text:
\section{Introduction}

In cosmological models of galaxy formation the formation history of galaxies, and hence their present day properties, are intimately linked with the formation history and properties of the dark matter (DM) haloes in which they reside. Therefore, if we wish to understand the process of galaxy formation it is important to observationally establish a link between the properties of galaxies and those of the halos in which they reside.

In recent years many studies have linked galaxy properties to halo mass using clustering, gravitational lensing, satellite kinematics, group catalogues or subhalo abundance matching, with the main focus being on linking the stellar properties (stellar luminosity, stellar mass, color, SFR) or those of the central black hole (luminosity, black hole mass) to the galaxy host dark matter halo properties. This work has shown strong correlations between halo mass and stellar mass, color, star formation rate, or morphology, such that more massive (luminous), redder (less star-forming), or more spheroidal galaxies live in more massive halos \citep[e.g.][]{Li06a,Yang08,Yang09,Zehavi11,More11,Mandelbaum06,Leauthaud11}. For AGN the relationships are less clear although correlations do exist between narrow line AGN luminosity or radio luminosity \citep{Wake04,Li06b,Wake08b,Mandelbaum09} and halo mass.
Perhaps unsurprisingly the strongest relationship occurs with stellar mass, which for central galaxies in halos show a tight correlation with a relatively small scatter of ~0.17 dex \citep{Yang11}. At fixed stellar mass properties that indicate the star formation history of a galaxy then show little dependence on halo mass \citep{More11}, when only considering central galaxies.

In this work we focus on investigating how the dynamical properties of galaxies, such as velocity dispersion (\Vdisp) or surface mass density (\Mden), in addition to stellar mass are related to the clustering amplitude of galaxies and hence their host dark matter halo properties. This is a particularly relevant question as it is becoming increasingly clear that many galaxy properties such as their current star-formation rates, star-formation histories, metalicities, and black hole masses are more closely related to these dynamical properties than their total stellar mass \citep[e.g.][]{Bender93,Ferrarese00,Gebhardt00,Kauffmann03b,Franx08}. If the formation history and properties of the host dark matter halo are the major underlying cause of these galaxy properties, we might expect that \Vdisp~or \Mden~are better indicators than stellar mass of these halo properties.

In this paper we make use of the very large sample of galaxies with velocity dispersion, stellar mass, size, color and morphology measurements from the seventh data release of the Sloan Digital Sky Survey \citep[SDSS DR7;][]{Abazajian09}. We split these galaxies into narrow bins of one parameter, in particular mass or \Vdisp, and then see if there is any dependence of the clustering amplitude on another galaxy parameter within that narrow bin. In this way we can investigate if there are any residual dependencies on halo properties manifested by higher or lower clustering amplitudes as one parameter is varied whilst another remains fixed.

Throughout this paper, we assume a flat $\Lambda$--dominated CDM cosmology with $\Omega_m=0.27$, $H_0=73 $km s$^{-1} $Mpc$^{-1}$, and $\sigma_8=0.8$ unless otherwise stated.

\section{Data}
\label{sec:data}

The galaxy data used in this analysis are gathered from the seventh data release of the SDSS \citep{Abazajian09}. We begin with the Large Scale Structure samples of the NYU Value Added Galaxy catalog \citep[VAGC;][]{Blanton05}. These samples have been carefully constructed for measurements of large scale structure and include corrections for fiber collisions, the tracking of spatially dependent completeness and appropriate random catalogs all of which are required to accurately measure clustering. The sample we use has an $r$ band magnitude range of $14.5 < r < 17.6$. In addition the NYU VAGC gives k-corrected (to z=0.1) absolute magnitudes \citep{Blanton03}, velocity dispersion measurements from the Princeton Spectroscopic pipeline, and circularised sersic fits for each galaxy, all of which we make use of in this analysis.

For estimates of the stellar mass we make use of the MPA-JHU value added catalog which provides stellar mass estimates based on stellar population fits to the SDSS photometry \citep{Kauffmann03, Salim07}. The overlap between the MPA-JHU and NYU VAGCs is close to but to quite 100\% and so we remove the regions where they do not match from the analysis and adjust the completeness corrections appropriately (see section \ref{sec:clus}). We also remove any region of the survey that has a spectroscopic completeness less than 70\%. This leaves an area of 7640 deg$^2$ and a total sample of 521,313 galaxies.

The SDSS velocity dispersions are measured within the 3" diameter SDSS fiber. We correct to a common aperture of one eighth of an effective radius ($r_e$), the central velocity dispersion, using the relation $\sigma_0 = \sigma_{ap}(8r_{ap}/r_e)^{0.066}$ where $r_{ap}$ = 1."5 \citep{Cappellari06}. $r_e$ is taken from the best fitting circularised sersic profile fit.

In addition to investigating how clustering depends on stellar mass and velocity dispersion, we also include the dynamical mass (\Mdyn) as an addition galaxy mass indicator. Estimates of galaxy stellar masses are uncertain due to the complex nature of the star formation history, stellar population synthesis modeling, extinction law and initial mass function \citep[e.g. see][]{Marchesini09, Muzzin09, Conroy09}. The dynamical mass, which is estimated purely from the velocity dispersion and the size of the galaxy, will not be affected by these same systematic uncertainties and will likely have errors more similar to those of the velocity dispersion. In addition there is a strong and fairly tight correlation between stellar mass and dynamical mass in the SDSS \citep[][see also Figure \ref{fig:MstarMdyn}]{Taylor10} and so both masses are largely tracing the same physical property of a galaxy.

To estimate dynamical mass we follow \citet{Taylor10} where
\begin{equation}
	 M_{dyn} = K_V \sigma_0^2 r_e/G
\end{equation}
with
\begin{equation}
	K_V = \frac{73.32}{10.465 + (n-0.95)^2} + 0.954
\end{equation}
where $n$ is the sersic $n$ parameter and the gravitational constant $G = 4.3 \times 10^{-3}$ pc $M_\odot^{-1}$ km$^2$ s$^{-2}$.

Finally we will make use of both galaxy color and morphology to further parameterize our galaxy samples. Throughout we use $g-r$ colors from the K-corrected NYU VAGC absolute magnitudes. As already stated these are corrected to $z=0.1$; although we will refer to them as $g-r$ colors they are not quite $g-r$ at rest. The morphological classifications we use come from Galaxy Zoo \citep{Lintott11} which provides multiple visual classifications for each galaxy in the SDSS spectroscopic sample. The parameter we use is the probability that a galaxy is an elliptical ($P_{el}$) corrected for redshift bias whereby higher redshift galaxies are more likely to be classified as ellipticals due to their smaller apparent sizes \citep[see ][ for details]{Lintott11}.

\begin{figure}

\vspace{11cm}
\special{psfile=vdispSM_paper.ps hoffset=0 voffset=0  hscale=43 vscale=43 angle=0}
\caption{\small The distribution of galaxies from the parent sample with \Mstar~$> 6\times10^{10}M_\odot$ in the \Mstar~-- \Vdisp~plane. The colored regions in the top panel show the high and low \Vdisp~samples at fixed \Mstar~and in the bottom panel they show the high and low \Mstar~samples at fixed \Vdisp.
\label{fig:VdSM}}
\end{figure}

\begin{figure*}

\vspace{11cm}
\special{psfile=2ptcross_wp_VdatSM.ps hoffset=-10 voffset=0  hscale=40 vscale=40 angle=0}
\special{psfile=2ptcross_wp_SMatvd.ps hoffset=250 voffset=0  hscale=40 vscale=40 angle=0}
\caption{\small The projected correlation functions of high and low \Vdisp~samples at fixed \Mstar~(left).  The projected correlation functions of high and low \Mstar~at fixed \Vdisp~(right). The correlation function measurements are colored to match the selection regions shown in Figure \ref{fig:VdSM}.
\label{fig:2ptVdSM1}}
\end{figure*}

\begin{figure*}

\vspace{11cm}
\special{psfile=2ptcross_wp_ratio_VdatSM.ps hoffset=-10 voffset=0  hscale=40 vscale=40 angle=0}
\special{psfile=2ptcross_wp_ratio_SMatvd.ps hoffset=250 voffset=0  hscale=40 vscale=40 angle=0}
\caption{\small The ratio of the projected correlation functions between high and low velocity dispersion samples at fixed stellar mass (left).  The ratio of the projected correlation functions between high and low stellar mass samples at fixed velocity dispersion (right). The best fit ratio on scales $1.6 < r_p < 25.1$ h$^{-1}$Mpc is shown as the dashed line.
\label{fig:2ptVdSM}}
\end{figure*}

\begin{figure*}

\vspace{11cm}
\special{psfile=2ptcross_wp_ratio_VdatdM.ps hoffset=-10 voffset=0  hscale=40 vscale=40 angle=0}
\special{psfile=2ptcross_wp_ratio_dMatvd.ps hoffset=250 voffset=0  hscale=40 vscale=40 angle=0}
\caption{\small The ratio of the projected correlation functions between high and low velocity dispersion samples at fixed dynamical mass (left).  The ratio of the projected correlation functions between high and low dynamical mass samples at fixed velocity dispersion (right). The best fit ratio on scales $1.6 < r_p < 25.1$ h$^{-1}$Mpc is shown as the dashed line.
\label{fig:2ptVddM}}
\end{figure*}

