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Using the atmospheric parameters. a distance modulus of Gn—M);=13°45. and an interstellar absorption of Ay 0747, we derived masses for our target stars as described in Moehler et al. (20000).
Using the atmospheric parameters, a distance modulus of $(m-M)_0 = \magpt{13}{45}$, and an interstellar absorption of $A_V = \magpt{0}{47}$ , we derived masses for our target stars as described in Moehler et al. \cite{mosw00}) ).
The masses for the helium-rich stars are somewhat underestimated as we used theoretical brightness values for solar-helium atmospheres. which are brighter in the optical range than helium-rich atmospheres.
The masses for the helium-rich stars are somewhat underestimated as we used theoretical brightness values for solar-helium atmospheres, which are brighter in the optical range than helium-rich atmospheres.
The helium abundances plotted in Fig.
The helium abundances plotted in Fig.
5 shows a clear distinction. between helium-poor stars with P26350I. 6Copensquares. f teryxand GrouplAierea starswithheliumabundane MAW eroóBovelsbl Per PEUrdeOQ roup2eRryrer).
\ref{Fig:Teff_loghe} shows a clear distinction between helium-poor stars with $<-1.6$ (open squares, hereafter) and stars with helium abundances close to or above solar (filled triangles, hereafter).
Moehler et al. (2007))
Moehler et al. \cite{modr07}) )
noted an asymmetric spatial distribution of the heltum-rich stars.
noted an asymmetric spatial distribution of the helium-rich stars.
To verify the significance of this effect. we investigated the spatial distribution of the faint HB stars. B. >17. adopting the combined Advanced Camera for Surveys (ACS) and Wide Field Imager (WFI) photometric catalog (Castellani et al. 2007)).
To verify the significance of this effect, we investigated the spatial distribution of the faint HB stars, $B>$ 17, adopting the combined Advanced Camera for Surveys (ACS) and Wide Field Imager (WFI) photometric catalog (Castellani et al. \cite{cast07}) ).
We selected candidate helium-rich and helium-poor HB stars according to the magnitudes of the spectroscopically confirmed samples.
We selected candidate helium-rich and helium-poor HB stars according to the magnitudes of the spectroscopically confirmed samples.
We assumed helium-rich stars to be those with B> 18.35 and helium-poor stars to be those with B <18.35.
We assumed helium-rich stars to be those with $B>$ 18.35 and helium-poor stars to be those with $B\le$ 18.35.
The spatial distribution of the two samples does not exhibit any significant asymmetry in the four quadrants of the cluster.
The spatial distribution of the two samples does not exhibit any significant asymmetry in the four quadrants of the cluster.
There is mild evidence of an overabundance of hot HB stars in general in the southeast
There is mild evidence of an overabundance of hot HB stars in general in the southeast
event data (exchiding point sources) mn a square region centered ou the pixel.
event data (excluding point sources) in a square region centered on the pixel.
The region size was determined by requiring at least SOO net (Lo. background. subtracted) counts in the 0.17.0 keV enerev rauge. but with a naxinimui box size of «183 ACTS pixels. or ο”.
The region size was determined by requiring at least 800 net (i.e. background subtracted) counts in the 0.4–7.0 keV energy range, but with a maximum box size of $\times$ 183 ACIS pixels, or $\times$.
The maxims box size was ouly reached ii the outskirts of the cluster.
The maximum box size was only reached in the outskirts of the cluster.
The total counts iu each region were vtween 1.5 and 2 times the 8SOO count minium to account for backerouud subtraction.
The total counts in each region were between 1.5 and 2 times the 800 count minimum to account for background subtraction.
For each spectrin. a backerouud spectrum was extracted from the blauk sky vackeround event file iu the same region.
For each spectrum, a background spectrum was extracted from the blank sky background event file in the same region.
RME and ARF files were constructed for specific locations on the CCD. with a spacing of 32 aud 50 pixels; respectively.
RMF and ARF files were constructed for specific locations on the CCD, with a spacing of 32 and 50 pixels, respectively.
