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The shaded regions in Fig.
The shaded regions in Fig.
represent the predictions from our model by taking into account the above mentioned uncertainties on SNR parameters.
\ref{fig:te-tp-sn1006} represent the predictions from our model by taking into account the above mentioned uncertainties on SNR parameters.
Thus, the predicted electron temperature agrees well with fits to NW-1 region in ?,, but smaller, than the temperatures obtained by ??..
Thus, the predicted electron temperature agrees well with fits to NW-1 region in \cite{Long2003}, but smaller, than the temperatures obtained by \cite{Vink2003,Acero2007}.
Part of the discrepancy between the measured and expected electron temperature might be explained by the uncertainties in the determination of SNR parameters such as the external gas density or the shock velocity.
Part of the discrepancy between the measured and expected electron temperature might be explained by the uncertainties in the determination of SNR parameters such as the external gas density or the shock velocity.
Dependence of the electron and proton temperature on acceleration efficiency for SN 1006 is shown in Fig. [7].
Dependence of the electron and proton temperature on acceleration efficiency for SN 1006 is shown in Fig. \ref{fig:te-tp-w-sn1006}. .
Both temperatures quickly decreasing with increasing w. The result shown in Fig.
Both temperatures quickly decreasing with increasing $w$ The result shown in Fig.
[6|corresponds to w= 0.05.
\ref{fig:te-tp-sn1006} corresponds to $w=0.05$ .
Recent detection of SN 1006 NE and SW regions at TeV gamma rays by H.E.S.S. (?) implies thatCRs protons and/or
Recent detection of SN 1006 NE and SW regions at TeV gamma rays by H.E.S.S. \citep{HESSsn1006} implies thatCRs protons and/or
have corrected for dust extinction.
have corrected for dust extinction.
In Sect.
In Sect.
?? we compare these estimates to values reported in previous studies.
\ref{sec:SFRDcomparison} we compare these estimates to values reported in previous studies.
Note. however. that some sources like AGN. which might be included in our dropout samples. add to the total UV luminosity density in the Universe. though do not contribute to the SFRD.
Note, however, that some sources like AGN, which might be included in our dropout samples, add to the total UV luminosity density in the Universe, though do not contribute to the SFRD.
Our fiducial template model is a 100 Myr old continuously star-forming galaxy with a uniform distribution of dust centred around E(B— V)20.25.
Our fiducial template model is a 100 Myr old continuously star-forming galaxy with a uniform distribution of dust centred around $E(B-V)$ =0.25.
This dust distribution was chosen such that the distribution of UV-continuum slopes of the recovered simulated sources matches the distribution of UV-continuum slopes in the real data (see Fig. 3)).
This dust distribution was chosen such that the distribution of UV-continuum slopes of the recovered simulated sources matches the distribution of UV-continuum slopes in the real data (see Fig. \ref{fig:uvcontslopesu}) ).
We test some of the assumptions we made in Sect.
We test some of the assumptions we made in Sect.
2? by checking their influence on the final LFs.
\ref{sec:modelgalaxies} by checking their influence on the final LFs.
As a reference SED we use a 100 Myr old galaxy model with constant star formation and a single dust attenuation value of E(B— V)=0.25.
As a reference SED we use a 100 Myr old galaxy model with constant star formation and a single dust attenuation value of $E(B-V)$ =0.25.
We consider redder (bluer) templates by either increasing (decreasing) the age of the star-forming period. or increasing (decreasing) the amount of dust.
We consider redder (bluer) templates by either increasing (decreasing) the age of the star-forming period, or increasing (decreasing) the amount of dust.
In Fig.
In Fig.
10 the colours of these alternative templates. as they would be measured by the MegaCam ugriz filter set. are shown as a function of redshift.
\ref{fig:colortrackall} the colours of these alternative templates, as they would be measured by the MegaCam $ugriz$ filter set, are shown as a function of redshift.
As the quality of the Schechter fit is high in all cases (y-/dof< 1.0). we present the differences by comparing the Schechter parameters: Some studies (e.g.?) make use of a starburst template instead of a continuously star-forming model.
