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Also. because the models were tit to the same data their results should not be coadded: they are. both presented to demonstrate that similar results are obtained with using independent codes. | Also, because the models were fit to the same data their results should not be coadded: they are both presented to demonstrate that similar results are obtained with using independent codes. |
Since the agreement is so good. we express no preference of one model versus the other (multiply-broken power-law versus spline). | Since the agreement is so good, we express no preference of one model versus the other (multiply-broken power-law versus spline). |
However. we note that the spline model has a narrower flux density window function about each knot. and thus represents the differential number counts of the knot position slightly more accurately locally than the power-law model. | However, we note that the spline model has a narrower flux density window function about each knot, and thus represents the differential number counts of the knot position slightly more accurately locally than the power-law model. |
For comparison to other number counts models. one can either (i) select the fits with the FIRAS prior. which assumes that the remaining portion of the CFIRB unaccounted for by our priorless fits is encompassed in the range between the upper limit on dN/dS at 0.1 mJy and the 2 miy knot (tat 250 gum) — this method is simpler: or (ii) select the fits without the CFIRB prior. in which case the prior should be applied independently. | For comparison to other number counts models, one can either (i) select the fits with the FIRAS prior, which assumes that the remaining portion of the CFIRB unaccounted for by our priorless fits is encompassed in the range between the upper limit on $dN/dS$ at 0.1 mJy and the 2 mJy knot (at 250 ) – this method is simpler; or (ii) select the fits without the CFIRB prior, in which case the prior should be applied independently. |
The latter does not require that the model share the same assumptions about the number counts at low flux densities as our fits. | The latter does not require that the model share the same assumptions about the number counts at low flux densities as our fits. |
Our fits are compared with other measurements in figures and 6.. | Our fits are compared with other measurements in figures \ref{fig:brokpow} and \ref{fig:brokpowoliver}. . |
Ignoring the lowest knot (where only an upper limit is available). our fits predict a CFIRB flux density of 0.54+0.08. 0.39+0.06. and 0.16+0.03MJysr.! from all sources down to 2 mJy in the three bands: the dominant error in all cases is due to the 15 per cent calibration uncertainty of SPIRE. | Ignoring the lowest knot (where only an upper limit is available), our fits predict a CFIRB flux density of $0.54 \pm 0.08$, $0.39 \pm 0.06,$ and $0.16
\pm 0.03\, \mathrm{MJy}\, \mathrm{sr}^{-1}$ from all sources down to 2 mJy in the three bands; the dominant error in all cases is due to the 15 per cent calibration uncertainty of SPIRE. |
The contribution from each flux range is shown in figure 7.. | The contribution from each flux range is shown in figure \ref{fig:cfirb_contrib}. |
The CFIRB from Fixsenetal. integrated over the SPIRE bands is 0.85£0.19. 0.65£0.19. and 0.39x0.10 MIy !. respectively. so our fits therefore account or 64416.60x20 and 43+12 percent in the SPIRE 250. 350. and 500 bbands. respectively. | The CFIRB from \citet{Fixsen:1998} integrated over the SPIRE bands is $0.85 \pm
0.19$, $0.65 \pm 0.19$, and $0.39 \pm 0.10$ MJy $^{-1}$, respectively, so our fits therefore account for $64 \pm 16, 60 \pm 20$ and $43 \pm 12$ percent in the SPIRE 250, 350, and 500 bands, respectively. |
We expect to resolve a smaller fraction of the CFIRB at longer wavelengths because the size of the SPIRE beam is proportional to wavelength. and hence the 500 bband is more confused. | We expect to resolve a smaller fraction of the CFIRB at longer wavelengths because the size of the SPIRE beam is proportional to wavelength, and hence the 500 band is more confused. |
Here the errors are dominated by the uncertainty in the FIRAS measurement. | Here the errors are dominated by the uncertainty in the FIRAS measurement. |
We tind marginalized values for the instrumental noise that are 1.02. 1.1. and 1.01 times he values given in table |. at 250. 350. and 500yam. respectively. giving a 47 of 42 for 3 degrees of freedom. | We find marginalized values for the instrumental noise that are 1.02, 1.1, and 1.01 times the values given in table \ref{tbl:data} at 250, 350, and 500, respectively, giving a $\chi^2$ of 4.2 for 3 degrees of freedom. |
