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Therefore. it is questionable whether the porosity model for the restructuiug phase is correct. | Therefore, it is questionable whether the porosity model for the restructuring phase is correct. |
Significant changes in the porosity of ageregatesOO jas the potential to siguificautlv alter our collision model aud thus the obtained results. | Significant changes in the porosity of aggregates has the potential to significantly alter our collision model and thus the obtained results. |
It is still debated how the porosity aud the fractal dimension evolves duxiug the evolution of dust ageregates. | It is still debated how the porosity and the fractal dimension evolves during the evolution of dust aggregates. |
OO As this is a centre dodsue du determuning the cust properties. we need detailed information on the porosity evolution of dust ageeregates. | As this is a central issue in determining the dust properties, we need detailed information on the porosity evolution of dust aggregates. |
To resolve these issues. we plan to follow the hit&sstick aud restructuring pliases of a particle distribution iu a solf-consisteut way by combining the AMoute Carlo model of ZsDOs with a molecular dynamics code in a follow-up paper. | To resolve these issues, we plan to follow the stick and restructuring phases of a particle distribution in a self-consistent way by combining the Monte Carlo model of ZsD08 with a molecular dynamics code in a follow-up paper. |
The particle sizes at the midplane of the disk are rather μια] (~ 100 microns ifa=10 2) as we see in the previous section. | The particle sizes at the midplane of the disk are rather small $\sim$ 100 microns if $\alpha=10^{-2}$ ) as we see in the previous section. |
The nuestion arises: under what couditious could plauctesimeals form via successive collisions of dust agereeaSÁAOOTOOo:es? | The question arises: under what conditions could planetesimals form via successive collisions of dust aggregates? |
Or row do large enough dust agerceateseo forni that could. under favorable couditious. be concentrated iu e.g. vortices or turbuleut eddies. become solf-gravitatiug. anc form eventually plauetesinials (Johansenetal..2007:Cuzziοal.2008:Youdin.2011:Johansenctal.. 2011)77? | Or how do large enough dust aggregates form that could, under favorable conditions, be concentrated in e.g. vortices or turbulent eddies, become self-gravitating, and form eventually planetesimals \citep{Johansen:2007p65, Cuzzi2008, Youdin2011, Johansen2011}? |
One answer o these questions could be icy agerceates. | One answer to these questions could be icy aggregates. |
OO The molecular dvuamics sumlatious of showed that icy aggregatesCC are very resilient to restructurne. | The molecular dynamics simulations of showed that icy aggregates are very resilient to restructuring. |
They observed sticking between icy aeerceates af a relative velocity as high as 50 in/s. The uncertainty m these simulations ds the mucrophysical parameters of the dev monomers (such as critical displacement. surface enerev. Youug moduluρα ete). | They observed sticking between icy aggregates at a relative velocity as high as 50 m/s. The uncertainty in these simulations is the microphysical parameters of the icy monomers (such as critical displacement, surface energy, Young modulus etc.). |
Recently laboratory experiments were performed using nderon-szed dee monomers by Cundlachoetal.(2011). | Recently laboratory experiments were performed using micron-sized ice monomers by \cite{Gundlach2011}. |
. They ucasured the rolling energv between icv 1iononiers aud it turned out the previously assumed valuey. by Wadaetal.(2008):Suviuna(2008) are in good agreement with the measured laboratory values. | They measured the rolling energy between icy monomers and it turned out the previously assumed values by \cite{Wada2008, Suyama2008} are in good agreement with the measured laboratory values. |