This was done to account for variations in the response across the CCD. without having to create individual RME and ARF files for each region which would be computationally demanding.
This was done to account for variations in the response across the CCD, without having to create individual RMF and ARF files for each region which would be computationally demanding.
For a given region. the RME and ARF used to fit the spectrum were chosen by selecting the response files with positions closest to the count-weighted average position of the eveuts im each region.
For a given region, the RMF and ARF used to fit the spectrum were chosen by selecting the response files with positions closest to the count-weighted average position of the events in each region.
The spectra were erouped to have 25 counts per biu aud were fitted in ISIS using the thermal model.
The spectra were grouped to have 25 counts per bin and were fitted in ISIS using the thermal model.
The Calactic Lydrogen column deusitv. redshift. and abundance were fixed to ie values found for the full cluster spectrum 77 above).
The Galactic hydrogen column density, redshift, and abundance were fixed to the values found for the full cluster spectrum \ref{sec:full} above).
Ouly the teiiperature and normalization of the inoclel were allowed to vary.
Only the temperature and normalization of the model were allowed to vary.
In ecucral. the errors ou 1ο temperature map are about in the temperature.
In general, the errors on the temperature map are about in the temperature.
Although. for pixels with higher best-fit tempcratures or rose near the edge of the map. the errors are larger. iu rc range of70%.
Although, for pixels with higher best-fit temperatures or those near the edge of the map, the errors are larger, in the range of.
. This is because of the low lieh-energy sensitivity of aud the lower statistics of 1e outer regions.
This is because of the low high-energy sensitivity of and the lower statistics of the outer regions.
The temperature map shown in Figure 8. is colored such that the coolest reeious (ALz| keV) are red.
The temperature map shown in Figure \ref{fig:tmap} is colored such that the coolest regions $kT \approx 4$ keV) are red,
for metal-poor stars. we only use spectra that are not affected by saturation effects. which typically start to be noticable at B,~14.0. and we only include spectra with S/N>10 (which roughly corresponds to B;~ 16.4). because at lower S/N an efficient selection of metal-poor stars. by means of a weak or absent Ca K line. is not feasible anymore.
for metal-poor stars, we only use spectra that are not affected by saturation effects, which typically start to be noticable at $B_J\sim 14.0$, and we only include spectra with $S/N>10$ (which roughly corresponds to $B_J\sim 16.4$ ), because at lower $S/N$ an efficient selection of metal-poor stars, by means of a weak or absent Ca K line, is not feasible anymore.
However. for most other object types. including DAs. we adopt the 56 magnitude limit.
However, for most other object types, including DAs, we adopt the $5\sigma$ magnitude limit.
The atmospheric cutoff at the blue end. and the sharp sensitivity cutoff of the IIHa-J emulsion (red edge") result in a wavelength range of 3200A<A<5300A (see Fig. 3).
The atmospheric cutoff at the blue end, and the sharp sensitivity cutoff of the IIIa-J emulsion (“red edge”) result in a wavelength range of $3200\,\mbox{\AA} < \lambda < 5300\,\mbox{\AA}$ (see Fig. \ref{fig:noisedata_demo}) ).
The spectral resolution of the HES is primarily seemg-limited.
The spectral resolution of the HES is primarily seeing-limited.
For plates taken during good seeing conditions. the pixel spacings chosen in the digitization process result in an under-sampling. so that in these cases the spectral resolution ts also limited by the sampling.
For plates taken during good seeing conditions, the pixel spacings chosen in the digitization process result in an under-sampling, so that in these cases the spectral resolution is also limited by the sampling.
The definition of the HES survey area makes use of the mean star density and average column density of neutral hydrogen for each ESO/SERC field (?)..
The definition of the HES survey area makes use of the mean star density and average column density of neutral hydrogen for each ESO/SERC field \citep{hespaperIII}.
The adopted criteria roughly correspond to galactic latitudes of |5b|> 30°.
The adopted criteria roughly correspond to galactic latitudes of $|b|>30^{\circ}$ .
The declination range covered by the HES is |2.5°>6787.
The declination range covered by the HES is $+2.5^{\circ}>\delta> -78^{\circ}$.