Hence. our instrumental noise values are consistent with the Nguyenetal.(2010). prior. | Hence, our instrumental noise values are consistent with the \citet{Nguyen:2010} prior. |
Our basic tool for estimating the importance of a particular systematic is to compute the Alog£ between the wwith and without the etfect for maps the same size and depth as our data. | Our basic tool for estimating the importance of a particular systematic is to compute the $\Delta \log \mathcal{L}\,$ between the with and without the effect for maps the same size and depth as our data. |
We use the PO9 best fit model as a basis for this computation. | We use the P09 best fit model as a basis for this computation. |
Recall that à Alog£ of 0.5 corresponds roughly to a lo statistical error. | Recall that a $\Delta \log \mathcal{L}\,$ of 0.5 corresponds roughly to a $1 \sigma$ statistical error. |
Because ditferent parts of the map are sampled by ditterent bolometers. and the beam shape varies across the bolometer array. the effective beam will vary over the map. | Because different parts of the map are sampled by different bolometers, and the beam shape varies across the bolometer array, the effective beam will vary over the map. |
We evaluated. this etfect by choosing 200 random pixels in our maps and computing the fractional contribution of each bolometer to each pixel. | We evaluated this effect by choosing 200 random pixels in our maps and computing the fractional contribution of each bolometer to each pixel. |
We then built per-bolometer maps from our Neptune observations. and combined these to tind the ettective beam at each of these locations. | We then built per-bolometer maps from our Neptune observations, and combined these to find the effective beam at each of these locations. |
The beam varies across the map in a complicated fashion because even in our deepest map each pixel only samples a limited subset of bolometers. | The beam varies across the map in a complicated fashion because even in our deepest map each pixel only samples a limited subset of bolometers. |
This produces significant variation in the wwith position. | This produces significant variation in the with position. |
In general. the ccomputed for the bolometer-averaged beam does not have to be the same as the ccomputed for each bolometer and then averaged across the array (which is the oof the entire map). | In general, the computed for the bolometer-averaged beam does not have to be the same as the computed for each bolometer and then averaged across the array (which is the of the entire map). |
To evaluate the importance of thisvariation. we compare the ffor the average beam to the ccomputed for all 200 pixelsand then averaged. | To evaluate the importance of thisvariation, we compare the for the average beam to the computed for all 200 pixelsand then averaged. |
The Alog£ of this comparison is « 0.01. so for our analysis this is negligible. | The $\Delta \log \mathcal{L}\,$ of this comparison is $< 0.01$ , so for our analysis this is negligible. |
slightly less than οι. | slightly less than $M_{\rm
Ch}$. |
We can now ask what encproduct would have emerged had AZ been sliehtly larger then Mj. and the resulting collapse had. left a remnant rather than provoking complete disruption. | We can now ask what end–product would have emerged had $M$ been slightly larger then $M_{\rm Ch}$, and the resulting collapse had left a remnant rather than provoking complete disruption. |
We first consider the merger process in a little more detail. | We first consider the merger process in a little more detail. |
I£ the mass ratio q is less than 0.63 mass transfer is stable. and continues at à rate governed by gravitational racdation. | If the mass ratio $q$ is less than 0.63 mass transfer is stable, and continues at a rate governed by gravitational radiation. |
However. if q2»0.63. mass transfer is dynamically unstable. | However, if $q > 0.63$, mass transfer is dynamically unstable. |
Mass is then transferred rapidly. until gq«0.63. | Mass is then transferred rapidly until $q < 0.63$. |
Stability is achieved on a timescale of 7—TRUMDU where P? is the orbital period and Z4 is the timescale specifying the rate at which transfer begins. | Stability is achieved on a timescale of $ \tau \sim t_{\rm grav}^{2/3}P^{1/3}$ , where $P$ is the orbital period and $t_{\rm grav}$ is the timescale specifying the rate at which transfer begins. |
