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For iustauce. in the SN-blowout scenario. uetals tend to ect ejected into the ICAL for galaxies less nassive than 10? AD. 6 or LOt! NL. €2).. while in the uetalauixiug scenario. the ceutral regions aud outermost regious of the «wait galaxy should have the same metal abudance.
For instance, in the SN-blowout scenario, metals tend to get ejected into the IGM for galaxies less massive than $^{9}$ $_{\odot}$ \citep{maclow99} or $^{11}$ $_{\odot}$ \citep{strickland04}, while in the metal-mixing scenario, the central regions and outermost regions of the dwarf galaxy should have the same metal abundance.
Therefore. abundance gradieuts (or a lack hereof) im the extended gaseous disks of chwart galaxies nav help to untangle the physical origin of the massnetallicity relalon.
Therefore, abundance gradients (or a lack thereof) in the extended gaseous disks of dwarf galaxies may help to untangle the physical origin of the mass-metallicity relation.
NGC 2915 is oue of the most extreme examples of a ue compact dwiuf galaxy with an extended gascous disk (Moeurer e al.
NGC 2915 is one of the most extreme examples of a blue compact dwarf galaxy with an extended gaseous disk (Meurer et al.
1996: hereafter M96)).
1996; hereafter \nocite{meurer96}) ).
This nearby (1.1 Mpe. Meurer ο al.
This nearby (4.1 Mpc, Meurer et al.
2003 )) dwarf galaxwv has an III disk that extends 5 times bevoud the optical stellar conrponeut (12 Ipc for the gas: 2.3 ο for the stars: sec Figure 1l. aud Table | for a list of its full properties).
2003 \nocite{meurer03}) ) dwarf galaxy has an HI disk that extends 5 times beyond the optical stellar component (12 kpc for the gas; 2.3 kpc for the stars; see Figure 1, and Table 1 for a list of its full properties).
Its total barvonic lass (gas plus stars: ~10° ML.) puts it on the lieh-anass cud of the spectrum of dwarf ealaxies. aud its tota dynamical mass eives it one of the hiehest-known nasx-o-light ratios for a gas-ricli galaxy (M96).
Its total baryonic mass (gas plus stars; $\sim10^{9}$ $_{\odot}$ ) puts it on the high-mass end of the spectrum of dwarf galaxies, and its total dynamical mass gives it one of the highest-known mass-to-light ratios for a gas-rich galaxy (M96).
Recent Πα tages of NGC 2915 have revealed several s11all pockets of star formation embedded in its extended gaseous disk at projected radi of — 3kpc that otherwise coutaius few stars (see Figure 1).
Recent $\alpha$ images of NGC 2915 have revealed several small pockets of star formation embedded in its extended gaseous disk at projected radii of $\sim3$ kpc that otherwise contains few stars (see Figure 1).
Iu addition. new. very deep (ter) ~ll ks) uuages from the
In addition, new, very deep $_{exp}$ = $\sim14$ ks) images from the
However, much more information is contained in the oscillation spectra of these large number of red giants.
However, much more information is contained in the oscillation spectra of these large number of red giants.
In this Letter, we analyze the properties of red giant adiabatic oscillation spectra and relate them with their evolutionary state.
In this Letter, we analyze the properties of red giant adiabatic oscillation spectra and relate them with their evolutionary state.
Stellar models were computed with the code ATON3.1
Stellar models were computed with the code ATON3.1
We extracted a source catalogue from the SpUDS image using the software SEXTRACTOR (Bertin Arnouts 1996) with a ‘mexhat’ kernel.
We extracted a source catalogue from the SpUDS image using the software SEXTRACTOR (Bertin Arnouts 1996) with a `mexhat' kernel.
This type of kernel is very efficient in crowded fields, as it facilitates source deblending.
This type of kernel is very efficient in crowded fields, as it facilitates source deblending.
Considering only the region overlapping the 3.6 Lm map, and excluding edges and regions around bright stars, our 4.5 zm catalogue contains 67,937 sources.
