text:
\section{Motivation}
\label{motiv}

Recent observations of the evolution of galaxy clustering have
explored both the regime
$z \simless 1$, and have probed the distribution of galaxies at $z
\approx 3$.  The low-redshift works include a wide-field ($4^\circ
\times 4^\circ$) $I$-selected angular sample (\cite{postman98ap}),
Canada-France Redshift Survey galaxies with redshifts between $0 < z <
1.3$ (\cite{lefevre96ap}), the Hubble Deep Field
(\cite{connolly98ap}), field galaxies from the Canadian Network for
Observational Cosmology (CNOC) survey (\cite{shepherd97ap}), the
Hawaii $K$-selected redshift survey (\cite{carlberg97ap}), and a
redshift survey performed on the Palomar 200-inch telescope
(\cite{small99ap}).  The results of these surveys are still rather
discrepant; they don't yet give a consistent picture for how galaxy
clustering evolves with time.
The evolution of the relative clustering of old and
and young galaxies is also of interest, because it yields direct
information on where galaxy formation occurs as a function of
redshift. \cite{lefevre96a} made a simple attempt at measuring this
evolution by separating their sample by color. They found that red and
blue galaxies have comparable correlation amplitudes at $z>0.5$,
although red galaxies are more clustered today, by a factor of about
1.5 (in agreement with other local estimates, such as
\cite{davis76ap}, \cite{giovanelli86ap}, \cite{santiago92ap},
\cite{loveday95ap}, \cite{loveday96ap}, \cite{hermit96ap}, and
\cite{guzzo97ap}).  The evolution of the density-morphology relation
in clusters also contains information about where galaxies form as a
function of redshift, showing that at $z\sim 0.5$ there is
significantly more star formation in clusters than there is today
(Butcher \& Oemler 1978, 1984; \cite{couch87ap}; \cite{dressler92ap};
\cite{couch94ap}; \cite{oemler97ap}; \cite{dressler97ap};
\cite{poggianti99ap}).

Measurements of the clustering of Lyman-break objects (LBOs) at $z\sim 3$
(\cite{steidel98ap}) give a more unambiguous indication of the
evolution in clustering.  In particular, measurements of the amplitude of
counts-in-cells fluctuations (\cite{adelberger98ap}) or the angular
autocorrelation function (\cite{giavalisco98ap})
suggest that galaxies were as strongly clustered in comoving
coordinates at $z \sim 3$ as they are today.  If the LBOs are unbiased
tracers of the mass density field, these results contradict the widely accepted
gravitational instability (GI) model for the formation of large-scale
structure, unless one assumes an unacceptably low value of $\Omega_0$ in order
to prevent the growth of the clustering of galaxies between $z=3$
and today.  Therefore, the objects observed at high redshift are probably more
highly ``biased'' tracers of the mass density field than are galaxies
today. That is, they have a high value of $b_g\equiv\sigma_g/\sigma$, where
$\sigma_g\equiv\avg{\delta_g^2}^{1/2}$ is the rms galaxy density fluctuation
and $\sigma\equiv\avg{\delta^2}^{1/2}$ is the rms mass fluctuation. The
counts-in-cells analysis of \cite{adelberger98a} suggests that
at $z=3$ the bias of LBOs is $b_g \sim 2 b_0$ (for $\Omega_0=0.2$,
$\Omega_\Lambda = 0$), $b_g \sim 4 b_0$ (for $\Omega_0=0.3$, $\Omega_\Lambda =
0.7$), or $b_g\sim 6 b_0$ (for $\Omega_0=1$), where $b_0$ is the bias of
galaxies today.

How does the observed clustering since $z\approx 3$ relate to the underlying
mass density fluctuations? From a theoretical perspective, the bias decreases
with time because of three effects. First, at early times, collapsed objects
are likely to be in the highest peaks of the density field, since one needs a
dense enough clump of baryons in order to start forming stars.  Such
high-$\sigma$ peaks are highly biased tracers of the underlying density field
(\cite{doroshkevich70ap}; \cite{kaiser84ap}; \cite{bardeen86ap};
\cite{bond91ap}; \cite{mo96ap}).  As time progresses, lower peaks in the
density field begin to form galaxies, which are less biased tracers of the mass
density field. Second, the very densest regions soon become filled with
shock-heated, virialized gas which does not easily cool and collapse to form
galaxies (\cite{blanton98ap}). These two effects cause a shift of galaxy
formation to lower density regions of the universe. This shift is evident in
the real universe: young galaxies are not found in clusters at $z=0$.  To keep
track of these effects, we define the bias $b_\ast$ and correlation
coefficient $r_\ast$ of galaxy formation as
\begin{equation}
b_\ast \equiv \frac{\avg{\delta_\ast^2}^{1/2}}{\avg{\delta^2}^{1/2}} \quad
{\mathrm{and}}\quad
r_\ast \equiv \frac{\avg{\delta_\ast\delta}}{\avg{\delta_\ast^2}^{1/2}
\avg{\delta^2}^{1/2}},
\end{equation}
where $\delta\equiv\rho/\avg{\rho}-1$ is the overdensity of mass and
$\delta_\ast\equiv\rho_\ast/\avg{\rho_\ast}-1$ is the overdensity field of
``recently formed'' galaxies, each defined at some smoothing scale. By
``recently formed,'' we mean material that has collapsed and formed stars
within the last 0.5 Gyrs. Alternatively, one can consider $\delta_\ast$ as the
overdensity field of galaxies weighted by the star formation rate in each ---
for the purposes of this paper we consider the formation of a galaxy equivalent
to the formation of stars within it. As functions of redshift, $b_\ast(z)$ and
$r_\ast(z)$ are essentially differential quantities which keep track of where
stars are forming at each epoch. They both decrease with time for the reasons
stated above. Predictions of $b_\ast(z)$ and $r_\ast(z)$ are complementary to
predictions of the star formation rate as a function of redshift
(\cite{madau96ap}; \cite{nagamine99ap}; \cite{somerville98bp};
\cite{baugh98ap}); whereas those studies examine {\it when} galaxies form, we
examine {\it where} they form.

The third effect is that after galaxies form, they are subject to the same
gravitational physics as the dark matter; thus, the two distributions become
more and more alike, debiasing the galaxies gravitationally (\cite{fry96ap};
\cite{tegmark98ap}; see Section \ref{burst}). The history of $b_\ast(z)$ and
$r_\ast(z)$ convolved with effects of gravitational debiasing determines the
history of the bias of all galaxies, quantified as
\begin{equation}
b_g \equiv \frac{\avg{\delta_g^2}^{1/2}}{\avg{\delta^2}^{1/2}} \quad
{\mathrm{and}}\quad
r_g \equiv \frac{\avg{\delta_g\delta}}{\avg{\delta_g^2}^{1/2}
\avg{\delta^2}^{1/2}},
\end{equation}
where $\delta_g\equiv\rho_g/\avg{\rho_g}-1$ is the overdensity of
galaxies.  Here, $b_g(z)$ and $r_g(z)$ are integral quantities, which
refer to the entire population of galaxies.
Until recently, most
papers on this subject have considered only the effect of bias ($b_g$)
on large-scale structure statistics. However, observational and
theoretical arguments suggest that scatter in the relationship
between galaxies and mass may also be important (\cite{tegmark98bp};
\cite{blanton98ap}); treating the relationship as purely deterministic
when analyzing peculiar velocity surveys or redshift-space distortions
of the power spectrum can produce observational inconsistencies
(\cite{pen98ap}; \cite{dekel98ap}).  Thus, even at lowest order, these
treatments need to include consideration of the correlation
coefficient $r_g$.

Finally, we will also define the cross-correlation of all galaxies and of young
galaxies as
\begin{equation}
b_{\ast g} \equiv
\frac{\avg{\delta_\ast^2}^{1/2}}{\avg{\delta_g^2}^{1/2}}
\quad {\mathrm{and}}\quad
r_{\ast g} \equiv \frac{\avg{\delta_\ast\delta_g}}
{\avg{\delta_\ast^2}^{1/2} \avg{\delta_g^2}^{1/2}}.
\end{equation}
These quantities are important because they are potentially
observable, by comparing number-weighted and star-formation weighted galaxy
density fields.

Previous theoretical efforts have focused on the evolution of the
clustering of all galaxies, or equivalently, the evolution of
the integral quantities $b_g(z)$ and $r_g(z)$. There has been notable
success in this vein in explaining the nature of the LBOs. In the
peaks-biasing formalism, the halo mass of collapsed objects determines
both their number density and their clustering strength
(\cite{doroshkevich70ap}; \cite{kaiser84ap}; \cite{bardeen86ap};
\cite{bond91ap}; \cite{mo96ap}); interestingly, halos with masses $>
10^{12} M_\odot$ at $z=3$ have both a number density and clustering
strength similar to those of LBOs, in reasonable cosmologies
(\cite{adelberger98ap}), a result verified by $N$-body simulations
(\cite{wechsler98ap}; \cite{kravtsov98ap}). This fact is reflected in
the results for high-redshift clustering of semi-analytic galaxy
formation models, which also find that galaxies at $z\sim 3$ are
highly biased (\cite{kauffmann97ap}; \cite{kauffmann98ap};
\cite{somerville98ap}; \cite{baugh98ap}). Furthermore, hydrodynamic
simulations using simple criteria for galaxy formation
(\cite{evrard94ap}; \cite{katz98ap}; \cite{cen98ap}) find that the
distribution of galaxies at $z=3$ is indeed biased with respect to the
mass distribution, and that the clustering strength of galaxies
depends only weakly on redshift.