Typically we expect 10" vr. P— a few hours. ancl thus 7 to be of order a few vunelrecl vears. | Typically we expect $t_{\rm grav} \sim
10^6$ yr, $P\sim$ a few hours, and thus $\tau$ to be of order a few hundred years. |
However. the mass transfer rate for an pn=3/2 polvtrope obevs ADAMDp"εινϱ)V7, valid for time { less than some reference time fg. (Webbink 1985). so the sulk of the mass transfer before stability is achieved occurs on a timescale of several orbital periods. | However, the mass transfer rate for an $n=3/2$ polytrope obeys $\dot{M}/M \sim P^{1/2}(t_0 - t)^{-3/2}$, valid for time $t$ less than some reference time $t_0$, (Webbink 1985), so the bulk of the mass transfer before stability is achieved occurs on a timescale of several orbital periods. |
Once stability is achieved. transfer slows once more towards the rate governe ον eravitational radiation. | Once stability is achieved, transfer slows once more towards the rate governed by gravitational radiation. |
Jecause no existing. computation has been able to consider accretion of Hle or of €C/O on to a white cdwarl at such high rates. there is still considerable uncertainty as to what the final outcome might be. | Because no existing computation has been able to consider accretion of He or of C/O on to a white dwarf at such high rates, there is still considerable uncertainty as to what the final outcome might be. |
For cxaniple. Regoss et al (2000) argue. from population svnthesis mocdels. tha the majority of SNe la are caused by rapid. accretion of lle on to a subChancrasckharmass white chvarl and a subsequent edgeLit detonation of carbon. leading to the complete thermonuclear cisintegration of the white dwar, | For example, Regőss et al (2000) argue, from population synthesis models, that the majority of SNe Ia are caused by rapid accretion of He on to a sub–Chandrasekhar–mass white dwarf and a subsequent edge–lit detonation of carbon, leading to the complete thermonuclear disintegration of the white dwarf. |
In contrast. as we remarked above. many authors contend ju such edgelit ignition can lead to quiet burning of the ο. ‘Oto O/Ne/Ale. and thus speculatively to a quiet acerction --nduced collapse (at least for AZ= Mg) to form a neutron gaar but with no supernova explosion. and thus with no supernova remnant. | In contrast, as we remarked above, many authors contend that such edge–lit ignition can lead to quiet burning of the CO to O/Ne/Mg, and thus speculatively to a quiet accretion induced collapse (at least for $M = M_{\rm Ch}$ ) to form a neutron star but with no supernova explosion and thus with no supernova remnant. |
While the computations have vet to be wrbed out. H seems to us hard to escape the conclusion wt if the Chancdrasekhar limit is exceeded during the mass transfer. collapse to neutron star densities must ensue. | While the computations have yet to be carried out, it seems to us hard to escape the conclusion that if the Chandrasekhar limit is exceeded during the mass transfer, collapse to neutron star densities must ensue. |
Η. during such a collapse. we assume conservation of angular momentum and magnetic lux as the stellar radius shrinks from the Ay23«107 em of BE J0317S53 to the #=10" em of a neutron star. we [ind a spin period P=ΠεΓη) Toms and a field 2B=BolRufRY=35N1015 €. We draw attention to the fact that these values are remarkably close to. those required. in the magnetar model now thought to provide an explanation of the properties of soft. ganna repeaters (SCRs) and the related anomalous NX.ray pulsars (AXPs) (see “Thompson. 1999. and Kouveliotou. 1999. for. recent reviews). | If, during such a collapse, we assume conservation of angular momentum and magnetic flux as the stellar radius shrinks from the $R_0 \simeq
3\times 10^8$ cm of RE J0317--853 to the $R= 10^6$ cm of a neutron star, we find a spin period $P = P_0(R/R_0)^2 = 7$ ms and a field $B =
B_0(R_0/R)^2 = 3.5 - 8\times 10^{13}$ G. We draw attention to the fact that these values are remarkably close to those required in the magnetar model now thought to provide an explanation of the properties of soft gamma repeaters (SGRs) and the related anomalous X–ray pulsars (AXPs) (see Thompson, 1999, and Kouveliotou, 1999 for recent reviews). |
Moreover. we might expect even more extreme values of these two parameters for two reasons. | Moreover, we might expect even more extreme values of these two parameters for two reasons. |