\begin{figure*}

\vspace{14.7cm}
\special{psfile=2ptcross_wp_ratio_MdenatSM.ps hoffset=-10 voffset=0  hscale=53 vscale=53 angle=0}
\special{psfile=2ptcross_wp_ratio_SMatMden.ps hoffset=250 voffset=0  hscale=53 vscale=53 angle=0}
\caption{\small The ratio of the projected correlation functions between high and low surface mass density samples at fixed stellar mass (left) and high and low stellar mass samples at fixed surface mass density (right). The best fit ratio on scales $1.6 < r_p < 25.1$ h$^{-1}$Mpc is shown as the dashed line.
\label{fig:2ptMdenSM}}
\end{figure*}

\begin{figure*}

\vspace{18cm}
\special{psfile=wpratiofit_SMVd.ps hoffset=60 voffset=560  hscale=45 vscale=45 angle=-90}
\special{psfile=wpratiofit_dMVd.ps hoffset=60 voffset=390  hscale=45 vscale=45 angle=-90}
\special{psfile=wpratiofit_MdenSM.ps hoffset=60 voffset=220  hscale=45 vscale=45 angle=-90}
\caption{\small The best fit large scale bias ratios for the samples plotted in Figures \ref{fig:2ptVdSM}, \ref{fig:2ptVddM} and  \ref{fig:2ptMdenSM}. The top panels show the bias ratio for high and low \Mstar~at fixed \Vdisp~and high and low \Vdisp~at fixed \Mstar. The middle panels show the bias ratio for high and low \Mdyn~at fixed \Vdisp~and high and low \Vdisp~at fixed \Mdyn. The bottom panels show the bias ratio for high and low \Mden~at fixed \Vdisp~and high and low \Vdisp~at fixed \Mden. There is a significant dependence of the bias on \Vdisp~or \Mden~at fixed mass, whereas there is little or no dependence on mass at fixed \Vdisp~or \Mden.
\label{fig:biasrat}}
\end{figure*}

\begin{table*}
  \begin{center}
    \caption{\label{tab:ratfit} Fits to correlation funtion ratios}
	\begin{tabular}{lcccc}
	\tableline
      	\multicolumn{1}{l}{Sample} &
      	\multicolumn{1}{c}{Best fit ratio} &
      	\multicolumn{1}{c}{Best fit $\chi^2$} &
      	\multicolumn{1}{c}{Ratio = 1 $\chi^2$} &
      	\multicolumn{1}{c}{Ratio = 1 prob} \\
	\tableline
\\
\Mstar~at \Vdisp~1 & 0.92 $\pm$ 0.06 & 1.69 & 3.26 & 0.661\\
\Mstar~at \Vdisp~2 & 1.01 $\pm$ 0.07 & 2.07 & 2.07 & 0.839\\
\Mstar~at \Vdisp~3 & 1.15 $\pm$ 0.12 & 5.52 & 6.97 & 0.223\\
\Mstar~at \Vdisp~All & - & - & 12.30 & 0.66\\\\
\Vdisp~at \Mstar~1 & 1.17 $\pm$ 0.07 & 7.51 & 12.10 & 0.033\\
\Vdisp~at \Mstar~2 & 1.23 $\pm$ 0.10 & 2.24 & 7.31 & 0.198\\
\Vdisp~at \Mstar~3 & 1.32 $\pm$ 0.12 & 4.88 & 11.54 & 0.042\\
\Vdisp~at \Mstar~All & - & - & 30.95 & 0.0089\\\\
\Mdyn~at \Vdisp~1 & 0.97 $\pm$ 0.05 & 0.40 & 0.74 & 0.981\\
\Mdyn~at \Vdisp~2 & 1.11 $\pm$ 0.07 & 3.15 & 5.27 & 0.384\\
\Mdyn~at \Vdisp~3 & 1.13 $\pm$ 0.12 & 2.13 & 3.18 & 0.673\\
\Mdyn~at \Vdisp~All & - & - & 9.18 & 0.87\\\\
\Vdisp~at \Mdyn~1 & 1.18 $\pm$ 0.05 & 6.81 & 14.87 & 0.011\\
\Vdisp~at \Mdyn~2 & 1.26 $\pm$ 0.09 & 4.62 & 12.80 & 0.025\\
\Vdisp~at \Mdyn~3 & 1.56 $\pm$ 0.16 & 3.06 & 13.89 & 0.016\\
\Vdisp~at \Mdyn~All & - & - & 41.57 & 0.00026\\\\
\Mstar~at \Mden~1 & 1.09 $\pm$ 0.05 & 0.22 & 2.60 & 0.762\\
\Mstar~at \Mden~2 & 1.04 $\pm$ 0.16 & 2.98 & 3.05 & 0.692\\
\Mstar~at \Mden~3 & 1.00 $\pm$ 0.14 & 0.46 & 0.46 & 0.994\\
\Mstar~at \Mden~4 & 1.17 $\pm$ 0.07 & 5.88 & 10.73 & 0.057\\
\Mstar~at \Mden~All & - & - & 16.84 & 0.66\\\\
\Mden~at \Mstar~1 & 1.23 $\pm$ 0.09 & 4.24 & 10.31 & 0.067\\
\Mden~at \Mstar~2 & 1.12 $\pm$ 0.05 & 6.55 & 10.69 & 0.058\\
\Mden~at \Mstar~3 & 1.22 $\pm$ 0.09 & 1.96 & 6.54 & 0.257\\
\Mden~at \Mstar~4 & 1.11 $\pm$ 0.08 & 9.47 & 11.23 & 0.047\\
\Mden~at \Mstar~All & - & - & 38.77 & 0.0071\\\\

	\tableline
    \end{tabular}
\end{center}
\end{table*}

\section{Samples}
\label{sec:samples}

We define a parent sample with stellar mass $> 6 \times 10^{10}M_\odot$ and 0.04 $< z <$ 0.113. The stellar mass limit and redshift cuts are chosen to yield the largest stellar mass limited sample of galaxies that can be defined from the NYU SDSS VAGC galaxy catalog, thus maximizing the number of galaxies available for clustering measurements. This relatively high stellar mass cut is also helpful as the SDSS velocity dispersions are only reliable at $>$ 75 km/s and thus become incomplete in \Vdisp~at low stellar masses. By inspecting the distribution of velocity dispersion in narrow stellar mass bins we estimate that 98\% of galaxies with stellar mass $> 6 \times 10^{10}M_\odot$ have velocity dispersion in excess of 75 km/s. Finally we remove galaxies with unreliable \Vdisp~measurements by requiring that the error in \Vdisp~be less than 10\%.

Since there is a significant scatter in the relation between stellar mass and velocity dispersion we must make further cuts if we wish to define samples that are complete in both. To define the velocity dispersion completeness limit
we investigate the distribution of stellar mass in narrow velocity dispersion bins for the full DR7 sample. Using these measurements we find the velocity dispersion that defines a complete sample of galaxies at the stellar mass of $6 \times 10^{10} M_\odot$. We find that for galaxies with a velocity dispersion of 210 km/s 85\% have stellar masses greater than $6 \times 10^{10}M_\odot$ and thus we restrict our sample to have \Vdisp~grater than this limit when defining \Vdisp~limited samples.

The aim of this work is to investigate which is more fundamental in determining the clustering amplitude, a galaxy's mass, either stellar or dynamical, or its central velocity dispersion. We approach this question by measuring the clustering where we have fixed the mass and allowed \Vdisp~to vary and visa-versa.
We define a series of samples with a narrow range in one parameter and then take the upper and lower quartile of the second parameter. We begin by defining the first velocity dispersion range, starting at the velocity dispersion completeness limit (210 km/s) and cutting at a dispersion of 242.3 km/s, the limit that contains 20\% of the galaxies with \Vdisp~larger than 210 km/s. We then split that sample by either stellar mass or dynamical mass into upper and lower quartiles. In a similar manner we construct two more samples with the same interval in \Vdisp~with successively higher \Vdisp~limits again splitting into highest and lowest quartiles in either stellar mass or dynamical mass. Details of these samples are given in Tables \ref{tab:SMatVd} and \ref{tab:dMatVd} in Appendix \ref{sec:appsamp}. To make the reciprocal samples, i.e. highest and lowest quartiles in \Vdisp~at fixed stellar mass or dynamical mass, we find the appropriate starting minimum mass and interval that produces three samples with the same number of galaxies as in the \Vdisp~ range samples. We then spit these into the highest and lowest quartiles of \Vdisp. Details of these samples are given in Tables \ref{tab:VdatSM} and \ref{tab:VdatdM}. Figure 1 shows the distribution of galaxies in the \Vdisp~-\Mstar~plane for the parent sample as well as the samples at fixed \Vdisp~and \Mstar.