If experiments also confirma that icy agereeates can stick at relative velocitics as high as 50 u/s. that would provide away to formi large chough dust agereeatesOO bevond the suow-lue iu the solar nebula. | If experiments also confirm that icy aggregates can stick at relative velocities as high as 50 m/s, that would provide a way to form large enough dust aggregates beyond the snow-line in the solar nebula. |
Ciouninie(1996) proposed the coucept of lavered accretion isks. | \cite{Gammie1996} proposed the concept of layered accretion disks. |
If the ionization fraction of the eas is not suffBcieut o support maenueto-rotational instability (AIRT - Balbus&Hawley (1991))). the turbulence parameter drops aud a cad-zoue forms at the midplane of the disk. | If the ionization fraction of the gas is not sufficient to support magneto-rotational instability (MRI - \cite{Balbus1991}) ), the turbulence parameter drops and a dead-zone forms at the midplane of the disk. |
The exteut of 16 cleac-zoue is uncertain. as the ionization processes of 1e eas are not well-coustrained. | The extent of the dead-zone is uncertain, as the ionization processes of the gas are not well-constrained. |
For typical TEau disks it can extend between 0.1 - | AU (D'Alessioetal..1998). | For typical TTauri disks it can extend between 0.1 - 4 AU \citep{D'Alessio1998}. |
. Tnside 0.1. AU. the thermal radiation roni the star can seep the gas sufficiently. ionized for MBRI. aud outside 1 AU. the gas surface density is typically below 100 αι”. ierefore cosnic rays can penetrate the disk and keep it MRI active at all heights. | Inside 0.1 AU, the thermal radiation from the star can keep the gas sufficiently ionized for MRI, and outside 4 AU, the gas surface density is typically below 100 $^2$, therefore cosmic rays can penetrate the disk and keep it MRI active at all heights. |
It was proposed by Okuzumi(2009) that negative charges on the surfaces of graius cotπο prohibit growth. | It was proposed by \cite{Okuzumi2009} that negative charges on the surfaces of grains could prohibit growth. |
As we use a \oute Carlo code to ollow the evolution of aggregates. it is possible to include a third particle property: the amount of charges prescut on the erain. | As we use a Monte Carlo code to follow the evolution of aggregates, it is possible to include a third particle property: the amount of charges present on the grain. |
Iu order to follow the charge evolution of the eraius. we necd to solve for the ionization state of the eas (1.0. amount of charges available in the gas phase). how efficicutly these charges are collected by the dust erams aud how the charges affect the relative velocity of the agerceates, | In order to follow the charge evolution of the grains, we need to solve for the ionization state of the gas (i.e. amount of charges available in the gas phase), how efficiently these charges are collected by the dust grains and how the charges affect the relative velocity of the aggregates. |
OO We plan to investigate how dust evolves in a lavered disk model. | We plan to investigate how dust evolves in a layered disk model. |
Suiall dust particles can very efficicuthy sweep up charges in the eas. | Small dust particles can very efficiently sweep up charges in the gas. |
As shown by Turneretal.(2010).. he dead-zoue can esteud to 2 Π for 1 mücron-sized yarticles. but it shrinks below 0.5 I7, for ageregates that are 100 nuücron in size. | As shown by \cite{Turner2010}, the dead-zone can extend to 2 $H_g$ for 1 micron-sized particles, but it shrinks below 0.5 $H_g$ for aggregates that are 100 micron in size. |
Iu a simulation Like the One xeseuted here. this would mean that as the particles grow. he dead-zone shrinks. | In a simulation like the one presented here, this would mean that as the particles grow, the dead-zone shrinks. |
When the dead-zone disappears. he whole disk becomes MBI active and the particles settled to the umidplane might be fragmented aud stirred vack up. | When the dead-zone disappears, the whole disk becomes MRI active and the particles settled to the midplane might be fragmented and stirred back up. |