First. the stronely increased shearing resulting from a collapse to much smaller cimensions is likely to increase the strength of the magnetic field considerably CEhompson Duncan. 1995: IxIuzniak Ruclerman. 1998). | First, the strongly increased shearing resulting from a collapse to much smaller dimensions is likely to increase the strength of the magnetic field considerably (Thompson Duncan, 1995; Kluzniak Ruderman, 1998). |
Second. with a surface temperature of ~4.107 Ix. RE JO0317.S53's spin period at birth could. have been considerably. shorter than the current 725 s. as even tiny amounts of mass [oss coupling to its large magnetic moment would have caused spindown within its cooling age of several 10* vr. | Second, with a surface temperature of $\sim 4\times 10^4$ K, RE J0317–853's spin period at birth could have been considerably shorter than the current 725 s, as even tiny amounts of mass loss coupling to its large magnetic moment would have caused spindown within its cooling age of several $10^7$ yr. |
Alore extreme fields and rotation rates pul us squarely in the parameter space (2= few ms. DzLot! C) inferred for magnetars at. birth. | More extreme fields and rotation rates put us squarely in the parameter space $P = $ few ms, $B \ga 10^{14}$ G) inferred for magnetars at birth. |
We conclude that. the probable outcome of a magnetic white chwarl merger with AL7Mog is à magnetar. | We conclude that the probable outcome of a magnetic white dwarf merger with $M > M_{\rm Ch}$ is a magnetar. |
We have argued that the merger of two CO white cwarls results in a remnant which is both rapicly rotating and highlv magnetic. | We have argued that the merger of two CO white dwarfs results in a remnant which is both rapidly rotating and highly magnetic. |
I£ the total mass is less than Alou. the remnant is a massive. magnetic white dwarf. | If the total mass is less than $M_{\rm Ch}$, the remnant is a massive, magnetic white dwarf. |
And if the total mass exceeds Acgy. the remnant is a rapidly rotating. strongly magnetic neutron star. | And if the total mass exceeds $M_{\rm Ch}$, the remnant is a rapidly rotating, strongly magnetic neutron star. |
We have identified: such remnants as magnetars. | We have identified such remnants as magnetars. |
This conclusion leads to another. | This conclusion leads to another. |
Soft. gamma ray repeaters (and anomalous Xrav pulsars) are associate with supernova remnants (see. for example. the discussion in Ixouveliotou. 1999). | Soft gamma ray repeaters (and anomalous X–ray pulsars) are associated with supernova remnants (see, for example, the discussion in Kouveliotou, 1999). |
"his implies that the collapse caused by the merger is not a quicscent “accretion induce collapse’. but actually gives rise to a supernova explosion. | This implies that the collapse caused by the merger is not a quiescent `accretion induced collapse', but actually gives rise to a supernova explosion. |
If our identification of magnetars as CO white dwarl merger products is correct. then the supernovae associatec with them should have highvelocity carbon and highermass elements (from the disrupted. reninant disc). but. no ivdrogen or helium. | If our identification of magnetars as CO–CO white dwarf merger products is correct, then the supernovae associated with them should have high–velocity carbon and higher--mass elements (from the disrupted remnant disc), but no hydrogen or helium. |
We conclude. therefore. that CO white dwarf mergers produce both a Tvpe L supernova and a neutron star remnant. and. further. that if one of he merging white chvarls has a significant magnetic field (estimated at around. 25 per cent of the total). then this neutron star is a magnetar. | We conclude, therefore, that CO–CO white dwarf mergers produce both a Type I supernova and a neutron star remnant, and, further, that if one of the merging white dwarfs has a significant magnetic field (estimated at around 25 per cent of the total), then this neutron star is a magnetar. |
We may use this now to estimate an occurrence rate for hese supernovae. | We may use this now to estimate an occurrence rate for these supernovae. |
SGRs and ANDPs are known to have rather short lifetimes ~103 vr. (cf IXouveliotou. 1999:oc ‘Thompson. 1999). from arguments based on the observed: spindown imescale |P/P|. and the typical age of the associated supernova remnants. | SGRs and AXPs are known to have rather short lifetimes $\sim 10^4$ yr, (cf Kouveliotou, 1999; Thompson, 1999), from arguments based on the observed spindown timescale $|P/\dot P|$, and the typical age of the associated supernova remnants. |