While the issue of $b_g(z)$ and $r_g(z)$ is the one which observations
are currently best-suited to address, perhaps other statistics can
constrain the nature of galaxy formation more powerfully. After all,
the fundamental prediction of theories for galaxy formation, such as
ours and such as the semi-analytic models mentioned above, is the
location of star formation as a function of time. Important
information about galaxy formation may be lost if one examines only
the integral quantities, which have been affected by the entire
history of galaxy formation convolved with their subsequent
gravitational evolution.
Therefore, we focus here on the evolution of the large-scale
clustering of galaxy {\it formation}, defined as the formation of the
galaxy's constituent stars --- that is, the evolution of $b_\ast$ and
$r_\ast$. Now is an opportune time to investigate such questions,
since large redshift and angular surveys which can examine this and
related properties of galaxies are imminent.

In this paper, we measure the clustering of galaxy formation in the
hydrodynamical simulations of \cite{cen98a}, which we describe in Section
\ref{simulations}. In Section \ref{timeformation}, we consider the properties
of galaxy formation in these simulations as a function of time, studying the
first two effects discussed above and the redshift dependence of $b_\ast$ and
$r_\ast$.  In Section \ref{burst}, we discuss the gravitational debiasing, the
third effect mentioned above. In Section \ref{observables}, we discuss
observable effects of the trends in galaxy formation found in the
simulations. Especially important is the strong evolution of the
cross-correlation between the star-formation weighted density field and the
galaxy density field; this evolution should be observable with surveys
such as the Sloan Digital Sky Survey (SDSS; \cite{gunn95ap}). In addition, the
evolution of the location of galaxy formation in the universe may be related to
the observed Butcher-Oemler effect and may affect the mass-to-light ratios of
clusters.  We conclude in Section \ref{conclusions}.

\setcounter{section}{1}
\section{Simulations}
\label{simulations}

The work of \cite{ostriker95a} motivated the choice of a flat cold
dark matter cosmology for the simulation used in this paper, with
$\Omega_0 = 0.37$, $\Omega_\Lambda = 0.63$, and
$\Omega_b=0.049$. Recent observations of high redshift supernovae have
lent support to the picture of a flat, low-density universe
(\cite{perlmutter97ap}; \cite{garnavich98ap}). Great uncertainty
remains, however, and future work along the lines of this paper will
need to address different cosmologies. The
Hubble constant was set to $H_0 = 100$~$h$~km~s$^{-1}$~Mpc$^{-1}$, with
$h=0.7$.  The primordial perturbations were adiabatic and random
phase, with a power spectrum slope of $n = 0.95$ and amplitudes such
that $\sigma_8=0.8$ for the dark matter at $z=0$, at which time the
age of the universe is 12.7 Gyrs. We use a periodic box 100 $h^{-1}$
Mpc on a side, with $512^3$ grid cells and $256^3$ dark matter
particles. Thus, the dark matter mass resolution is about $5\times
10^9 $ $h^{-1}$ $M_\odot$ and the grid cell size is $\sim$ 0.2
$h^{-1}$ Mpc.
The smallest smoothing length we consider is a 1 $h^{-1}$ Mpc radius top hat,
which is considerably larger than a cell size. On these scales and larger, the
relevant gravitational and hydrodynamical physics are correctly handled.  On
the other hand, subgrid effects such as the fine grain structure of the gas and
star formation may influence large-scale properties of the galaxy
distribution. As we describe here, we handle these effects using crude, but
plausible, rules.

\cite{cen98a} describe the hydrodynamic code in detail; it is similar
to but greatly improved over that of Cen \& Ostriker (1992a,b).
The simulations
are Eulerian on a Cartesian grid and use the Total Variation
Diminishing method with a shock-capturing scheme (\cite{jameson89ap}).
In addition, the code accounts for cooling processes and incorporates
a heuristic galaxy formation criterion, whose essence is as follows:
if a cell's density is high enough, if the cooling time of the gas in
it is shorter than its dynamical time, if it contains greater than the
Jeans mass, and if the flow around that cell is converging, it will
have stars forming inside of it. The code turns the baryonic fluid
component into collisionless stellar particles (hereafter ``galaxy
particles'') at a rate proportional to $m_b/t_{\mathrm{dyn}}$, where
$m_b$ is the mass of gas in the cells and $t_{\mathrm{dyn}}$ is the
local dynamical time.  These galaxy particles subsequently contribute
to metal production and the background ionizing UV radiation.  This
algorithm is essentially the same as that used by \cite{katz92a} and
Gnedin (1996a,b).
The masses of these galaxy particles range from
about $10^6$ to $10^9$ $M_\odot$. Thus, many galaxy particles are
contained in what would correspond to a single luminous galaxy in the
real universe. However, rather than grouping the particles into
galaxies, in this paper we simply define a galaxy mass density field
from the distribution of galaxy particles themselves. More details
concerning the galaxy formation criteria and their consequences are
given in Appendix \ref{formation}.

We will examine the results of the simulations at four output times: $z=3$,
$z=1$, $z=0.5$ and $z=0$. At each output time, we will consider the properties
both of all the galaxy particles and of those galaxy particles formed within
the previous 0.5 Gyrs. We will take these ``recently'' formed particles to be
representative of the properties of galaxy formation at that output time, and
label their overdensity field $\delta_\ast\equiv\rho_\ast/\avg{\rho_\ast} - 1$,
the ``galaxy formation density field.''

\setcounter{section}{2}
\section{Time dependence of Galaxy Formation}
\label{timeformation}

In this section, we study the relationship between the mass density,
the gas temperature, and the galaxy formation density fields at each
epoch.  We will show the evolution of the the quantities $b_\ast$ and $r_\ast$
with redshift, and demonstrate that this evolution is largely due to
the changing relationship between mass density and temperature.

Let us begin by considering the evolution of the temperature and mass density
fields as a function of redshift. At each of our four output times, we smooth
the fields with a top hat of 1 $h^{-1}$ Mpc comoving radius. In Figure \ref{dT}
we show the joint distribution of $1+\delta$, the normalized mass density, and
$T$, the gas temperature, as a function of redshift. We could instead have
considered the distribution of $1+\delta_b$, the baryonic density;
the results would have been nearly identical, because the dark matter
and baryonic overdensities are closely related on these scales. Most
of the gas, that is, does not cool, fall to the central parts of
galaxies, and form stars, but instead follows the same distribution as
the dark matter (\cite{cen98bp}). As the universe evolves, the
variance in density increases. In addition, as gas falls into the
potential wells, it shocks and heats up to the virial temperature
necessary to support itself in the potential well, raising the average
temperature of gas in the universe. Thus, volume elements above the
mean density move up and to the right on this diagram. These results
are consistent with previous work with the same code (for instance,
\cite{cen93bp}) and with other codes (for a summary, see
\cite{kang94ap}). Note that on 1 $h^{-1}$ Mpc scales, the importance
of cooling physics to the gas temperature is not immediately apparent;
in Appendix A, we show this same figure at the scale of a single cell,
which shows quite clearly the effects of including the radiative
physics of the gas.

We now consider the equivalent plot for the galaxy formation density
field. Figure \ref{dTg} shows the conditional mean of the galaxy formation
density field $1+\delta_\ast$ as a function of $1+\delta$ and $T$:
$\avg{1+\delta_\ast|1+\delta, T}$.
At any fixed density, the star formation rate declines as temperature
rises.
It is clear that the densest regions cannot cool and collapse at late
times because they are too hot.  To illustrate what Figure \ref{dTg}
implies about the relationship between galaxy formation and mass
density, Figure \ref{dendenstar} shows the conditional probability
$P(1+\delta_\ast|1+\delta)$ as the logarithmic grey scale and the
conditional mean $\avg{1+\delta_\ast|1+\delta}$ as the solid line. The
dashed lines are 1$\sigma$ limits around the mean. At high redshift,
the high density regions are still cool enough to have clumps of gas
in them cooling quickly; in this sense, the temperature on these
scales is not particularly important, making the relationship between
galaxy formation and mass density close to deterministic. At low
redshift, many regions become too hot to form new galaxies; in
particular, galaxy formation is completely quenched in the densest
regions, causing a turnover in $\avg{1+\delta_\ast|1+\delta}$. In
addition, at low redshifts, the galaxy formation rate depends strongly
on temperature, adding scatter to the relationship between galaxy
formation and mass (\cite{blanton98ap}).

The most obvious consequence of this evolution is that the bias of
galaxy formation is a strong function of time.  Figure
\ref{brstartime} shows $b_\ast$ and $r_\ast$ (defined in Section
\ref{motiv}) as a function of redshift for top hat smoothing radii of
$R=1$ and $R=8$ $h^{-1}$ Mpc. The bias of galaxy formation $b_\ast$ is
clearly a strong function of redshift, especially at small scales. The
decrease in the bias is due to the fact that the galaxy formation has
moved to lower $\sigma$ peaks and out of the hottest (and densest)
regions of the universe, as described in Section \ref{motiv}.

We can compare these results to those of the peaks-bias formalism for
the bias of dark matter haloes.  If we assume that the distribution of
galaxy formation is traced by $M > 10^{12}$ $M_\odot$ halos (that is,
halos with typical bright galaxy masses) which have just collapsed,
then according to the peaks-bias formalism (\cite{doroshkevich70ap};
\cite{kaiser84ap}; \cite{bardeen86ap}; \cite{bond91ap};
\cite{mo96ap}), the bias of mass in such halos with respect to the
general mass density field is:
\begin{equation}
b_\ast(z) = 1 + \frac{\delta_c}{\sigma^2(M,z)} \mathrm{,}
\end{equation}
where $\delta_c\sim 1.7$ is the linear overdensity of a sphere which
collapses exactly at the redshift of observation, and $\sigma(M,z)$ is
the rms mass fluctuation on scales corresponding to mass $M$, again at
the redshift of the observations.  Note that this formula differs from
the standard one for the bias of all halos which have collapsed before
redshift $z$. The dotted line in the upper panel of Figure
\ref{brstartime} shows the resulting bias. Thus, the prediction for
$b_\ast$ of the pure halo bias model is not much different from that
of our hydrodynamic model on large scales, even though the former does
not include all the physical effects of the latter.
That is, measuring
$b_\ast(z)$ alone cannot easily distinguish the two models.