We also define a series of samples in narrow stellar mass ranges where we take the highest and lowest quartiles in stellar surface mass density (\Mden) and their reciprocals (Tables \ref{tab:MdenatSM} and \ref{tab:SMatMden}) again ensuring that they are complete in both stellar mass and surface mass density. This is an important consistency check for our measurements. It is possible that the scatter introduced by larger errors on \Mstar~could reduce any differences in relative clustering amplitude compared to \Vdisp, something which should be reduced by using \Mdyn. Whilst any errors on \Mdyn~will be different and likely to be smaller than those on \Mstar~they will still be larger than the error on \Vdisp~due to the additional uncertainties in fitting the profile to determine \Re~and the sersic-n parameter. However, \Mden, which should show similar trends to \Vdisp, contains both the errors on \Mstar~and on \Re. Therefore, any reduction in clustering trends due to scatter in the measurement of the physical parameters should be largest for this sample.

For each pair of samples (e.g. high and low stellar mass at fixed dispersion) we find that the mean of the fixed parameter changes very little between the samples split into high and low quartiles. For a fair comparison we compare the mass ratio to the square of the \Vdisp~ratio since mass is proportional to $\sigma^2$. For all samples the ratio of the mean of the fixed parameter varies by less than 5\% and so should have a negligible effect on the clustering amplitude. Conversely the ratio of the means of the varying parameter covers a factor of 2 to 3.5.

In the Appendix \ref{sec:appsamp} we plot redshift, velocity, mass, mass density and morphology distributions for each sample where appropriate. As expected, since we have defined a volume limited parent sample and have only made cuts where we are complete in \Vdisp, $M_{den}$ and mass, the redshift distributions for all samples are the same.
\\

\section{Clustering measurement techniques}
\label{sec:clus}

The two-point correlation function, $\xi(r)$, is defined as the excess probability above Poisson of finding an object at a physical separation $r$ from another object. This is calculated by comparing the number of pairs as a function of $r$ in our galaxy catalogs with the number in a random catalog that covers the same volume as our data.

Since the space density of galaxies in our subsamples is very low shot noise would be a significant source of error for measurements of their auto-correlation functions. However, we can overcome this problem by using a much denser sample of galaxies to trace the underlying density field and measure the clustering of our sub-samples relative to this larger sample using the cross-correlation function.
The obvious choice for the larger sample is the parent sample we defined above containing all galaxies passing our basic selection criteria. This sample contains almost 65,000 galaxies and so has a space density almost 20 times higher than our largest sub-sample.
Whilst the individual cross-correlation functions will reflect the intrinsic clustering amplitude of both the sub- and parent samples the ratio between any two of these cross correlations will just reflect the ratio between the clustering of the two sub-samples in question, with the clustering of the parent sample in effect being 'canceled out'.

Measuring the line-of-sight distance using redshifts introduces distortions into the correlation function. The effect of these distortions can be overcome by separating the clustering signal into contributions perpendicular ($r_p$) and parallel ($\pi$) to the line-of-sight ($\xi(r_p,\pi)$). One can then integrate over the line of sight direction to estimate the projected correlation function
\begin{equation}
	\label{eq:wprp}
	w_p(r_p) = 2\int^{\infty}_0 d\pi\,\xi(r_p,\pi)
	        = 2\int^{\infty}_{r_p} \frac{r\,dr\,\xi(r)}{(r^2-r_p^2)^{1/2}}.
\end{equation}
The final expression only involves the real-space correlation function $\xi(r)$ showing that $w_p(r_p)$ is not compromised by redshift space distortions \citep{Davis83}. In practice it is only possible to integrate out to some maximum $\pi$ because $\xi(r_p,\pi)$ is poorly known on very large scales resulting in additional noise being introduced to the measurement. We integrate to 60$h^{-1}$Mpc which is sufficiently large to include most correlated pairs and gives stable results.

We make this measurement using the \citet{Landy93} estimator in the cross-correlation form, with
\begin{displaymath}
  \xi(r_p,\pi)  = \hspace{0.77\columnwidth}
\end{displaymath}
\begin{equation}
  \frac{DD1}{RR}\left(\frac{n_R^2}{n_D n_{D1}}\right) - \frac{DR}{RR}\left(\frac{n_R}{n_D}\right)  - \frac{D1R}{RR}\left(\frac{n_R}{n_{D1}}\right) + 1
\end{equation}
  where DD1 are the pair counts between the parent and sub-sample, DR are the pair counts between parent and random sample, D1R are the pair counts between sub-sample and random sample and RR are the pair counts between the random sample, all split into the $r_p$ and $\pi$ directions. We are able to use the same random sample in each term as all samples are complete throughout the same volume, i.e. they cover the same spatial extent and have the same redshift distributions. We calculate the pair counts in a grid which is logarithmically spaced in $r_p$ of width 0.2 log($h^{-1}{\rm Mpc}$) and linearly spaced in the $\pi$ direction of width 2$h^{-1}{\rm Mpc}$~with all separations in co-moving coordinates.
The random catalogue is based on the one provided by the NYU VAGC with additional cuts to match the exact spatial coverage of the MPA/JHU stellar masses and redshifts matching the redshift distribution of our samples. The resulting random catalogue contains almost 1.9 million randoms, close to 29 times as many as in our parent galaxy catalog, which is a sufficient number such that our errors are never dominated by shot noise in the random pair counts.

Since the individual bins in a correlation function measurement are highly correlated we need to generate accurate covariance matrices if we wish to compare our clustering measurements in a meaningful way. The simplest approach and the one we chose to follow is to use jackknife resampling \citep{Scranton02}. There is some debate about the accuracy of covariance matrices generated in this way; for instance \citet{Norberg09} suggest that the structure of jackknife covariance matrices may not be entirely accurate for $w_p(r_p)$~ measurements, although the variance is reliable. Conversely \citet{Zehavi02, Zehavi04, Zehavi05} find that they can closely reproduce the structure and amplitude of covariance matrices generated by mock catalogs using jackknife resampling. Because of this uncertainty, it might be preferable to generate covariance matrices from large numbers of mock galaxy catalogues generated by populating dark matter halo catalogs so as to reproduce the clustering and density of each sample. However, since we have so many sub-samples, each with a complex selection, it would be enormously challenging to undertake such a scheme. We have therefore chosen to use jackknife resampling which should be sufficient for our purposes. We split the SDSS area into 146 equal area regions and then repeatedly calculate $w_p(r_p)$~removing one area at a time. These 146 $w_p(r_p)$~measurements are then used to generate a full covariance matrix.

\section{Results}

\begin{figure}

\vspace{8.1cm}
\special{psfile=MstarMdynMorph_paper.ps hoffset=-10 voffset=0  hscale=57 vscale=57 angle=0}
\caption{\small The relationship between dynamical and stellar mass for all DR7 galaxies with 0.04 $< z <$ 0.113 and \Vdisp~$>$ 75 km/s (black contours) and those galaxies classified as either ellipticals (red contours) or spirals (blue contours). The points show the median \Mstar~in bins of \Mdyn~and the solid lines the biweight best fit. The dotted line shows the one-to-one relation. This relationship is almost identical independent of morphology over the whole mass range covered by this plot, and becomes indistinguishable for the mass range of interested in this paper.
\label{fig:MstarMdyn}}
\end{figure}

\subsection{Is galaxy mass or \Vdisp~more closely related to clustering amplitude?}

Figure \ref{fig:2ptVdSM1} shows the $w_p(r_p)$~measurements for the high and low \Vdisp~samples at fixed \Mstar~(left) and the high and low \Mstar~samples at fixed \Vdisp~(right). We find that when the mass is held fixed the high \Vdisp~samples have a higher clustering amplitude than the low \Vdisp~samples. This is true on all scales and for all mass ranges. However, when \Vdisp~is held fixed there appears to be little or no dependence of the clustering amplitude on \Mstar. This is the central result of this paper: clustering amplitude depends on \Vdisp~at fixed mass, but does not depend on mass at fixed \Vdisp.

This result is illustrated more clearly in Figure \ref{fig:2ptVdSM} which shows the ratio of $w_p(r_p)$~between the high and low \Vdisp~samples at fixed \Mstar~(left) and the high and low \Mstar~samples at fixed \Vdisp~(right). Figure \ref{fig:2ptVddM} is similar to Figure \ref{fig:2ptVdSM}, except \Mstar~is replaced by \Mdyn~and shows exactly the same trends as with \Mstar~. We also show in Figure \ref{fig:2ptMdenSM} the ratio of $w_p(r_p)$~ between high and low \Mden~samples at fixed \Mstar~and high and low \Mstar~samples at fixed \Mden. This is, in effect, the same as splitting by size at fixed mass or mass at fixed size. Since \Mdyn~and \Mstar~are highly correlated one would expect galaxies with smaller \Re~at a fixed \Mstar, thus higher \Mden, to have a higher \Vdisp. These samples should then be analogous to those with varying \Vdisp~at fixed \Mstar~and indeed they show the same trend of higher clustering amplitude at higher \Mden~when \Mstar~is fixed and very little dependence with \Mstar~when \Mden~is fixed. As discussed in Section \ref{sec:samples} this also implies that these observed trends are not the result of larger measurement errors on \Mstar~or \Mdyn~compared to \Vdisp, which could have reduced the clustering dependence on mass compared to \Vdisp.