Considering only the region overlapping the 3.6 $\rm \mu m$ map, and excluding edges and regions around bright stars, our 4.5 $\rm \mu m$ catalogue contains 67,937 sources.
We measured aperture photometry for all our sources and obtained aperture corrections using the curve of flux growth for isolated stars in the field.
We measured aperture photometry for all our sources and obtained aperture corrections using the curve of flux growth for isolated stars in the field.
Our derived total 4mmagnitudes —referenced as [4.5] hereafter- correspond to measured 4-arcsec-diameter aperture magnitudes corrected by a constant -0.31 mag.
Our derived total magnitudes –referenced as [4.5] hereafter-- correspond to measured 4-arcsec-diameter aperture magnitudes corrected by a constant -0.31 mag.
This aperture size is usual for IRAC photometry (see e.g. [bert et al.
This aperture size is usual for IRAC photometry (see e.g. Ilbert et al.
2010), as it constitutes a good balance between directly measuring most of the source encircled energy and minimising contamination from close neighbours (the IRAC point-spread function full width half maximum is ~1.9 arcsec at )).
2010), as it constitutes a good balance between directly measuring most of the source encircled energy and minimising contamination from close neighbours (the IRAC point-spread function full width half maximum is $\sim$ 1.9 arcsec at ).
We performed simulations to assess the completeness and reliability of our catalogue.
We performed simulations to assess the completeness and reliability of our catalogue.
To test completeness, we used the IRAF task ‘gallist’ to generate a list of 50,000 artificial objects following a power-law distribution between magnitudes 18 and 26.
To test completeness, we used the IRAF task `gallist' to generate a list of 50,000 artificial objects following a power-law distribution between magnitudes 18 and 26.
We then created a set of 100 mock maps based on the real image, in each of which we have randomly inserted 500 of the artificial objects (using ‘mkobjects’ in IRAF).
We then created a set of 100 mock maps based on the real image, in each of which we have randomly inserted 500 of the artificial objects (using `mkobjects' in IRAF).
We then ran SExtractor on each of these mock maps with the same configuration file used for the real image, and checked the fraction of artificial sources recovered as a function of magnitude.
We then ran SExtractor on each of these mock maps with the same configuration file used for the real image, and checked the fraction of artificial sources recovered as a function of magnitude.
Through this procedure, we determined that our catalogue is and complete to magnitudes [4.5]—22.4 and 24.0, respectively.
Through this procedure, we determined that our catalogue is and complete to magnitudes [4.5]=22.4 and 24.0, respectively.
We tested the reliability of our catalogue by repeating the source extraction procedure on the negative of the umimage, and considering the fraction of negative sources versus magnitude.
We tested the reliability of our catalogue by repeating the source extraction procedure on the negative of the image, and considering the fraction of negative sources versus magnitude.
At [4.5]222.4 mag, the percentage of spurious sources is below0.
At [4.5]=22.4 mag, the percentage of spurious sources is below.
5%.. At fainter magnitudes [4.5]=23.5-24.0 mag, this percentage rises to around10%.
At fainter magnitudes [4.5]=23.5-24.0 mag, this percentage rises to around.
. However, after imposing that the 4.5umsources have acounterpart in the independently extracted K-band catalogue (see below), the fraction of spurious sources becomes negligible even at such faint magnitudes.
However, after imposing that the sources have acounterpart in the independently extracted $K$ -band catalogue (see below), the fraction of spurious sources becomes negligible even at such faint magnitudes.
We measured 3.6 jum aperture photometry for all the um--selected sources running Sextractor in dual-image mode.
We measured 3.6 $\rm \mu m$ aperture photometry for all the -selected sources running Sextractor in dual-image mode.
The derived total 3.6 wm magnitudes correspond to the measured 4-arcsec-diameter aperture magnitudes corrected by a constant -0.27 mag (as also determined through the curve of flux growth of isolated stars).
The derived total 3.6 $\rm \mu m$ magnitudes correspond to the measured 4-arcsec-diameter aperture magnitudes corrected by a constant -0.27 mag (as also determined through the curve of flux growth of isolated stars).
