 |  |
Astron. Astrophys. 345, 329-362 (1999)
Appendix A: characteristics of galactic halos
Any dark matter halo of radius R can be characterized by its
overall density contrast or
equivalently by the parameter x introduced in (8). We assume
that these potential wells have a mean density profile of the form
where
is the slope of the two-points
correlation function (we shall come
back to this point below). Since is
close to 2, the halo is close to isothermal and the velocity
dispersion is nearly constant,
which agrees with observations. With such a density profile, the
velocity dispersion of the dark matter verifies:
![[EQUATION]](img739.gif)
which leads to
![[EQUATION]](img740.gif)
The energy equipartition , where
is the mean molecular weight of the
gas and the proton mass, gives for
the gas temperature:
![[EQUATION]](img744.gif)
which also leads to the hydrostatic equilibrium for the gas, using
, where
and
are the baryon number density and
mass density, if . Hence we shall
assume that the gas initially follows the spatial distribution of the
dark matter in the virialized halo, before it starts cooling, which is
consistent with numerical simulations (Evrard 1990). More precisely we
assume:
![[EQUATION]](img749.gif)
where is the present ratio of
the baryon density to the critical density. We shall take
in the case
, and
in the case
. Both values are consistent with
the bounds given by primordial nucleosynthesis (Walker et al. 1991).
Finally, we note:
![[EQUATION]](img751.gif)
which correspond to halos of primordial composition (with an helium
mass fraction ), where
is the electron number density. We
note V the circular velocity of the galaxy at its external
radius R:
![[EQUATION]](img754.gif)
We also define a luminous radius
, and the circular velocity
at
, by:
![[EQUATION]](img756.gif)
We shall use to compare our
model to the observed Tully-Fisher relation, which relates the
luminosity to the circular velocity at a radius
. Since
we have
(the rotation velocity is roughly
constant throughout the halo).
The time introduced in Sect. 3.1
corresponding to the turn-around epoch of a given halo (or to the time
when it became non-linear) is given by the spherical collapse model
(Peebles 1980):
![[EQUATION]](img760.gif)
The time of turn-around is simply
, and the radius of maximum
expansion is . When the overdensity
virializes, at , its radius is
, and the averaged density within
is
. Thus we obtain:
![[EQUATION]](img766.gif)
which gives the time of turn-around
of the halo as a function of its
density.
The slope of the dark matter
halos mainly enters our calculations as a numerical factor of order
unity in (A2). Hence we do not need a precise description of the
detailed density profile of the objects we deal with. Moreover, we
explicitly consider that very large halos defined by
which correspond to clusters of
galaxies (at low z) contain several higher-density sub-units
which are identified as distinct galactic halos. In fact, we recognize
directly these smaller objects without dealing (in this article) with
their larger host halo.
Appendix B: star formation model for an isolated halo
With the prescription introduced in Sect. 3.1 we are able to obtain
the mass function of galaxies, or the temperature, radius functions,
but we do not have the luminosity function yet. Indeed, the luminosity
of galaxies depends on the processes which govern star formation,
which we need to take into account explicitly. We shall adopt a very
simple model for the formation of stars within the halos we previously
considered.
B.1. Model
For each galaxy we divide stars in two populations: a first class
of massive stars, with a life-time
shorter than the age t of the galaxy, and a second class of
small stars with a life-time larger
than t. Thus, the gas used to form these small stars has not
been recycled in the ISM, since these stars are still on the main
sequence, while the large stars consist of many successive generations
which have continuously recycled part of their mass through supernovae
explosions, planetary nebulae and winds. We consider explicitly the
mass recycled by SNII, and by stars in the AGB phase, but we neglect
the mass ejected by SNI (believed to be associated with white dwarf
coalescence and explosion) which is very small as compared to the one
involved in the former processes. To include SNI would be
straightforward, but it would not change our results as long as we do
not consider the history of Si or Fe. We note
,
and the total mass in the form of
gas, short-lived stars and long-lived stars. Moreover, we consider two
gaseous phases: some low-density diffuse gas
spread over the halo, and some
dense gas within the core of the
galaxy in the form of clouds which turns into stars with a time-scale
. Initially, we have
and
with
the mass of baryons in the halo
(hence we assume that at the time of virialization the baryon fraction
within any halo is representative of the universe: there has been no
prior segregation between baryonic and dark matter). The diffuse phase
is continuously replenished by
stellar winds and supernovae, which eject and heat part of
. Meanwhile, the diffuse gas settles
in the central parts of the galaxy and forms dense clouds over a
dynamical time-scale . Indeed, the
gas ejected by supernovae or ionized by stellar winds, or initially
hot after virialization, cools over a time-scale
and then falls back into the center
of the potential well over a time .