This could lead to initial oscillations before an equilibrium state is reached. | This could lead to initial oscillations before an equilibrium state is reached. |
excludes aregionalmost as large as Figure 12. Vhe normalised (7r) mask. and aj = 0.5 the excluded16(wo different ο. than the initial forINQS5 (7vr) mask. | resolution $N_{\hbox{\scriptsize side}} =16$ excludes a region almost as large as the initial KQ75 (7yr) mask, and for $x_{\hbox{\scriptsize th}}=0.5$ the excluded region is even smaller than the initial KQ85 (7yr) mask. |
otal cCrrear QU) B decreases. by. increasing Nu h ROS Cr a larger value of riy increases the or N aquaremin = more dilliculties for larger ài dash-dotted eurve. Ehis error in figure 1H.. | Since the reconstruction accuracy decreases by increasing the mask and because a larger value of $x_{\hbox{\scriptsize th}}$ increases the mask, the reconstruction has more difficulties for larger $x_{\hbox{\scriptsize th}}$ as can be seen in figure \ref{Fig:Q_1000lcdm_KQ85_FWHM_000arcmin_nside_16_abh_schwelle}. |
One observes in the upper panel mnean error obtained from the total reconstruction errors within dlaved as α dashed three thresholds ci, are relatively small as distribution of the errors 5. | One observes in the upper panel that the differences in the total reconstruction errors within the mask for the three thresholds $x_{\hbox{\scriptsize th}}$ are relatively small as long as $l_{\hbox{\scriptsize max}} \lesssim 5$. |
But withincreasingmultipoles lux the as a light grey strongly. with wri. Phe | But with increasing multipoles $l_{\hbox{\scriptsize max}}$ the total reconstruction error increases strongly with $x_{\hbox{\scriptsize th}}$ . |
Auge = 82. respectively. the mask for ay, — Ol. otal reconstructionerrors inside typically larger than 1 for Ax ο 15. 13 and11.respectively. | The total reconstruction error within the mask for $x_{\hbox{\scriptsize th}}=0.1$ , 0.5 and 0.9 is typically larger than 1 for $l_{\hbox{\scriptsize max}} \gtrsim 15$, 13 and 11, respectively. |
These represents the largest multipoles Ai, for which a reconstruction can be carried. out in order to see equation (42). In | These represents the largest multipoles $l_{\hbox{\scriptsize max}}$ for which a reconstruction can be carried out in order to avoid constructing random patterns. |
But for cosmological for the 1000 ACDAL of Q(4,,) near one can for a mask threshold implies an total error of a typical The reconstruction | But for cosmological parameter extractions, even values of $Q(l_{\hbox{\scriptsize max}})$ near one can be insufficient, since this implies an total error of a typical temperature fluctuation. |
using the method. of reconstructions have used the covariance fies 2 Othe dillerence (3)). | Up to now, all reconstructions have used the covariance matrix \ref{Eq:covariance_matrix}) ) in equation \ref{Eq:ar_by_A}) ). |
TFhus. we finally compare Thus. for the reconstruction using the covariance matrix algorithm using the covariance method. of direct. inversion. where οἱ [or the larger multipo | Thus, we finally compare the reconstruction results by using the covariance matrix with those of the method of direct inversion, where $A$ is the unit matrix. |
les Choosing the unit matrix renders the due to its smaller method independent of an underlving cosmological model. | Choosing the unit matrix renders the method independent of an underlying cosmological model, see equation \ref{Eq:covariance_matrix}) ). |
figure 15. this comparison is carried out avoid constructing random: patterns. simulations using the INQSS (Tyr) mask »wameter extractions. even values i, = 0.5 at aresolutionof Nog. = 16. | In figure \ref{Fig:Q_1000lcdm_KQ85_FWHM_000arcmin_nside_16_bis_256_kov_und_di} this comparison is carried out for the 1000 $\Lambda$ CDM simulations using the KQ85 (7yr) mask for a mask threshold $x_{\hbox{\scriptsize th}}=0.5$ at a resolution of $N_{\hbox{\scriptsize side}} = 16$. |
ος insullicient.sincethis covariance matrix works better emperature Iuctuation. than the direct. inversion | The reconstruction using the covariance matrix works better than the method of direct inversion for $l_{\hbox{\scriptsize max}} \lesssim 8$. |