The magnetar model gives similar (or even shorter) spindown ages. | The magnetar model gives similar (or even shorter) spindown ages. |
From the current: observed otal number of SGRs and ANPs (~ 10). this characteristic age implies an estimate for the formation rate of magnetars of ~107 1 in the Galaxy. | From the current observed total number of SGRs and AXPs $\sim 10$ ), this characteristic age implies an estimate for the formation rate of magnetars of $\sim
10^{-3}$ $^{-1}$ in the Galaxy. |
We now ask: what kind of Type LE supernovae do the COmergers correspond. to? | We now ask: what kind of Type I supernovae do the CO–CO–mergers correspond to? |
We note first that. the inferred SNe la rate for the Galaxy is approximately ~1% + (Yungelson Livio 2000). | We note first that the inferred SNe Ia rate for the Galaxy is approximately $\sim 10^{-3}$ $^{-1}$ (Yungelson Livio 2000). |
Thus the estimated occurrence rates provide no obvious grounds for rejecting the possibility that SNe la might. result. from white dwarl mergers. | Thus the estimated occurrence rates provide no obvious grounds for rejecting the possibility that SNe Ia might result from white dwarf mergers. |
Moreover they cannot be of Type Ib. which are associated with high-mass stars. and. if the above estimates are correct. they are toonumerous to be of Type le (Cappellaro et al.. | Moreover they cannot be of Type Ib, which are associated with high-mass stars, and, if the above estimates are correct, they are toonumerous to be of Type Ic (Cappellaro et al., |
LOOT show that the combined rate for Types Ib and Ic is lower than for Pype Ia). | 1997 show that the combined rate for Types Ib and Ic is lower than for Type Ia). |
The white dwarf merger scenario is currently. perhaps | The white dwarf merger scenario is currently perhaps |
completeness level is measured at U(Vega)=26.6, while at U=27.0 we have a formal completeness of30%. | completeness level is measured at $U(Vega)=26.6$, while at $U=27.0$ we have a formal completeness of. |
. The number counts corrected for incompleteness are shown again in Fig.1.. | The number counts corrected for incompleteness are shown again in \ref{fig:lognsu}. |
Given the wide magnitude interval from U(Vega)=19.5 to U(Vega)=27.0 available in the present survey, the shape of the counts can be derived from a single survey in a self-consistent way, possibly minimizing offsets due to systematics in the photometric analysis of data from multiple surveys (zero point calibration, field to field variation, etc). | Given the wide magnitude interval from $U(Vega)=19.5$ to $U(Vega)=27.0$ available in the present survey, the shape of the counts can be derived from a single survey in a self-consistent way, possibly minimizing offsets due to systematics in the photometric analysis of data from multiple surveys (zero point calibration, field to field variation, etc). |
A clear bending is apparent at U(Vega)>23.5. | A clear bending is apparent at $U(Vega)> 23.5$. |
To quantify the effect we fitted the shape of the counts in the above magnitude interval with a double power-law. | To quantify the effect we fitted the shape of the counts in the above magnitude interval with a double power-law. |
The slope changes from 0.58+0.03 to 0.24+0.05 for magnitudes fainter than Όψεις=23.6. | The slope changes from $0.58\pm 0.03$ to $0.24\pm 0.05$ for magnitudes fainter than $U_{break}=23.6$. |
The uncertainty in the break magnitude is however large, ~0.5, since the transition between the two regimes of the number counts is gradual. | The uncertainty in the break magnitude is however large, $\sim 0.5$, since the transition between the two regimes of the number counts is gradual. |
In Fig.l we compare our galaxy number counts with those derived by shallow surveys of large area (SDSS EDR, Yasudaοἱal. (2001))) or of similar area (GOYA by Eliche-Moraletal. (2006);; VVDS-F2 by Radovichetal. (2004)), and with deep pencil beam surveys (Hawaii HDFN by Capaketal.(2004); WHT, HDFN, and HDFS by Metcalfeetal. (2001))). | In \ref{fig:lognsu} we compare our galaxy number counts with those derived by shallow surveys of large area (SDSS EDR, \cite{sdss}) ) or of similar area (GOYA by \cite{goya}; ; VVDS-F2 by \cite{radovich}) ), and with deep pencil beam surveys (Hawaii HDFN by \cite{capak04}; WHT, HDFN, and HDFS by \cite{wht}) ). |