By definition of our halos, the constraints (15) ensure that
hence
is the only one relevant
time-scale. In fact we even have at
high redshifts or small temperatures when
, in this case most of the gas
is cold. This would be different
for galaxies in clusters, where the gas may be spread all over the
cluster, cooling is less efficient, and where the potential wells of
the galactic halos are expected to be modified by the additional
cluster gravitational energy. The properties of galaxy clusters,
however, will be treated in a forthcoming paper. Finally, we can
write:
![[EQUATION]](img777.gif)
where is the mass fraction of
the IMF corresponding to short-lived stars, for
of gas which is processed into
stars, and is the fraction of mass
which is locked within white dwarfs or neutron stars after the death
of these massive stars, and is not recycled in the galaxy to form
other generations of stars. We have
because in the case of usual stellar initial mass functions (IMF) most
of the mass is within low mass long-lived stars. In a fashion similar
to Kauffmann et al. (1993) we write the mass of gas heated and ejected
by supernovae as:
![[EQUATION]](img781.gif)
where is the fraction of the
energy delivered by supernovae
transmitted to the gas, and we defined:
![[EQUATION]](img784.gif)
using and
erg. This value of
is consistent with the IMF we shall
use, and it is constrained by the observed supernovae rates. The
effect of stellar winds can also be incorporated into this model
through .
Using the fact that by definition of short-lived stars
we can make the approximation that
evolves in a quasi-static way:
. Hence we obtain:
![[EQUATION]](img790.gif)
Then we solve numerically (B1) to get the evolution of
,
and all other quantities.
B.2. Analytic approximations
For faint galaxies characterized by a small virial temperature
the system (B1) leads to a simple
approximation, which also provides usefull insight into the behaviour
of more massive galaxies, as can be checked numerically. More
precisely, this approximation is valid provided
. In this case, a quasi-stationary
regime sets in very quickly, where the galactic evolution is regulated
by supernovae (and stellar winds) and the dynamical time-scale: the
sink term for the star-forming gas ,
corresponding to matter ejected by supernovae (which involves the star
formation rate and the supernovae efficiency parameterized through
), balances the source term due to
the infall of gas from the extended halo
(which involves the dynamical
time-scale). Hence the global star formation rate is governed by the
interplay of the supernovae efficiency and the dynamical time-scale.
Then, evolves in a quasi-static way
and follows closely the mass of the reservoir
:
![[EQUATION]](img793.gif)
Note that the condition of validity of this approximation implies
that . Then, since
we obtain
![[EQUATION]](img796.gif)
where is the age of the galaxy
and we defined:
![[EQUATION]](img798.gif)
Thus, as we explained above, the galactic evolution is governed by
and
, the time-scale
does not appear in the global gas
mass, or stellar content. The instantaneous star formation rate is
![[EQUATION]](img800.gif)
since , hence
(we neglect the mass in the form of
short-lived stars). The mass within massive short-lived stars is:
![[EQUATION]](img803.gif)
while the mass in the form of small long-lived stars is:
![[EQUATION]](img804.gif)
The mass locked in star remnants, white dwarfs or neutron stars,
is
![[EQUATION]](img805.gif)
Appendix C: redshift evolution and merging of galaxies
C.1. Model
In the previous section we considered non-evolving halos, in the
sense that the total mass of the galaxy, and its time-scales
and
, remained constant with time.
However, as we explained in Sect. 3.2, the characteristics of the
galactic halos we consider evolve with time, following the curve
(see Fig. 2). Thus, we now have to
model the evolution of the matter located on
through its merging history.