[or Aus SS. For Up tonow. all betweenthe two methods is marginal. | For $l_{\hbox{\scriptsize max}} \gtrsim 9$ the difference between the two methods is marginal. |
matrix (4)) in equation. of the Lowest. multipoles the he reconstruction results by matrix is preferable. whereas with those of the the direct inversion can be chosen is the unit matrix. computational elfort. | Thus, for the reconstruction of the lowest multipoles the algorithm using the covariance matrix is preferable, whereas for the larger multipoles the direct inversion can be chosen due to its smaller computational effort. |
In the case of the method. of direct. inversion. the mean value of the total | Inthecase of the method of direct inversion, the mean value of the total |
According to our current understzuddiug. the cenerev-matter couteut of the Universe is dominated by dark coniponents: dark energy (DE) (~ 73%) aud dark matter (DM) (~22% .with ordinary barvouic matter accounting for oulv ~55 of the total (~ critical) density (e.g...sce2)... | According to our current understanding, the energy-matter content of the Universe is dominated by dark components: dark energy (DE) $\sim 73\%$ ) and dark matter (DM) $\sim 22\%$ ), with ordinary baryonic matter accounting for only $\sim 5\%$ of the total $\sim$ critical) density \citep[e.g., see][]{2011ApJS..192...18K}. |
Iu contrast to the poorly understood DE the substance causing the Universe to expand in an accelerated fashion we have physically wellanotivated models for the DAL | In contrast to the poorly understood DE – the substance causing the Universe to expand in an accelerated fashion – we have physically well-motivated models for the DM. |
Among those. the most promising scenario states that the DAI of the Universe consists of thermal relic density of. stable weakly interacting massive particles (WIMPs). | Among those, the most promising scenario states that the DM of the Universe consists of thermal relic density of stable weakly interacting massive particles (WIMPs). |
It is quite niraculous that having particles with masses aud annihilation cross sectious set bv the electroweak scale automatically provide the right DM density after frecze-—out (77). | It is quite miraculous that having particles with masses and annihilation cross sections set by the electroweak scale automatically provide the right DM density after freeze-out \citep{1996PhR...267..195J,2005PhR...405..279B}. |
The WIMP hypothesis. along with its poteutially observable plenomenology. has initiated stroug effort im the particle- and astrophysics comnmmuities to ty to find other than purely gravitational manifestations of DM, | The WIMP hypothesis, along with its potentially observable phenomenology, has initiated strong effort in the particle- and astrophysics communities to try to find other than purely gravitational manifestations of DM. |
So. fu. we have good knowledge of DAL ouly through its C»eravitational effects. starting from the scale of egalaxies aud galaxy clusters. up to the cosmologically largest observable seales (2??).. | So far, we have good knowledge of DM only through its gravitational effects, starting from the scale of galaxies and galaxy clusters, up to the cosmologically largest observable scales \citep{1996PhR...267..195J,2005PhR...405..279B,2009arXiv0901.0632E}. |
Ilowever. as there is already an impressive list of ongoing and upcoming direct DAL detection experiuents along with various indirect nieans of detection (see.ο,foroverview). the hopes are very high that in the nearest future the 1uvsterv of DM night at last be solved. | However, as there is already an impressive list of ongoing and upcoming direct DM detection experiments along with various indirect means of detection \citep[see][for overview]{2010ARA&A..48..495F}, the hopes are very high that in the nearest future the mystery of DM might at last be solved. |
