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Iu he last few vears. several works have investigated the observational aspects of the CG cavarf problem (Wyse Culmore 1995:: Rocha-Pinto Maciel 1996.. 19972:: Flvnu Morell 1997)).
In the last few years, several works have investigated the observational aspects of the G dwarf problem (Wyse Gilmore \cite{wyse}; Rocha-Pinto Maciel \cite{RPM96}, \cite{RPM97a}; Flynn Morell \cite{flynn}) ).
All these works have folowed the steps delineated by Paecl Patchett (1975)) fex the selection of a unbiased metallicity distribution of loue-lved ciwarfs. * choosing stars in a volume Πίος, sauple aud τιsine photometric metallicities.
All these works have followed the steps delineated by Pagel Patchett \cite{pagel}) ) for the selection of a unbiased metallicity distribution of long-lived dwarfs, by choosing stars in a volume limited sample and using photometric metallicities.
The receut paper by Favata et al. (1997 ))
The recent paper by Favata et al. \cite{favata1}) )
also analyzes he iuetallicity distribution of the solar icielibourhliood.
also analyzes the metallicity distribution of the solar neighbourhood.
The najor novelty of this work is that the authors nace the first attempt to systematically study the ocal metallicity disributiou by usine specrToscopic netallicities.
The major novelty of this work is that the authors made the first attempt to systematically study the local metallicity distribution by using spectroscopic metallicities.
Iu fact. the first local specrToscopic net:itv distribution was made by Rana Basu (1990)).
In fact, the first local spectroscopic metallicity distribution was made by Rana Basu \cite{ranabasu}) ).
Ilowever. their selection criteria WLC not ap]ypriate to define a unbiased sample. axd thei LCT.101v database was largely. heterogeneous.
However, their selection criteria were not approppriate to define a unbiased sample, and their metallicity database was largely heterogeneous.
Receitly. SOIC papers have also ταςe use of a specrToscopic netalliciv distributioi from the data of Edvarcdsso1 et al. (1993)).
Recently, some papers have also made use of a spectroscopic metallicity distribution from the data of Edvardsson et al. \cite{Edv}) ).
Tlowever. this distribution camot be taken as representative either. as Edvardsson ct al.
However, this distribution cannot be taken as representative either, as Edvardsson et al.
have selected heir stars m order to rave nearly equal iuuboers of t10111 in pre-determined metallicity IS.
have selected their stars in order to have nearly equal numbers of them in pre-determined metallicity bins.
The results by Favata et al. (1997))
The results by Favata et al. \cite{favata1}) )
are quite peculiar: stars hotter than 5100 I& present motalicities spaninue the whole rauge of [Fe/TI| vaues expeced for the disk. whereas amongst the cooler objecta. no stars show ο<0.140 dex.
are quite peculiar: stars hotter than 5100 K present metallicities spanning the whole range of [Fe/H] values expected for the disk, whereas amongst the cooler objects, no stars show ${\rm [Fe/H]} < -0.40$ dex.
Their sample comprises 91 stars. 65 of which are cousiered as € ¢warts and 26 are I& απάτες, their separation beige made a 5100 K.
Their sample comprises 91 stars, 65 of which are considered as G dwarfs and 26 are K dwarfs, their separation being made at 5100 K.
In a recent paper Chevalier and Li (1999) pointed out that some of the GRB afterglow light-curves are best modeled when the density of the circum-burst medium is taken to fall off as r7 (this is referred to as the model).
In a recent paper Chevalier and Li (1999) pointed out that some of the GRB afterglow light-curves are best modeled when the density of the circum-burst medium is taken to fall off as $r^{-2}$ (this is referred to as the ).
These afterglows show no evidence for a jet. re. their light-curves follow a power-law decline without any break.
These afterglows show no evidence for a jet, i.e. their light-curves follow a power-law decline without any break.
This is puzzling since collimated outflows are expected in the collapsar model for GRBs (MacFadyen. Woosley Heger 2000).
This is puzzling since collimated outflows are expected in the collapsar model for GRBs (MacFadyen, Woosley Heger 2000).
We offer a possible explanation for this puzzle by showing that the light-curve resulting from the interaction of a jet with a pre-ejected wind falls off as a power-law whose index changes very slowly with time.
We offer a possible explanation for this puzzle by showing that the light-curve resulting from the interaction of a jet with a pre-ejected wind falls off as a power-law whose index changes very slowly with time.