To compile the corresponding UV through near-IR photometry for our galaxies, we extracted an independent catalogue based on the UDS K-band image, and ran SExtractor on dual-image mode on the U,B,V,R,i,z,J and H-band maps, using the position of the K-band sources.
To compile the corresponding UV through near-IR photometry for our galaxies, we extracted an independent catalogue based on the UDS $K$ -band image, and ran SExtractor on dual-image mode on the $U, B, V, R, i, z, J$ and $H$ -band maps, using the position of the $K$ -band sources.
In these bands, we obtained total magnitudes from aperture-corrected 2-arcsec aperture magnitudes in all cases.
In these bands, we obtained total magnitudes from aperture-corrected 2-arcsec aperture magnitudes in all cases.
All magnitudes have been corrected for galactic extinction.
All magnitudes have been corrected for galactic extinction.
We finally cross-correlated the catalogue (that included 3.6 ym photometry) with the K-band catalogue (that contained U-band through K-band photometry), with a matching radius r—1.5 arcsec.
We finally cross-correlated the catalogue (that included 3.6 $\rm \mu m$ photometry) with the $K$ -band catalogue (that contained $U$ -band through $K$ -band photometry), with a matching radius $r=1.5$ arcsec.
The final overlapping area of all our datasets is 0.60 deg?.
The final overlapping area of all our datasets is 0.60 $^2$.
Our catalogue with K-band counterparts over this area contains 52,693 sources.
Our catalogue with $K$ -band counterparts over this area contains 52,693 sources.
We note that the depth of the near-IR images matches very well the depth of the IRAC data in the UDS.
We note that the depth of the near-IR images matches very well the depth of the IRAC data in the UDS.
Within the clean overlapping area of 0.60 deg?, the K-band catalogue allows us to identify more than of the sources with [4.5|«22.4 mag.
Within the clean overlapping area of 0.60 $^2$, the $K$ -band catalogue allows us to identify more than of the sources with $<22.4$ mag.
For the deeper [4.5]«24.0 mag catalogue, the percentage of identifications is9296.
For the deeper $<24.0$ mag catalogue, the percentage of identifications is.
. Our reliability tests performed on the catalogues suggest that most of the remaining unidentified sources are likely to be spurious IRAC sources.
Our reliability tests performed on the catalogues suggest that most of the remaining unidentified sources are likely to be spurious IRAC sources.
We excluded galactic stars from our sample via a colour- diagram.
We excluded galactic stars from our sample via a colour-colour diagram.
As discussed by McLure et al. (
As discussed by McLure et al. (
2009), the use of the SExtractor stellarity parameter SSTAR alone is not a secure way to segregate stars CLASS.from z galaxies when using ground-based data, as some of the galaxies are compact and could also have large stellarity parameters (CLASS_STAR>0.8— 0.9).
2009), the use of the SExtractor stellarity parameter STAR alone is not a secure way to segregate stars from $z$ galaxies when using ground-based data, as some of the galaxies are compact and could also have large stellarity parameters $\rm CLASS\_STAR>0.8-0.9$ ).
Instead, colour segregation is much more reliable.
Instead, colour segregation is much more reliable.
Fig.
Fig.
1 shows that stars form a separate sequence in the (B—J) versus (J—[3.6]) colour-colour diagram.
\ref{fig_stargal} shows that stars form a separate sequence in the $(B-J)$ versus $(J-[3.6])$ colour-colour diagram.
Through this colour diagnostic, we determined that 2372 out of our 52,693 sources are galactic stars.
Through this colour diagnostic, we determined that 2372 out of our 52,693 sources are galactic stars.
Note, however, that this colour-colour diagram cannot segregate red dwarf stars, which are a potential source of contamination for high-z galaxy samples (cf.
Note, however, that this colour-colour diagram cannot segregate red dwarf stars, which are a potential source of contamination for $z$ galaxy samples (cf.
Section refsec,ge5)).
Section \\ref{sec_zge5}) ).