In particular, the WHT galaxy counts (Metcalfeetal. (2001))) are based on a 34h exposure time image reaching U(Vega)=26.8 but at the much lower 3o level in the photometric noise and in an area of ~50 arcmin?, while the GOYA survey at the INT telescope is complete at level at U(Vega)=24.8. | In particular, the WHT galaxy counts \cite{wht}) ) are based on a 34h exposure time image reaching $U(Vega)=26.8$ but at the much lower $\sigma$ level in the photometric noise and in an area of $\sim$ 50 $^2$, while the GOYA survey at the INT telescope is complete at level at $U(Vega)=24.8$. |
These counts are shown together with the two pencil beam surveys in the Hubble Deep Fields (Metcalfeetal. (2001))). | These counts are shown together with the two pencil beam surveys in the Hubble Deep Fields \cite{wht}) ). |
The agreement with the GOYA survey (900 sq. | The agreement with the GOYA survey (900 sq. |
arcmin.) | arcmin.) |
is remarkable, and suggests that once big areas of the sky are investigated, the effects of cosmic variance are slightly reduced. | is remarkable, and suggests that once big areas of the sky are investigated, the effects of cosmic variance are slightly reduced. |
The present UV counts obtained during the commissioning of LBC-Blue are thus a unique combination of deep imaging in the U band and of large sky area, with the result of a considerable reduction of the cosmic variance effects for U>21. | The present UV counts obtained during the commissioning of LBC-Blue are thus a unique combination of deep imaging in the U band and of large sky area, with the result of a considerable reduction of the cosmic variance effects for $U\ge 21$. |
For brighter magnitude limits, we refer to larger area surveys, shallower than our survey, as shown in Fig.1.. | For brighter magnitude limits, we refer to larger area surveys, shallower than our survey, as shown in \ref{fig:lognsu}. |
Table 1 summarizes the galaxy number counts, corrected for incompleteness, with their upper and lower 1 o confidence level uncertainties, assuming Poisson noise and cosmic variance effect. | Table \ref{tab:lognsU} summarizes the galaxy number counts, corrected for incompleteness, with their upper and lower 1 $\sigma$ confidence level uncertainties, assuming Poisson noise and cosmic variance effect. |
For the latter, we used the Cosmic Variance Calculator (v1.02) developed by Trenti&Stiavelli(2008) using as input values a linear size of 22 arcmin (corresponding to our deeper area of 478.2 arcmin?) and redshift from 0.0 to 3.0, with standard A-CDM cosmology. | For the latter, we used the Cosmic Variance Calculator (v1.02) developed by \cite{trenti} using as input values a linear size of 22 arcmin (corresponding to our deeper area of 478.2 $arcmin^2$ ) and redshift from 0.0 to 3.0, with standard $\Lambda$ -CDM cosmology. |
At U=27, for example, the computed cosmic variance is4. | At U=27, for example, the computed cosmic variance is. |
5%.. Using the Q0933+28 and the other three fields in the SXDS area, we study the field to field variation of the number counts in the U band. | Using the Q0933+28 and the other three fields in the SXDS area, we study the field to field variation of the number counts in the U band. |
We find that the typical variation from one LBC field to another is 0.04 in LogN for U~20, while it reduces gradually to 0.01 at U=24.5, well below the poissonian uncertainties described in Table 1.. | We find that the typical variation from one LBC field to another is 0.04 in LogN for $U\sim 20$, while it reduces gradually to 0.01 at U=24.5, well below the poissonian uncertainties described in Table \ref{tab:lognsU}. |
This ensures that the zero-point calibration of the images is robust and the area of this survey is sufficient to decrease the cosmic variance effects below the statistical uncertainties of the galaxy number counts. | This ensures that the zero-point calibration of the images is robust and the area of this survey is sufficient to decrease the cosmic variance effects below the statistical uncertainties of the galaxy number counts. |
We complement these internal checks on the galaxy number counts in U with an external consistency test, comparing our final number counts with shallower NC derived in different areas or deep pencil beam surveys in Fig.1.. | We complement these internal checks on the galaxy number counts in U with an external consistency test, comparing our final number counts with shallower NC derived in different areas or deep pencil beam surveys in \ref{fig:lognsu}. |
We find that the survey-to-survey maximal variations are of the order of 0.1 in LogN at all magnitudes, with lower scatter for the wider surveys considered here (GOYA, SDSS-EDR, VVDS-F2). | We find that the survey-to-survey maximal variations are of the order of 0.1 in LogN at all magnitudes, with lower scatter for the wider surveys considered here (GOYA, SDSS-EDR, VVDS-F2). |