Similarly to White & Frenk (1991), we can write for the comoving
stellar content of the universe at time t:
![[EQUATION]](img806.gif)
![[EQUATION]](img807.gif)
where is the probability (which
we do not know) that matter which was in a halo of parameter
at time
will be part of a halo of parameter
x - at t, and
is the star formation rate of the
corresponding halo. We can define halos by their parameter x
for both PS and non-linear scaling approaches because we noticed in
Sect. 2 that the usual linear parameter
is a function of x only, see
(13). If individual halos are stable once in the non-linear regime
(when and
), their parameter x remains
constant with time, but they accrete some mass as their virialization
radius gets larger with time and they may join together to form a
larger halo. Hence, we shall make the approximation that the mass
which is within halos at t
was within halos of the same range in x at all earlier times.
This also satisfies the constraint that mass be conserved since the
mass fraction within halos does not
depend on time, and is a function of the sole variable x, see
(10). In fact, the conservation of mass implies to use a distribution
in x, or to take x constant which should be a good
approximation if this distribution is peaked around a particular
value. This also ensures that we do not mix the mass of non-evolving
galaxies located on with the halos
on , and that the mass at a given
time t comes from older less massive halos characterized by a
slightly weaker potential well since for a fixed x the virial
temperature T is smaller at higher redshifts. This is quite
natural since as time goes on potential wells merge to form deeper
ones. In other words, we neglect the scatter in all possible "merger
trees" and simply use a "mean history" defined by compatibility
requirements. This analysis also applies to the PS approach, which
would only give a different function
, hence a different mass
fraction.
In fact, when one expects that
the correlation disappears, or at
least gets weaker, but this is not a problem if the stellar content of
a given object at t is dominated by its recent star formation
history, which is the case. Moreover, within the framework of our
model for star formation small galaxies are regulated by the interplay
between supernovae (which eject gas) and the infall of gas from the
outer parts of the halo and their luminosity is dominated by recently
formed stars which are more numerous. As a consequence the details of
their previous stellar history are not very important. On the other
hand, very massive and bright galaxies are not affected by the
supernovae feedback mechanism (since their potential well is
sufficiently deep to retain the gas very efficiently) so that their
past history matters. Besides, at low redshifts their star formation
rate begins to decline significantly as they exhaust their gas
content. This means that their luminosity and stellar properties are
governed by old stars which formed during ealier and more active
periods. However, in our astrophysical model we assume that these
galaxies (located on the cooling curve
) do not evolve significantly any
more so that our approximation
becomes correct for these objects. Thus, our approximation is
consistent with our model and it should provide a reasonably good
description. Moreover, it allows one to get simple analytic insights
into the global galaxy formation process, which clearly show the
general trends implied by any such model based on hierarchical
structure formation supplemented by cooling constraints. Note that
using a different galaxy formation model Kauffmann et al. (1998) found
that their results were not very sensitive on the details of the
merging trees of their halos (they obtained similar results with
N-body simulations and an extended Press-Schechter theory for the
properties of individual galaxies although the merger trees differ in
detail). Using (9) we obtain
![[EQUATION]](img819.gif)
In fact, this approach simply means that we can still use the sytem
(B1) to get the proportion of the mass of gas which is converted into
stars in a galaxy, but the time-scales
and
, and the virial temperature
T, are now functions of time.
C.2. Analytical solutions
Although in practice we compute numerically the solution of the
system (B1), we present now the case of the simplified
quasi-stationary regime, corresponding to small galaxies, to give a
clear illustration of the effects of this additional time-dependence.
Moreover, since the temperature T decreases at higher
redshifts, for a fixed x, all galaxies follow this regime when
they are young.