As the quality of the Schechter fit is high in all cases $\chi^{2}/\rm{dof} < 1.0$ ), we present the differences by comparing the Schechter parameters: Some studies \citep[e.g.][]{st2} make use of a starburst template instead of a continuously star-forming model.
The stellar population in a starburst template is older on average. and therefore the colours will be redder.
The stellar population in a starburst template is older on average, and therefore the colours will be redder.
However. for a template age of 100 Myr the difference in colours is very small.
However, for a template age of 100 Myr the difference in colours is very small.
We compare the Schechter parameters that we measure after using our reference model (i.e. a 100 Myr continuously star-forming template with a dust reddening of E(B- V)=0.25) with a model where we change the star-formation law to a starburst.
We compare the Schechter parameters that we measure after using our reference model (i.e. a 100 Myr continuously star-forming template with a dust reddening of $E(B-V)$ =0.25) with a model where we change the star-formation law to a starburst.
We find the Schechter parameters to change in the directions that are expected for a redder template. as explained above.
We find the Schechter parameters to change in the directions that are expected for a redder template, as explained above.
However the differences are insignificant since they are much smaller than the statistical errors on the Schechter parameters.
However the differences are insignificant since they are much smaller than the statistical errors on the Schechter parameters.
eas in the vicinity of galactic halos.
gas in the vicinity of galactic halos.
This is consistent with the results of ?.. who found that in a hvedrodynamic CDAL simulation. systems with column censities of ~10iem 7. typical of LL systems. are produced. in regions with overdensities of ~LOO at z=3.
This is consistent with the results of \citet{dhkw:99}, who found that in a hydrodynamic CDM simulation, systems with column densities of $\sim 10^{17} \cm2$ , typical of LL systems, are produced in regions with overdensities of $\sim 100$ at $z=3$.
One can see from these simulations that these svstems tend to reside in the weakly non-linear filaments surrounding halos.
One can see from these simulations that these systems tend to reside in the weakly non-linear filaments surrounding halos.
This gas may be enriched. by material ejected by supernovae from. the halos ancl will probably have velocity widths 100kms
This gas may be enriched by material ejected by supernovae from the halos and will probably have velocity widths $\sim 100 \kms$.
A line of sight passing through 1. kpe of 99*A lonized gas with an average over-density of LOO at z=5 acquires enough optical depth to be above the Lyman limit.
A line of sight passing through 1 kpc of $99\%$ ionized gas with an average over-density of 100 at $z=3$ acquires enough optical depth to be above the Lyman limit.
These are conditions that would not be unusual around galaxy mass halos.
These are conditions that would not be unusual around galaxy mass halos.
Further hydrodynamic simulations will be needed to study this non-linear regime in more detail.
Further hydrodynamic simulations will be needed to study this non-linear regime in more detail.
Alore data are required. to identify the origin of LL absorbers at high redshift and it is quite possible that hot eas in galactie halos. cold gas in mini-halos. and uncollapsed eas around halos all play a non-negligible role.
More data are required to identify the origin of LL absorbers at high redshift and it is quite possible that hot gas in galactic halos, cold gas in mini-halos, and uncollapsed gas around halos all play a non-negligible role.
Studies of the ionization state of the gas. its column density. distribution and its kinematics will help identifv the nature of these absorption systems.
Studies of the ionization state of the gas, its column density distribution and its kinematics will help identify the nature of these absorption systems.
A kinematic investigation of sub-DLA svstems provides a generic. direct test of the multiple component mocel.
A kinematic investigation of sub-DLA systems provides a generic, direct test of the multiple component model.
In any multiple component model. most lines of sight pass though only a single component.
In any multiple component model, most lines of sight pass though only a single component.
The only way for DLA systems to be dominated by multiple components is for the column density of a single component to be below the DLA cutoll.
The only way for DLA systems to be dominated by multiple components is for the column density of a single component to be below the DLA cutoff.
This means that at some lower column density. (sub-LLA) the absorption systems must become dominated. by single component encounters.
This means that at some lower column density (sub-DLA) the absorption systems must become dominated by single component encounters.
La our model this happens at HEIL column densities less than 107"em as shown in Figure 7..