To quantify these ratios in $w_p(r_p)$, which constitutes a ratio in galaxy bias, we find the best fitting scale independent amplitude on scales $1.6 < r_p < 25.1$ h$^{-1}$Mpc. These scales are sufficiently large as to be dominated by pair counts between DM halos, rather than galaxies within halos, and so should show a scale independence with respect to the dark matter clustering and give an indication of the relative linear bias of the two samples. For the $w_p(r_p)$~ratios shown in Figures \ref{fig:2ptVdSM}, \ref{fig:2ptVddM} and \ref{fig:2ptMdenSM} this appears to be the case and indeed a scale independent ratio is an acceptable fit for all but one of the samples. These fits are made using the full covariance matrices for the $w_p(r_p)$~ratio, and are shown as the dashed lines in Figures \ref{fig:2ptVdSM}, \ref{fig:2ptVddM} and \ref{fig:2ptMdenSM}. Details of the fits are given in Table \ref{tab:ratfit} and the best fit bias ratios and errors are plotted for all these samples in Figure \ref{fig:biasrat}. In addition to the best fit we also calculate the $\chi^2$ for a $w_p(r_p)$~ratio of one over the same scales, and give the $\chi^2$ value as well as the probability of an acceptable fit in Table \ref{tab:ratfit}. In all cases the best fit ratio is higher when \Vdisp~or \Mden~is varied at fixed mass than when \Vdisp~or \Mden~are fixed and the mass allowed to vary. Similarly when \Vdisp~or \Mden~are fixed the $w_p(r_p)$~ratios between the high and low mass samples are consistent with one in all but one case whereas the varying \Vdisp~or \Mden~samples at fixed mass are nearly all inconsistent with a $w_p(r_p)$~ratio of one. For each parameter pair we can combine the samples and determine the probability that all are consistent with a $w_p(r_p)$~ratio of 1. Again we find that at fixed \Vdisp~or \Mden~the samples are indeed consistent with showing no dependence of the clustering amplitude on mass at the 66\%, 87\% and 66\% levels, whereas there is only a 0.9\%, 0.03\% and 0.7\% chance that all three of the varying \Vdisp~or \Mden~samples at fixed mass are consistent with no variation in clustering amplitude on large scales.

On small scales the differences are just as clear with the varying \Vdisp~or \Mden~samples typically showing even larger $w_p(r_p)$~ratios than at large scales. The samples with varying mass at fixed \Vdisp~or \Mden~ occasionally show moderately larger $w_p(r_p)$~ratios on small scales than on large scales, but often there is no difference with the $w_p(r_p)$~ratio remaining consistent with one on all scales.

Overall these measurements make it clear that velocity dispersion or stellar mass surface density are more closely related to galaxy bias than either stellar mass or dynamical mass.
\\
\\

\subsection{The Importance of Morphology and Color}

\begin{table*}
  \begin{center}
    \caption{\label{tab:ratfitcolel} Fits to correlation funtion ratios for sample split by morphology and color}
	\begin{tabular}{lcccc}
	\tableline
      	\multicolumn{1}{l}{Sample} &
      	\multicolumn{1}{c}{Best fit ratio} &
      	\multicolumn{1}{c}{Best fit $\chi^2$} &
      	\multicolumn{1}{c}{Ratio = 1 $\chi^2$} &
      	\multicolumn{1}{c}{Ratio = 1 prob} \\
	\tableline
\\
\Pel~at \Vdisp~1 & 0.92 $\pm$ 0.05 & 2.44 & 4.55 & 0.473\\
\Pel~at \Vdisp~2 & 1.06 $\pm$ 0.09 & 4.29 & 4.71 & 0.452\\
\Pel~at \Vdisp~3 & 1.07 $\pm$ 0.10 & 2.95 & 3.41 & 0.638\\
\Pel~at \Vdisp~All & - & - & 12.67 & 0.63\\
\\
\Pel~at \Mdyn~1 & 1.12 $\pm$ 0.05 & 2.60 & 6.16 & 0.291\\
\Pel~at \Mdyn~2 & 1.20 $\pm$ 0.08 & 1.05 & 5.77 & 0.329\\
\Pel~at \Mdyn~3 & 1.10 $\pm$ 0.12 & 1.43 & 2.02 & 0.847\\
\Pel~at \Mdyn~All & - & - & 13.95 & 0.53\\
\\
$g-r$ at \Vdisp~1 & 1.35 $\pm$ 0.11 & 3.35 & 11.81 & 0.037\\
$g-r$ at \Vdisp~2 & 1.36 $\pm$ 0.14 & 4.55 & 11.34 & 0.045\\
$g-r$ at \Vdisp~3 & 1.17 $\pm$ 0.17 & 5.69 & 6.64 & 0.248\\
$g-r$ at \Vdisp~All & - & - & 29.80 & 0.013\\
\\
$g-r$ at \Mdyn~1 & 1.34 $\pm$ 0.10 & 6.66 & 16.34 & 0.006\\
$g-r$ at \Mdyn~2 & 1.50 $\pm$ 0.16 & 2.60 & 12.76 & 0.026\\
$g-r$ at \Mdyn~3 & 1.13 $\pm$ 0.11 & 3.83 & 5.19 & 0.394\\
$g-r$ at \Mdyn~All & - & - & 34.29 & 0.0031\\
\\
\Vdisp~at \Mdyn~El 1 & 1.29 $\pm$ 0.08 & 1.51 & 12.27 & 0.031\\
\Vdisp~at \Mdyn~El 2 & 1.32 $\pm$ 0.10 & 4.73 & 13.46 & 0.019\\
\Vdisp~at \Mdyn~El 3 & 1.29 $\pm$ 0.12 & 2.82 & 7.57 & 0.181\\
\Vdisp~at \Mdyn~El All & - & - & 33.30 & 0.0043\\
\\
\Vdisp~at \Mdyn~red 1 & 1.21 $\pm$ 0.06 & 2.32 & 12.08 & 0.034\\
\Vdisp~at \Mdyn~red 2 & 1.15 $\pm$ 0.08 & 1.08 & 4.49 & 0.482\\
\Vdisp~at \Mdyn~red 3 & 1.48 $\pm$ 0.15 & 1.34 & 10.71 & 0.058\\
\Vdisp~at \Mdyn~red All & - & - & 27.28 & 0.027\\
	\tableline
    \end{tabular}
\end{center}
\end{table*}

\begin{figure*}

\vspace{12cm}
\special{psfile=wpratiofit_Pel.ps hoffset=60 voffset=390  hscale=45 vscale=45 angle=-90}
\special{psfile=wpratiofit_col.ps hoffset=60 voffset=220  hscale=45 vscale=45 angle=-90}
\caption{\small The dependence of large scale bias on elliptical probability (top) and $g-r$ color (bottom) at fixed \Mdyn~(left)and \Vdisp~(right). The bias does depended on elliptical probability at fixed mass but not at fixed \Vdisp. However, there is a significant dependence of the bias on color at both fixed mass and \Vdisp.
\label{fig:biasrat2}}
\end{figure*}

\begin{figure*}

\vspace{12cm}
\special{psfile=wpratiofit_dMVd_El.ps hoffset=60 voffset=390  hscale=45 vscale=45 angle=-90}
\special{psfile=wpratiofit_dMVd_red.ps hoffset=60 voffset=220  hscale=45 vscale=45 angle=-90}
\caption{\small The dependence of large scale bias on \Vdisp~at fixed \Mdyn~(left) and \Mdyn~at fixed \Vdisp~(right) for elliptical galaxies (P$_{el} >$ 0.6; top) and red galaxies ($g-r >$ 0.9; bottom). The same result as for the whole sample remains, there is significant dependence of the bias on \Vdisp~at fixed \Mdyn~but none on \Mdyn~at fixed \Vdisp.
\label{fig:biasrat3}}
\end{figure*}

We have included the distribution in elliptical probability for each of the samples in the plots in Appendix \ref{sec:appsamp} as it demonstrates one area that is both potentially a concern but also scientifically important for this analysis. \Vdisp~is much better correlated with morphology or color than stellar mass is. \Mden~is also a better discriminator than mass, but not as good as \Vdisp~(see Wake et al. 2012 for a detailed study of these trends). Because of this when we fix \Vdisp~we come pretty close to fixing morphology regardless of the mass and when we split into high and low \Vdisp~samples at fixed mass we are pretty close to splitting into disks and spheriods (we also see a splitting by color in the same way). This is of course the heart of our investigation: is a tighter correlation between \Vdisp~and halo properties (compared to the correlation between mass and halo properties) the explanation as to why \Vdisp~is a better indicator than stellar mass of a galaxy's stellar population? This does however raise a potential worry regarding systematics: are we measuring the same thing when we measure \Vdisp~for a disk galaxy as compared to a spheroidal galaxy?