Since , and
in this case, we obtain:
![[EQUATION]](img822.gif)
Thus we have an equation similar to the one describing halos
located on , but now the global star
formation time-scale depends on
. The density
of the halos located on
, which virialize at the time
, is according to the spherical
model:
![[EQUATION]](img825.gif)
Hence , whatever the value of
. If clustering is stable, for
, the quantity
is constant, hence
. Thus, for a constant parameter
we obtain for halos on
:
![[EQUATION]](img831.gif)
As a consequence, since for
halos such that , see (B7), we
get:
![[EQUATION]](img833.gif)
Hence, if we note the age of the
universe at the redshift we consider, and
the star formation time-scale at
this date, we can write:
![[EQUATION]](img834.gif)
using . We can note that this
integral converges for , and
T (which measures the depth of the potential well) decreases at
higher redshifts, provided , which
corresponds to the range of interest where hierarchical clustering is
valid. Hence our analysis applies to all relevant power-spectra
. Thus we obtain for the gas mass
fraction at any time t:
![[EQUATION]](img838.gif)
In the case we have for the gas
mass fraction at time , when we
calculate ,
![[EQUATION]](img839.gif)
Thus, we obtain a relation similar to (B6), with an "effective age"
for the galaxy given by
. Hence the time-evolution of
reduced this age by a factor
, as compared to (B6), since for
the time-scale
increases at high redshifts, which
leads to a less efficient star formation, because the temperature
T decreases. This would not be the case for large n,
where the dominant effect would be the increase of the density. Note
however that the variation with n of the factor
can simply be incorporated into the
parameters and
. Galaxies located on
with a high virial temperature
have a slightly more complicated
history. There is a first stage, at small times, where
and they follow the behaviour we
have just described, and a second stage where
and
. Hence we divide the integral of
(C3) in two parts, and we get a similar result, with an effective age:
. In fact, the relation (B6) does
not apply to these massive galaxies, but it still gives a good
estimate of their evolution, and this simple result shows that the
effective age is increased because the temperature remains constant
for some time, as could be expected, but only by a logarithmic term.
For massive galaxies located on we
have constant down to the time
when
and we switch onto
. At small redshifts
the fact that
is constant means that the gas mass
fraction follows a simple exponential decline
, usually different from the
evolution along
. The time of virialization is
simply and the star formation
time-scale at this date is . Hence
these galaxies have an effective age
which is the sum of their effective
age at , which we obtained above,
and of the time which has elapsed since this date:
. Thus, to sum up, for all galaxies
the quasi-stationary approximation gives again the relations of the
previous section, (B6) to (B11), with an effective age given by:
![[EQUATION]](img856.gif)
Note that halos on satisfy
by definition. Thus, the gas mass
fraction within halos at time is
given by a relation of the form ,
whatever the precise dependence on z of the star formation
time-scale, provided the integral of the right-hand side of (C3)
converges (star formation does not occur as a sudden burst at high
redshifts). Moreover, the variation with n of the factor
in the age of the galaxy, when it
is on , is simply incorporated into
the parameter which enters the
definition of , see (B7). Thus, as
far as star formation processes are concerned, all galaxies have
roughly the same age (of the order of the age of the universe), even
if they did not exist as distinct entities over this whole period of
time: they continuously accreted some mass or merged with
neighbours.
We can see that the time evolution of these virialized halos does
not depend on . This is due to the
fact that the internal dynamics of overdensities given by the
spherical model does not depend on the background universe. However,
the number of such halos will naturally vary with the cosmological
parameters. Besides, the redshift evolution depends on
, in parallel to the relation
time-redshift. For instance, if we
have while
if
and
. Thus, in the case
we have for halos on
defined by a fixed parameter
x:
![[EQUATION]](img862.gif)
where is the present age of the
universe. In the case of a low-density universe the redshift evolution
is slower, because of the faster expansion which implies that the same
multiplying factor in redshift corresponds to a smaller factor in
time.
We can note that for halos on ,
the time-scale which governs their merging history is
. Hence, if star formation is also
enhanced by gravitational interactions with surroundings and merging
with other halos, the natural time-scale is again
which gives another justification
for our star formation time-scale .
The gas of halos which undergo this succession of mergings can be
reheated to the virial temperature by the energy released during these
violent encounters. However, for halos located on
we have by definition
, hence we can neglect these
successive phases of reheating.
The evolution equation (C3) we obtained is interesting as it
readily shows the influence of the parameterization adopted for the
star formation time-scale on the
history of galaxies. Indeed, since ,
we can see that the integral on the right-hand side diverges for
if
is a strong power-law of the
density: with
. In fact, there is a cutoff at high
redshifts because for a fixed parameter x the temperature gets
smaller in the past, and when K
cooling is very inefficient so that star formation is suppressed.