We carry out a detailed modeling of the multi-wavelength afterglow flux data for GRB 990510. which provides the best evidence for a jet propagation in a untform density medium (Harrison et al.
We carry out a detailed modeling of the multi-wavelength afterglow flux data for GRB 990510, which provides the best evidence for a jet propagation in a uniform density medium (Harrison et al.
1999, Stanek et al.
1999, Stanek et al.
1999). to show that effects associated with a finite jet opening-angle are insufficient to explain the observed rapid steepening ofthe light-curve.
1999), to show that effects associated with a finite jet opening-angle are insufficient to explain the observed rapid steepening ofthe light-curve.
In refdynamies we calculate the propagation of a jet ina stratified medium and in refsynchrotron we describe the calculation of the synchrotron emission and afterglow light-curve.
In \\ref{dynamics} we calculate the propagation of a jet ina stratified medium and in \\ref{synchrotron} we describe the calculation of the synchrotron emission and afterglow light-curve.
The dynamical evolution of Jets and its synchrotron emission have been previously investigated by à number of people. e.g. Rhoads (1999), Panaitescu (1999), Sart. Piran Halpern (1999). Moderski. Sikora. Bulik (2000). Huang et al. (
The dynamical evolution of jets and its synchrotron emission have been previously investigated by a number of people, e.g. Rhoads (1999), Panaitescu (1999), Sari, Piran Halpern (1999), Moderski, Sikora, Bulik (2000), Huang et al. (
2000).
2000).
The evolution of the Lorentz factor (DL) can be calculated from the following set of equations where Ó is the half-opening angle of the jet. My. and Cy are the initial mass and Lorentz factor ofthe ejecta. AZ, is the swept-up mass. p(r)=<tr? is the density of the circum-stellar medium. and f=c/c, is the ratio of the speed of light to that of the jet sideways expansion: f Is a parameter of order unity whose effect can be absorbed in Dy. and which has little effect on the light-curve.
The evolution of the Lorentz factor $\Gamma$ ) can be calculated from the following set of equations where $\theta$ is the half-opening angle of the jet, $M_0$, and $\Gamma_0$ are the initial mass and Lorentz factor ofthe ejecta, $M_1$ is the swept-up mass, $\rho(r)=A r^{-s}$ is the density of the circum-stellar medium, and $f=c/c_s$ is the ratio of the speed of light to that of the jet sideways expansion; $f$ is a parameter of order unity whose effect can be absorbed in $\Gamma_0$, and which has little effect on the light-curve.
O is the angle between the velocity vector at the jet edge and the jet axis (in the lab frame) and is determined by the modification of particle trajectory due to the sideways expansion.
$\Theta$ is the angle between the velocity vector at the jet edge and the jet axis (in the lab frame) and is determined by the modification of particle trajectory due to the sideways expansion.
The last equation above expresses the conservation of energy and it applies to an adiabatie shock when the heating of the original baryonic material of rest mass AJy by the reverse shock is ignored.
The last equation above expresses the conservation of energy and it applies to an adiabatic shock when the heating of the original baryonic material of rest mass $M_0$ by the reverse shock is ignored.
The above equations can be combined and rewritten in the following non-dimensional form which is applicable for relativistic as well as non-relativistic jet dynamics Where Ξ/ Rau. yy,= U/Ty. yo= 0/04. and
The above equations can be combined and rewritten in the following non-dimensional form which is applicable for relativistic as well as non-relativistic jet dynamics where $x = r/R_{da}$ , $y_1 = \Gamma/\Gamma_0$ , $y_2 = \theta/\theta_0$ , and
match all stars in each chip. regardless of the filter. in order to find an accurate coordinate transformation between the frames.
match all stars in each chip, regardless of the filter, in order to find an accurate coordinate transformation between the frames.
The matched solutions were then fed to MONTAGE? in order to build a stacked image of each chip.
The matched solutions were then fed to MONTAGE2 in order to build a stacked image of each chip.
In this way we could eliminate all the cosmic rays and obtain an image of the stars with the highest signal-to-noise ratio.
In this way we could eliminate all the cosmic rays and obtain an image of the stars with the highest signal-to-noise ratio.
We ran the DAOPHOT/FIND routine and the PSF-fitting on the stackec image in order to obtain a deep master star list.
We ran the DAOPHOT/FIND routine and the PSF-fitting on the stacked image in order to obtain a deep master star list.
The master list was then used as input for ALLFRAME (Stetson1994).. which simultaneously determines the brightness for stars 11 all frames while enforcing one set of centroids and one transformation between all images.