Basically all of the 2372 colour-segregated objects have CLASS_STAR> 0.8, but they constitute less than a half of the total number of sources with CLASS_STAR>0.8 within our sample (in our case, we measured the CLASS_STAR parameter on the K-band images).
Basically all of the 2372 colour-segregated objects have $\rm CLASS\_STAR>0.8$ , but they constitute less than a half of the total number of sources with $\rm CLASS\_STAR>0.8$ within our sample (in our case, we measured the $\rm CLASS\_STAR$ parameter on the $K$ -band images).
After the star separation,
After the star separation,
The CC models consist of NOC = 20 star clusters aud are diced according to a Plummer distribution (Plummer1911:kroupa2008).
The CC models consist of $N_{\rm 0}^{\rm CC}$ = 20 star clusters and are diced according to a Plummer distribution \citep{plum1911, krou08}.
. The cutoll radius. ROG. of the CC is four times the Plummer radius. Cr.
The cutoff radius, $R_{\rm cut}^{\rm CC}$, of the CC is four times the Plummer radius, $R_{\rm pl}^{\rm CC}$.
The initial velocity distribution of the CC models is chosen such that the CC is in virial equilibrium.
The initial velocity distribution of the CC models is chosen such that the CC is in virial equilibrium.
A detailed description of the generation of initial coordinates (space and. velocity) for Plummer models is given in the appendix of Aarsethetal.(1971).
A detailed description of the generation of initial coordinates (space and velocity) for Plummer models is given in the appendix of \cite{aarseth}.
. The individual star clusters building up the CC's in our simulations are Pluuuner spheres witli a Pluuuuer radius of 1?M= [pe and a cutolf radius of ROG=20 pe.
The individual star clusters building up the CCs in our simulations are Plummer spheres with a Plummer radius of $R_{\rm pl}^{\rm SC} = 4$ pc and a cutoff radius of $R_{\rm cut}^{\rm SC} = 20$ pc.
Each star cluster has a nass of ABS=0.05xM and consists of NPC = 1000000 particles.
Each star cluster has a mass of $M^{\rm SC} = 0.05 \times M^{\rm CC}$ and consists of $N_{\rm 0}^{\rm SC}$ = 000 particles.
The velocity distribution of tlie ----—cliviclual star clusters is chosen to be initially in virial equilibrium.
The velocity distribution of the individual star clusters is chosen to be initially in virial equilibrium.
Iun total. we cousidered 27different models (see Tables 2 and 3)). which are denoted x qz. herexisthemunb in units of 109 NL... and z is the CC Plummer radius. Rey . in pc.
In total, we considered 27 different models (see Tables \ref{tbl-inipar} and \ref{tbl-2}) ), which are denoted $x$ $y$ $z$, where $x$ is the number of the initial configuration, i.e. the detailed distribution of the individual star clusters in the CC, $y$ is the CC mass, $M^{\rm CC}$, in units of $^{6}$ $_{\odot}$ and $z$ is the CC Plummer radius, $R_{\rm pl}^{\rm CC}$ in pc.
Figure 3. visualizes the CC parameter range covered in the ACC vs. üt space.
Figure \ref{figmatrix} visualizes the CC parameter range covered in the $M^{\rm CC}$ vs. $R_{\rm pl}^{\rm CC}$ space.
Figure | illustrates the cilferent initial distributions.
Figure \ref{figinimodel} illustrates the different initial distributions.
Figure laa aud b are the same initial distribution of star clusters that were scaled according to their "n. while Figure [ec shows a less concentrated distribution of star clusters.
Figure \ref{figinimodel}a a and b are the same initial distribution of star clusters that were scaled according to their $R_{\rm pl}^{\rm CC}$, while Figure \ref{figinimodel}c c shows a less concentrated distribution of star clusters.
We carried out 27 differeut numerical sunulatious to get au estimate of the iuflueuce of varying initial CC conditions.
We carried out 27 different numerical simulations to get an estimate of the influence of varying initial CC conditions.
All calculations start at the perigalactic passage at /j = —0.568 Cyr ancl are calculated up to the current position of 22119.
