived from the two tracers of ammonia and submillimetre emission.
\ref{fig:Temp_Graph} we present two scatter plots comparing the temperatures (upper panel) and column densities (lower panel) derived from the two tracers of ammonia and submillimetre emission.
We show the linear-square fit to the data as a solid line.
We show the linear-square fit to the data as a solid line.
Additionally. in the temperature plot. we include a dashed line indicating the position of the data if both temperatures were equal.
Additionally, in the temperature plot, we include a dashed line indicating the position of the data if both temperatures were equal.
There is quite a lot of scatter in the distributions seen in both plots.
There is quite a lot of scatter in the distributions seen in both plots.
However. there is a general correlation between the kinetic and dust temperatures and the H» and NH; column densities.
However, there is a general correlation between the kinetic and dust temperatures and the $_2$ and $_3$ column densities.
The dust temperatures are generally slightly higher than the observed kinetic temperatures.
The dust temperatures are generally slightly higher than the observed kinetic temperatures.
The ratio of dust temperature to ranges from 0.9 to [.6 with a mean of 1.2. this slightly higher dust temperature may be attributed to the fact that submillimetre emission 1s associated with a wide range of densities. covering the star-forming core itself as well as the warm envelope surrounding ye core Cand the interface between the two).
The ratio of dust temperature to ranges from 0.9 to 1.6 with a mean of 1.2, this slightly higher dust temperature may be attributed to the fact that submillimetre emission is associated with a wide range of densities, covering the star-forming core itself as well as the warm envelope surrounding the core (and the interface between the two).
As ammonia emission requires a critical density of*.. it is likely to trace the inner. more dense regions of the protostellar core.
As ammonia emission requires a critical density of, it is likely to trace the inner, more dense regions of the protostellar core.
It should be noted yat the dust temperatures were derived using fluxes from the IRAS with a significantly larger beam than the present observations.
It should be noted that the dust temperatures were derived using fluxes from the IRAS with a significantly larger beam than the present observations.
These observations are therefore likely to incorporate more of the yotter dust at the edges of the BRCs.
These observations are therefore likely to incorporate more of the hotter dust at the edges of the BRCs.
We therefore conclude that the Wo tracers are probing material at similar temperatures (difference between median averages is «3 K). though the submillimetre observations may incorporate some additional material associated with the warm protostellar envelopes and cloud rims.
We therefore conclude that the two tracers are probing material at similar temperatures (difference between median averages is $<$ 3 K), though the submillimetre observations may incorporate some additional material associated with the warm protostellar envelopes and cloud rims.
Although there is some correlation seen in the comparison jxot of the H» and NH; column densities the scatter is significant.
Although there is some correlation seen in the comparison plot of the $_2$ and $_3$ column densities the scatter is significant.
The fractional abundance of mmay be found through simple comparison of the derived H and ccolumn densities?.
The fractional abundance of may be found through simple comparison of the derived $_2$ and column .
. Looking at individual sources we find the Tactional abundances range from a few times " to a few times 5.
Looking at individual sources we find the fractional abundances range from a few times $^{-9}$ to a few times $^{-8}$.
The mean fractional abundance of to Hs is 2.6 x 7. this is the value used in Fig.
The mean fractional abundance of to $_2$ is 2.6 $\times$ $^{-8}$, this is the value used in Fig.
3. to illustrate a line of constant fractional abundance.
\ref{fig:Temp_Graph} to illustrate a line of constant fractional abundance.
The scatter in the plot of vs. H» column density reflects the variation of fractional abundance from source to source.
The scatter in the plot of vs. $_2$ column density reflects the variation of fractional abundance from source to source.
Overall. the determined values of fractional abundance are typical across a wide range of protostellar environments. from low-mass. starless cores (2? and low to intermediate mass dense cores (??).. to complex. PDR-associated regions (2). and high-mass star forming regions (2?
Overall, the determined values of fractional abundance are typical across a wide range of protostellar environments, from low-mass starless cores \citep{Tafalla2006,Crapsi2007} and low to intermediate mass dense cores \citep{Hotzel2001,Friesen2009}, to complex, PDR-associated regions \citep{Larsson2003} and high-mass star forming regions \citep{Kuiper1995,Pillai2006}.