The slope of the galaxy number counts in the U band at U~23.5 changes from 0.58 to 0.24, which implies that the contribution of galaxies to the integrated EBL in the UV has a maximum around this magnitude. | The slope of the galaxy number counts in the U band at $U\sim 23.5$ changes from 0.58 to 0.24, which implies that the contribution of galaxies to the integrated EBL in the UV has a maximum around this magnitude. |
The contribution of observed galaxies to the optical extragalactic background light (EBL) in the UV band can be computed directly byintegrating the emitted flux | The contribution of observed galaxies to the optical extragalactic background light (EBL) in the UV band can be computed directly byintegrating the emitted flux |
at some Galactic GCs have LEAS because they formed from massive gaseous. clumps developed: from. merging of dillerent. gaseous regions with clillercnt initial Fe/1]. | that some Galactic GCs have HEAS because they formed from massive gaseous clumps developed from merging of different gaseous regions with different initial [Fe/H]. |
However. Fig. | However, Fig. |
4 shows that the degree of LIEAS (GN Fe/11]) depends strongly on ay such that A Fe/L] is larger (~0.2 dex) for the steeper metallicity graclient (ic. the larger absolute magnitude of o4). | 4 shows that the degree of HEAS $\Delta$ [Fe/H]) depends strongly on $\alpha_{\rm d}$ such that $\Delta$ [Fe/H] is larger $\sim 0.2$ dex) for the steeper metallicity gradient (i.e., the larger absolute magnitude of $\alpha_{\rm d}$ ). |
Fig. | Fig. |
5 shows that a vounger population can have FefM]- Lin MCC2 in the model with chemical evolution (M). though the mass fraction the population with the age ess than 0.2 Cir is only ~0.05. | 5 shows that a younger population can have $\sim -1$ in MGC2 in the model with chemical evolution (M7), though the mass fraction the population with the age less than 0.2 Gyr is only $\sim 0.05$. |
Although the prolonged star formation can be seen. the vast majority of stars are ormed in a burst at the epoch of massive clump formation. | Although the prolonged star formation can be seen, the vast majority of stars are formed in a burst at the epoch of massive clump formation. |
Furthermore. there appears to be an age-metallicity relation hat vounger stars are more metal-rich in MCOGC2. | Furthermore, there appears to be an age-metallicity relation that younger stars are more metal-rich in MGC2. |
Ht should oe stressed that the relation can depend. on how the supernova cjecta can influence the later star formation within cluster-forming massive gas clumps. which needs to »e investigated by more sophisticated models in our future works: Ehe Fe/l] spread. could. be overestimated owing o the adopted instantaneous recycling approximation. | It should be stressed that the relation can depend on how the supernova ejecta can influence the later star formation within cluster-forming massive gas clumps, which needs to be investigated by more sophisticated models in our future works: The [Fe/H] spread could be overestimated owing to the adopted instantaneous recycling approximation. |
The mean metallicities and internal Fe/1] spread of MIGCs are arecr in models with larger ua (og... MS) in the present study. | The mean metallicities and internal [Fe/H] spread of MGCs are larger in models with larger $y_{\rm met}$ (e.g., M8) in the present study. |
The physical properties of MCCs (e.g.. masses and ocations) are not different between models with cülferent numerical resolutions (Ml ancl LII). | The physical properties of MGCs (e.g., masses and locations) are not different between models with different numerical resolutions (M1 and H1). |
The present chemodsnamical study has first demonstrated that AlGCs with LEAS can be formed from. massive gas clumps developed. from merging of different gaseous regions with clillerent metallicities. | The present chemodynamical study has first demonstrated that MGCs with HEAS can be formed from massive gas clumps developed from merging of different gaseous regions with different metallicities. |
Therefore. NGCS with HEAS can be formed. even without chemical enrichment »w supernovae during their formation. | Therefore, MGCs with HEAS can be formed even without chemical enrichment by supernovae during their formation. |
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