Indeed. the first signals from DAL. particles could potentially have already been detected: the (expected) animal modulation signal from DAMA/LIDRA (7). signals from the CDMS (7). and CoGeNT (7) uuclear recoil experiments. anomalies of the cosmic ray positrons as revealed by PAMELA satellite (2).. or positrons|electrons as obtained by the Fermi satellite (2?) and TESS atmospheric Cherenkov telescope (2).. | Indeed, the first signals from DM particles could potentially have already been detected: the (expected) annual modulation signal from DAMA/LIBRA \citep{2010EPJC...67...39B}, signals from the CDMS \citep{2011PhRvL.106m1302A} and CoGeNT \citep{2011PhRvL.106m1301A} nuclear recoil experiments, anomalies of the cosmic ray positrons as revealed by PAMELA satellite \citep{2009Natur.458..607A}, or positrons+electrons as obtained by the Fermi satellite \citep{2009PhRvL.102r1101A} and HESS atmospheric Cherenkov telescope \citep{2009A&A...508..561A}. |
While the cosmic ray positron anomaly can possibly be explained by TeV-scale DAL (22???).. the signal frou CoGeNT calls for Leht WINMIPs within the mass rauge 712 GeV (?).. | While the cosmic ray positron anomaly can possibly be explained by TeV-scale DM \citep{2008PhRvD..78j3520B,2009PhLB..672..141B,2009NuPhB.813....1C,2009PhRvD..79a5014A,2009PhRvD..79h3528F}, the signal from CoGeNT calls for light WIMPs within the mass range $7-12$ GeV \citep{2011PhRvL.106m1301A}. |
Cousisteut analyses of combined data from CoGeNT and DAMA/LIBRA determine the light DM mass to be 6& GeV (7).. | Consistent analyses of combined data from CoGeNT and DAMA/LIBRA determine the light DM mass to be $6-8$ GeV \citep{2010PhRvD..82l3509H}. |
Although this mass rauge is probed by the CDAIS (2).. NENONIO (2).. and NENONLOO (77) experiments. interpretation of those results (77). requires an ability to reliably recoustruct unclear recoils at very low energy νι as well as precise knowledge of DM distribution aud velocity in the local halo. | Although this mass range is probed by the CDMS \citep{2011PhRvL.106m1302A}, XENON10 \citep{2009PhRvD..80k5005A}, and XENON100 \citep{2010PhRvL.105m1302A,2011arXiv1103.0303X} experiments, interpretation of those results \citep{2010JCAP...02..014K,2010arXiv1011.5432S} requires an ability to reliably reconstruct nuclear recoils at very low energy \citep{2011PhRvD..83e5002S}, as well as precise knowledge of DM distribution and velocity in the local halo. |
Therefore the CoGeNT aud DAMA/LIBRA hints of light DM cannot be ruled out wnambiguoushy. | Therefore the CoGeNT and DAMA/LIBRA hints of light DM cannot be ruled out unambiguously. |
In addition. there is an independent positive clan of the existence of OC10) GeV nues DAL. | In addition, there is an independent positive claim of the existence of (10) GeV mass DM. |
A recent study by ? also suggests that aunihilatine DAI with similarly low asses Gpap=do20 GeV) may give a good match to the observed Fermi aud WALAP haze C2?).. | A recent study by \citet{2011arXiv1102.5095D} also suggests that annihilating DM with similarly low masses $m_{{\rm DM}}=1-20$ GeV) may give a good match to the observed Fermi and WMAP haze \citep{2010ApJ...717..825D,2008ApJ...680.1222D}. |
Towever. all those claims depend strongly ou the knowledge of the profile of the DM halo of our Galaxy aud precise knowledge of local DM density aud lado substrncture | However, all those claims depend strongly on the knowledge of the profile of the DM halo of our Galaxy and precise knowledge of local DM density and halo substructure. |
Thus the several interesting claims of the existence of OCL0) GeV iuass DM call for modclindepeudent tests of the light DAL scenario. | Thus the several interesting claims of the existence of (10) GeV mass DM call for model-independent tests of the light DM scenario. |
Since lower DAL particle masses nuply higher number densities (ωνXOpi /mp). and as the energy input from annihilations scales as x τη oue might expect strong constraints on annililation (Loss section. which Ισ possibly reach below the 5faidard thermal production value of (aye,23«&10 ο + (T). | Since lower DM particle masses imply higher number densities $n_{\rm DM}\propto \Omega_{\rm DM}h^2/m_{{\rm DM}}$ ), and as the energy input from annihilations scales as $\propto n_{{\rm DM}}^2$ , one might expect strong constraints on annihilation cross section, which might possibly reach below the standard thermal production value of $\cs\simeq 3\times10^{-26}$ $^3$ $^{-1}$ \citep{1996PhR...267..195J}. |