The fractional abundances found here reflect a more general trend in the properties of ammonia in star forming regions.
The fractional abundances found here reflect a more general trend in the properties of ammonia in star forming regions.
The physical properties of our sources. as determined from our ammonia observations. are typical in most star forming environments. with only very hot cores showing any significant variation. in. column density or temperature (c.f. 229).
The physical properties of our sources, as determined from our ammonia observations, are typical in most star forming environments, with only very hot cores showing any significant variation in column density or temperature (c.f. \citealt{Longmore2007,Pillai2007}) ).
The implication of our analysis is that ammonia.once excited beyond its critical threshold. is insensitive to environmental circumstances.i.e. resistant to depletion in cold. dense cores and likely shielded from photoionisation in high-radiation environments.
The implication of our analysis is that ammonia,once excited beyond its critical threshold, is insensitive to environmental circumstances,i.e. resistant to depletion in cold, dense cores and likely shielded from photoionisation in high-radiation environments.
Our target5 selection sampled a diverse range.5 of stellar parameters. such as evolution. surface chemistry. metallicity and luminosity.
Our target selection sampled a diverse range of stellar parameters, such as evolution, surface chemistry, metallicity and luminosity.
Phough our sample is bv no means unbiased (see below). we obtain a much more representative sample of a globular clusters dust. production than previous studies. Lebzelteretal.(2006).
Though our sample is by no means unbiased (see below), we obtain a much more representative sample of a globular cluster's dust production than previous studies. \citet{LPH+06},
.. the closest similar study. focussed on the higher-metallicity Γον 0.7) cluster 47 Tuc and observed. stars. chosen for their luminosity ancl pulsation niodes. resulting in their more homogeneous sample.
the closest similar study, focussed on the higher-metallicity $\sim$ –0.7) cluster 47 Tuc and observed stars chosen for their luminosity and pulsation modes, resulting in their more homogeneous sample.
Prom our diverse sample. we arrive at some significant conclusions: (1) Dust. production in the cluster is limited. to a small number of highlv-evolved. objects.
From our diverse sample, we arrive at some significant conclusions: (1) Dust production in the cluster is limited to a small number of highly-evolved objects.
Several of our 14 targets have no dust emission. corroborating our recent finding that dust production first. occurs. in. stars. above 1000 L. and becomes ubiquitous at ~2000 L. (MyVLD: Joverοἱal.2009:: McDonaldctal. 201Ib:: MeDonaldetal. 2011a)).
Several of our 14 targets have no dust emission, corroborating our recent finding that dust production first occurs in stars above 1000 $_\odot$ and becomes ubiquitous at $\sim$ 2000 $_\odot$ (MvLD; \citealt{BMvL+09}; \citealt{MBvL+11}; \citealt{MBvLZ11}) ).
Stellar temperature would appear to be the main [actor influencing whether dust is produced or not: with the exception of the post-AGB star VI. dust-producing stars all have temperatures of Ix. while dustless stars are all 23950 Ix. However. an <3950intentional selection bias was introduced. to favour cooler targets that may. have been recdelened by dust. (
Stellar temperature would appear to be the main factor influencing whether dust is produced or not: with the exception of the post-AGB star V1, dust-producing stars all have temperatures of $\lesssim$ 3950 K, while dustless stars are all $\gtrsim$ 3950 K. However, an intentional selection bias was introduced to favour cooler targets that may have been reddened by dust. (
2) Despite being lew in number. the metal-rich population appears to produce most of the dust.
2) Despite being few in number, the metal-rich population appears to produce most of the dust.
Assuming V42 is metal-rich. the post-AGB star VI (LIELD 32029) is the only dust-producing star with a metallicity below Fe/LI] = 145. whereas only of cluster stars have Fe/L] > 1.45 (Johnson&Pilachowski2010).
Assuming V42 is metal-rich, the post-AGB star V1 (LEID 32029) is the only dust-producing star with a metallicity below [Fe/H] = –1.45, whereas only of cluster stars have [Fe/H] $>$ –1.45 \citep{JP10}.