More interesting is the evolution of the correlation coefficient
$r_\ast$ as a function of redshift, shown in the lower panel of Figure
\ref{brstartime}. At all scales, the correlation coefficient falls
precipitously for $z<1$, when the densest regions become too hot to
form new galaxies.  On the other hand, in the case of peaks-biasing,
\cite{mo96a} find a scaling between the halo and mass cross- and
autocorrelations that implies $r_\ast\sim 1$ on large scales at all
redshifts\footnote{On scales of 1 $h^{-1}$ Mpc, things are more
complicated, because $10^{12}$ $M_\odot$ halos so close together
actually overlap in Lagrangian space --- see \cite{sheth98ap}.}. This
is an important difference between the predictions of the models of
\cite{mo96a} and ours, which is presumably due to the more realistic
physics used in our model. Semi-analytic models can predict the
evolution of $r_\ast$; it will be interesting to see how dependent
this statistic is to the details of the galaxy formation model.  We
discuss a way to get a handle on $r_\ast$ observationally in Section
\ref{observables}.

\setcounter{section}{3}
\section{Gravitational Evolution of Bias}
\label{burst}

After galaxies form, they fall into potential wells under the influence of
gravity. Because the acceleration on galaxies is the same as that on the dark
matter, this gravitational evolution after formation will tend to bring both
the bias $b_g$ and the correlation coefficient $r_g$ closer to unity, as
described by \cite{fry96a} and \cite{tegmark98a}.  The evolution of the bias,
then, is determined by the properties of forming galaxies (outlined in the
previous section) and how those properties evolve after formation. Here we
investigate this process and show that the linear approximations of
\cite{fry96a} and \cite{tegmark98a} describe this evolution well, even in the
nonlinear regime.

\subsection{Evolution of the Clustering of Coeval Galaxies}

\cite{fry96a} and \cite{tegmark98a} rely on the continuity equation to
study the evolution of the density field of galaxies formed at a given
epoch.  In this subsection, subscript $c$ will refer to this coeval
set of galaxies. Both galaxies and mass satisfy the same equation,
which is to first order
\begin{equation}
\label{continuity}
{\dot \delta} + \nabla\cdot\vv{v} = 0\mathrm{,}
\end{equation}
assuming that galaxies are neither created nor destroyed. Since we are
dealing with a coeval set of galaxies, they cannot be created by
definition. Although it is possible to disrupt or merge galaxies in
dense regions (\cite{kravtsov98ap}), we are following the stellar mass
density in this paper, not the galaxy number density, and thus do not
consider these effects.

Assuming that there is no velocity bias between the volume-weighted velocity
fields of mass and of galaxies (which is borne out by the simulations), it
follows that ${\dot \delta} = {\dot \delta_c}$. This statement means that on
linearly scaled plots of $\delta_c$ against $\delta$, volume elements are
constrained to evolve along $45^\circ$ lines. We test this prediction on 30
$h^{-1}$ Mpc top hat scales, which should be close to linear, in Figure
\ref{evolve30}. Here we consider a burst of galaxies formed at $z=1$. The solid
lines are $\avg{\delta_c|\delta}$ at $z=1$, $z=0.5$ and $z=0$. The dashed lines
are the predictions extrapolated from $z=1$ as above, to
$z=0.5$ and $z=0$, respectively. Notice
use the growth factor of mass, $\sigma(z=0)/\sigma(z=1)$, which on these scales
is close to its linear theory value, to determine $\Delta\delta$, and assume
that $\Delta\delta_c$ is the same. Evidently the linear continuity equation
works on these scales. We also test this prediction on the nonlinear scale of 1
$h^{-1}$ Mpc in Figure \ref{evolve1}. We find that it works extremely well in
the range $3 < \delta < 100$; in higher and lower density regions, nonlinear
corrections to Equation (\ref{continuity}) are clearly important.

\cite{tegmark98a} use the continuity equation to make further
predictions about the bias properties of coeval galaxies. In
particular, given a ``bias at birth'' of $b_c(z_0)$ and a
``correlation coefficient at birth'' of $r_c(z_0)$, one can express
$b_c(z)$ and $r_c(z)$ in terms of the linear growth factor relative to
the epoch of birth $D(z)/D_0$:
\begin{eqnarray}
\label{bandr}
b_c(z)r_c(z) &=& 1 + \frac{b_c(z_0) r_c(z_0) - 1}{D(z)/D_0}\cr
b_c^2(z) &=& \frac{\left[(1-D(z)/D_0)^2 - 2(1-D(z)/D_0)b_c(z_0) r_c(z_0) +
b_c^2(z_0)\right]}{(D(z)/D_0)^2}
\end{eqnarray}
In Figure \ref{brevolve} we show as the solid lines the values of $b_c$ and
$r_c$ for the burst of galaxies at $z=1$, at each output time. The dashed lines
are the predictions based on $z=1$ for the results at $z=0.5$ and $z=0$. Notice
that on small scales, the prediction for $b_c$ remains extremely good. For
$r_c$, the linear prediction underestimates the degree to which galaxies and
mass become correlated on small scales; essentially, nonlinearities enhance the
rate at which initial conditions are forgotten.

We can compare the effects of debiasing to the decline in the
correlation between galaxy formation and mass with redshift. In Figure
\ref{debias} we show $b_\ast(z)$ and $r_\ast(z)$ at 8 $h^{-1}$ Mpc
scales, from Figure \ref{brstartime}, as the solid lines. The dotted
lines originating at each output redshift show how the galaxies formed
at that redshift would evolve according the continuity
equation. Naturally, $b_c(z)$ declines while $r_c(z)$ rises. Note that
$b_\ast(z)$ falls more quickly than debiasing can occur, which is why
old galaxies at redshift zero are still more highly biased than young
galaxies (\cite{blanton98ap}), despite having had more time to debias.

\subsection{Evolution of the Clustering of the Full Galaxy Population}

These results show that the decrease in the bias of the galaxy density field
with time found by \cite{cen98a} must be partly due to gravitational debiasing
(described in this section) as well as the decrease in $b_\ast$ (described in
Section \ref{timeformation}). We investigate this process here by showing the
evolution of the bias of all the galaxies in Figure \ref{csstartime} as the
solid lines, for a tophat smoothing of 8 $h^{-1}$ Mpc. The evolution of the
bias of galaxy formation, from Figure \ref{brstartime}, is shown as the dashed
lines. Notice that $b_g(z)$ and $b_\ast(z)$ are nearly the same, even though
$r_g(z)$ and $r_\ast(z)$ differ considerably; $r_\ast(z)$ plummets after $z=1$,
while $r_g(z)$ remains close to unity. About half the star formation in the
simulation occurs at $z<1$.  Although this recent star formation has a
low $r_\ast$, and is thus poorly
correlated with the mass distribution, this has little effect on
$r_g$, partly due to the gravitational debiasing.

Using the approximations of \cite{tegmark98a}, we can reconstruct
$b_g(z)$ and $r_g(z)$ from the properties of galaxy formation as a
function of redshift. We get equations similar to those of
equation~(\ref{bandr}), now integrated over the star formation
history:
\begin{eqnarray}
\label{fullev}
b_g(z) r_g(z) &=& 1 + \frac{1}{D(z) G(z)} \int dz' \left[b_\ast(z') r_\ast(z')
- 1\right] D(z') \frac{dG}{dz'}\mathrm{,}\cr b_g^2(z) &=& b_g^2(z) r_g^2(z) +
\frac{s^2}{\sigma^2}\mathrm{,}
\end{eqnarray}
where $D(z)$ is the linear growth factor, $G(z)$ is the cumulative
mass of stars formed by redshift $z$, and $\sigma$ is the rms mass
fluctuation. Calculating $b_g(z)$ requires first evaluating
$b_g(z)r_g(z)$ substituting it into the expression given.  In the
second term, the quantity $s^2$ is defined as:
\begin{equation}
s^2 \equiv \frac{1}{G^2(z)} \int dz' \frac{dG'}{dz'} \int dG''
\frac{dG''}{dz''} \avg{\delta_\perp(z') \delta_\perp(z'')} \mathrm{,}
\end{equation}
where $\delta_\perp \equiv \delta_\ast - b_\ast r_\ast \delta$ is the component
of the galaxy formation field which is uncorrelated with the local
density.\footnote{Note that the definition of $b_\ast$ in \cite{tegmark98a} is
equivalent to our quantity $b_\ast r_\ast$.}  These equations are simply a
result of applying the continuity equation (Equation \ref{continuity}) to the
case of continuous star formation, rather than an instantaneous burst, as in
Equation (\ref{bandr}).  Figure \ref{csstartime} shows $b_g(z)$, $r_g(z)$, and
$b_g(z) r_g(z)$ for all galaxies reconstructed from the properties of our
galaxy formation fields. $b_g(z)r_g(z)$ represents the linear regression of the
galaxy density on the mass density. Note that the reconstruction of this
quantity is quite accurate; on the other hand, the reconstructions of $b_g(z)$
and $r_g(z)$ separately, which require knowledge of $\avg{\delta_\perp(z')
\delta_\perp(z'')}$, have significant errors.
These errors are
mostly due to the poor time resolution of our output.\footnote{The results of
these simulations take large amounts of disk space, and thus when they were run
we did not attempt to store more than a handful of output times. It would be
impractical to rerun the simulations again for the sole purpose of obtaining
more output redshifts.} The continuity equation will prove
useful to future theoretical and observational work, as we discuss in Section
\ref{conclusions}.

\setcounter{section}{4}
\section{Observing the Evolution of Galaxy Formation}
\label{observables}

Here we discuss the observational consequences of the evolution of the spatial
distribution of galaxy formation.  First, we consider
observable properties of the star formation density field.  Second, we consider
the resulting properties of galaxy clusters.