In our model this happens at I column densities less than $10^{20} \cm2$, as shown in Figure \ref{fig:num}.
Chis figure shows the fraction of absorption svstenis produced by more than one gas disk as a function of column density.
This figure shows the fraction of absorption systems produced by more than one gas disk as a function of column density.
Phe sub-DLAX systems are very dilferent below a log column density of 20.
The sub-DLA systems are very different below a log column density of $20$.
They. are almost. entirely. composed of single disk svstems.
They are almost entirely composed of single disk systems.
Thus we expect a significant change in the measured. kinematies for these lower column density systems.
Thus we expect a significant change in the measured kinematics for these lower column density systems.
The cdilference in the measured Ae for the low ions is shown in the upper two panels of Figure S..
The difference in the measured $\delv$ for the low ions is shown in the upper two panels of Figure \ref{fig:sub}. .
One sees the transition to many more small Ar svstems.
One sees the transition to many more small $\delv$ systems.
Observing the low-ion Ae in these systems should be a direct test of the multiple component model.
Observing the low-ion $\delv$ in these systems should be a direct test of the multiple component model.
? have studied à svstem at z=2.5 with a log column density of 19.4.
\citet{omea:01} have studied a system at $z=2.5$ with a log column density of $19.4$.
This svstem is neutral and thus by our definition should be refered to as a sub-DLA system even though its column density is less than the truncation value we use in our model.
This system is neutral and thus by our definition should be refered to as a sub-DLA system even though its column density is less than the truncation value we use in our model.
Phe svstem has very simple kineniatics clearly indicating it is a single component svstem: however. it was also selected. for its simple kinematics το study deuterium: so it is unclear if ib is representative of the population.
The system has very simple kinematics clearly indicating it is a single component system; however, it was also selected for its simple kinematics to study deuterium so it is unclear if it is representative of the population.
An unbiased. investigation of svstems like this one Is needed to test the multiple-component scenario.
An unbiased investigation of systems like this one is needed to test the multiple-component scenario.
‘The strong trend with column density seen in our moclel may be an artifact of the fact that we have rather artificially truncated all gas disks at the same value.
The strong trend with column density seen in our model may be an artifact of the fact that we have rather artificially truncated all gas disks at the same value.
A spread in values would tend to weaken the ellect: nevertheless. the trend should. exist for any multiple component model for DLA systems because such a model must always have a larger cross-section to single encounters than multiple encounters.
A spread in values would tend to weaken the effect; nevertheless, the trend should exist for any multiple component model for DLA systems because such a model must always have a larger cross-section to single encounters than multiple encounters.
Thus we believe the kinematics of sub-DLA systems is a critical test of the multiple component model.
Thus we believe the kinematics of sub-DLA systems is a critical test of the multiple component model.
A similar ellect. would. be predicted. for CIV. profiles if they are composed of multiple components.
A similar effect would be predicted for CIV profiles if they are composed of multiple components.
Again. lines of sight through single components are preferentially lower column density. systems.
Again, lines of sight through single components are preferentially lower column density systems.
The case of fou=1 is shown the right. side of Figure 7 [or CIV. associated with DLA and sub DLA systems and or CLV with no associated. low ions.
The case of $f_{sub}=1$ is shown the right side of Figure \ref{fig:num} for CIV associated with DLA and sub DLA systems and for CIV with no associated low ions.
The large dillerence in systems with column densities between 13.5 and 14.5 suggests that it may be possible to identify which svstems contain cold neutral gas from the CIV. kinematics.
The large difference in systems with column densities between $13.5$ and $14.5$ suggests that it may be possible to identify which systems contain cold neutral gas from the CIV kinematics.
This provides vet another diagnostic of our model for the high ions.
This provides yet another diagnostic of our model for the high ions.
The difference between the velocity widths zNecsy for systems with and without low ions is quite striking (Figure S lower three panels).
The difference between the velocity widths $\delv_{CIV}$ for systems with and without low ions is quite striking (Figure \ref{fig:sub} lower three panels).
This trend. holds even if fo.=0 where all svstems ave produced by a single component.
This trend holds even if $f_{sub} = 0$ where all systems are produced by a single component.