In result. the survey area consists of 380 fields.
In result, the survey area consists of 380 fields.
Between 1989 and 1998. objective-prism plates were taken for all of these. and the plates were subsequently digitized and reduced at Hamburger Sternwarte.
Between 1989 and 1998, objective-prism plates were taken for all of these, and the plates were subsequently digitized and reduced at Hamburger Sternwarte.
As one ESO Schmidt plate covers approximately RIEN5deg on the sky. the nominal survey area is 9500 ddeg?. or the total southern extragalactic sky.
As one ESO Schmidt plate covers approximately $5\times 5\deg^2$ on the sky, the nominal survey area is $9\,500$ $^2$, or the total southern extragalactic sky.
Note. however. that the survey area Is ~25 (?)..
Note, however, that the survey area is $\sim 25$ \citep{hespaperIII}.
Overlapping spectra (hereafter shortly called overlaps) are detected automatically using the direct plate data of the Digitized Sky Survey I (DSS I).
Overlapping spectra (hereafter shortly called overlaps) are detected automatically using the direct plate data of the Digitized Sky Survey I (DSS I).
For each spectrum to be extracted. it is looked for objects in the dispersion direction on the direct plate.
For each spectrum to be extracted, it is looked for objects in the dispersion direction on the direct plate.
If there 1s one. the automatic procedure marks the corresponding spectrum. so that it can later be excluded from further processing. 1f this is desired.
If there is one, the automatic procedure marks the corresponding spectrum, so that it can later be excluded from further processing, if this is desired.
desired for stellar work. since the feature detection and object selection algorithms would get confused otherwise. and a lot of "garbage" would enter the candidate samples.
desired for stellar work, since the feature detection and object selection algorithms would get confused otherwise, and a lot of “garbage” would enter the candidate samples.
The digital HES data base for stellar work consists of —4 million extracted. overlap-free spectra with average S/N>5 in the B; band.
The digital HES data base for stellar work consists of $\sim 4$ million extracted, overlap-free spectra with average $S/N>5$ in the $B_J$ band.
As described in ?).. the calibration of HES B; magnitudes is done plate by plate with individual photometric sequences.
As described in \cite{hespaperIII}, the calibration of HES $B_J$ magnitudes is done plate by plate with individual photometric sequences.
The B; band is formally defined by the spectral sensitivity curve of the Kodak IIIa-J emulsion multiplied with the filter curve of a Schott GG395 filter.
The $B_J$ band is formally defined by the spectral sensitivity curve of the Kodak IIIa-J emulsion multiplied with the filter curve of a Schott GG395 filter.
The overall errors of the HES B; magnitudes. including zero point errors. are less than +0.2 mmag.
The overall errors of the HES $B_J$ magnitudes, including zero point errors, are less than $\pm 0.2$ mag.
Note that B; can be converted to B using the formula which ts valid for main sequence stars in the colour range O1<(BV)<1.6(?).
Note that $B_J$ can be converted to $B$ using the formula which is valid for main sequence stars in the colour range $-0.1<(B-V)<1.6$ \citep{Hewettetal:1995}.
A global dispersion relation for all HES plates was determined by using A-type stars.
A global dispersion relation for all HES plates was determined by using A-type stars.
In HES spectra of these stars the Balmer lines at least up to Hijo. are resolved (see Fig. 3)).
In HES spectra of these stars the Balmer lines at least up to $_{10}$ are resolved (see Fig. \ref{fig:noisedata_demo}) ),
so that a dispersion relation can be derived by comparing the v-positions (scan length in umm) of these limes with the known wavelengths.
so that a dispersion relation can be derived by comparing the $x$ -positions (scan length in $\mu$ m) of these lines with the known wavelengths.
?) used the position of the “red edge" of objective-prism spectra to determine the zero point of the wavelength calibration. but noticed that the position depends on the energy distribution of the object.
\cite{Borraetal:1987} used the position of the “red edge” of objective-prism spectra to determine the zero point of the wavelength calibration, but noticed that the position depends on the energy distribution of the object.