We tackle this question in several ways. Firstly we show in Figure \ref{fig:MstarMdyn} the observed relationship between \Mstar~and \Mdyn~for all the galaxies in SDSS with $0.04 < z < 0.113$ and \Vdisp~$>$ 75 km/s. We further split this sample into spheriods or disks based on the Galaxy Zoo classifications. The relationship is essentially identical regardless of morphology over practically the entire mass range. There is a small deviation at lower masses but this is below the mass range considered in this work. This gives us confidence that the velocity dispersion is measuring the same physical quantity for both disks and ellipticals within the SDSS fiber radius.

The second approach is a more direct one: we can see if morphology itself has any effect on the clustering amplitude of our galaxies at fixed mass or \Vdisp. We thus define samples with high and low elliptical probabilities in narrow ranges of \Mdyn~and \Vdisp. We note that we are unable to just take the quartiles of the distribution in elliptical probability as we have done for parameters previously as there is a redshift dependence to the probabilities assigned. This results from galaxies being harder to classify at higher redshift due to their smaller angular size and surface brightness dimming. Whilst there has been some correction for this effect applied to the Galaxy Zoo probabilities we find that it does not entirely remove this bias resulting in the samples split into upper and lower quartiles in \Pel~having different redshift distributions. We thus define our samples making use of the expectation that the morphological mix does not vary significantly over our narrow redshift range. We find the best fit linear relations between elliptical probability and redshift that produce the 25\% most and least likely ellipticals at each redshift and use these relations to define our samples. Details of these samples are given in Tables \ref{tab:PelatdM} and \ref{tab:PelatVd} and their distributions are plotted in Appendix \ref{sec:appsamp}.

Figure \ref{fig:biasrat2} shows the large scale $w_p(r_p)$~ratios of these high and low \Pel~samples at fixed mass and \Vdisp. As before we fit the $w_p(r_p)$~ratio (shown in Figure \ref{fig:2ptPel} in Appendix \ref{sec:appsamp}) between $1.6 < r_p < 25.1$ h$^{-1}$Mpc and determine the probability that the ratio is consistent with one. Details of these fits are give in Table \ref{tab:ratfitcolel}. At fixed \Vdisp~there is no evidence for any dependence of the clustering amplitude on morphology at any scale. At fixed mass the ratios are all non-zero with galaxies with a higher \Pel~showing a higher clustering amplitude than those with a low \Pel. However, the significance of these positive $w_p(r_p)$~ratios is low with all being consistent with no difference in the clustering amplitude. This implies that the correlation of morphology with dispersion is not the determining factor in the strong correlation of clustering amplitude with \Vdisp~at fixed mass.

Whilst the strong correlation of color with \Vdisp~is unlikely to introduce any systematics in our measurements it is still informative to investigate whether there is any residual clustering dependence on color at either fixed mass or \Vdisp. Since color is better correlated with \Vdisp~than mass one might imagine that any residual clustering dependence on color would be lower at fixed \Vdisp~than at fixed mass if the halo properties are key to determining the color, much as is seen with morphology above. To test this we show in Figure \ref{fig:biasrat2} the best fit large scale correlation function ratios of high and low $g-r$ color samples at fixed mass and dispersion and list the fitting results in Table \ref{tab:ratfitcolel} (the full $w_p(r_p)$~ratios are shown in Figure \ref{fig:2ptcol} in Appendix \ref{sec:appsamp}). Since the color evolves with redshift we have again had to split the samples in a similar way to the elliptical probability samples such that we have the reddest and bluest quartiles at any redshift.
Now, unlike with the elliptical probability, we see a residual clustering dependence on color at both fixed mass and \Vdisp~such that red galaxies cluster more strongly than blue.
This is most likely the result of the truncation of star formation in satellite galaxies in massive dark halos, resulting in satellite galaxies at fixed mass or \Vdisp~having redder colors than central galaxies with the same mass or \Vdisp~\citep[e.g.][]{Yang09}. The fact that we see a significant residual color dependence and not much of a residual morphology dependence suggests that the environmental mechanism for transforming the color of a galaxy from red to blue does not simultaneously change the morphology. A similar result was observed by \citet{Skibba09} using the marked correlation function applied to SDSS galaxies.

Since we do see some residual color dependence and perhaps a hint of morphology dependence in the clustering amplitude at fixed mass it is worth asking if the \Vdisp~dependence remains when morphology or color is fixed. We show in Figure \ref{fig:biasrat3} the large scale $w_p(r_p)$~ratio of high and low \Vdisp~samples at fixed \Mdyn~and high and low \Mdyn~samples at fixed \Vdisp~where we have restricted the galaxies to be either red ($g-r > 0.9$) or have high elliptical probabilities ($P_{el} >$ 0.6). The fit details given in Table \ref{tab:ratfitcolel} and the full $w_p(r_p)$~ratios shown in Figures \ref{fig:2ptVddMred} and \ref{fig:2ptVddMel} in Appendix \ref{sec:appsamp}. Despite the sample sizes being reduced and hence the errors increasing, the original trend of high \Vdisp~galaxies having a higher clustering amplitude at fixed mass remains significant and the large scale ratios stay essentially the same within the errors. There is a hint that the $w_p(r_p)$~ratios are slightly reduced, but by removing the blue or spiral galaxies we have removed many lower \Vdisp~galaxies and reduced the difference between the high and low \Vdisp~samples.
This is a clear demonstration that galaxies with higher \Vdisp~cluster more strongly than galaxies with lower \Vdisp~ regardless of their mass, morphology or color.

\section{Discussion}
\label{sec:dis}

\begin{figure}

\vspace{11cm}
\special{psfile=HODmassbin_modcenmt.ps hoffset=0 voffset=0  hscale=40 vscale=40 angle=0}
\caption{\small Top: An example halo occupation distribution representing the case where correlation between \Vdisp~and dark matter halo mass is tighter than the correlation between \Mstar~and halo mass. The black line represents an HOD for a galaxy population with a narrow slice in \Mstar. The red and blue lines each contain 25\% of the \Mstar slice sample and have had their central halo mass thresholds adjusted to sample slightly higher and lower halo masses from within that sample, to represent high and low \Vdisp~samples. In each case the dashed lines show the central galaxies and the dotted the satellites. Bottom: The auto- (solid) and cross- (dotted) correlation function ratios between the example high and low \Vdisp HODs. They show the very similar characteristics to the measured correlation function ratios on both small and large scales.
\label{fig:HOD}}
\end{figure}

We have shown that at fixed mass (stellar or dynamical) galaxies with high \Vdisp~(or \Mden) cluster more strongly than galaxies with low \Vdisp. Conversely, at fixed \Vdisp~(or \Mden) our measurements are consistent with high and low mass galaxies clustering the same. If the clustering of galaxies is dominated by the clustering of the DM halos in which they reside, as expected in the CDM paradigm, then this implies that even at fixed galaxy mass higher \Vdisp~galaxies live in more clustered halos than low \Vdisp~galaxies. The main determinant of a halo's clustering amplitude is its mass, but it has also been shown in simulations that halos with different formation histories also cluster differently, with older more centrally concentrated halos clustering more strongly \citep{Gao05,Wechsler06,Wetzel07,Gao07,Jing07,Li08}. This means that galaxies with higher \Vdisp~at fixed mass could be preferentially be living in either more massive or older more centrally concentrated halos.

When considering how galaxies occupy halos it is also important to make the distinction between the galaxy that has been formed at the center of a given DM halo, the central galaxy, and those that initially formed at the centers of other halos and have later been accreted into this halo, satellite galaxies. The properties of a central galaxy will be largely determined by the formation history and properties of its host halo, whereas any effect the current host halo has on satellite galaxies is limited to the time after it has been accreted.

In the following sections we address whether our result can be explained by a relationship between \Vdisp~and halo mass for central galaxies (Section \ref{sec:cenmass}) or for satellite galaxies (Section \ref{sec:satmass}), or by a relationship between \Vdisp~and halo formation history (Section \ref{sec:age})

\subsection{Central galaxy halo mass correlations}
\label{sec:cenmass}
Since DM halo mass has the largest effect on clustering amplitude, the simplest explanation for our results is that \Vdisp~is better correlated with its host halo mass than stellar or dynamical mass are. For galaxies living at the centers of halos, central galaxies, there is a strong correlation between stellar mass and halo mass \citep[e.g.][]{Yang09,Wake11}, but with a significant scatter \citep{Yang09,Yang11}.
If the scatter between \Vdisp~and halo mass for centrals is substantially lower than the scatter with \Mstar~this could result in clustering observations much as we have observed.