In that case the DLA and sub-DLA systems arise from lines of sight passing through the central parts of the halo and thus are more likely to have large zNecsy.
In that case the DLA and sub-DLA systems arise from lines of sight passing through the central parts of the halo and thus are more likely to have large $\delv_{CIV}$.
Lines of sight that do not intersect cold gas are farther from the halo center anc sample a smaller range of velocities.
Lines of sight that do not intersect cold gas are farther from the halo center and sample a smaller range of velocities.
We note however tha since some other state of gas is giving rise to most of the LL systems this gas may also produce CIV and thus complicate this picture.
We note however that since some other state of gas is giving rise to most of the LL systems this gas may also produce CIV and thus complicate this picture.
Further conclusions will not be possible withoualso modelling the other sources of LL absorption (νου, the ones unaccounted for bv our moclel)
Further conclusions will not be possible withoutalso modelling the other sources of LL absorption (i.e., the ones unaccounted for by our model).
measure “supply rates” rather than absolute numbers of infalling satellites we normalise the curves by the number of satellites present at the formation time of the host halo.
measure “supply rates” rather than absolute numbers of infalling satellites we normalise the curves by the number of satellites present at the formation time of the host halo.
The hin line represents the total normalised number of satellites which have been accreted. while the thick line refers to the number of satellites.
The thin line represents the total normalised number of satellites which have been accreted, while the thick line refers to the number of satellites.
The criterion used to define idal clisruption is the reduction in the number of particles within a given satellites. tidal radius to fewer than 15.
The criterion used to define tidal disruption is the reduction in the number of particles within a given satellite's tidal radius to fewer than 15.
This definition is somewhat arbitrary. although ultimately owed. upon the numerical resolution.
This definition is somewhat arbitrary, although ultimately based upon the numerical resolution.
For a more detaile discussion please refer toGKGL.
For a more detailed discussion please refer to.
. The increase in the total number of satellites (thin curve) reflects the richness” of the environment arounc the halo: halos with a steep slope benelit from a constan supply of satellite galaxies wheres hosts that. only show a mild increase draw upon a pool of fewer satellites in their immeciate vicinity.
The increase in the total number of satellites (thin curve) reflects the “richness” of the environment around the halo: halos with a steep slope benefit from a constant supply of satellite galaxies wheres hosts that only show a mild increase draw upon a pool of fewer satellites in their immediate vicinity.
This is illustrated. by the case of halo #11 which lies in a particularly rich. environment. in which several filaments intersect (οἱ.
This is illustrated by the case of halo 1 which lies in a particularly rich environment in which several filaments intersect (cf.
below).
below).
As a consequence. ib aceretes a total of nearly five times the initial number of satellites while simultaneously. showing a high satellite disruption rate.
As a consequence, it accretes a total of nearly five times the initial number of satellites while simultaneously showing a high satellite disruption rate.
The case of halo #33 is similar. but less extreme.
The case of halo 3 is similar, but less extreme.
Llalos 477 and #88. by contrast. experience only moderate infall. ancl in these halos nearly all the satellites survive.
Halos 7 and 8, by contrast, experience only moderate infall, and in these halos nearly all the satellites survive.
Phe situation is illustrated. for ialos #11 and #88 in4.. which shows the orbital xuhis followed by all the satellites from the formation epoch up to the present day.
The situation is illustrated for halos 1 and 8 in, which shows the orbital paths followed by all the satellites from the formation epoch up to the present day.
In the upper panel we clearly see he filament arms that [ους halo #11 ancl how the satellites spiral into the dark matter halo.
In the upper panel we clearly see the filament arms that feed halo 1 and how the satellites spiral into the dark matter halo.
Phe filaments are helical oecause they consist of smaller satellites orbiting a larger vost that is falling into the massive host halo.
The filaments are helical because they consist of smaller satellites orbiting a larger host that is falling into the massive host halo.
The small rut rapid rise in the satellite infall for halo £11 3)) is caused. by a group of satellites falling into the halo for the first time.
The small but rapid rise in the satellite infall for halo 1 ) is caused by a group of satellites falling into the halo for the first time.