Therefore. in the HES we decided to use a zero point specified by an astrometric transformation between direct plates and spectral plates.
Therefore, in the HES we decided to use a zero point specified by an astrometric transformation between direct plates and spectral plates.
The wavelength calibration is accurate to +10gmm. This corresponds to £4.5 at Hy and £2.3 at A=3500A.
The wavelength calibration is accurate to $\pm 10\,\mu$ m. This corresponds to $\pm 4.5$ at $\gamma$ and $\pm 2.3$ at $\lambda = 3500$.
. Following the approach of ?).. we determine the amplitude of pixel-wise noise as a function of photographic density D plate by plate using A- and F-type stars.
Following the approach of \cite{Hewettetal:1985}, , we determine the amplitude of pixel-wise noise as a function of photographic density $D$ plate by plate using A- and F-type stars.
A straight line fit is done to the spectral region between Hp and Hy (see Fig. 3)).
A straight line fit is done to the spectral region between $\beta$ and $\gamma$ (see Fig. \ref{fig:noisedata_demo}) ).
4 The | G-scatter around this pseudo-continuum fit ts taken as noise amplitude.
The $1\,\sigma$ -scatter around this pseudo-continuum fit is taken as noise amplitude.
In this approach we assume that the scatter is mainly due to noise. since in early-type stars the spectral region under consideration includes only very few absorption lines at the spectral resolution of the HES.
In this approach we assume that the scatter is mainly due to noise, since in early-type stars the spectral region under consideration includes only very few absorption lines at the spectral resolution of the HES.
Moreover. itis expected that the population of A- and F-type stars found at high galactic latitudes is dominated by metal-poor stars. so that metal Imes are usuallyvery weak.
Moreover, itis expected that the population of A- and F-type stars found at high galactic latitudes is dominated by metal-poor stars, so that metal lines are usuallyvery weak.
However. we can not exclude that we
However, we can not exclude that we
other merger types are occurring. but these cannot dominate the merger process.
other merger types are occurring, but these cannot dominate the merger process.
In this final subsection we address the question of whether he asymmetry criteria for locating mergers could. be significant allected by star formation events.
In this final subsection we address the question of whether the asymmetry criteria for locating mergers could be significant affected by star formation events.
While it has oen shown through using the clumpiness index (Conselice 2003). and a comparison between asvmmetries and distorted kinematics (Conseliee et al.
While it has been shown through using the clumpiness index (Conselice 2003), and a comparison between asymmetries and distorted kinematics (Conselice et al.
2000b).. as well as. visual estimates of mergers (Conselice et al.
2000b), as well as visual estimates of mergers (Conselice et al.
2005). that ultra-high asvnunetrics correlate. with merging galaxies. we provide "urther evidence here based on the asvmimetrey. time-scale.
2005), that ultra-high asymmetries correlate with merging galaxies, we provide further evidence here based on the asymmetry time-scale.
We argue this based on the fact that the merger time-scale is roughly στ0.6 Car. and is no higher than ~11 ινε αἲ ος1.2.
We argue this based on the fact that the merger time-scale is roughly $\tau_{\rm m} \sim 0.6$ Gyr, and is no higher than $\sim 1.1$ Gyr at $z < 1.2$.
I£ the asymmetric regions in these galaxies were due to star forming complexes. they would last no longer than a few tens of Myr. as the ages of star formation regions are pies no older than 10-20 Myr (e.g... Palla Galli LOOT).
If the asymmetric regions in these galaxies were due to star forming complexes, they would last no longer than a few tens of Myr, as the ages of star formation regions are typically no older than 10-30 Myr (e.g., Palla Galli 1997).
Thus. within roughly half a Civr. these star forming regions would no longer be distinct from the rest of the galaxy. and as such would not stand out when measuring asvmmetries.
Thus, within roughly half a Gyr, these star forming regions would no longer be distinct from the rest of the galaxy, and as such would not stand out when measuring asymmetries.
We conclude that it is unlikely [or star formation to be the cause of the very high asvnimetrics we attribute to merging galaxies.