. It may be that the metal-poor population possesses a sulliciently high gas-to-dust ratio that dust is not important in their winds.
It may be that the metal-poor population possesses a sufficiently high gas-to-dust ratio that dust is not important in their winds.
We note that the aforementioned temperature selection bias also juases us towards metal-rich stars. which are cooler at a eiven Luminosity. (
We note that the aforementioned temperature selection bias also biases us towards metal-rich stars, which are cooler at a given luminosity. (
3) The dominant form of dust produced in the cluster is ikely to be metallic iron. followed by silicates.
3) The dominant form of dust produced in the cluster is likely to be metallic iron, followed by silicates.
Only the two most metal-rich stars have visible silicate emission features. compared to five other (still comparatively metal-rich) stars hat produce solely metallic iron.
Only the two most metal-rich stars have visible silicate emission features, compared to five other (still comparatively metal-rich) stars that produce solely metallic iron.
The availability of iron to »oduce such opacity is discussed in Section 4.5..
The availability of iron to produce such opacity is discussed in Section \ref{ImplySect}.
As we will discuss in the next section. the inaccuracies in determining mass-loss rates with absolute accuracy means hat we can neither determine the true composition of the dust. produced: within the cluster. nor the clusters. dust-»oduction rate.
As we will discuss in the next section, the inaccuracies in determining mass-loss rates with absolute accuracy means that we can neither determine the true composition of the dust produced within the cluster, nor the cluster's dust-production rate.
We note. however. that the mass-Ioss rates or individual stars in Table 3.λ have increased by a factor of 7-6 from those listed in MvLD.
We note, however, that the mass-loss rates for individual stars in Table \ref{DustyTable} have increased by a factor of $\sim$ 6 from those listed in MvLD.
Ehe summed dust production rate of these stars is approximately that listed in MyvLD. winciplv due to the determination of V42 as metal-rich.
The summed dust production rate of these stars is approximately $\times$ that listed in MvLD, principly due to the determination of V42 as metal-rich.
We remind the reader that we have not necessarily observed. all he clusters clusty stars in this work.
We remind the reader that we have not necessarily observed all the cluster's dusty stars in this work.
refAlBolkcliPie shows w Cen’s stars in context with other globular cluster giants.
\\ref{MBolFeHFig} shows $\omega$ Cen's stars in context with other globular cluster giants.
Metal-poor. 1.2) stars appear to only produce iron dust. with silicates becoming more prevalent with increasing metallicity.
Metal-poor $\lesssim$ –1.2) stars appear to only produce iron dust, with silicates becoming more prevalent with increasing metallicity.
Crystalline silicates appear confined to stars with lower luminosities and there is a lack of luminous metal-poor stars.
Crystalline silicates appear confined to stars with lower luminosities and there is a lack of luminous metal-poor stars.
The low terminal velocities implied by our mocelling are typically lower than the thermal speed. of small molecules and the turbulent velocity in the wind. and much. lower than the pulsation amplitude and. escape velocity of the stars Clable 3)).
The low terminal velocities implied by our modelling are typically lower than the thermal speed of small molecules and the turbulent velocity in the wind, and much lower than the pulsation amplitude and escape velocity of the stars (Table \ref{DustyTable}) ).
This problem has been well-noted in other elobular clusters (MeDonaldetal.2009:DoverοἱAMeDonaldetal.2010. 2011a).
This problem has been well-noted in other globular clusters \citep{MvLD+09,BMvL+09,MSZ+10,MBvLZ11}.
. As gravity is not Cully modelled inDUSTY. it is not clear whether such outllows can be sustained.
As gravity is not fully modelled in, it is not clear whether such outflows can be sustained.
This implies that raciation pressure on dust is probably not the dominant method of accelerating dust from the star. therefore the wind. velocity (and. by implication. the mass-loss rate) may be higher than we model.
This implies that radiation pressure on dust is probably not the dominant method of accelerating dust from the star, therefore the wind velocity (and by implication, the mass-loss rate) may be higher than we model.