\subsection{Star Formation Density Field}

We noticed in the last section that the correlation coefficient
between star forming galaxies and mass should decrease considerably
with time. We cannot currently observe this decrease directly in the
real universe.\footnote{Weak lensing studies (\cite{mellier99ap}) and
peculiar velocity surveys (\cite{strauss95ap}) do probe the mass
distribution and may prove useful for studying the evolution of
$b_g(z)$ and $r_g(z)$ directly.} However, from Figure \ref{csstartime} we note
that the galaxy distribution as a whole {\it does} correlate well with
the mass, in the sense that $r_g(z)\sim 1$ at all
redshifts. Therefore, we should be able to detect the evolution of
$r_\ast(z)$ by cross-correlating galaxy formation with the
distribution of all galaxies. In Figure \ref{grecent} we plot $b_{\ast
g}\equiv\sigma_\ast/\sigma_g$ and $r_{\ast
g}\equiv\avg{\delta_\ast\delta_g}/\sigma_\ast\sigma_g$ between the
galaxy formation density field and all galaxies as a function of
redshift, at 8 $h^{-1}$ Mpc scales. While the evolution in $b_{\ast
g}$ is rather weak, the evolution in $r_{\ast g}$ is striking, and
should be observable.

Observationally, measuring this correlation will require mapping the
density field of {\it star formation} in the universe, which has not
yet been done. Given that the fundamental prediction of galaxy
formation models is the location of star formation as a function of
time, such a map would be extremely useful. The spectral coverage of
the Las Campanas Redshift Survey (LCRS) includes a star formation
indicator ([OII] equivalent widths; \cite{schechtman96ap};
\cite{hashimoto98ap}); thus, one can measure this correlation at low
redshift using this data.  Using the LCRS, \cite{tegmark98b} have
addressed a related question by measuring the correlation between the
distributions of early and late spectral types (as classified by
\cite{bromley98ap}); they found $r\sim 0.4$--$0.7$, in qualitative
agreement with our findings here, if one makes a correspondence
between spectral type and star formation rate.  They can calculate $r$
because they understand the properties of their errors, which are due
to Poisson statistics; however, in the case of measuring spectral
lines to determine the star formation rate in a galaxy, the errors are
much greater and more poorly understood. Therefore, since $\delta_g$
is likely to be much better determined than $\delta_\ast$, the
quantity of interest will not be $r_{\ast g}$, but the combination
$b_{\ast g} r_{\ast g}=\avg{\delta_\ast\delta_g}/\sigma_g^2$, which is
the linear regression of star formation density on galaxy density and
is independent of $\sigma_\ast$.  Future redshift surveys such as the
SDSS will probe redshifts as high as $z\sim 0.2$---$0.3$ and will have
spectral coverage which will include measures of star formation such
as [OII] and H$\alpha$. Figure \ref{csstartime} indicates that $b_{\ast
g} r_{\ast g} \sim 0.35$ at $z=0$ and $b_{\ast g} r_{\ast g} \sim 0.5$
at $z=0.25$ (linearly interpolating between $z=0$ and $z=0.5$), a
difference that should be measureable.  A cautionary note is that the
linear interpolation in this range
may not be accurate, and that simulations with finer time
resolution are necessary to make more solid predictions.

In addition, the SDSS photometric survey will probe to even higher
redshift. Using the multiband photometry, one will be able to produce
estimates both of redshift and of spectral type. These measurements
will allow a calculation of the angular cross-correlation of galaxies
of different types or colors as a function of redshift out to
$z\sim 0.5$---$1$; Figure \ref{grecent} shows that this
evolution should be strong. The drawback to this approach is that one
cannot make a quantitative comparison between our models and the
cross-correlations of galaxies of different colors, because we can not
yet reliably identify individual galaxies in the simulations and
because there is not a one-to-one correspondence between galaxy color
and ages.  Needless to say, the observational question is still
worth asking, because quantitative comparisons will be possible in the
future using hydrodynamical simulations at higher resolution, and are
even possible today using semi-analytic models (\cite{kauffmann98ap};
\cite{somerville98ap}; \cite{baugh98ap}).

\subsection{Clusters of Galaxies}

The measurement of $b_{\ast g}$ and $r_{\ast g}$ directly in the field
is not possible given current data. However, the observed evolution of galaxy
properties in clusters
does give us a handle on the evolution
of the distribution of galaxy formation. Here, we investigate cluster
properties in the simulations. First, we describe the effect of the
clustering of galaxy formation on cluster mass-to-light ratios, and
how that subsequently affects estimates of $\Omega$ based on
mass-to-light ratios. Second, we discuss the Butcher-Oemler (1978,
1984) effect.
We select the three objects in the simulation with the largest
velocity dispersions, whose properties are listed in Tables
\ref{clustersa} and \ref{clustersb} at redshifts $z=0.5$ and
$z=0$. This number of clusters of such masses in the volume of the
simulations is roughly consistent with observations
(\cite{bahcall98ap}). Clusters \#2 and \#3 are about 5 $h^{-1}$ Mpc
away from each other at $z=0$, and have a relative velocity of 1000 km
s$^{-1}$ almost directly towards each other; thus, they will merge in
the next 5 Gyrs.

To calculate mass-to-light ratios, we must calculate the luminosity associated
with each galaxy particle. There are two steps: first, we assign a model for
the star formation history to each particle; then, given that star formation
history, we use spectral synthesis results provided by Bruzual \& Charlot
(1993, 1998) to follow the evolution of their
rest-frame luminosities in $B$, $V$, and $K$. The simplest model for the
star formation history of a single particle is that its entire mass forms stars
immediately, the instantaneous burst (IB) approximation.
However, it is unrealistic to expect that all of the star formation
will occur immediately; at minimum, it will at least a dynamical time
for gas to collapse from the size of a resolution element to the size
of a galaxy. Thus, we also consider an alternative model based on the
work of Eggen, Lynden-Bell, \& Sandage (1962; hereafter ELS), which
spreads the star formation out over the local dynamical time.  We
assign a star formation rate of
\begin{equation}
\frac{dm_\ast}{dt} = \frac{m_p}{t_{\mathrm{dyn}}} \frac{t}{t_{\mathrm{dyn}}}
e^{-t/t_{\mathrm{dyn}}},
\end{equation}
to each particle, where $m_p$ is the mass of the galaxy particle and
$t_{\mathrm{dyn}}$ is the local dynamical time at the location of the
particle at the time it was formed.
The evolution of the mass-to-light ratios of clusters
are qualitatively the same for both the IB and ELS models; the
evolution of the $B-V$ colors of cluster galaxies does differ
somewhat between the models, as described below.

We can calculate the mass-to-light ratios of these clusters in the
$B$-band, $\Upsilon_B \equiv (M/L_B)/(M_\odot/L_{\odot, B})$, and
compare them to the critical mass-to-light ratio $\Upsilon_{B,c}$
necessary to close the universe. We do the same in the $V$ and
$K$-bands, and show the results in Tables \ref{clustersa} and
\ref{clustersb} at redshifts $z=0$ and $z=0.5$, respectively.  An
observer in the simulated universe would thus estimate
$\Omega_{\mathrm{est}}(z=0) \equiv \Upsilon_{B}/\Upsilon_{B,c}\approx
0.4$--$0.5$ based on cluster mass-to-light ratios, not far from the
correct value for the simulation ($\Omega_0=0.37$).  The galaxy bias,
which causes $\Omega_{0,\mathrm{est}}$ to underestimate $\Omega_0$ by
a factor of about 1.6, is partially cancelled by the relative fading
of the light of the older cluster galaxies with respect to the younger
field galaxies.
The bias effect (as we have shown above) increases in
importance with redshift, while the differential fading of cluster
galaxies decreases in
importance. Thus, in the simulations, the cluster mass-to-light ratio
estimates of $\Omega_{\mathrm{est}}(z)$ decrease with redshift, even
though $\Omega(z)$ itself increases. We find similar results for
analyses performed in $V$ and $K$, which we also list in Tables
\ref{clustersa} and \ref{clustersb}. For the ELS star formation model,
the mass-to-light ratios are all higher, but the estimated values for
$\Omega$ and their redshift dependence do not change substantially.

\cite{carlberg96a} studied 16 X-ray selected clusters between $z\sim
0.2$ and $0.5$, in the K-corrected $r$-band. Their estimate of
$\Omega(z\approx 0.3) = 0.29 \pm 0.06$ is not far from what observers
in our simulation would conclude for that redshift,
$\Omega(z\approx 0.3) \approx 0.38$, using $V$-band
luminosities.  However, the correct value in the simulations is
$\Omega(z=0.3) = 0.56$.
\cite{carlberg96a} found no statistically significant dependence of
either $\Upsilon_r$ or $\Upsilon_{r,c}$ on redshift, but
their errors are large enough to be consistent with the level of
evolution of these quantities seen in the simulations.  We caution,
therefore, that estimates of $\Omega_0$ from cluster mass-to-light
ratios can be affected by bias, by the differential fading between the
cluster galaxies and the field galaxies, and by the evolution of both
these quantities with redshift.

As an aside, Tables \ref{clustersa} and \ref{clustersb} also show that
$\Omega_0$ estimated from the baryonic mass in each cluster, $\Omega_b
M_{\mathrm{tot}}/M_{\mathrm{baryons}}$, is biased slightly high. This effect
occurs because of the slight antibias (5 -- 10\%) of baryons with respect to
mass at low redshift (due, presumably, to shocking and outflows in the gas
which prevent baryons from flowing into the potential wells as efficiently as
dark matter does). This result is consistent with previous work
(\cite{evrard90ap}; \cite{cen93ap}; \cite{white93ap}; \cite{lubin96ap}).
Measuring $M_{\mathrm{baryons}}$ is possible in the clusters because the gas is
hot enough to be visible in X-rays; the main difficulty is in measuring
$\Omega_b$, which is generally based on high-redshift deuterium abundance
measurements (e.g., \cite{burles98ap}) and Big Bang nucleosynthesis
calculations (e.g., \cite{schramm98ap}).
The fact that the baryon mass in clusters is closely related to the total mass
makes this method of estimating $\Omega_0$ less prone to the complications of
hydrodynamics, galaxy formation, and stellar evolution than using mass-to-light
ratios.