However, this large decrease of T by a factor 100 (from
K to
K) means that the redshift of
cutoff corresponding to present
galaxies is rather high: . Thus,
such a model for would imply that
most stars formed at and that the
global star formation rate has been very low ever since. This is
certainly inconsistent with observations, which show that the star
formation rate has not experienced such a dramatic decline since
and that star formation is still
active in the present universe. If
varies weakly with :
, the integral converges and star
formation is dominated by the latest epochs, and increasingly so for
smaller , until all the gas is
converted into stars (at some time in the future). The case
, which corresponds to our
prescription, is intermediary as the divergence would only be
logarithmic, which is not a problem because of the cutoff. In fact,
the additional temperature dependence
introduces another redshift factor
which makes the integral converge. This strongly suggests that the
star formation time-scale should
vary as , at least at high redshift,
(with a possible additional dependence on T), independently of
the arguments presented in the previous section, so that star
formation is neither dominated by a sudden burst at high redshift when
most of the mass reaches K, nor by
the very recent epochs, since these both cases are inconsistent with
observations. Note that it is correct to consider the quasi-stationary
regime in this analysis since we are interested in the earliest stages
of galactic evolution when .
C.3. Total mass in stars and global star formation rate
We can also consider the evolution with redshift of the total mass
in stars per comoving . The mass of
baryons within galaxies is . Using
we obtain:
![[EQUATION]](img882.gif)
where is the stellar density
parameter and is the mass fraction
in galaxies of mass between M and
, given by (3) and (10) for the PS
and non-linear scaling prescriptions. Naturally, we always have
, as is clearly seen in (C11), since
. In fact, there is also a low
temperature cutoff at K, but up to
this only involves a very small
fraction of the total mass.
We obtain the comoving star formation rate in the same way. We have
, for long-lived stars, hence:
![[EQUATION]](img890.gif)
For the quasi-stationary regime we get for the derivative of the
stellar comoving mass density:
![[EQUATION]](img891.gif)
It first increases with redshift because the gas content of bright
galaxies gets higher (depletion term
) and the star formation time-scale
decreases. Indeed, since
, see (B7), and
for most galaxies which are close
to , we obtain
as long as
. However, at high redshifts the
comoving star formation rate gets smaller because the mass contained
in deep potential wells starts to decrease (influence of the cutoff at
K), and more importantly because as
the virial temperature declines the star formation time-scale
starts to increase (in the case
), see (B7). Naturally, if we
neglect the very small apparent mass loss at
K, we have:
![[EQUATION]](img897.gif)
by construction, as implied by (C2) (and checked numerically).
We can also look at the evolution with redshift of the star
formation rate of individual halos
defined by a fixed temperature T. Note that two such halos
defined by the same temperature at different redshifts are not
necessarily formed by the same matter. Along
, we have
, hence
, and
. For
the age of the universe scales as
, and
, hence we obtain
constant with time. In a similar
fashion, for halos located on we
also get constant as long as
. Thus, the star formation rate is
roughly constant with time for these objects, which is consistent with
observations.
Appendix D: stellar properties of galactic halos
We can note that the mass in the form of short-lived stars is
always much smaller than the mass contained in long-lived stars, and
increasingly so for well evolved galaxies (when
) as could be expected. Indeed these
galaxies have already consumed most of their gas content, hence their
present star formation rate is relatively small (as compared to their
past) and their stellar population is dominated by all stars which
were formed all along the galaxy history. Thus, for the
quasi-stationary approximation we obtain:
![[EQUATION]](img905.gif)
where we used , since in the case
of usual stellar initial mass functions (IMF) most of the mass is
within small long-lived stars, and we have
. Thus, luminous galaxies, which
correspond to large circular velocities (as is observed through the
Tully-Fisher relation) and high densities (because of the cooling
constraint, see the curve in
Fig. 2), hence to a small global star formation time-scale
, have consumed most of their gas
and will be redder than faint galaxies. This is an important success
of our model as this trend is actually observed (Lilly et al. 1991,
Metcalfe et al. 1991), but usually difficult to get by common models.
We can also notice that the mass in the form of white dwarfs or
neutron stars is always very small as compared to the total stellar
mass from (B11). Indeed we get (with
and
):
![[EQUATION]](img908.gif)
as is the case in any reasonable stellar evolution model. We can
check that mass is conserved with time in the sense that:
![[EQUATION]](img909.gif)
In fact we have a slight excess of mass
, which is negligible since we
noticed above that for instance.