The constraints from gamma-ray nicasurements (227777777777). along with CMB bounds (77777).. indicate that this might indeed be the case. | The constraints from gamma-ray measurements \citep{2009PhRvD..79d3507B,2009JCAP...03..009B,2009PhRvD..79h1303B,2009NuPhB.821..399C,2010NuPhB.831..178M,2010NuPhB.840..284C,2010JCAP...03..014P,2010JCAP...07..008H,2010PhRvD..82l3511B,2011JCAP...01..011A,2010PhRvD..82l3519V,2011PhRvD..83l3513Z} along with CMB bounds \citep{2009PhRvD..80b3505G,2009PhRvD..80d3526S,2009JCAP...10..009C,2009A&A...505..999H,2010PThPh.123..853K}, indicate that this might indeed be the case. |
Iu this paper we investigate how well DM annihilation cross sections for WIMPs with masses py=5100 GeV cu be constrained with CAIB measurements. in particular focusing on the lower end of this mass range. | In this paper we investigate how well DM annihilation cross sections for WIMPs with masses $m_{{\rm DM}}=5-100$ GeV can be constrained with CMB measurements, in particular focusing on the lower end of this mass range. |
The main advantage of CMD over other indirect probes. like eiua | The main advantage of CMB over other indirect probes, like gamma |
To describe a galaxy’s morphology we use the bulge-total (B-T) ratio of absolute. WK-bancl. rest. frame. Iuminosity (R=—L&ioaef bae). | To describe a galaxy's morphology we use the bulge-total (B-T) ratio of absolute, K-band, rest frame luminosity $R=L_{K,bulge}/L_{K,total}$ ). |
Although most photometric measurements are made in the D-band. we chose the [x-band because it reflects. the stellar mass quite closely. even at moderate redshifts ο.WKaullmann&Charlot1998:Laceyetal. 2008). | Although most photometric measurements are made in the B-band, we chose the K-band because it reflects the stellar mass quite closely, even at moderate redshifts \citep[e.g.][]{Kauffmann1998,Lacey08}. |
. This choice has the further advantage that the predictions are then relatively insensitive to uncertain details of the current star formation and reddening corrections in the model. | This choice has the further advantage that the predictions are then relatively insensitive to uncertain details of the current star formation and reddening corrections in the model. |
Galaxies are. divided into three broad. morphological types: “spirals” (2« 0.4). “SOs” (0.4Hox 0.6) ancl ~cllipticals” (/?> 0.6). | Galaxies are divided into three broad morphological types: “spirals" $R<0.4$ ), “S0s” $0.4\leq R\leq0.6$ ) and “ellipticals" $R>0.6$ ). |
This classification is. to some extent. arbitrary. but at least. in the DB-band Tranetal.(2001). found that galaxies classified as late Llubble types in the NASA Extragalactic Database are well by a rest-frame B-banel D-T. ratio of less than 0.4. consistent with our definition of spirals. | This classification is, to some extent, arbitrary, but at least in the B-band \citet{Tran2001} found that galaxies classified as late Hubble types in the NASA Extragalactic Database are well by a rest-frame B-band B-T ratio of less than 0.4, consistent with our definition of spirals. |
In addition. we split our two z—0 galaxy populations bv Iuminosity. with the division at Alyy5losh=22.17. i.c. one magnituce fainter than the characteristic luminosity in the Ix-band. (Coleetal.2001:Smith2008.e. | In addition, we split our two $z=0$ galaxy populations by luminosity, with the division at $M_{K}-\rm{5logh}=-22.17$, i.e. one magnitude fainter than the characteristic luminosity in the K-band \citep[e.g.]{Cole01,Smith2008}. |
g... Throughout this work. we refer to these as the and populations. | Throughout this work, we refer to these as the and populations. |