The master list was then used as input for ALLFRAME \citep{ste94}, which simultaneously determines the brightness for stars in all frames while enforcing one set of centroids and one transformation between all images.
Finally. all the magnitudes for each star were normalized to a reference frame and averaged together. and the photometric error was derived as the standard deviation of the repeated measures.
Finally, all the magnitudes for each star were normalized to a reference frame and averaged together, and the photometric error was derived as the standard deviation of the repeated measures.
We note here that the presence of saturated stars iu these deep images is the major source of artefacts causing spurious detections. especially in the core regions where most of the red giant stars are located.
We note here that the presence of saturated stars in these deep images is the major source of artefacts causing spurious detections, especially in the core regions where most of the red giant stars are located.
In order to clea our catalogues from false detections. we used a statistical approach similar to the one proposed by Cooletal.(1996). that employs the sharpness (5/7) parameter provided as a output by ALLFRAME as the source quality diagnostic.
In order to clean our catalogues from false detections, we used a statistical approach similar to the one proposed by \cite{co96}, that employs the sharpness $sh$ ) parameter provided as an output by ALLFRAME as the source quality diagnostic.
By plotting s/f as a function of the magnitude we founc that spurious objects. detected around the haloes and along diffraction spikes of saturated stars. have sharpness values that differ from the ones representative of bona-fide stars. which typically have —0.15<sf«0.15.
By plotting $sh$ as a function of the magnitude we found that spurious objects, detected around the haloes and along diffraction spikes of saturated stars, have sharpness values that differ from the ones representative of bona-fide stars, which typically have $-0.15 < sh < 0.15$.
In Figure 2. we show that the effectiveness goodness of the selection in sharpness (left panel) in identifying false detections is confirmed by the fact that the objects with large sharpness values have also larger photometric errors (right panel).
In Figure \ref{sharp} we show that the effectiveness goodness of the selection in sharpness (left panel) in identifying false detections is confirmed by the fact that the objects with large sharpness values have also larger photometric errors (right panel).
We finally transformed the instrumental F606W (V) and F814W (I) magnitudes to the VEGAMAG system following the prescriptions of Siriannietal.(2005) and Holtzmanetal.(1995) for the ACS and WFPC2 samples. respectively.
We finally transformed the instrumental F606W (V) and F814W (I) magnitudes to the VEGAMAG system following the prescriptions of \cite{si05} and \cite{ho95} for the ACS and WFPC2 samples, respectively.
The relative star coordinates of both samples were transformed to the absolute right ascension and declination values (J2000) using the wide field catalogue published by Pollardetal.(2005) as secondary astrometric standard catalogue.
The relative star coordinates of both samples were transformed to the absolute right ascension and declination values (J2000) using the wide field catalogue published by \cite{pol05} as secondary astrometric standard catalogue.
In Figure we show the color-magnitude diagram (CMD) of the entire 9.data set.
In Figure \ref{cmd} we show the color–magnitude diagram (CMD) of the entire data set.
The WFPC?2 final catalogue (left panel) contains 4995 objects.
The WFPC2 final catalogue (left panel) contains 4995 objects.
The same data set have already been reduced by DeMarchi&Paresce(1996) and later by Piotto&Zoccali (1999).
The same data set have already been reduced by \cite{dem96} and later by \cite{pio99}.
. By comparing our photometry with the CMD of the latter (see their Figure 1). no differences are evident.
By comparing our photometry with the CMD of the latter (see their Figure 1), no differences are evident.
The consistency of the two photometric analyses 18 further confirmed by a direct comparison of their published lummosity function (LF: see Table 4) and the one calculatec in this work for the WF2 chip (see Section 3. for a detailec discussion).
The consistency of the two photometric analyses is further confirmed by a direct comparison of their published luminosity function (LF; see Table 4) and the one calculated in this work for the WF2 chip (see Section \ref{lumin} for a detailed discussion).
Due to the long exposure time of the WFPC2 images. the stars at the turn-off (TO) level in this data set are saturated.
Due to the long exposure time of the WFPC2 images, the stars at the turn-off (TO) level in this data set are saturated.
Ii order to obtain a CMD in the WFPC? area with a I magnitude range comparable with that of the ACS data set. we decidec to complement our observations with a V. vs. (V—7) grounc based catalogue from Rosenbergetal.(2000)http://www.