This is due to our quasi-static approximation
. Finally, we also consider that for
of gas converted into stars a
fraction goes into "invisible"
compact objects, such as brown dwarfs, which we included among the
long-lived stars. Since observations seem to show that this mass
fraction is rather small we choose
in the numerical calculations (in fact we could as well use
or
, since this parameter has almost no
influence as long as it remains small). Then, the mass
of luminous stars is in our model
, since we have to remove the part
of formed by dark objects, but this
fraction is negligible. Besides, ,
and we have already noticed that
. Thus, we obtain:
![[EQUATION]](img919.gif)
At small times when the gas content of the galaxy is still
important we have:
![[EQUATION]](img920.gif)
It is clear on this expression, which is valid for any model of
star formation and does not rely on the quasi-stationary
approximation, that the observed ratio
of the Milky Way and its age give
directly its star formation time-scale
(whence the parameter
).
Thus we now have attached a peculiar stellar content to each halo,
or galaxy. To get the luminosity of such a galaxy, we only need to
precise the luminosity of its stars. We note
and
the global luminosity of
short-lived and long-lived stars per unit mass, so that the luminosity
L of the galaxy is:
![[EQUATION]](img924.gif)
Now we have to precise the values of the quantities
and
. We shall derive them from the
initial mass function (IMF) of stars and mass luminosity and mass
life-time relations. For of matter
converted into stars, the number of stars
formed in the mass range
is
![[EQUATION]](img928.gif)
where m is the star mass in units of
and a the normalization
constant. We use for
and
for
, which is similar to the IMFs given
by Salpeter (1955) and Scalo (1986). This applies to stellar masses
between and
. We could change somewhat this IMF
(for instance choose for
) without significant variation in
our results. Moreover, a fraction
may go into "invisible" compact objects, such as brown dwarfs, so we
have
![[EQUATION]](img936.gif)
which defines the normalisation of
. We note
the mass which separates the two
classes of stars we introduced above. Then, we obtain:
![[EQUATION]](img939.gif)
and
![[EQUATION]](img940.gif)
The mass is formed of luminous
stars, with , and of dark objects.
Next we use the mass luminosity and the mass life-time relations:
![[EQUATION]](img942.gif)
with , which is consistent with
the mean observed mass - B band luminosity relation for stars on the
main sequence. Hence we have:
![[EQUATION]](img944.gif)
and
![[EQUATION]](img945.gif)
Similarly, we get:
![[EQUATION]](img946.gif)
Using (D7) and the previous mass-luminosity relation we can see
that the luminosity of the galaxy is dominated by the contribution of
stars of mass close to . Finally we
use , and the mass
which separates the two classes of
stars we introduced above is chosen to be given by:
![[EQUATION]](img948.gif)
so that is smaller than the age
of the galaxies, which is close to the age of the universe at the time
of interest. For instance, in the case
a galaxy like the Milky Way, that
is with a circular velocity km/s,
corresponds in the present universe to
years,
and
.
Thus we can attach a luminosity to each galaxy, which enables us to
get the luminosity function of galaxies from the mass function:
![[EQUATION]](img953.gif)
We can also use this model to obtain the supernovae rate in
galaxies. Thus, we assume that stars more massive than
will explode as supernovae after
they leave the main sequence. Naturally, they must also be part of our
class of short-lived stars to explode during the life-time of the
galaxy. The mass in the form of these massive stars is:
![[EQUATION]](img955.gif)
Thus, in the case of the quasi-stationary regime we obtain for the
number of such stars at any time:
![[EQUATION]](img956.gif)
and the supernova rate is:
![[EQUATION]](img957.gif)
with
![[EQUATION]](img958.gif)
In the case , we obtain for a
galaxy similar to the Milky Way a supernovae rate of 2.5 explosions
per century, which is close to the observed value for type II
supernovae.
Appendix E: metallicity
Finally, we can derive the metallicity from our model (B1). The
metallicity here is understood as being the abundance of Oxygen, or
any other element that is not significantly produced in SNI which are
not included in our model. We define
and
as the fractions of metals within
the diffuse gas and within the gas
in the core of the galaxy . We note
the mean stellar metallicity. Thus,
we obtain:
![[EQUATION]](img959.gif)
where y is the yield. The fractions of metals in both gas
phases and
vary because of the exchange of
matter between these two components. In addition, the central gas
is enriched by stellar ejecta. The
mass of metals in stars increases as metals are incorporated from the
star-forming gas . In the case of
the quasi-stationary regime, we obtain for the gas in the diffuse
phase:
![[EQUATION]](img960.gif)
while we get for the dense central phase:
![[EQUATION]](img961.gif)
where is the age of the galaxy.