All calculations start at the perigalactic passage at $t_{\rm 0}$ = –9.568 Gyr and are calculated up to the current position of 2419.
The mereine process of mocel 1100 is shown in Figure 5 as contour plots ou the xv-plaue to illustrate the detailed evolution of the merging process.
The merging process of model 100 is shown in Figure \ref{fig_timeevol} as contour plots on the xy-plane to illustrate the detailed evolution of the merging process.
The suapshots were taken at ÉÜ — d — ty = 0. 50. 100. 300. 760 and 1500 Myr.
The snapshots were taken at $t$ ' = $t$ – $t_{\rm 0}$ = 0, 50, 100, 300, 760 and 1500 Myr.
Ας 50 Myr the mereer object is already in he process of formiug. but the majority of star clusters are still iudividual objects.
At $t$ ' = 50 Myr the merger object is already in the process of forming, but the majority of star clusters are still individual objects.
In the course ol time more aud more star clusters are captured by the mereer object.
In the course of time more and more star clusters are captured by the merger object.
Thus the mereer object jecomies more extended.
Thus the merger object becomes more extended.
After 10 crossing times (/ = 760 Myr) there are still 2 unmerged star clusters in the vicinity of the mereer object.
After 10 crossing times $t$ ' = 760 Myr) there are still 2 unmerged star clusters in the vicinity of the merger object.
In. the last snapshot at / = 1500 Myr the mereine orocess is completed aud 19 out of 20 star cluster have mereecl forming a smooth extended object.
In the last snapshot at $t$ ' = 1500 Myr the merging process is completed and 19 out of 20 star cluster have merged forming a smooth extended object.
One star cluster escaped the merging process.
One star cluster escaped the merging process.
It follows the merger object on its orbit arowud the lilkv Way at a distance of about Li kpe (at / = 9.568 Cyr).
It follows the merger object on its orbit around the Milky Way at a distance of about 14 kpc (at $t$ ' = 9.568 Gyr).
The timescale of the merging process depeuds ou the iuitial CC mass.the CC size aud he distribution of star clusters within the CC.
The timescale of the merging process depends on the initial CC mass,the CC size and the distribution of star clusters within the CC.
For model 1100.50 percent of the
For model 100,50 percent of the
process remains uncertain (e.g.Croftetal.2002:Wollmeicretal. 2003).
process remains uncertain \citep[e.g.][]{Croft02, Kol03}.
. Together with the increase in numerical resolution provided by our simulations. it is of interest to see how refinements in. physical. modelling modify. the predictions of DLA properties in a CDM universe.
Together with the increase in numerical resolution provided by our simulations, it is of interest to see how refinements in physical modelling modify the predictions of DLA properties in a CDM universe.
In this paper. we focus on the abundance of DLAs in the redshift range z=O)4.5.
In this paper, we focus on the abundance of DLAs in the redshift range $z=0-4.5$.
Phe present work extends and complements earlier numerical work by Ixatzetal.(1996) and Ciardneretal.(2001).
The present work extends and complements earlier numerical work by \citet{Katz96-dla} and \citet{Gar01}.
Physical properties of DLAs such as their star formation rates. metallicities. and their relation to galaxies will be presented. elsewhere.
Physical properties of DLAs such as their star formation rates, metallicities, and their relation to galaxies will be presented elsewhere.
The paper is organised as follows.
The paper is organised as follows.
In Section 2.. we μείον describe the numerical parameters of our simulation set.
In Section \ref{section:simulation}, we briefly describe the numerical parameters of our simulation set.
We then present. the evolution of the total neutral hivelrogen mass density in the simulations in Section 3..
We then present the evolution of the total neutral hydrogen mass density in the simulations in Section \ref{section:OmegaHI}.
In Section 4.. we describe how we compute the column clensity ancl DLA cross-section as a function of total halo mass.
In Section \ref{section:cross}, we describe how we compute the column density and DLA cross-section as a function of total halo mass.