From the results of Section \ref{timeformation}, we expect that
cluster galaxies at $z=0.5$ should be younger and bluer than cluster
galaxies at $z=0$. Does this account for the Butcher-Oemler effect ---
the existence of a blue tail in the distribution of $B-V$ colors of
cluster galaxies at $z\sim 0.5$ (Butcher \& Oemler 1978, 1984)?  The
simplest approach to this question is to ask whether the mass ratio of
recently formed galaxies to all galaxies
in the cluster changes from $z=0$ to
$z=1$. Figure \ref{cgages} shows the distribution of formation times
of galaxy particles in each cluster at $z=0$ and at $z=0.5$, assuming
the IB model of star formation. For comparison, the thick histogram
shows the star formation history of the whole box.  At both $z=0$ and
at $z=0.5$, there has been no star formation in the previous 1 Gyr in
any cluster. On the other hand, the more realistic ELS model allows
star formation to persist somewhat longer.  Figure \ref{jerryfig}
illustrates this effect by showing the fraction of the stars in the
clusters formed in the previous 0.5, 1. and 2 Gyrs at $z=0$, $z=0.5$,
and $z=1$, now using the ELS model. For comparison, we show the same
curves for the whole box. Clearly, the fraction of young stars
increases with redshift more quickly in the clusters than in the
field. This is qualitatively in agreement with the observed
Butcher-Oemler effect.

We can look at the problem in a more observational context by
calculating the $B-V$ colors of cluster galaxies as a function of
redshift.  Following Butcher \& Oemler (1978, 1984), we define the
quantity $f_b$ (the ``blue fraction'' of galaxies) to be the fraction
of mass in galaxy particles whose colors are more than 0.2 mag bluer
than the peak in the $B-V$ distribution.  Observationally, $f_b\sim
0.05$ at $z=0$, but at redshift $z=0.5$, $f_b \sim 0.1$--$0.25$
(Butcher \& Oemler 1978, 1984; \cite{oemler97ap}).  We consider both
the IB and ELS approximations. Under the IB approximation, the colors
redden as the galaxy populations evolve (about 0.1 mag between $z=0.5$
and $z=0$), but the shape of the $B-V$ distribution changes little;
for all the clusters at both $z=0$ and $z=0.5$, $f_b \sim 0.05$ for
the IB approximation.  However, using the ELS model improves the
situation considerably;
we find $f_b \sim
0.05$ at $z=0$ and $f_b \sim 0.1$--$0.15$ at $z=0.5$, in good agreement
with observations. Thus, these simulations may be revealing the
mechanism behind the Butcher-Oemler effect.

It is worth noting that the astrophysics involved in the star
formation history of cluster galaxies is clearly much more complicated
than that which we model here.  First, the star formation history
inside each galaxy particle we create is surely more complicated than
any the models discussed in the beginning of this section.  Second,
star-burst mechanisms such as ram-pressure induced star formation,
which would affect galaxies falling into clusters
(\cite{dressler90ap}), or merger-induced star formation, which would
affect galaxies in dense environments, could be important. These
mechanisms are not modelled by these simulations.  Third, as stressed
by \cite{kauffmann95a}, the population of clusters observed at $z=0.5$
in an $\Omega = 1$ universe necessarily contains rarer peaks than the
population of clusters observed at $z=0$ (\cite{andreon99ap}), and the
differences in the formation histories of such different objects may
account for the Butcher-Oemler effect. On the other hand, this effect
should be unimportant for a low-density universe, in which structure
forms relatively early.

\setcounter{section}{5}
\section{Conclusions}
\label{conclusions}

We have examined the spatial distribution of galaxy formation as a function of
redshift in a cosmological hydrodynamic simulation of a $\Lambda$CDM universe
with $\Omega_0=0.37$. We quantified the evolution of the clustering of galaxy
formation with the bias $b_\ast(z)$ and the correlation coefficient $r_\ast(z)$
of galaxy formation. In our simulations, $r_\ast(z)$ evolves considerably,
whereas in the peaks-biasing formalism it remains unity at all redshifts.
The time history of these quantities, combined with the
gravitational debiasing, causes the evolution of $b_g(z)$ and $r_g(z)$ of all
galaxies. As described in Section \ref{observables}, this history of galaxy
formation could be probed observationally by examining the evolution of
$b_{\ast g} r_{\ast g}$, the linear regression of the star formation weighted
galaxy density fields on the number-weighted galaxy density field. The
mass-to-light ratios of clusters are also profoundly affected by this history,
with the effect that while $\Omega(z)$ increases with redshift, the
estimated $\Omega_{\mathrm{est}}(z)$ actually decreases. Finally, the evolution
of the distribution of galaxy formation in the simulation bears a qualitative
relation to the Butcher-Oemler (1978, 1984) effect, and under certain
assumptions about the star formation history of each galaxy particle can even
quantitatively account for it.

Understanding these results completely will require future work.
First, the low resolution of these hydrodynamic simulations (relative to
state-of-the-art $N$-body calculations) calls into question the
accuracy with which we can follow the process of galaxy formation, and
makes us unable to identify individual galaxies in high-density
regions. Thus we cannot follow adequately the effects of the merging
and destruction of halos, especially in clusters. This fact was the
basis of our decision to examine the stellar {\it mass} density field
rather than the galaxy {\it number} density field. Observationally, it
is possible to trace the stellar mass density crudely by weighting the
galaxy density field by luminosity, especially at longer
wavelengths. The evolution of bias in the
luminosity-weighted galaxy density field is dominated by the three
mechanisms described in Section \ref{motiv}. The evolution of bias
in the {\em number}-weighted galaxy density field is additionally affected
by the process of merging in dense regions.  We do not have the
resolution to treat this effect here; \cite{kravtsov98a} explore this
using a high-resolution $N$-body code.

Equally important is to explore the dependence of the evolution of
$b_\ast(z)$ and $r_\ast(z)$ on cosmology.  As we saw in Section
\ref{timeformation}, their evolution was dominated by the evolution of
the density-temperature relationship; as this relationship and its
time-dependence varies from cosmology to cosmology, we expect
$b_\ast(z)$ and $r_\ast(z)$ to vary as well. Just as important is the
uncertainty in the star formation model used, whose properties are
evidently rather important in determining the clustering and
correlation properties of the galaxies.
Furthermore, understanding the statistical properties of galaxy
clusters in the simulations will require more realizations than the
single one we present. Finally, larger volumes than we simulate will
be necessary to compare our results to the large redshift surveys,
such as the SDSS, currently in progress.

Since these simulations are expensive and time-consuming to run, we would like
to find less expensive ways of increasing the volume of parameter space and
real space which we investigate. It may be possible to capture the important
aspects of the hydrodynamic code by using much less expensive $N$-body
simulations. One way to do so is to determine the relationship between galaxy
density, mass density, and velocity dispersion at $z=0$, and simply apply that
relation to the output of an $N$-body code at redshift zero, as suggested by
\cite{blanton98a}. However,
the
final relationship between galaxies, mass, and temperature will depend both
on the time evolution of the mass-temperature relationship, and the
gravitational debiasing. For instance, if all galaxies form at high
redshift, galaxies will have had
time to
debias completely. To take into account such effects explicitly, we want to
apply a galaxy formation criterion at each time step, and follow the
gravitational evolution of the resulting galaxies to find the final
distribution at $z=0$.  If one could do so, one could run large volume dark
matter simulations, in which one formed galaxies in much the same way as they
form here. Motivated by Figure \ref{dTg}, we propose applying our measured
$\avg{\delta_\ast|\delta, T}$ on 1 $h^{-1}$ Mpc scales in order to form
galaxies in such an $N$-body simulation, using the local dark-matter velocity
dispersion or the local potential as a proxy for temperature. This approach
assumes only that the dependence of galaxy formation on local density and local
temperature is not a strong function of cosmology. This method would be similar
in spirit to, but simpler than, the semi-analytic models which have been
implemented in the past.

The results of Section \ref{burst} suggest a simple way of exploring the
effects of changing the galaxy formation criteria in such $N$-body simulations,
or for that matter in the hydrodynamical simulations themselves, as long as one
is content with studying second moments and with ignoring the effects of the
feedback of star formation. Given more output times than we have available from
these simulations, one can simply determine the location of galaxy formation at
each time step -- {\it after the fact} -- and use Equation (\ref{fullev}) to
propagate the results to $z=0$, or to whichever redshift one wants. Thus, one
could easily examine the effects that varying the galaxy formation criteria
would have. Compared to rerunning the full simulation, it is computationally
cheap to determine the properties of $\delta_\ast$ at each redshift (given the
galaxy formation model) and then to reconstruct the evolution of $b_g(z)$ and
$r_g(z)$.

The continuity equation may also prove useful in comparing observations to
models. For instance, large, deep, angular surveys in multiple bands, such as
the SDSS, will permit the cross-correlation of different galaxy types as a
function of redshift, using photometry to estimate both redshift and galaxy
type (\cite{connolly98ap}). If one properly accounts for the evolution of
stellar colors, one will be able to test the hypothesis that two galaxy types
both obey the continuity equation. The sense and degree of any discrepancy will
shed light on whether one type of galaxy merges to form another, or whether new
galaxies of a specific type are forming.

Estimates of the star formation rate as a function of redshift are now possible
(\cite{madau96ap}). Perhaps the next interesting observational goal is to study
the evolution of the clustering of star formation. The Butcher-Oemler effect
tells us something about the evolution of star formation in dense regions, but
it is necessary to understand the corresponding evolution in the field, as
well.  The correlation of star-forming galaxies at different redshifts with
the full galaxy population may be a more sensitive discriminant
between galaxy formation models than measures of the clustering
of all galaxies.