In the bottom panel of we feature halo ZéNN: in contrast to halo #11. halo #88 was formed in à relatively isolated region which saw a rapid. collapse.
In the bottom panel of we feature halo 8; in contrast to halo 1, halo 8 was formed in a relatively isolated region which saw a rapid collapse.
We can. however. confirm that even. though the satellite accretion rate in halo 688 is far less the mass of the infalling objects is much higher.
We can, however, confirm that even though the satellite accretion rate in halo 8 is far less the mass of the infalling objects is much higher.
This is derived [rom the fact tha halo 3éNS acquires half its mass by cligesting those few satellites in a time span of approximately 3 Cavers (cf. 1)).
This is derived from the fact that halo 8 acquires half its mass by digesting those few satellites in a time span of approximately 3 Gyrs (cf. ).
We note though that there also exists a significan age dillerence between halo 4211 ancl #288: this explains why ido ZSS satellites are traced for a shorter time leading to he "shorter" lines in4.
We note though that there also exists a significant age difference between halo 1 and 8; this explains why halo 8 satellites are traced for a shorter time leading to the “shorter” lines in.
. However. there still exis noticeable dillerences in the satellite accretion curves for ialos #11 and 488 (cl. 3)
However, there still exist noticeable differences in the satellite accretion curves for halos 1 and 8 (cf. )
) when restricting halo o the first 3.5 Caves of its existence.
when restricting halo 1 to the first 3.5 Gyrs of its existence.
We define the substructure “richness” as the ratio of he final to initial number of satellites. and list its value for cach of the eight halos in1.
We define the substructure “richness” as the ratio of the final to initial number of satellites, and list its value for each of the eight halos in.
. The number of surviving satellites is not directly correlated with the richness. but rather to the orbital characteristics of the aceretecl satellites. as we will demonstrate in detail below.
The number of surviving satellites is not directly correlated with the richness, but rather to the orbital characteristics of the accreted satellites, as we will demonstrate in detail below.
In general. the accreted satellites are not immediately disrupted. but are progressively. destroved over time.
In general, the accreted satellites are not immediately disrupted, but are progressively destroyed over time.
To further investigate the link between: satellite disruption and satellite infall we calculate the ratio of disrupted (or 7dead) satellites to the total number of satellites that fall into the host halo.
To further investigate the link between satellite disruption and satellite infall we calculate the ratio of disrupted (or “dead”) satellites to the total number of satellites that fall into the host halo.
Phe result is presented in5.
The result is presented in.
. Lt is now possible to interpret the slope of this figure as the "rate of disruption" of satellite galaxies.
It is now possible to interpret the slope of this figure as the “rate of disruption” of satellite galaxies.
For all halos this disruption rate (i.e. slope) is very similar.
For all halos this disruption rate (i.e. slope) is very similar.
“Phere seems to be no strongly pronounced correlation with either niws. environment or age.
There seems to be no strongly pronounced correlation with either mass, environment or age.
In this respect. the destruction rate of satellite galaxies appears to be "common" in CDM halos.
In this respect, the destruction rate of satellite galaxies appears to be “common” in CDM halos.
However. there also appears to be à (marginal) trend that host mass is related to the ability to disrupt satellites (within the limited mass range presented here).
However, there also appears to be a (marginal) trend that host mass is related to the ability to disrupt satellites (within the limited mass range presented here).
This can be seen explicitly for halos 2211 ancl #233: destrovs its satellites more ellicienth than 3533. ane is also the more massive of the two.
This can be seen explicitly for halos 1 and 3: 1 destroys its satellites more efficiently than 3 and is also the more massive of the two.
However. these halos also have a large dilference in triaxialitv (refer to 1)).
However, these halos also have a large difference in triaxiality (refer to ).
Conversely. as halo #332) is comparable in mass to halo #44 with a strikinglv similar satellite destruction rate.
Conversely, as halo 3 is comparable in mass to halo 4 with a strikingly similar satellite destruction rate.
But as halo #33 and #44 are close in triaxialitv. we rather suspect the disruption rate to correlate with mass than with triaxialitv.
But as halo 3 and 4 are close in triaxiality, we rather suspect the disruption rate to correlate with mass than with triaxiality.