Since the halo is not enriched directly, but through the mass loss of
the galactic core, its metallicity remains for a long time much
smaller than the one attached to this central component which receives
the stellar ejecta. The second term of
, which is constant in time,
corresponds to the fact that very quickly a "quasi equilibrium" regime
sets in where the gain of metals within this central phase
from stellar ejecta balances the
loss due to the exchange of matter with the diffuse phase, which
replaces some gas with the metallicity
by some gas falling from the halo
with the metallicity . Since this
exchange of gas between both components
and
is driven by supernovae, or stellar
winds, whose importance is parameterized by
, see (B2), the equilibrium
metallicity is smaller for small temperatures (weak potential wells)
where these flows of matter are more important. Then
increases linearly with time as
receives some metals from
at a constant rate (the term in
corresponds to the second term in
, simply multiplied by a
temperature-dependent factor and time). Naturally, when
reaches the "stationary" value
described above for , this
"equilibrium" regime stops, both phases have the same metallicity
which increases linearly with time as the enrichment process goes on.
The stellar metallicity is:
![[EQUATION]](img962.gif)
The second term in , which is
constant in time, corresponds to the "stationary" regime we described
for . Since stars form from the
dense phase , their metallicity
quickly reaches the surrounding gas metallicity
which is constant with time. Later,
when most baryons are incorporated into stars
( ), the stellar metallicity
increases to reach y if the previous equilibrium value was
smaller than y. Indeed, at very long times when all the gas is
converted into stars the mean stellar metallicity
must be equal to the yield by
definition, since our system is closed (there is no global mass loss
nor gain although the mass of individual galaxies evolves with
time).
Appendix F: role of parameters and scalings
The model we constructed in the previous sections has only two main
specific parameters: and
, which determine respectively the
size (and mass) of galaxies and their star formation rate. For massive
galaxies, with , there is also a
dependence on , while for faint
galaxies there is a dependence on ,
but this is not critical. Naturally, it also depends on the usual
cosmological parameters , and on the
power-spectrum for the multiplicity
functions. Now we shall see how we can get the value of
and
, for a given set of cosmological
parameters and a fixed .
Let us consider a galaxy like the Milky Way located on the curve
(see Fig. 2), defined by a fixed
temperature T or circular velocity V. From the relation
we obtain
, and then all the characteristics
of this galaxy. Thus, we get:
![[EQUATION]](img967.gif)
and
![[EQUATION]](img968.gif)
Besides, since we have
, and increasingly so for massive
galaxies like the Milky Way as we noticed earlier (in fact, for faint
galaxies which have not exhausted their gas content
while for bright galaxies which
have already consumed most of their gas content
). Hence, a larger
leads to a higher gas/star mass
ratio and a larger luminosity, which is quite natural since it means a
less constraining cooling constraint, whence a broader, more massive
and lower density halo. Similarly, a larger
leads to a higher gas/star mass
ratio, since it means a longer star formation time-scale, whence fewer
stars. It does not influence the luminosity because the mass in the
form of long-lived stars is of the order of the initial mass of gas
for these dense galaxies. As a consequence, the observed luminosity
and gas/star mass ratio of the Milky Way, which corresponds to a
circular velocity of 220 km/s and a temperature
K, give the value of
and
, as a function of the cosmological
parameters. Thus we obtain:
![[EQUATION]](img974.gif)
Now, we can use these values of
and to get the variations of all
physical characteristics of the galaxies we considered in our model
with the cosmological parameters. Some of these scalings are shown in
Table F1. However, these relations are quite general. For instance,
the fact that for the Milky Way
gives if the initial ratio of
baryons in the halo is representative of the Universe, there has been
no loss of baryons since the formation of the galaxy and most of the
gas is in the disk. Then, the luminosity
of the Galaxy, and its ratio
, lead to
. In this way we obtain the mass and
the radius of the halo from which the baryons which constitute the
Milky Way came, whence the position of the curve
and the value of the product
. For
, we get
. In Table F1 we consider two types
of galaxies: i) massive galaxies like the Milky Way located on the
cooling curve , which have a high
luminosity and have already consumed most of their initial gas, and
ii) small galaxies located on
(hence characterized by the density contrast
), which are faint and have a small
stellar content.