Where the r-band is also shown. we divide the populations at Al,Slogh=19.83 (Blantonctal.2001) and define morphological classes according to the same D-T ratios as in thelx-band. | Where the r-band is also shown, we divide the populations at $M_{r}-\rm{5logh}=-19.83$ \citep{Blanton2001} and define morphological classes according to the same B-T ratios as in theK-band. |
DeLucia&Blaizot note that. in order to assign a morphology to a galaxy with confidence. its merger history must. be well resolved. | \citet{DeLuciaBlaizot2007} note that, in order to assign a morphology to a galaxy with confidence, its merger history must be well resolved. |
They etermine that this condition imposes a lower limit of 41075.5fal. in. stellar mass. which. we apply consistently. to the bright and faint populations in both models. | They determine that this condition imposes a lower limit of $4\times10^{9}h^{-1}M_{\odot}$ in stellar mass, which we apply consistently to the bright and faint populations in both models. |
This cut has virtually no impact on the bright population but it reduces the numbers in the faint population by ~ο94%. leaving us with 1.298.118 bright and 1.589.131 faint galaxies in the AIPA model ancl 1.280.154 bright. 1.598.908 faint galaxies in the Durham moclel. | This cut has virtually no impact on the bright population but it reduces the numbers in the faint population by $\sim92-94\%$, leaving us with 1,298,118 bright and 1,889,131 faint galaxies in the MPA model and 1,280,154 bright, 1,598,908 faint galaxies in the Durham model. |
With our galaxy samples thus defined. we now consider some basic properties of the two mocels. | With our galaxy samples thus defined, we now consider some basic properties of the two models. |
Firstly. we examine their morphological content. that is. the relative fractions of each morphology at a given redshift. | Firstly, we examine their morphological content, that is, the relative fractions of each morphology at a given redshift. |
Fie. | Fig. |
1 tracks the fraction of the total bright galaxy. populations in the Ix-band. (left panel) and r-band (right panel) that are spirals. SOs and ellipticals in cach model. | \ref{fig:morph_frac} tracks the fraction of the total bright galaxy populations in the K-band (left panel) and r-band (right panel) that are spirals, S0s and ellipticals in each model. |
Phe r-band is included here in order to compare with the observational data of Bensonet.al. (2007). | The r-band is included here in order to compare with the observational data of \citet{Benson2007}. |
. Clearly, in. both bands. the two models cdiller considerably. particularly at high redshifts. | Clearly, in both bands, the two models differ considerably, particularly at high redshifts. |
“Phe Durham nmoclel preclicts a substantial population of cllipticals at early times. with steady evolution to a clisk-clominatecd phase after 2~3.4. | The Durham model predicts a substantial population of ellipticals at early times, with steady evolution to a disk-dominated phase after $z\sim3-4$. |
In contrast. the MIA model shows more modest evolution. with spirals remaining the most prevalent structures throughout. | In contrast, the MPA model shows more modest evolution, with spirals remaining the most prevalent structures throughout. |
Even so. the two prescriptions result in fairly similar present cay morphological compositions (sec table 1. for Webancl fractions). | Even so, the two prescriptions result in fairly similar present day morphological compositions (see table \ref{tab:morph_frac} for K-band fractions). |
Fractions in the Durham model are consistent with the ranges defined by the observational data. but the SIPA model seems to produce too many spirals ancl not cnough SOs. | Fractions in the Durham model are consistent with the ranges defined by the observational data, but the MPA model seems to produce too many spirals and not enough S0s. |
We will explain the origin of these ranges in our cliscussion of Fig. 2.. | We will explain the origin of these ranges in our discussion of Fig. \ref{fig:BT}. |