It is striking in Figures \ref{fig:2ptVdSM} and \ref{fig:2ptVddM} that the clustering ratio between high and low \Vdisp~samples becomes even larger as the scale decreases. The clustering amplitude on such scales is determined by the separations of galaxies within individual halos, so between central and satellite galaxies. Thus these smaller scale clustering measurements can provide an additional constraint as to whether a tighter correlation between \Vdisp~and halo mass (\Mhalo) for central galaxies could produce the observed clustering results.

We show in Figure \ref{fig:HOD} an illustrative attempt at modeling the effect of a smaller scatter between \Vdisp~and \Mhalo~than between \Mstar~and \Mhalo~using the halo model \citep[see][for details of our model]{Wake11}. We have fitted halo occupation distributions (HOD), the mean number of central and satellite galaxies as a function of halo mass, to the clustering measurements for a series of samples of SDSS galaxies limited in stellar mass (i.e. \Mstar $>$M$_{\rm low}$) \citep[see][for details of these measurements]{Wake12}. Subtracting two of the resulting HODs with slightly different M$_{\rm low}$ gives the HOD for a sample of galaxies with a narrow range in \Mstar. We show an HOD for such a sample as the black line in the top panel of Figure \ref{fig:HOD}, which has been chosen as it matches the lowest \Mstar~ sample we use ($11.04 <$ log(\Mstar) $< 11.19$). We can then attempt to mimic the effect of splitting into high and low \Vdisp~samples under the assumption that \Vdisp~for central galaxies is better correlated with halo mass than \Mstar~is, so that the high \Vdisp~sample will have higher average halo masses than the low \Vdisp~sample. We do this by slightly adjusting the central galaxy halo mass thresholds that define the high and low halo mass cut offs in our HODs. The HODs of these two samples, representing high and low \Vdisp~quartiles at fixed \Mstar, are shown as the red and blue lines in the top panel of Figure \ref{fig:HOD}. These mock high and low \Vdisp~samples each contain 25\% of the central and satellite galaxies of the full sample, with the size of the central HOD controlled by the mass threshold adjustments and the satellite just random sampled to 25\% of the number density, i.e. the form of the satellite HOD is left unchanged. The resulting $w_p(r_p)$ ratio is shown in the bottom panel of Figure \ref{fig:HOD} for both the auto- and cross-correlations. The cross-correlation is calculated with an HOD suitable for the parent sample we use throughout this work (i.e. log(\Mstar) $>$ 10.777).

The model $w_p(r_p)$~ratio shown in Figure \ref{fig:HOD} is quite similar to the measured ratios shown in Figures \ref{fig:2ptVdSM}, \ref{fig:2ptVddM} and \ref{fig:2ptMdenSM}, showing a constant increase in the cross-correlation amplitude on intermediate and large scales and then an increasing amplitude at small scales. It is always tempting to interpret changes in small scale (1-halo) clustering as reflecting changes in the satellite population, but this is a clear example of how this is not necessarily the case. The satellite population has not changed between the mock low and high \Vdisp~samples, and it is the change in the central galaxies which is causing a change in the numbers of central-satellite pairs that causes the increased clustering amplitude on small scales. More explicitly, at a given stellar mass the higher \Vdisp~galaxies are in more massive halos, which typically contain more satellite galaxies. This results in an increase in the number of central-satellite pairs, thus increasing the small scale clustering amplitude. The converse is true for lower dispersion centrals i.e. they are in less massive halos, with fewer satellites and so fewer central-satellite pairs. The satellite-satellite pairs remain unchanged, but since for these massive galaxies the satellite fraction is low so there may only be at most one or two satellites in a given halo the central-satellite pairs make up a significant contribution to the small scale clustering amplitude.

This exercise clearly demonstrates that if there is a much tighter correlation between \Vdisp~and halo mass than between \Mstar~and halo mass then the clustering ratios we measure would be expected. There is, of course, some theoretical expectation that this would be the case. The stellar mass of a central galaxy depends on a large number of complicated astrophysical baryonic processes such as gas cooling and feedback as well as mergers from satellite galaxies, which may give rise to a large scatter between halo mass and stellar mass. \Vdisp, on the other hand, is tracing the depth of the potential at the center of the halo and whilst this may be modified by the evolution of the baryons it is likely to be much more directly linked to the halo properties and in particular its mass.

\subsection{Satellite galaxy halo mass correlations}
\label{sec:satmass}
Whilst our example halo model shows that our results can be produced just by central galaxies, it is of course possible to produce similar clustering trends by modifying the satellite distribution or both the central and satellite distributions. To increase the clustering amplitude of galaxies at fixed mass by modifying the satellites requires that higher \Vdisp~satellites are preferentially found in more massive halos.

One possible process that could create such an effect is the stripping of the outer regions of a satellite galaxy by tidal interactions as it orbits it parent halo. This would likely have a minimal effect on \Vdisp~whilst reducing the mass and size of the galaxy. The likelihood of a galaxy getting disrupted in this way increases as the halo mass increases but decreases as the mass of the galaxy increases. Since, the galaxies in this study are all more massive than $6\times10^{10}M_\odot$ it would only be effective for satellites passing very close to the center of the most massive halos an occurrence that would be quite rare.

However, assuming that this process was an effective one we would expect to see its affects on the clustering both when the mass is held fixed and \Vdisp~varied and visa-versa. Satellite galaxies at fixed mass would have higher \Vdisp~in higher mass halos, since they would have been stripped more.  This would mean that the satellite galaxies in the higher \Vdisp~samples would be preferentially found in higher mass halos and hence would cluster more strongly, just as we have observed. The opposite would be true of satellite galaxies with fixed \Vdisp; one would expect them to have lower masses in more massive halos since again they would have experienced more tidal stripping.

One could then imagine a scenario that could explain our observations. If we assume that the more massive a central galaxy or the higher its \Vdisp~then the more massive its parent halo, then for centrals one would observe higher clustering amplitudes both for higher mass galaxies at fixed \Vdisp~and higher \Vdisp~galaxies at fixed mass. At fixed \Vdisp~the higher mass satellites would typically be in lower mass halos (where they haven't been stripped) and visa-versa, resulting in an overall reduction in the clustering ratio between the high and low mass samples. The opposite would be true at fixed mass, where the higher \Vdisp~satellite galaxies would preferentially be in higher mass halos (where the stripping is effective), increasing the clustering ratio between high and low \Vdisp~samples. A similar effect could also occur when considering \Mdyn~rather than \Mstar~since the size of a galaxy would be reduced as it is stripped, thus reducing \Mdyn. This does seem to be a viable explanation of our results, although we note that the fraction of satellite galaxies should be relatively low in our samples, $<$ 20\%.

\subsection{Central galaxy halo age correlations}
\label{sec:age}
Finally, as already mentioned, there is an alternative to the halo mass dependence outlined above, whereby instead of a tight correlation between central galaxy \Vdisp~and halo mass there is a residual correlation between \Vdisp~and a halo's formation history or age. N-body simulations show that at a given mass halos that formed earlier (and are more concentrated) are more clustered than younger halos \citep{Gao05,Wechsler06,Wetzel07,Gao07,Jing07,Li08}. This is an appealing explanation since it would link together both the correlation between \Vdisp~and clustering amplitude as well as that between \Vdisp~and the star formation history of galaxies. At a given mass galaxies with higher \Vdisp~exhibit older stellar populations which would be naturally explained by the earlier formation of their parent halos and thus their higher clustering amplitude.

\subsection{Consequences of these relationships}
\begin{figure}
\vspace{11cm}
\special{psfile=SMVdispatMdyn.ps hoffset=0 voffset=180  hscale=30 vscale=30 angle=-90}
\special{psfile=ReVdispatSM.ps hoffset=0 voffset=330  hscale=30 vscale=30 angle=-90}
\caption{\small Top: The relationship between \Re~and \Vdisp~at fixed \Mstar~($10.85 <$ log(\Mstar) $< 10.9$). The blue points show the running median. At a given \Mstar~galaxies with higher \Vdisp~are smaller. Bottom: The relationship between \Mstar~and \Vdisp~at fixed \Mdyn~($11.35 <$ log(\Mdyn) $< 11.45$), showing very little trend.
\label{fig:ReatVdisp}}
\end{figure}

Assuming that a tighter relationship exists between \Vdisp~and halo properties than between galaxy mass and halo properties for central galaxies, as outlined in Sections \ref{sec:cenmass} and \ref{sec:age}, we can use our measurements to infer how \Vdisp, \Mstar, \Mdyn~and \Re~interrelate with one another, and with halo mass and concentration. We expect that \Vdisp, \Mstar~and \Mdyn~all depend on halo mass and each other as follows:
\begin{equation}
\sigma^2 \sim \frac{GM_{dyn}}{R_e} \propto  \frac{M_{star}}{R_e} + \frac{M_{halo}}{R_{vir}/c}
\end{equation}
where \Mhalo~is the halo mass, $R_{vir}$ is the halo virial radius and $c$ is the halo concentration \citep{Hopkins09}.
 Therefore, when \Mstar~is fixed and \Vdisp~varied either \Re, \Mhalo~or $c$ must vary. Since the clustering amplitude does change then either \Mhalo~or $c$ must also change, such that higher dispersion galaxies must live in more massive or more concentrated (older) halos. Whilst it is the case that galaxies with higher \Vdisp~at a fixed \Mstar~typically have a smaller \Re~(see Figure \ref{fig:ReatVdisp}) they must also occupy more massive or more concentrated halos. Conversely as \Mstar~is increased at fixed \Vdisp~\Re~must be changing as well such that more massive galaxies have larger \Re, since there is no change in the clustering amplitude so \Mhalo~and $c$ aren't varying. This means that at fixed \Vdisp~increasing \Mstar~increases the ratio between \Mstar~and \Mhalo.