In order to obtain a CMD in the WFPC2 area with a I magnitude range comparable with that of the ACS data set, we decided to complement our observations with a $V$ vs. $(V-I)$ ground based catalogue from \cite{ros00}.
astro.unipd.it/globulars/.. This data set was obtained using the 1.0mm Jacobus Kapteyn Telescope (JKT) at La Palma (Canary Island).
This data set was obtained using the $1.0$ m Jacobus Kapteyn Telescope (JKT) at La Palma (Canary Island).
We transformed the standard Johnson V./ magnitudes of the JKT catalogue to the WFPC2? VEGAMAG system adopting color term as derived by comparison of all the non-saturated stars in the WFPC2 chips that were also measured in the ground-based images.
We transformed the standard Johnson $V, I$ magnitudes of the JKT catalogue to the WFPC2 VEGAMAG system adopting color term as derived by comparison of all the non-saturated stars in the WFPC2 chips that were also measured in the ground-based images.
No color term is necessary for the 7 band.
No color term is necessary for the $I$ band.
The uncertainties in the V. zero points and in the (V—7) color transformations are of the order of 0.007 mag.
The uncertainties in the $V$ zero points and in the $(V-I)$ color transformations are of the order of $0.007$ mag.
Due to the extremely low crowding conditions of the area covered by the WFPC2 and to the relative proximity of M110 (Ruy=44 kkpe: Harris 1996). the completeness of the ground based catalogue in this area is expected to be very high.
Due to the extremely low crowding conditions of the area covered by the WFPC2 and to the relative proximity of 10 $R_{\rm sun}=4.4$ kpc; Harris 1996), the completeness of the ground based catalogue in this area is expected to be very high.
By comparing the observed LFs from the WFPC2 and JKT data in the same area. we found a good agreement in the magnitude range 19<7«20 (corresponding to the mass range of approximately 0.6M..<M<0.7M..).
By comparing the observed LFs from the WFPC2 and JKT data in the same area, we found a good agreement in the magnitude range $19 < I < 20$ (corresponding to the mass range of approximately $0.6M_{\odot}<M<0.7M_{\odot}$ ).
We therefore decided to use the JKT catalogue for stars with 7<20 and the WFPC2 catalogue at fainter magnitudes.
We therefore decided to use the JKT catalogue for stars with $I < 20$ and the WFPC2 catalogue at fainter magnitudes.
In the right panel of Figure 9 we show the CMD as derived from the photometric reduction of the ACS data set.
In the right panel of Figure \ref{cmd} we show the CMD as derived from the photometric reduction of the ACS data set.
The final catalogue contains 56812 objects.
The final catalogue contains 56812 objects.
The MS of the cluster is clearly visible and well sampled well above the TO that occurs at [ο17.5.
The MS of the cluster is clearly visible and well sampled well above the TO that occurs at $\sim17.5$.
A population of candidate blue stragglers departing from the TO along a bright extension of the MS is also recognizable.
A population of candidate blue stragglers departing from the TO along a bright extension of the MS is also recognizable.
For /<16 saturation starts to occur. thus making the photometry of brighter stars unreliable.
For $I< 16$ saturation starts to occur, thus making the photometry of brighter stars unreliable.
According to Piotto&Zoceali(1990)... due to the Galactic latitude of 110 (5=23). the contamination from foreground/background stars is small and should not effect the LF.
According to \cite{pio99}, due to the Galactic latitude of 10 $b=23^{\circ}$ ), the contamination from foreground/background stars is small and should not effect the LF.
On the other hand Pollardetal.(2005).. using wide field imaging of evolved stellar populations. claim that field contamination. mainly from the Galactic disk. should be taken into account.
On the other hand \cite{pol05}, using wide field imaging of evolved stellar populations, claim that field contamination, mainly from the Galactic disk, should be taken into account.
Since no direct measurement of the field contamination in our magnitude range is possible. we used a statistical approach.
Since no direct measurement of the field contamination in our magnitude range is possible, we used a statistical approach.
A catalogue of stars using the Galactic model from Robinetal.(2003) covering an area of | square degree around the cluster center wasused’.
A catalogue of stars using the Galactic model from \cite{rob03} covering an area of 1 square degree around the cluster center was.
. After scaling for the ACS and WFPC2 FOV. we found a contamination of 425 and 159 stars in our magnitude range respectively for each sample.
After scaling for the ACS and WFPC2 FOV, we found a contamination of 425 and 159 stars in our magnitude range respectively for each sample.