Despite this. observations of low-metallicity stars (Marshall2004) have so far followed the same velocityluminositymetallicity relation we use here (eq. (3)):
Despite this, observations of low-metallicity stars \citep{MvLM+04} have so far followed the same velocity--luminosity--metallicity relation we use here (Eq. \ref{VEqun}) );
see also 2000)).
see also \citealt{vanLoon00}) ).
Velocities as low as 3 km + have been found. in Lalo carbon stars (Lagaceectal.2010).
Velocities as low as 3 km $^{-1}$ have been found in Halo carbon stars \citep{LZM+10}.
. Llowever. it is not ‘lear that effective clusty outflows can exist at lower outllow velocities. given the other physical mechanisms at work.
However, it is not clear that effective dusty outflows can exist at lower outflow velocities, given the other physical mechanisms at work.
AleDonaldetal.(2011a) discuss possible means to modify the output wind. parameters listed in Table 3. by changing the input wind parameters (grain size. density aud porosity: wind-driving mechanism: οἱοι).
\citet{MBvLZ11} discuss possible means to modify the output wind parameters listed in Table \ref{DustyTable} by changing the input wind parameters (grain size, density and porosity; wind-driving mechanism; etc.),
while keeping the nmiass-loss rate below limits implied. by the pace of stellar evolution.
while keeping the mass-loss rate below limits implied by the pace of stellar evolution.
In that work. the cluster 47 Tuc was examined.
In that work, the cluster 47 Tuc was examined.
At Fefl]- 0.7. it is somewhat more metal-rich than a Cen.
At [Fe/H] = –0.7, it is somewhat more metal-rich than $\omega$ Cen.
Lere. a combination of necdle-like iron grains ancl a gas-to-dust ratio closer to unity were proposed. to both increase wind velocity without substantially increasing mass-Ioss rate. and to bring the relative fractions of iron ane silicates in the wind. closer to canonical predictions for stars where silicates also condense.
Here, a combination of needle-like iron grains and a gas-to-dust ratio closer to unity were proposed to both increase wind velocity without substantially increasing mass-loss rate, and to bring the relative fractions of iron and silicates in the wind closer to canonical predictions for stars where silicates also condense.
H£ one replaces the assumed spherical metallic iron. grains with elongated. evlinders of the same volume. one can more-cllicicnthy accelerate the wind.
If one replaces the assumed spherical metallic iron grains with elongated cylinders of the same volume, one can more-efficiently accelerate the wind.
Such grains would need to be substantially elongated: a typical
Such grains would need to be substantially elongated: a typical
Eq.(A-3)) is valid if àzb for all voi>0.
\ref{xxx}) ) is valid if $\delta \leq b$ for all $n,m > 0$.
Furthermore. the sumuuation over m is estimated to be sinaller than m times the sumunation over coefficients for which m=0.
Furthermore, the summation over $m$ is estimated to be smaller than $m^{2}$ times the summation over coefficients for which $m=0$.
From Eq.(A-3)). it follows that: As a result of Eq.CÀ-1)) we can estimate an upper limit of the double suni iu Eq.(15)).
From \ref{xxx}) ), it follows that: As a result of \ref{estimate}) ) we can estimate an upper limit of the double sum in \ref{final}) ).
Because the coefficieuts Aonpion| aud |I»,|3,] ave proportional to AAs,quu] and |Bo,)1,9). we cau estimate the sununation over » in Eq.(15)) is proportional to the unperturbed soliton.
Because the coefficients $|\hat{A}_{2n+1,m}|$ and $|\hat{B}_{2n+1,m}|$ are proportional to $|\hat{A}_{2n+1,0}|$ and $|\hat{B}_{2n+1,0}|$, we can estimate the summation over $n$ in \ref{final}) ) is proportional to the unperturbed soliton.
The summation over 0 can be carried out independently, and remains finite because it forms a Ooecometric series.
The summation over $m$ can be carried out independently, and remains finite because it forms a geometric series.
Finally we obtain:
Finally we obtain:
thermal and/or turbulent pressure. as well as the presence of strong magnetic fields might preferentially yield higher mass prestellar cores than in more benign environs (Morris 1993., Stolte et al. 2005..
thermal and/or turbulent pressure, as well as the presence of strong magnetic fields might preferentially yield higher mass prestellar cores than in more benign environs (Morris \cite{morris93}, Stolte et al. \cite{stolte05}, ,
Larson 2006.. Klessen et citeklessenO7)).