We see a similar effect with \Mdyn. When \Mdyn~is held fixed and \Vdisp~varied \Re~must also vary such that higher \Vdisp~leads to lower \Re. We also know that either \Mhalo~or $c$ increases with \Vdisp~at fixed \Mdyn~since the clustering amplitude increases. \Mstar~could potentially vary in either direction with the size of the change depending on the ratio of the contributions of dark and stellar mass to the potential and the magnitude of the change in \Mhalo~or $c$ with \Vdisp. In fact Figure \ref{fig:ReatVdisp} shows that at fixed \Mdyn~there is very little average change in \Mstar~as \Vdisp~increases, indicating that \Mhalo~or $c$ have to increase with \Vdisp~at fixed \Mdyn~just as we observe.
When \Mdyn~is varied at fixed \Vdisp~\Re~must also change, increasing as \Mdyn~increases. Since the clustering amplitude does not change, \Mhalo~and $c$ do not change and so \Mstar~must be increasing. This implies that at fixed \Vdisp~galaxies with higher \Mdyn~will have both larger \Mstar~and \Re.

\section{Summary and Conclusions}

We have investigated how the clustering of galaxies depends on stellar mass, dynamical mass, velocity dispersion, surface mass density, color and morphology using large samples of massive galaxies from the SDSS. We split the samples into narrow ranges in mass, \Vdisp~or \Mden~and measure any residual clustering dependence on the other parameters. We find the following:

\begin{enumerate}
\item When \Mstar~or \Mdyn~are fixed there is a significant dependence of the clustering amplitude on \Vdisp~on all scales, such that galaxies with higher \Vdisp~are more strongly clustered. Conversely when \Vdisp~is fixed there is no dependence of the clustering amplitude on either \Mstar~or \Mdyn. These trends remain when we limit the samples to galaxies that are red or morphologically elliptical. We see a similar trend using \Mden~instead of \Vdisp.

\item When \Mstar~or \Mdyn~are fixed there is a weak dependence of the clustering amplitude on morphology. When \Vdisp~ is fixed there is no significant morphological dependent clustering.

\item There always remains a strong dependence of the clustering amplitude on a galaxy's $g-r$ color at fixed mass or \Vdisp. This is most likely caused by satellite galaxies in massive halos always being preferentially redder than central galaxies of the same mass or \Vdisp.

\end{enumerate}

We suggest that for our main finding, point 1. above, that there are three possible explanations; the relationship between \Vdisp~or \Mden~and halo mass for central galaxies is tighter than that between \Mstar~or \Mdyn~and halo mass; the relationship between \Vdisp~or \Mden~and halo age (or concentration) for central galaxies is tighter than that between \Mstar~or \Mdyn~and  halo age (or concentration); tidal stripping of satellite galaxies reduces the size and mass of the galaxy whilst having a minimal effect on \Vdisp~and is more effective in more massive halos. Or it could be a combination of all three effects. If the host halo mass or age are indeed better correlated with \Vdisp~and \Mden~than with \Mstar, these halo properties may also drive the star formation history of galaxies, explaining why \citet{Kauffmann03b} found that star formation rate is better correlated with \Mden~than \Mstar, and why \citet{Franx08} found that color and star formation rate are better correlated with \Vdisp~than \Mstar.

\acknowledgments{

DAW would like to thank Nikhil Padmanabhan, Carlton Baugh, Violeta Gonzalez, Rachel Bezanson, Britt Lundgren and Ravi Sheth for helpful discussions on this work. We would like to thank the NYU and MPA-JHU groups for making their value added data products freely available.

This work makes use of data from the Sloan Digital Sky Survey (SDSS). Funding for the Sloan Digital Sky Survey (SDSS) has been provided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Aeronautics and Space Administration, the National Science Foundation, the U.S. Department of Energy, the Japanese Monbukagakusho, and the Max Planck Society. The SDSS Web site is http://www.sdss.org/.

The SDSS is managed by the Astrophysical Research Consortium (ARC) for the Participating Institutions. The Participating Institutions are The University of Chicago, Fermilab, the Institute for Advanced Study, the Japan Participation Group, The Johns Hopkins University, Los Alamos National Laboratory, the Max-Planck-Institute for Astronomy (MPIA), the Max-Planck-Institute for Astrophysics (MPA), New Mexico State University, University of Pittsburgh, Princeton University, the United States Naval Observatory, and the University of Washington.
}

\clearpage

redpajama_set_name: RedPajamaArXiv


An EPA inspector visited the site on the afternoon of Monday 27 July 2015 to assess the incident and to take an independent dust sample for analysis.
The EPA Inspector's report established that dust emissions from the incident extended beyond the licence boundary, affecting neighbouring houses and cars. The cause of this incident was the opening of a poke hole, in an attempt to free a blockage at the stage 4 preheater tower, for kiln 6. Results of the dust sample taken indicated that the dust was composed of oxygen, magnesium, aluminium, silicon, sulphur, chlorine, potassium, calcium and iron. Irish Cement's Air Dispersion Modelling Report of the dust release was received by the Agency in September 2015. The report concluded that the predicted concentration levels are in compliance with the relevant limit values.
The Agency's investigation found that Irish Cement was non-compliant with Conditions 5.1 & 5.2 of their licence, and the company have carried out a number of corrective and preventative actions with regard to this incident. Corrective actions have been completed and other environmental improvements have been implemented to ensure that the necessary management practices are in place to eliminate the causes of this type of incident and to protect the environment.
The EPA was informed of an incident at the site of Irish Cement, Castlemungret, Co. Limerick at approximately 11.00am on Saturday 25th July 2015. The EPA was advised that a blockage occurred in a preheater tower and while removing the blockage, a dust release occurred at approximately 04.00am early Saturday morning resulting in an emission to air.
A number of complaints, relating to the deposition of dust, were received by the EPA from residents in the area following the incident.
An EPA Inspector is visiting the site on the morning of the 27th July to assess the situation. The EPA will continue to monitor and assess the situation and communicate with the licensee and local residents.
The EPA will require a full investigation and assessment report in relation to this incident, which will address corrective and preventative actions to be taken. On foot of this information, further action will be considered by the EPA in line with our enforcement policy.
The priority for the EPA is to ensure that the necessary management practices are in place to eliminate the causes of this type of incident and protect the environment.
In relation to possible health implications, the Health Service Executive (HSE) West have advised that exposure to the dust while in the air may have had the potential to cause minor irritation, mainly of the eye. The recommended treatment for this is washing of the eyes, face and skin. Should any symptoms persist, HSE West recommends consulting a GP. The HSE West has confirmed there have been no reported presentations to University Hospital Limerick in connection with this incident.


Her speech seemed spontaneous, but was in fact carefully prepared beforehand.
A crowd of people gathered spontaneously at the scene of the accident.
She wished to travel abroad and thereby she could learn about different customs.


text:
Aaron Franklin, Author
Pitmaster, pit builder, television star, dad – these all define Aaron Franklin of Austin's Franklin Barbecue. By next year you'll also be able to call him an author. Not only was his new television series with KLRU announced two weeks ago, but now comes a book deal with Ten Speed Press. The working title is simply BARBECUE.
Here are further details from the press release:
"Celebrated pitmaster and owner of the wildly popular Franklin Barbecue—winner of Texas Monthly's coveted "Best Barbecue Joint in Texas"—Aaron Franklin's BARBECUE, a meat-smoking manifesto featuring stories and recipes, chapters on the theory and philosophy of Texas barbecue, tips for building or hacking your own backyard smoker, how to source and cure wood, and much more to be written with James Beard Award-winning author Jordan Mackay, to editor Emily Timberlake at Ten Speed Press by Franklin's agent David Hale Smith at Inkwell Management LLC. The book will be published in 2015."
Now we'll just have to wait and see how many secrets Franklin plans to reveal. Between the new book, the show, and the upcoming additions to the BBQ with Franklin web series, I'm not sure if he'll have any left. I guess that's better for the rest of us.
Full disclosure: Aaron Franklin and I are represented by the same literary agent.
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redpajama_set_name: RedPajamaCommonCrawl