\acknowledgments

This work was supported in part by the grants NAG5-2759, NAG5-6034,
AST93-18185, AST96-16901, and the Princeton University Research
Board. MAS acknowledges the additional support of Research
Corporation. MT is supported by the Hubble Fellowship HF-01084.01-96A
from STScI, operated by AURA, Inc., under NASA contract NAS5-26555.
We would like to thank James E.~Gunn, Chris McKee, Kentaro Nagamine,
and David N.~Spergel for useful discussions, as well as St\'ephane
Charlot for kindly providing his spectral synthesis results.


text:
Evans - We deserved to win
Steve Evans gives his post match thoughts on today's 1-1 draw with Chesterfield.
Steve Evans felt his side deserved more form today's 1-1 draw with local rivals Chesterfield.
The Millers went behind early on to a Jordan Bowery strike but after dominating large periods of the game Rotherham deservedly equalised in the second half through Kayode Odejayi.
"I think we dominated for long spells today, we played some wonderful stuff and I think we put in a really good shift," Evans told Millers Player after the game.
"If we keep dominating for spells like we did today and keep creating the chances then we will win. We have had enough possession, enough good play and enough openings around their box to win the game. Ainsworth was terrific until he ran out of legs, the same for Gareth Evans."
It was a disastrous start for the Millers after a slip from Scott Shearer presented the hosts with the opening goal, but Evans praised his 'keepers response to the error.
"Within a couple of minutes we have a corner, there is a hopeful ball into our half and Scott Shearer slips and they score. That is a one in a million moment and I felt for the big fella but he showed great character, his handling was good and he made a good block in the first half," he added.
Evans made two changes to his side with Lionel Ainsworth and Gareth Evans both starting and he was full of praise for his wide men.
"We thought we could get at them in wide areas and I thought we did," he said.
"There was plenty of width to our play, with plenty of pace and power, and I wanted Ben Pringle to get that free role, and I think it worked. Overall, I am pleased with the shift we put in today."
There is a full interview with Steve Evans on Millers Player now. Click here to listen.

redpajama_set_name: RedPajamaCommonCrawl


text:
Psychiatric Technician - Pine Rest Christian Homes, part-time 1st shift
Location	 Greater Grand Rapids, Michigan Area
Full-Time/Part-Time	 Part-Time
Shift	 First
The Psychiatric Technician in the Pine Rest Christian Homes program performs the role of physical and emotional care giver to clients of adult age who battle mental illness and/or developmental delays or disabilities. The Pine Rest Christian Homes program consists of five residential group home environments of which client populations vary in number of residents, age and level of care needed. If you have a passion for working with the Adult DD population (adult developmentally disabled), please continue reading for an explanation of other duties this type of role will include.
Primary Duties and Responsibilities include, but are not limited to:
Provides a safe and secure environment for patients and staff in both individual and group settings.
Will assist persons served with personal care. This can include bathing, shaving, washing hands, styling hair, using the bathroom, dressing, and any/all other activities of daily living.
Collaborates in day-to-day planning/development of patient programming and implementation of programs.
Is responsible to actively participate in safety management, crisis intervention and prevention. This also may include monitoring, assessment, de-escalation, implementation of restrictive measures, and emergency psychiatric and medical care.
May be required to survey, document, and report and all safety repair and maintenance needs.
May perform household duties such as cleaning, cooking and laundry. Drives and escorts persons served to community outings and to appointments.
Documents all progress notes, medication administration, and any other relevant information, reporting any immediate concerns according to departmental policies and procedures.
Responsible to monitor for and report to the designated staff any potential risk to person's served safety that could lead to an adverse outcome.
Education, Training, and Experience:
High School Diploma or equivalent is required.
Completion of six (6) months or more post high school education in behavioral sciences or similar experience is preferred.
CNA or similar certification, or one to two years of college education, is preferred though not required.
Specific skills, knowledge, and abilities:
Ability to provide care/service within the scope of: Holding a conviction to express Christ's love and compassion to recipients of services, coworkers, and surrounding communities through integrity, stewardship, empowerment, the promotion of diversity, and professional excellence.
Ability to provide cultural competent care with a wide range of individuals in a diverse community setting.
Requires physical and emotional stamina to deal with physical, emotional, social, mental and spiritual needs of patients/residents.
The candidate may be required to have a valid Michigan driver's license and ability access to access Pine Rest Transportation Vehicles for the performance of job duties.
Pine Rest is an EOE
About the Organization	 Pine Rest is a nonprofit, free standing, behavioral health system founded in 1910 in Grand Rapids, Michigan. This comprehensive behavioral health center, coupled with the Pine Rest network of 18 outpatient clinics and satellite offices in Michigan and Iowa, provide individualized and group therapy for people of all ages and all levels of need. Pine Rest clinicians offer therapeutic services in behavioral health for people of all ages and all levels of need across the continuum of care within a Christian framework.
Pine Rest has a 198-bed inpatient hospital program with a 36-bed child and adolescent inpatient and a large partial hospital program for adolescents. Additionally, Pine Rest has many inpatient services for adults, including: four 22-bed adult inpatient units each designed for a different level of acuity, a 22-bed co-occurring substance use disorder adult inpatient unit, a large adult partial hospital program, and a 26-bed older adult inpatient unit.
The Pine Rest Community and Residential Services Division also provides a wide array of services. With over 220 residential beds across a variety of programs, including treatment for substance use disorders, homes for adults with intellectual and developmental disorders, adults with mental illness, and a program for youth aged 11-18 with extensive trauma histories focusing on trauma treatment and life skills programming.
The Pine Rest Behavioral Health Solutions Division partners with behavioral health and medical organizations to increase access to psychiatry services and to provide a continuum of behavioral health and telepsychiatry services throughout many communities across the State of Michigan.
EOE Statement	 Pine Rest Christian Mental Health Services an equal employment opportunity employer and complies with the following:
RACE, COLOR, RELIGION, SEX, SEXUAL ORIENTATION, GENDER IDENTITY, NATIONAL ORIGIN
Executive Order 11246, as amended, prohibits employment discrimination based on race, color, religion, sex, sexual orientation, gender identity, or national origin, and requires affirmative action to ensure equality of opportunity in all aspects of employment.
PAY SECRECY
Executive Order 11246, as amended, protects applicants and employees from discrimination based on inquiring about, disclosing, or discussing their compensation or the compensation of other applicants or employees.
Section 503 of the Rehabilitation Act of 1973, as amended, protects qualified individuals with disabilities
from discrimination in hiring, promotion, discharge, pay, fringe benefits, job training, classification, referral, and other aspects of employment. Disability discrimination includes not making reasonable accommodation to the known physical or mental limitations of an otherwise qualified individual with a disability who is an applicant or employee, barring undue hardship to the employer. Section 503 also requires that Federal contractors take affirmative action to employ and advance in employment qualified individuals with disabilities at all levels of employment, including the executive level.
PROTECTED VETERANS
The Vietnam Era Veterans' Readjustment Assistance Act of 1974, as amended, 38 U.S.C. 4212, prohibits
employment discrimination against, and requires affirmative action to recruit, employ, and advance in
employment, disabled veterans, recently separated veterans (i.e., within three years of discharge or release from active duty), active duty wartime or campaign badge veterans, or Armed Forces service medal veterans.
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To search for an open position, please go to http://PRCMHS.appone.com
Psychiatric Technician - C&A Unit (Children & Adolescents),part time, 2nd shift in Grand Rapids, Michigan
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← Shop update tonight. But first….
I am really liking the looks of these mixed metal pieces!
Thanks LeAnn. I really like mixing the metals. Looks like I'll be doing more patina projects for components! Hope you're feeling better.
These are all so stinkin' gorgeous! I absolutley love your work! I neglected to leave a comment on your last post – Flat Stella looks totally satisfied with her visit! That post was adorable!
Hi Patti, Thanks. I still have more Stella photos I forgot to post. Was away for the weekend.
Love all your earrings and glad you had a good visit with your mom.
beautiful pieces. Stopping by to have a look at your blog and follow your journey through the bead soup blog party. This is my first one!


The band that MTV News and Substream Magazine labeled as "The Maine with a jersey-boy, Springsteen vibe," with a "sound like summer feels," has released a brand new EP following their 2016 smash-hit EP, I'm So Dead.
The Jersey boys just finished up their 'Fragile Heart Pt. II' tour and will now be co-headlining a cross-country tour which kicks off September 6th in Los Angeles with south Florida based pop artist Jake Miller. The tour wraps up with a few Florida dates in October.
The Stolen are a talented young band with a very strong up-beat pop rock vibe, honing the type of catchy alternative riffs and melodies that justify why they toured with bands like Neon Trees and the All American Rejects and played festivals such as Warped Tour and Surf & Skate.
I'm So Dead provided fans of the band with a bunch of pop rock jams. Fragile Heart has a more chilled-out, serene sort of feel to it. You can hear it in the beautifully played open string guitar chords and the echo-y & reverb-y solo patterns that add an old school flare to these new age songs.
One of the first thoughts I had after watching this was already pointed out by multiple YouTube commenters; this video has a Stranger Things vibe! The band even added the famous Stranger Things font on their self-titled wall poster.
The adolescent kids endlessly exploring on their bikes was definitely the main parallel to the show.
The video, directed by Felipe Gomez, is said to evoke memories of "the first taste of freedom and the nostalgia of night adventures in adolescence. The band even chose their own siblings to play the roles of the boy and girl.
Get tickets to see the band live with Jake Miller, and stream The Stolen's new album Fragile Heart HERE.