We conclude that it is unlikely for star formation to be the cause of the very high asymmetries we attribute to merging galaxies.
Lt is possible that star formation re-occurs throughout our time-scale. but the drop in the star formation rate is faster than the derived. merger fraction. suggesting the two are not coupled.
It is possible that star formation re-occurs throughout our time-scale, but the drop in the star formation rate is faster than the derived merger fraction, suggesting the two are not coupled.
For example. Baldry et al. (
For example, Baldry et al. (
2005) find that the star formation rate declines from 0.15 PMMpe: 7 at roughly «= 100 ~0.015 DMMpe 70230 2~0.
2005) find that the star formation rate declines from 0.15 $^{-1}$ $^{-3}$ at roughly $z = 1$ to $\sim 0.015$ $^{-1}$ $^{-3}$ at $z \sim 0$.
While Conselice et al. (
While Conselice et al. (
2009b) find that the merger fraction declines from fy,=0.13 at οΞ12 to fy=044 at 2=0.2.
2009b) find that the merger fraction declines from $f_{\rm m} = 0.13$ at $z = 1.2$ to $f_{\rm m} = 0.04$ at $z = 0.2$.
While the star formation rate declines by at least a factor of ten. the merger fraction drops by a factor of three.
While the star formation rate declines by at least a factor of ten, the merger fraction drops by a factor of three.
We have made the first empirical measurement of the time-scale for mergers within the CAS system. based. on the detailed: merger fraction. evolution. described. in. Conselice et al. (
We have made the first empirical measurement of the time-scale for mergers within the CAS system, based on the detailed merger fraction evolution described in Conselice et al. (
2009b).
2009b).
These merger fractions are taken from the Extended Groth Strip and COSMOS surveys. and constitute -20.000. ealaxies with stellar masses M;>LOMAL...
These merger fractions are taken from the Extended Groth Strip and COSMOS surveys, and constitute $> 20,000$ galaxies with stellar masses $_{*} > 10^{10}$.
Our major result is that the time-scale for CAS mergers ab ο< Lis between 1.1 Gyr and 0.3 Gye.
Our major result is that the time-scale for CAS mergers at $z < 1$ is between 1.1 Gyr and 0.3 Gyr.
Our best estimated time-scale is Tu,=0.6£0.3 Cyr. which gives the total : − ⊔⊔⊔↓∣⋈⋅↓⋅∪⇂⊔↓⋖⊾↓⋅⋏∙≟⋖⋅↓⋅⊳∖⋯⇍≼∼⊔↓⋅↓⋅↓⊔⋏∙≟⋜∐⋅⋅∖∕↓⋅−≽⋜↧⊳∖↓∖⋯∶∪⋅≤⋗∪∩⊽⊐⊽↾⊁⋡∩↽⊔ ⊳∖⊲↓⊔↓∐⋜⊔⋅⋯↓≻↓⋅∢⊾∖⋰↓∪⊔≱∖∖∖⊽∪↓⋅↳∣⋯≱∖⋖⋅∠⇂∩⊔↓∖⊽−∣⋡⇜⇂∙∖⇁≻↕↓↥↓⇂⇂↓⋜↧⇂↕⋖≱↓↥↿↕↓↥↓⋖⊾− scales. and from changes in the mass density of galaxies at οκ1 (Conselice et al.
Our best estimated time-scale is $\tau_{\rm m} = 0.6\pm0.3$ Gyr, which gives the total number of mergers occurring at $z < 1.2$ as $_{\rm m} = 0.90_{-0.23}^{+0.44}$, similar to previous work based on N-body simulation time-scales, and from changes in the mass density of galaxies at $z < 1$ (Conselice et al.
2007).
2007).
We BM that. on average. a galaxy with stellar mass Al,QUU will increase its stellar mass by due to "emergers.
We calculate that, on average, a galaxy with stellar mass $_{*} > 10^{10}$ will increase its stellar mass by due to these mergers.
This time-scale also rules out the possibility that star formation is the cause of asvmametries seen in galaxies. as our observed time-scales are over an order of magnitude too long to be produced by single star formation events.