In Section 5.. we determine the cumulative abundance of DLAs. and discuss the evolution of DLA abundance from := 45105=0.
In Section \ref{section:abundance}, we determine the cumulative abundance of DLAs, and discuss the evolution of DLA abundance from $z=4.5$ to $z=0$.
Vhe column. density distribution function is presented in Section 6..
The column density distribution function is presented in Section \ref{section:dist}.
Finally. we summarise and discuss the implication of our work in Section 7..
Finally, we summarise and discuss the implication of our work in Section \ref{section:discussion}.
We analyse a large set of cosmological SPL simulations that diller in box size. mass resolution and feedback strength. as summarise in Table 1..
We analyse a large set of cosmological SPH simulations that differ in box size, mass resolution and feedback strength, as summarised in Table \ref{table:sim}.
In particular. we consider box sizes ranging [rom 3.375 to 005Mpe on a side. with particle numbers between 2Lit? and 2324. allowing us to probe eascous mass resolutions in the range 4.2lot to 1.110A1 ο
In particular, we consider box sizes ranging from 3.375 to $100\,h^{-1}{\rm Mpc}$ on a side, with particle numbers between $2\times 144^3$ and $2\times 324^3$, allowing us to probe gaseous mass resolutions in the range $4.2 \times 10^4$ to $1.1\times 10^9\,h^{-1}{\rm M}_\odot$ .
simulations are partly taken [rom a study of the cosmic star formation history by Springel&Llernqtuist (2003b).. supplemented by additional runs with weaker or no ealactic winds.
These simulations are partly taken from a study of the cosmic star formation history by \citet{SH02c}, supplemented by additional runs with weaker or no galactic winds.
Phe joint analysis of this series of simulations allows us to significantly. broaden the range of spatial and niassescales that we can probe compared to what is presently attainable within a single simulation.
The joint analysis of this series of simulations allows us to significantly broaden the range of spatial and mass-scales that we can probe compared to what is presently attainable within a single simulation.
There are three main new features to our simulations.
There are three main new features to our simulations.
First. we use a new “conservative entropy formulation of SPL (Springe&Lernquist2002) which explicitly conserves entropy (in regions without shocks). as well as momentum and energv. even when one allows for Cully acaptive smoothing lengths.
First, we use a new “conservative entropy” formulation of SPH \citep{SH02a} which explicitly conserves entropy (in regions without shocks), as well as momentum and energy, even when one allows for fully adaptive smoothing lengths.
This formulation mocerates the overcooling problem present in earlier formulations of SPILL (secalsoYoshidaetal.2002:Pearceοἱ1999:Croft 2001).
This formulation moderates the overcooling problem present in earlier formulations of SPH \citep[see also][]{Yoshida02, Pearce99, Croft01}.
. Second. highly over-dense gas particles are treated with an ellective sub-resolution model for the ISM. as cleseribec by Springe&Llernquist(2003a).
Second, highly over-dense gas particles are treated with an effective sub-resolution model for the ISM, as described by \citet{SH02b}.
. In this mocdel. the dense ISAL is pictured to be a two-phase Iuid consisting of col clouds in pressure. equilibrium with a hot ambient. phase.
In this model, the dense ISM is pictured to be a two-phase fluid consisting of cold clouds in pressure equilibrium with a hot ambient phase.
Each eas particle represents à statistical mixture of these phases.
Each gas particle represents a statistical mixture of these phases.
Cold clouds grow by radiative cooling out of the ho medium. and this material forms the reservoir of barvons available for star formation.
Cold clouds grow by radiative cooling out of the hot medium, and this material forms the reservoir of baryons available for star formation.
Once star formation occurs. the resulting supernova explosions deposit energy into the ho eas. heating it. and also evaporate cold clouds. transferring cold gas back into the ambient phase.
Once star formation occurs, the resulting supernova explosions deposit energy into the hot gas, heating it, and also evaporate cold clouds, transferring cold gas back into the ambient phase.
This establishes a tigh seli-regulation mechanism for star formation in the ISM.
This establishes a tight self-regulation mechanism for star formation in the ISM.