The dillerence. between bands for both models is a small olfset toward higher D/T values in the r-band. which is a consequence of an increased. sensitivity to dust obscuration compared to the K-band. which acts to dim disk light. | The difference between bands for both models is a small offset toward higher B/T values in the r-band, which is a consequence of an increased sensitivity to dust obscuration compared to the K-band, which acts to dim disk light. |
Considering instead the faint galaxy population (Aly5losh=22.17. not shown here). we find a very similar result. | Considering instead the faint galaxy population $M_{K}-\rm{5logh}>-22.17$ , not shown here), we find a very similar result. |
“Phe plot looks almost identical for ALPA galaxies and similar for Durham galaxies. though there is an offset. of about 1015'4 in favour of more spirals at the expense of SOs and cllipticals. | The plot looks almost identical for MPA galaxies and similar for Durham galaxies, though there is an offset of about $10-15\%$ in favour of more spirals at the expense of S0s and ellipticals. |
The disagreement at high. redshift evident in Fig. | The disagreement at high redshift evident in Fig. |
1 mav be explained by the contrasting treatment of. disk instabilities in the two models. | \ref{fig:morph_frac} may be explained by the contrasting treatment of disk instabilities in the two models. |
As outlined in & instabilities trigger a total collapse of the ealactic disk in the Durham model. but only a partial “huckling” in the AIPA model. | As outlined in $\S$ \ref{sec:MERGE}, instabilities trigger a total collapse of the galactic disk in the Durham model, but only a partial “buckling" in the MPA model. |
As some of the results in § 5 demonstrate. this distinction appears to be the root cause of several differences in galaxy morphology in the two mocels. | As some of the results in $\S$ \ref{sec:RESULTS} demonstrate, this distinction appears to be the root cause of several differences in galaxy morphology in the two models. |
several attempts have been mace to quantify morphology through bulge-total measurements. at low redshift, (e.g.Tasca&White2005:Jensonetal. 2008). | Several attempts have been made to quantify morphology through bulge-total measurements at low redshift \citep[e.g.,][]{Tasca2005,Benson2007,Driver2007,Gadotti2008}. |
. In. particular. etal.(2007). showed that the Durham mocdoel (Bowerοἱal.2006) reproduces the luminosity function of disks aud remarkably accurately. | In particular, \citet{Benson2007} showed that the Durham model \citep{Bower2006} reproduces the luminosity function of disks and remarkably accurately. |
Fig. | Fig. |
2 uses their SDSS data to compare the fraction of spirals. SOs and. ellipticals in the local universe (2< 0.12) as a function of (AB. rest-Eramoe) r-band magnitude. with fractions from the two models at z=0. | \ref{fig:BT} uses their SDSS data to compare the fraction of spirals, S0s and ellipticals in the local universe $z<0.12$ ) as a function of (AB, rest-frame) r-band magnitude, with fractions from the two models at $z=0$. |
For this plot. morphologies in the mocels ave defined using rest-frame r-band light for consistency with the data. | For this plot, morphologies in the models are defined using rest-frame r-band light for consistency with the data. |
Benson et al. | Benson et al. |
determined. DT. ratios for their sample of ~9000 SDSS galaxies by fitting two component Dight profiles (bulee | disk) to each image. | determined B/T ratios for their sample of $\sim9000$ SDSS galaxies by fitting two component light profiles (bulge + disk) to each image. |
Analysis of their initial dataset showed that the distribution. of disk. inclination angles appeared to be biased. leading them to conclude that their code was fitting facce-on disks where the bulge varied significantly from. the anticipated. De Vaucouleurs profile. | Analysis of their initial dataset showed that the distribution of disk inclination angles appeared to be biased, leading them to conclude that their code was fitting face-on disks where the bulge varied significantly from the anticipated De Vaucouleurs profile. |
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