![[TABLE]](img982.gif)
Table F1. Scalings
Thus, the values of the cosmological parameters imply well-defined
galaxy characteristics. For instance, for a given
, a larger
(that is a higher baryon fraction)
leads to a smaller radius R (since the total baryon mass,
linked to the luminosity, must not vary), a smaller mass M,
whence a larger number of objects (measured by
). Since the radius of a galaxy
similar to the Milky Way should be larger than 60 kpc we get a higher
limit on , while the observed
luminosity function, which gives the number density of galaxies, sets
a lower limit. These two limits could have been incompatible, since
for there is no freedom in the
choice of the function which
determines the multiplicity function in the non-linear scaling
approach. Thus it appears to be a remarkable success that for
it is possible to find a baryon
fraction (in our case ) which is
compatible with the three constraints provided by 1) the
nucleosynthesis predictions, 2) the galaxy masses and 3) their
luminosity function. Note however that for this latter constraint we
still have the choice of the power-spectrum
, that is its local index n
and its amplitude parameterized by .
Nevertheless, these two parameters are also constrained by
observations and we find that the choice
and
or a CDM power-spectrum (which is
in good agreement with observations) provides satisfactory results. In
fact, we could also choose a lower value for
, but this would create some
problems for Lyman- clouds (Valageas
et al. 1998). In the case of a low-density universe
, the conditions 1) and 2) imply
.
Appendix G: approximate power-law regimes
From the locus of galaxy formation implied by virialization and
cooling we may distinguish using the quasi-stationary approximation
three regimes characterized by a specific power- law behaviour:
1) Very faint galaxies, located on
and
K, with a constant density
contrast .
2) Faint galaxies, located on :
kpc and
K, with a nearly constant
radius .
3) Bright galaxies located on
kpc and K, which nearly have
exhausted all their gas .
G.1. Star formation
1) Very faint galaxies
Using (A3), (B7) and (D5) (since these galaxies have only consumed
a very small fraction of their gas content) we get:
![[EQUATION]](img987.gif)
Moreover, since these galaxies have a small stellar content
we have
, hence:
![[EQUATION]](img989.gif)
2) Faint galaxies
We obtain:
![[EQUATION]](img990.gif)
3) Bright galaxies
Since these galaxies have lost most of their gas, which has already
formed stars, we now have , and
using we get:
![[EQUATION]](img993.gif)
G.2. Mass/Light ratio and Tully-Fisher relation
For a constant star-mass/luminosity ratio
we obtain for the 3 regimes we
described above the scaling relations:
1) Very faint galaxies:
![[EQUATION]](img994.gif)
2) Faint galaxies:
![[EQUATION]](img995.gif)
3) Bright galaxies:
![[EQUATION]](img996.gif)
G.3. Metallicity
1) Very faint galaxies:
Since we noticed earlier that ,
we obtain:
![[EQUATION]](img997.gif)
2) Faint galaxies:
We still have , so we get:
![[EQUATION]](img998.gif)
The increase of the slope of , as
compared to the previous regime, is due to the fact that the evolution
time-scale gets smaller for more
luminous galaxies (their density increases, which implies that their
dynamical time decreases), and for a constant galactic age (of the
order of the age of the universe) it means that the halo is more
evolved, hence more enriched.
3) Bright galaxies:
These galaxies have already converted most of their initial gas
content into stars, which implies that
. Most of the gas is in the dense
component , since supernovae are not
very efficient and , hence
and we recover the usual one
component closed-box model, with .
Thus, in our case we obtain . Since
we have:
![[EQUATION]](img1003.gif)
G.4. Slope of the luminosity function
Using the PS approximation, we get for an
initial spectrum (that gives
results quite close to those obtained with CDM initial conditions) the
following behaviour.
1) Very faint galaxies:
![[EQUATION]](img1005.gif)
2) Faint galaxies:
![[EQUATION]](img1006.gif)
3) Bright galaxies:
![[EQUATION]](img1007.gif)
Using the non-linear scaling approximation, we write
for
, where
, and
for
with
.
1) Very faint galaxies:
![[EQUATION]](img1014.gif)
2) Faint galaxies:
![[EQUATION]](img1015.gif)
3) Bright galaxies:
![[EQUATION]](img1016.gif)
© European Southern Observatory (ESO) 1999
Online publication: April 19, 1999
helpdesk.link@springer.de  |