SAHA's mission: To provide as many neglected, unwanted, slaughter bound horses with a second chance at life and love.
When Amanda Vella, the founder of the charity Save a Horse Australia, got engaged last Christmas, she put in on Facebook, definitely the modern way to communicate important events in our lives. But for Vella the announcement wasn't made to a few dozen, or even a few hundred, or even a few thousand people. It was made to an astonishing 20,000 people who follow Vella, her steadfast band of volunteers and the stories of the horses she rescues on a daily basis from her home at Beaudesert.
But despite the overwhelming support and congratulations from those who support her and her organization, there are only a few who know the full story behind the engagement and fewer still who know Vella's personal story of love lost and love gained.
But the rebellious streak was not surprising. Vella lost her mother to cancer when she was seven, and her father, who didn't cope well with her mother's death, committed suicide when she was 13. Vella, caught in a maelstrom of loss and grief, turned to horses even more. At 14, she rescued her first horse, Gypsy.
They say what doesn't kill you makes you stronger, and watching Vella at work – organising to pick up a surrender case, speaking with the local RSPCA, confirming the care requirements of a particular horse, and telling me she's had to make the heart-rending decision to euthanaze a horse that isn't going to make it, I wonder whether she feels that the loss of her parents – and of Gypsy – actually in some way prepared her for the life she leads now, a life in which she witnesses again and again the best and the worst of human behaviour and where she has to handle the prospect of a horse's death on an almost daily basis.
There are a few things that make Vella angry and one is the idea that saving broken-down or old or sick horses is not valid. "Sometimes we get comments on Facebook about it, as we also do about the people who have let the horses get in this condition, and also about the guys that run the 'kill' lists and buy horses on a kill quota from the abbatoir," she says. "I am absolutely firm on the fact that every horse deserves a chance at life no matter what their condition, and those of us that run the charity make the choices for good reasons about which horses to save. There's no point in making accusations about people – stuff happens, people get in bad situations, or they simply don't know, and the kill guys are just doing their job." It's a credo that she takes into her social media, frequently stopping negative lines of comment with a firm hand.
With all of this going on you would hardly think Vella would have time to look for romance, but it found her in the strangest way possible. "When I was at high school in Narrandera I had a boyfriend, Mark, (Davies) but we were young, and when I moved up to the Gold Coast we lost touch," she says. "Then for Christmas 2012 I went home to see the family, and I met Mark again, and basically we just reconnected. What was so strange was that he was living and working in the Gold Coast too – we'd been living near each other for years, and had no idea, and then we met up at home again." The romance quickly became serious, and Davies, who works in a quarry at Beaudesert has thrown himself into the SAHA work, helping Vella out at the weekends and whenever he has time.
It was a year later to the day that Davies proposed, and a delighted Vella accepted. Their long-term ambition is to move further out of the Gold Coast to Beaudesert or to the Lockyer Valley in order to open a horse sanctuary on their own property. Just to contemplate what this young woman has done with her life in the past 20 years is to know that there is absolutely no doubt she will succeed – and in the process she is not only, as she says, "making horses better and giving them a second-chance," she is giving many of us who are horse lovers a chance to be better people.
The old grey donkey, Eeyore stood by himself in a thistly corner of the Forest, his front feet well apart, his head on one side, and thought about things. Sometimes he thought sadly to himself, "Why?" and sometimes he thought, "Wherefore?" and sometimes he thought, "Inasmuch as which?" and sometimes he didn't quite know what he was thinking about.
A. A. Milne – Winnie the Pooh.
There's no doubt about it, our Shetland Pony is depressed.
But it's not gender confusion that's brought about this bout of depression, it's the loss of a friend.
During the past ten years we've bought, re-trained, trained and rescued a lot of horses, and Sal (as in Sal Mineo, or Salieri as our music-loving vet likes to call him), has been that wonderful bombproof child's pony every horsey family wants. He's a friendly little chap but with a touch of small man syndrome, and over the years he's often quite happily bullied horses ten times his size.
He's had a few friends, but nobody special, not until last year when Mr Blue – so named because of his strangely blue eyes came to visit for a while and stayed for a year. For Sally and Mr Blue it was love at first sight, and they hung out, grooming each other, eating beside each other and generally being best buddies for a whole year, but then finally Mr Blue had to go home, and Sal lost his friend… And his appetite, and his lust for life.
I recognise his symptoms, because I've suffered from depression myself – that dreadful sense that nothing is as it should be, when you can feel sad, anxious, empty, hopeless, worried, worthless, guilty, hurt, irritable and strangely restless – quite often all at once!
A depressed person loses interest in activities that were once pleasurable (in Sal's case eating, and play-fighting, busting through fences and trying to get into the feed shed) they may experience loss of appetite, or overeating, have problems concentrating, remembering details or making decisions and may contemplate, attempt or even desire suicide.
Insomnia, excessive sleeping, fatigue, loss of energy, or aches, pains or digestive problems that are resistant to treatment may manifest as well. Fortunately for Sally he doesn't have to make too many decisions, but even so, seeing him stand, head down, in the corner of his paddock with a little lonely bubble around him, is a bit hard to take.
To paraphrase the song by Chicago, depression takes away the biggest part of us, or so it seems to me. We become less than ourselves, and that biggest part of us seems to disappear down a tunnel.
I've learned a careful balancing act through my bouts of depression. I've learned that depression often hides extreme sadness and grief and that if we don't feel and acknowledge it then the blues or the black dog will stay much longer. But I've also learned that giving in completely is no option.
Acknowledging the depression is part of the battle, getting appropriate help is another part, and time passing another bit of the jigsaw puzzle, and there is nothing anybody can do about that.
While Sal is suffering, we're treating him with kid gloves – extra feeds, little walks to juicy patches of grass, lavender oil under his nostrils (yes, truly), even homeopathy, and lots of cuddles and love. He'll bounce back and be his naughty self again – and I can't wait.
I ran a story by Katherine Waddington in my horse anthology, The Infinite Magic of Horses. She rescued two brumbies in Western Australia who were sisters. Once they were rehabilitated the time came for them to go to new homes.
Lily coped well, but Sophie did not and fell into a deep depression. Fortunately the humans around her realised what had happened, and they organised a visit from her sister, which immediately perked up her pining sibling.
Then, to lessen the blow of separation, they brought the two together from time to time so that both of them would gradually realise the separation wasn't final. Sophie gradually became so secure in herself that finally she appointed herself the nurturer for all the newly-arrived brumbies.


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'Looper' is one of the best science-fiction films of the last 20 years
Posted on Published: September 28, 2012 - Last updated: October 2, 2012
Directed by Rian Johnson
Written by Rian Johnson
If there's any justice in this world, we'll look back on Looper in 10 or 20 years, and pinpoint it as the moment when Rian Johnson entered into the realm of stardom. Though he proved his directing savvy with Brick and The Brothers Bloom, it's Looper that cements Johnson as an exciting and ambitious auteur, someone whose next film is something we should all be anticipating breathlessly, no matter what it ends up being. We may soon drown in the hyperbole surrounding Looper, but every so often, a film earns such high praise. Looper is a thrilling and daring story that earns its place next to The Matrix and Children of Men as one of the best science-fiction films of the past 20 years.
Joseph Gordon-Levitt plays Joe, a criminal who works as a looper in Kansas City, circa 2044, when time travel has yet to be invented. However, in 2074, time travel not only exists, but it's outlawed and used only by major criminal syndicates. When these gangsters want someone in their time dead, they send the unfortunate soul back to 2044 in a specific spot, where loopers kill and dispose of the bodies. One day, Joe finds himself tasked with closing his loop, also known as killing…himself. The older Joe, that is, played by Bruce Willis. The 2074 version of Joe, however, is prepared to fight off his younger self, and runs away with a mysterious plan in mind to change the future. Both versions of Joe are soon on the run from each other, and from Abe, the mob boss in charge of loopers (Jeff Daniels), who wants Joe's loop closed at any cost.
One reason why Looper is so exhilarating, so gripping, is that Johnson, who wrote the film, has plenty of surprises up his sleeve. It's rare to applaud a movie's marketing campaign, but whoever came up with the trailers for Looper deserves a pat on the back. All you need to know to hightail it to the multiplex is that Bruce Willis travels in time to meet his younger self—the rest, you should find out on your own. Johnson's script is smart and perceptive for myriad reasons, deftly balancing complex concepts with riveting action sequences. The question of whether a person would travel back in time to, say, kill Hitler to prevent the Holocaust and World War II is commonplace by now. However, by analyzing a similar dilemma in Looper, Johnson chooses to deals with the emotional ramifications of what changing the future means, how it changes a person. That aside, Looper is equally intelligent because it never forgets to be a hell of a lot of fun. Johnson knows how to make an audience laugh (Daniels gets the wittiest dialogue in a movie bursting at the seams with it), to move them, and to compel them. From the opening scene, Johnson sets the tone for a story that's concurrently darkly funny, twisty, and tense.
The futuristic world of Looper—close to our own, with a few tweaks, such as telekinesis treated as normal and hovering motorcycles—is steeped in noir conventions, from the younger Joe's dry, knowing voiceover narration to his fashion sense to the shadows lurking around every corner in the grimy, forbidding city. Within this setting and the other primary location, a Kansas farmhouse, Johnson, as well as production designer Ed Verreaux and cinematographer Steve Yedlin, gets to subtly yet confidently build a unique environment that's still hauntingly familiar. From the sets to the achingly sad score by Nathan Johnson to character beats like Joe learning to speak French, Looper threads the needle between being a propulsive action film and a probing look at how we have the ability to be implacable and stubborn, to stick with something and ignore the good sense telling us otherwise.
Gordon-Levitt, in some ways a muse for Johnson, delivers another assured performance as Joe, confirming that he's one of the most enjoyable and talented young actors. He's been a vital and interesting performer for a long time; though others may have blanched under the conditions of playing Joe (he's made to look like what Willis would've looked like 30 years ago), he thrives with the extra challenge of resembling what Willis was like physically and aurally when he was younger. Willis, no stranger to science fiction (12 Monkeys is a superior entry in the sci-fi genre), acquits himself nicely as the older, more world-weary and mature Joe. Despite a spotty overall filmography, he's always been talented, just as able to project emotion as when he fires a weapon. In Looper, he gets to do plenty of both, yet he's strongest with the emotional material, appropriately injecting weighty pathos into the proceedings.
Emily Blunt and Pierce Gagnon have pivotal roles in the second half of the film as a mother and son who help the younger Joe out as he figures out a way to fend off his future. Blunt, especially, wipes away any memory of her more glamorous roles with a versatile turn as Sara, who's tougher than she initially looks. Gagnon may not act again in his entire life, but that would be a crying shame. Playing Sara's 5-year old son, Gagnon is disturbingly good, always natural in his interactions and not at all precocious. In smaller roles, Daniels, Noah Segan, and the chameleonic character actor Garret Dillahunt get to work with various antagonistic traits, the gruff leader, the wounded underling, and the no-nonsense specialist. Though each are quite good, Daniels, in his first scene, threatens to walk away with the whole film, oozing snake-oil-salesman-style charm.
Looper is the product of an exceptionally confident filmmaker, someone who knows exactly what he's doing, whose talents are on full display. Looper is also a fantastically entertaining hybrid of science fiction, romance, drama, and action, a film that begs to be seen repeatedly, simply to further drink in its pleasures. Though Joseph Gordon-Levitt headlines the film, this is Rian Johnson's show. Looper is his entrée into the big time, something so worthy that he now genuinely deserves to be compared to Steven Spielberg and Christopher Nolan. Looper, easily one of the best films of the year, is the kind of film that demands attention be paid, and absolutely deserves it. If you were let down with the majority of the summer's splashy, big-budget blockbusters, take heed: Looper is the movie you've been waiting for.
— Josh Spiegel
Bruce WillisEmily BluntJeff DanielsJoseph Gordon-LevittLooperRian Johnson
'Unforgivable' a bizarre, enigmatic drama about paranoia
'Pitch Perfect' an enjoyable college comedy that could've been great