Larson \cite{larson06}, , Klessen et \\cite{klessen07}) ).
Along with the Arches and Quintuplet clusters in the GC region. and the NGC 3603YC in the Sagittarius-Carina spiral arm. (Wd 1). located in the Scutum-Crux spiral arm. is one of the very few young. massive starburst clusters in the Milky Way.
Along with the Arches and Quintuplet clusters in the GC region, and the NGC 3603YC in the Sagittarius-Carina spiral arm, (Wd 1), located in the Scutum-Crux spiral arm, is one of the very few young, massive starburst clusters in the Milky Way.
Discovered by Westerlund (1961)). subsequent optical observations of the galactic open cluster Westerlund 1 (Wd 1) suggested an unusually rich population of cool and hot supergiants (Westerlund 1987)). from which a large cluster mass could be inferred.
Discovered by Westerlund \cite{west61}) ), subsequent optical observations of the galactic open cluster Westerlund 1 (Wd 1) suggested an unusually rich population of cool and hot supergiants (Westerlund \cite{west87}) ), from which a large cluster mass could be inferred.
Recent optical spectroscopic. and photometric observations. have confirmed these assertions (Clark Negueruela 2002:: Clark et al.
Recent optical spectroscopic and photometric observations have confirmed these assertions (Clark Negueruela \cite{cn}; ; Clark et al.
2005 (henceforth COS): Negueruela Clark 2005).
\cite{clark05} (henceforth C05); Negueruela Clark \cite{nc}) ).
Located close to the Galactic plane (b = —0.35°) at a distance of ~3-S kkpe. ΤΙ is subject to significant foreground extinction.
Located close to the Galactic plane (b = $-0.35^\circ$ ) at a distance of $\sim$ kpc, 1 is subject to significant foreground extinction.
Thus optical studies of the cluster were limited to the most massive stars of Wdl.
Thus optical studies of the cluster were limited to the most massive stars of Wd1.
COS spectroscopically identified about 50 cluster members with masses in excess of 30MM...
C05 spectroscopically identified about 50 cluster members with masses in excess of $_\odot$.
Adding 150 probable cluster members identified by means of photometry. they estimate that the high-mass stellar content of 11 alone amounts to MM...
Adding 150 probable cluster members identified by means of photometry, they estimate that the high-mass stellar content of 1 alone amounts to $_\odot$.
Assuming a Kroupa IMF to extrapolate from this population. COS then infer a likely total mass of ~I0 MM. for Wdl: directly comparable to the masses of SSCs observed in other galaxies.
Assuming a Kroupa IMF to extrapolate from this population, C05 then infer a likely total mass of $\sim 10^5$ $_{\odot}$ for Wd1; directly comparable to the masses of SSCs observed in other galaxies.
Up to now. however. only the evolved. high-mass stellar population of the cluster has been characterised.
Up to now, however, only the evolved, high-mass stellar population of the cluster has been characterised.
The presence of Wolf-Rayet stars (e.g.. Crowther et citecrowther06:; Skinner et citeskinner06a)). a pulsar indicative of a recent supernova (Skinner et citeskinnerO6b.. Muno et citemunoO6a)). as well as O supergiants. suggest an age between 3 and MMvr for the cluster.
The presence of Wolf-Rayet stars (e.g., Crowther et \\cite{crowther06}; Skinner et \\cite{skinner06a}) ), a pulsar indicative of a recent supernova (Skinner et \\cite{skinner06b}, Muno et \\cite{muno06a}) ), as well as O supergiants, suggest an age between 3 and Myr for the cluster.
Because of a visual foreground extinction of Ay=IO mmag. and the uncertainties in the intrinsic luminosity of the evolved. massive stars. distance determinations to 11 range from 2 to kkpc (COS).
Because of a visual foreground extinction of $_{\rm V} \approx 10$ mag, and the uncertainties in the intrinsic luminosity of the evolved, massive stars, distance determinations to 1 range from 2 to kpc (C05).