This means that. even in the worst case of the WFPC? sample. where the number of sources ts small. field contamination would be of the order of ~3%. and thus can be neglected.
This means that, even in the worst case of the WFPC2 sample, where the number of sources is small, field contamination would be of the order of $\sim 3\,\%$, and thus can be neglected.
The MS mean ridge lines for the two data sets (open circles in Figure 9)) were computed by using a 2nd order polynomial to fit the locus of MS stars. after rejecting those farther than 20 from the best fit line. where c 1s the combined photometric uncertainty in V and 7.
The MS mean ridge lines for the two data sets (open circles in Figure \ref{cmd}) ) were computed by using a ${\rm nd}$ order polynomial to fit the locus of MS stars, after rejecting those farther than $2\,\sigma$ from the best fit line, where $\sigma$ is the combined photometric uncertainty in $V$ and $I$.
Following De Marchi Pulone (2007: hereafter DPO7). we applied this same o—-clipping approach to identify the bona-fide stars to be used in computing the LF and MF of the cluster and. in order to increase the statistics. we decided to accept as bona-fide stars all those within 2.50 of the ridge line of best fit.
Following De Marchi Pulone (2007; hereafter DP07), we applied this same $\sigma-$ clipping approach to identify the bona-fide stars to be used in computing the LF and MF of the cluster and, in order to increase the statistics, we decided to accept as bona-fide stars all those within $2.5\,\sigma$ of the ridge line of best fit.
The catalogue obtained after this procedure. containing 464407 and 43390 stars respectively in the ACS and WFPC? field. will be used hereafter to derive the LF and MF.
The catalogue obtained after this procedure, containing 407 and 390 stars respectively in the ACS and WFPC2 field, will be used hereafter to derive the LF and MF.
We mark as shaded regions in the CMDs of Figure 9. the limits below which the photometric completeness. as detailed in 22.3. falls below calculation.
We mark as shaded regions in the CMDs of Figure \ref{cmd} the limits below which the photometric completeness, as detailed in 2.3, falls below calculation.
The MS ridge line that we derived in this way agrees very well with the models of Baraffe et al. (
The MS ridge line that we derived in this way agrees very well with the models of Baraffe et al. (
1997).
1997).
The level of
The level of
7. noted a correlation between the spectra of galaxies and the dominance of their central. bulge component.
\citet{Morgan1957} noted a correlation between the spectra of galaxies and the dominance of their central bulge component.
? elt that a shortcoming of the Hubble classification scheme was that it was not a strong indicator of spectral class.
\citet{Morgan1958} felt that a shortcoming of the Hubble classification scheme was that it was not a strong indicator of spectral class.
In order to rectily this. ? devised a galaxy classification svsten owed upon the central light concentration compared to its overall light. distribution.
In order to rectify this, \citet{Morgan1958} devised a galaxy classification system based upon the central light concentration compared to its overall light distribution.
This concentration classification scheme involved analysing the Dux of galaxies to determine he degree of concentration of the central component.
This concentration classification scheme involved analysing the flux of galaxies to determine the degree of concentration of the central component.
The »urpose of this scheme was to study the colour-concentration correlation in an attempt to identify ealactic evolutionary states.
The purpose of this scheme was to study the colour-concentration correlation in an attempt to identify galactic evolutionary states.
Due to the concentration parameter's direct relation with spectral class and type of stellar population. the concentration parameter was also found to be indicative of Formation history and properties. such as velocity dispersion. ealaxy size. luminosity. and (more recently) central black hole mass (?)..
Due to the concentration parameter's direct relation with spectral class and type of stellar population, the concentration parameter was also found to be indicative of formation history and properties, such as velocity dispersion, galaxy size, luminosity, and (more recently) central black hole mass \citep{Graham2001}.
Extending Morgans pioneering work. ?— proposed a new statistical measure of asymmetry. in conjunction with a revised. paranetrisation of Morgans concentration index.
Extending Morgan's pioneering work, \citet{Conselice2000b} proposed a new statistical measure of asymmetry, in conjunction with a revised parametrisation of Morgan's concentration index.
‘This classification svstem was based on the desire to classify galaxies quantitatively at a range of redshifts.
This classification system was based on the desire to classify galaxies quantitatively at a range of redshifts.
Asvnimetry was defined by rotating à galaxy 180. about a central axis and finding the absolute sum of the normalised residuals.
Asymmetry was defined by rotating a galaxy $\degrees$, about a central axis and finding the absolute sum of the normalised residuals.