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Leadership for Individuals
Career Direction & Integration
Leadership for Teams
Working Widow ↗
Your career vision statement
Career Repositioning / By Aurelian Coaching
Career crafting is looking beyond just your next job or position, and it begins with defining a career vision statement. You can use that vision as a lens through which you evaluate your various career options by asking, "Does Option A get me closer to that vision, or does Option B?"
Some people getting nervous about vision exercises. For some of my "Type A" Achiever clients, they interpret creating a career vision statement as something that they are now required to work toward. That can be nerve-wracking! You never really know what's around the corner. Having a vision so profound and far into the future can feel restrictive – and setting yourself up for failure. In addition, you may feel as though articulating a vision means that you're putting a stake in the ground, and that you must then create a plan to execute on achieving that vision.
A career vision statement is NOT a goal that you must create a plan to execute toward.
Let's revisit what a vision actually is. Generally, a vision is very futuristic, typically on a grand scale, something almost unattainable because you can't clearly see a path between Here and There. It is based on instinct and your own natural tendencies, a feeling, or even some sort of compulsion. Your career vision statement is something that you will always reach for, something that inspires you to act – it may even give you goosebumps! It answers the questions, "What profound legacy do I want to have? What mark do I want to make? How do I want to change my world? If I were granted an overarching career wish, what would it be?"
A career vision statement is audacious. You need to be brave enough to dig it out.
For many professionals, what inspires them or drives them is buried so deep that they would have a hard time digging it out. But as hokey as it sounds, there is great value in actually digging out that vision for yourself. This exercise is a good one if you feel that your career has little direction, or the path you're on has no clear purpose. If what you've been doing up to this point has suddenly and mysteriously become the wrong path for you, then you would benefit from the career vision statement to serve as an anchor for determining where to do from here.
Here are some vision statements from organizations you might be familiar with:
The Hunger Project – to see every person lead a healthy life of self-reliance and dignity
CARE – to achieve an end to poverty
ASPCA – to see the US be a place where all animals are treated with respect and kindness
Habitat for Humanity – to have a world where everyone has a decent place to live
Profound vision statements are not limited to "do-good" organizations. Plenty of for-profit businesses also have aspirational vision statements.
Amazon – to be earth's most customer-centric company
Cold Stone Creamery – to be the ultimate ice cream experience
Disney – to make people happy
Google – to make the world's information universally accessible and useful
Harley Davidson – to fulfill dreams through the experiences of motorcycling
IKEA – create a better everyday life for many people
TESLA – accelerate the world's transition to sustainable energy.
Here's a clue that you have a good vision statement: If you would be hard pressed to define the exact conditions under which the vision would actually be achieved, or if it even seems unattainable but you still wish it would come to fruition somehow, congratulations! It is truly aspirational. You've then got your career vision statement.
"That's fine for companies and organizations, but how do I create a vision statement for myself?"
This is where you need to do some brainstorming, meditation, or journaling. For example, ask the following questions, and see what comes up for you.
Have you felt compelled to act in a job situation in a certain way, despite the culture or the "standard" way of doing things being the opposite?
Do you have activities, hobbies, or interests that you really love spending time on outside of work? What is it exactly about those outside activities that is fulfilling? Do you find those qualities in jobs you've enjoyed or not?
Is there a problem or concern in your industry that you would love to see solved once and for all?
There may be other questions to ask, however. But you must dig deep to get to a core motivator for you to act in your career.
When you find the root of your motivations, you can create a career vision which serves as your "professional North Star."
Here are some examples of career vision statements that I have helped others create for themselves.
My personal career vision is to…
Ensure that every woman has a real chance at performing at all levels of leadership.
Always be in a truly safe and diverse space for everyone to come and do their best work.
See that every person has the communication skills to diplomatically articulate exactly what they want to be able to say.
Make sure work is always a thing that I do, and never a thing that I am.
Be forever working on the most absolutely cutting-edge new technology.
Create a way for workplaces everywhere to prioritize people over profits.
What profound statements! How can one little person ever realize such incredible outcomes? The reality is, one person can't. However, their career vision statements will drive them to craft their careers and decision-making always toward the realization of that vision.
Proactive vs Reactive Career Management
The Learning Cycle at Work
Managing with Limited Resources
© 2018 Aurelian Coaching LLC
Copyright © 2021 | Aurelian Coaching


Kay Duncan is the wife of Pastor Ben, mother to 4 active boys and one very artistic daughter. She received her Bachelors of Science in Biblical Studies in 2017. She started coding websites in 2009 and has been passionate about web design/presence since.


HomeNews N ViewsGuarantee Minimum Sense..!
The Guarantee Minimum Income Scheme that Rahul Gandhi promises is being hailed by his media cronies as a game changer . The grand old party is gung-ho about the scheme that they think will catapult them to power . But isn't it time for Congress to realise that the voters are not as gullible as they were a few years ago ?
'Garibi Hatao' , a slogan that resonated during Congress election rallies remained a election plank and nothing else , the Congress party never made any effort to alleviate poverty , let alone eliminate it , during its numerous stints in power . When such a party promises something as populist and capital intensive as minimum income guarantee scheme then every Indian has to understand that this is another promise that the Congress party has no intention of honoring once it comes to power.
With General elections just around the corner, it's but natural that such outlandish ideas popup in the scheming minds of our politicians , it's for us the citizens to remain sane and not fall pray to ideas that might never see the light of the day , particularly in this case because the party that is promising such a scheme has never had a past record of 'walking the talk' .
At best, the Guarantee Minimum Income Scheme is a last ditch attempt by a desperate Congress to claw back into reckoning but they forget that the common man is not bereft of common sense to fall for their false promises..!


Our FlixTrain network is starting with fast train connections within Germany! On a daily basis, you have the opportunity to travel cheaply and comfortably on a train between Berlin and Stuttgart or Berlin and Cologne as well as between Hamburg and Cologne. We have amazing cities in our network for these connections, such as Frankfurt am Main, Hanover, Duesseldorf, and more.
Find your train schedules here!
We would like to offer you additional connections soon. Until then, we are happy to bring you from A to B comfortably, quickly, and cheaply on our trains.
NEW: Now available between Berlin and Cologne!
With our green FlixTrains, you have the opportunity to travel through Germany quickly, and comfortably. Simply select your connection from our network and book your ticket right away. We currently offer fast train connections between Berlin and Stuttgart, Berlin and Cologne as well as between Hamburg and Cologne. We are working daily on connecting new cities to our train network so that low cost train travel across Germany as well as beyond can be quick and comfortable.
With FlixTrain, you can travel to your destination quickly and comfortably. The benefits are obvious: free Wi-Fi and outlets, easy to book and change a booking, baggage included, as well as snacks and drinks on board. Of course, these are not the only benefits you will enjoy while traveling with FlixTrain. We will provide you with detailed information on our products during the booking process. Nevertheless, should you still have questions, you can simply take a look at our FAQs. We also provide you with inspiration and suggestions for things to do on the train.
Comfortably search for your connection online and book your ticket directly using our simple and intuitive booking platform. The decision where to go is up to you, of course! However, we can promise you one thing: FlixTrain leaves little to be desired! Do you want to receive current information on all new connections and specials? Then simply sign up for our newsletter or become a fan on Facebook.


The Fashion events are the heart of the fashion industry through which the common men and the fashion lovers come to know about the various fashion trends going on all around the world. The fashion designers are able to showcase their creativity in form of the various fashion outfits through the various fashion events only.
The second annual NGV gala took place at the Melbourne's fantastic National Gallery of Victoria and it showcased some amazing outfits worn by the famous celebrities. The NGV gala 2018 was a charity event whose purpose was to raise the funds for the gallery.
It was basically the Aussie version of the New York's fancy Met Gala. Numerous celebrities were a part of this amazing event and they attracted the attention of the people visiting the gallery. Natalie Portman, Troye Sivan, Poppy Delevingne, Daniel Andrew and his wife Cath, model Victoria Lee were some of the notable celebrities. Check out the glimpses of the NGV gala 2018 and see the excellent outfits that make the appearance of the celebrities beautiful and elegant!