This time-scale also rules out the possibility that star formation is the cause of asymmetries seen in galaxies, as our observed time-scales are over an order of magnitude too long to be produced by single star formation events.
The fact that there is a good. agreement: between empirically derived merger time-scales and those based on ealaxv merger simulations suggests that we are beginning to understand the role of mergers within galaxy evolution.
The fact that there is a good agreement between empirically derived merger time-scales and those based on galaxy merger simulations suggests that we are beginning to understand the role of mergers within galaxy evolution.
While in the local universe roughly of galaxies. with masses AL,2107 ave disks. the majority of these contain large bulges. ancl very lew are pure disks (e.g. Conselice 2006b).
While in the local universe roughly of galaxies with masses $_{*} > 10^{10}$ are disks, the majority of these contain large bulges, and very few are pure disks (e.g., Conselice 2006b).
Likely. some of these massive galaxies are undergoing more evolution than others. ancl it is possible that some of the more clustered. systems. such as ellipticals are more likely to undergo more than one merger at z<1.2. which would also help nM the increase in sizes for these galaxies (c.g..resultsTrujillo ct al.
Likely, some of these massive galaxies are undergoing more evolution than others, and it is possible that some of the more clustered systems, such as ellipticals are more likely to undergo more than one merger at $z < 1.2$, which would also help explain the increase in sizes for these galaxies (e.g., Trujillo et al.
2WOT: Duitrago ct al.
2007; Buitrago et al.
2008).
2008).
These show that merecrs are an important part of the galaxy formation process at 2«1.2. when most ealaxies appear to have morphologics similar to todav (e.g. Conselice οἱ al.
These results show that mergers are an important part of the galaxy formation process at $z < 1.2$, when most galaxies appear to have morphologies similar to today (e.g., Conselice et al.
2005).
2005).
Xpplving this methodology to higher redshifts will prove more challenging. due to the active ongoing evolution of these svstems at early. times. and the likelihood that some fraction will undergo more than a single merger.
Applying this methodology to higher redshifts will prove more challenging, due to the active ongoing evolution of these systems at early times, and the likelihood that some fraction will undergo more than a single merger.
This can be probed in the future when large area surveys for galaxy mergers at z215 are carried out.
This can be probed in the future when large area surveys for galaxy mergers at $z > 1.5$ are carried out.
] thank the referee. Patrik Jonsson. for his comments which significantly. improved this paper.
I thank the referee, Patrik Jonsson, for his comments which significantly improved this paper.
L also thank Asa Bluck and Russel White for useful conversations on these topics. and support from the STEC.
I also thank Asa Bluck and Russel White for useful conversations on these topics, and support from the STFC.
for four values of1 and Figure 2. displays X(x) for four values of a.
for four values of $m$ and Figure \ref{fig:plot02-Einasto-profile} displays $\Sigma\left(x\right)$ for four values of $\alpha$.
In both it can be seen clearly that the respective index 1s very important in determining the overall behavior of the curves.
In both it can be seen clearly that the respective index is very important in determining the overall behavior of the curves.
The Sérrsic profile is characterized by a more steeper central core and extended external wing for larger values of the Sérrsic index 7.
The Sérrsic profile is characterized by a more steeper central core and extended external wing for larger values of the Sérrsic index $m$ .
For low values of ;i the central core is more flat and the external wing is sharply truncated.
For low values of $m$ the central core is more flat and the external wing is sharply truncated.
The Einasto profile has a similar behavior. with the difference that the external wings are most spread out.
The Einasto profile has a similar behavior, with the difference that the external wings are most spread out.
Also in the inner region for both profiles with low values of the respectively index we obtain larger values of X4 and X.
Also in the inner region for both profiles with low values of the respectively index we obtain larger values of $\Sigma_{S}$ and $\Sigma$.
However. the Einasto profile seems to be less sensitive to the value of the surface mass density for a given a and radius and in the inner region than the Sérrsic profile.
However, the Einasto profile seems to be less sensitive to the value of the surface mass density for a given $\alpha$ and radius and in the inner region than the Sérrsic profile.