This method measures the high frequency structure within each galaxy. whilst also considering the symmetry.
This method measures the high frequency structure within each galaxy, whilst also considering the symmetry.
The measure of asvmametrey focuses primarily on morphological shape. and has a strong correlation with colour. congruent with Morgan's concentration parameter.
The measure of asymmetry focuses primarily on morphological shape, and has a strong correlation with colour, congruent with Morgan's concentration parameter.
Xs such. this property has a correlation with both star formation and merger history.
As such, this property has a correlation with both star formation and merger history.
7. introduced. one additional. morphological measure sensitive to high spatial frequency clumpiness.
\citet{Conselice2003} introduced one additional morphological measure sensitive to high spatial frequency clumpiness.
“Phis parameter is defined by comparing a galaxy to a smoothed image of itself.
This parameter is defined by comparing a galaxy to a smoothed image of itself.
In doing so. the clumpiness parameter quantifies galaxy morphology in a manner which rellects star forming regions and evolutionary history.
In doing so, the clumpiness parameter quantifies galaxy morphology in a manner which reflects star forming regions and evolutionary history.
This parameter distinguishes between varying types of galaxies ancl thus. partially. resembles Llubble’s classification svstem.
This parameter distinguishes between varying types of galaxies and thus, partially, resembles Hubble's classification system.
Llowever. the clumpiness parameter quantifies galaxy morphology with respect to intrinsic characteristics and not morphology alone.
However, the clumpiness parameter quantifies galaxy morphology with respect to intrinsic characteristics and not morphology alone.
7? combined the high spatial frequeney ebumpiness parameter with both the asymmetry. index and the concentration index to complete what is now called the CAS classification svstem.
\citet{Conselice2003} combined the high spatial frequency clumpiness parameter with both the asymmetry index and the concentration index to complete what is now called the CAS classification system.
Underlving the CAS system's empirical nature lies the fundamental physics which governs its individual €. X. and S. components.
Underlying the CAS system's empirical nature lies the fundamental physics which governs its individual C, A, and S, components.
The CAS system hishlights the intrinsic nature of galaxies by considering their light distributions and spectral class.
The CAS system highlights the intrinsic nature of galaxies by considering their light distributions and spectral class.
The observable properties of galaxies are a function of their merger histories. masses and environments. cach of whieh are rellected in the CAS svstem.
The observable properties of galaxies are a function of their merger histories, masses and environments, each of which are reflected in the CAS system.
His fitting to apply this new classification. method to the theoretically oedieted: properties. of galaxies. and use it as à gauge o determine where our current understanding of galaxy ormation and evolution is correct and where it is deficient.
It is fitting to apply this new classification method to the theoretically predicted properties of galaxies and use it as a gauge to determine where our current understanding of galaxy formation and evolution is correct and where it is deficient.
Galaxy simulations are an integral tool that can help interpolate between known stages of formation history. and hus further our understanding of galaxy. evolution.
Galaxy simulations are an integral tool that can help interpolate between known stages of formation history, and thus further our understanding of galaxy evolution.
Within the observational community. the CAS svstem is become one of the most wiclely-usecl measures of galaxy morphology (??)..
Within the observational community, the CAS system has become one of the most widely-used measures of galaxy morphology \citep{Hern2008, Bertone2009}.
Since the completion of the combined CAS svstem. it has been applied: to numerous ealaxies including the 113 galaxies observed by 2..
Since the completion of the combined CAS system, it has been applied to numerous galaxies including the 113 galaxies observed by \citet{Frei1996}. .
However. it has not vet been applied systematically to hieh-resolution computational galaxy simulations as a method of comparison between observations ancl simulations.
However, it has not yet been applied systematically to high-resolution computational galaxy simulations as a method of comparison between observations and simulations.
In. this work. we clevclop a software package patterned on the ? and ? CAS system. calibrated on an optimised training set. and. applied to high resolution galaxy simulations.
In this work, we develop a software package patterned on the \citet{Conselice2000b} and \citet{Conselice2003} CAS system, calibrated on an optimised training set, and applied to high resolution galaxy simulations.
We show that the simulated galaxies exhibit both similarities ane differences to real galaxies. and highlight the intrinsic physical process that are responsible for the differences.
We show that the simulated galaxies exhibit both similarities and differences to real galaxies, and highlight the intrinsic physical process that are responsible for the differences.
Ins refSimSamp we describe our simulated. galaxy samples.
In \\ref{SimSamp} we describe our simulated galaxy samples.