text:
by Ramler Law Office, P.C. | Dec 12, 2012 | Uncategorized |
A prominent member of the Thompson Falls School Board is facing four felonies in connection with a reported incident of drunk driving. The man is being charged with two counts of vehicular homicide in relation to a DUI car accident that reportedly killed a 23-year-old passenger and the vehicle's 32-year-old driver.
The accident occurred on Sept. 8, when the school board member reportedly crossed the center lane in his Toyota pickup, slamming head-on into a Saturn sedan carrying the victims. The 23-year-old woman was pronounced dead at the scene, and her 32-year-old fiancé was declared dead at a hospital shortly after his arrival.
In addition, two young children were involved in the collision; the man's 2-year-old son and 4-year-old daughter also sustained serious injuries in the crash. Both suffered broken legs, though they were properly restrained in the backseat of the vehicle. Those injuries prompted a charge of criminal endangerment against the alleged drunk driver.
The man accused of DUI had a blood-alcohol content of 0.245, which is more than three times the legal limit in the state of Montana. The 46-year-old suspect has repeatedly denied drinking before the crash, telling officers instead that he had only consumed several non-alcoholic beers before getting behind the wheel that night. Still, the man's blood was drawn and tested the morning after the crash and that BAC result came to 0.11 percent, which is still higher than the legal limit.
Several witnesses have said they saw the suspect falling asleep at the bar shortly before getting in his vehicle. Other bystanders said they witnessed the bartender telling the man that he could not have any more to drink.
The victims' children could sue the drunk driver for continued medical costs and other claims that would allow them to maintain some standard of living. The young children are ostensibly left without a source of income, so a civil ruling in their favor would provide for their medical costs and future educational needs, among other necessities.
Source: The Billings Gazette, "Thompson Falls school board member charged with vehicular homicide while drunk," Vince Devlin, Dec. 4, 2012.


text:
Breaking News World News & Multi Media
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Work stops on Scarborough's town centre Premier Inn as contractor PDR Construction goes into administration
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By adam koooper	 On Jan 14, 2022 0
Administrators Leonard Curtis Business Rescue and Recovery were appointed earlier this week after a winding-up petition was issued for PDR Construction, who were contracted to build a 90-bedroom extension on Huntriss Row to the South Bay Premier Inn, which fronts onto Falconers Road.
All operations at the site have ceased and it is reported that all of the company's staff have been made redundant. The company's website and social media have been taken down.
At this stage, it is unknown what the future holds for the development, which is currently an unfinished building site and under construction.
Construction work at the Huntriss Row site remains unfinished.
The Scarborough News understands that work has not resumed at the site since the Christmas break.
The site's building office opposite the development is shuttered.
Scarborough company Ledden Developments Limited is now in the "exclusive possession and control" of the area, according to a notice on the Huntriss Row site.
Work to convert Scarborough's former Constitution Club into a 90-bedroom extension of the Premier Inn was granted demolition approval in 2015.
The site's building office opposite the development is left shuttered.
The work was forced to stop abruptly in January 2017 when heritage groups successfully campaigned for the front of the building to be Grade II listed; much of the rear of the property had already been demolished.
Plans to develop the now-listed building were passed in May 2017, but work on the site stalled and did not resume until late 2018.
Whitbread, Premier Inn's parent company, told The Scarborough News in March last year that builders were "on-site" and that construction was expected to be completed by early autumn 2021.
In its latest accounts to April 30 2020, PDR Construction made a pre-tax loss of £354,418 from a turnover of £82.7m, whilst employing 115 staff.
Construction barriers and hoardings remain in place at the building site.
In its accounts, Director Paul Dransfield said that growth was 10 per cent lower than expected due to the pandemic and that the firm posted its first loss for a decade.
The Scarborough News has approached Premier Inn, the administrators and Ledden Developments for comment.
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Shimla, Aug 23 (UNI) The Himachal Pradesh Assembly today unanimously adopted a resolution urging Prime Minister Manmohan Singh to help the state in getting its share in Bhakra Nangal, Pong Dam and Beas Projects, besides getting its share from Punjab and Haryana under the Re-organisation Act of 1966.
Initiating the debate on the issue under Rule 117, Irrigation and Public Health Minister Kaul Singh Thakur criticised Punjab and Haryana for not releasing the state's share after the states' re-organisation in 1966.
He demanded that the state's share of 7.19 per cent in Bhakra Beas Management Board (BBMB) and 12 per cent free electricity in various hydel projects should be released to it immediately.
Besides, Punjab should also hand over the Shanan hydel power project in the state to Himachal, he said, adding that it was only demanding its due share and not seeking alms.
Mr Thakur said Punjab was giving step-motherly treatment to the state, by not providing its 7.19 per cent share in the BBMB project that was decided on the state's population after the re-organisation of the states' in 1966.
Accusing Punjab of not releasing Himachal's share in the Pong Dam, he said it was also continuing to hold the Shanan hydel project, violating its earlier promise on the issue.
He also demanded 7.19 per cent share in Chandigarh.
The IPH Minister termed the Haryana and Punjab's opposition to the central package to the state as ''unfortunate'', saying the package had been extended for another three years despite their opposition.
Himachal approached the Supreme Court in 1998 due to the adamant attitude of its neighbouring states, he said, adding that despite the best efforts of former state chief minister P K Dhumal to resolve the issue outside the court, no solution was arrived at.


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SENATE FOREIGN RELATIONS COMMITTEE APPROVES ROBERT LEVINSON HOSTAGE RECOVERY AND HOSTAGE-TAKING ACCOUNTABILITY ACT
https://www.foreign.senate.gov/press/ranking/release/senate-foreign-relations-committee-approves-robert-levinson-hostage-recovery-and-hostage-taking-accountability-act
WASHINGTON — U.S. Senator Bob Menendez (D-N.J.), Ranking Member of the Senate Foreign Relations Committee, and Senator Marco Rubio (R-Fla.), Chairman of the Senate Foreign Relations Subcommittee on the Western Hemisphere, issued the following statements after the Senate Foreign Relations Committee approved their bipartisan bill to bolster U.S. government resources to bring back Americans held hostage or unlawfully detained abroad. The Robert Levinson Hostage Recovery and Hostage-Taking Accountability Act fortifies existing programs to address hostage-taking and equips the U.S. government with new tools to perform rescues, punish captors, and provide critical information and support to hostages and their families.
The bill is named in honor of former FBI agent Robert Levinson, who is presumed to have died in Iranian custody this year. Lasting more than twelve years, Levinson's unlawful detention by the Iranian regime is recognized as the longest-held hostage in American history.
"I am very proud to be able to deliver on my promise to the Levinson family on approving this important legislation in honor of Bob Levinson. Today, the United States is one step closer to holding the Iranian regime and other bad actors accountable for perpetrating unconscionable human rights abuses and inflicting gratuitous cruelties on individuals like Bob Levinson," Menendez said. "As we continue to push this bill forward towards its enactment into law, we must remain guided by the Levinson family's determination and persistence in their quest for justice. The United States must do everything possible to secure the resources necessary to safeguard American lives abroad and prevent others from enduring similar tragedies in the future."
"Following the tragic news earlier this year regarding death former FBI Agent Bob Levinson, who was the longest held hostage in American history, the Senate Committee on Foreign Relations pays tribute to his life by passing this important bipartisan bill to help ensure American hostages will be brought back home," Rubio said. "This bipartisan effort will strengthen the tools within the Executive Branch to facilitate the return of American hostages held overseas."
Joining Senator Menendez and Senator Rubio in cosponsoring the bill are Senators Patrick Leahy (D-Vt.), Chris Coons (D-Del.), and Jeanne Shaheen (D-N.H.).
"The barbarity of the Iranian regime was graphically illustrated in the case of Robert Levinson," Leahy said. "Countless appeals for his release were ignored, and in the end the Iranians achieved nothing by subjecting him to appalling cruelty all those years. When American citizens and nationals are arrested and imprisoned, our embassies should determine if there is reason to believe that they are being held as hostages or otherwise wrongly detained. This bill specifies criteria for making such determinations and would ensure that those Americans receive every available diplomatic or other assistance to protect their rights and obtain their release. There should be no higher priority for U.S. diplomacy than freeing American hostages."
"We must do everything we can to prevent the unlawful detention and hostage-taking of American citizens," Coons said. "This bipartisan bill honors the life of Bob Levinson, who was wrongfully detained in Iran for over a decade, by strengthening our ability to bring these individual Americans home and hold their captors accountable."
"Any time an American citizen is held unjustly, it demands the attention and full weight of the United States government to secure their freedom," Shaheen said. "This legislation reaffirms our country's commitment to bring Americans home safely and bolsters diplomatic powers for the President and administration to use to compel their release. This legislation honors Robert Levinson, who died in Iranian custody after being held hostage for 13 years, and every American who is or has been wrongfully detained. I'm pleased by the bipartisan support from the committee to move this bill forward and I'll continue to work across the aisle to see this legislation through Congress."
A copy of the bill can be found HERE.


These tours will get you moving without overwhelming you.
They're perfect for first-time travelers and walkers hoping for an active trip that never feels strenuous.
Your dream vacation doesn't have to be difficult! If you have a typical active lifestyle—with some light exercise every week—these tours are well within your reach. Enjoy gentle walks on well-maintained paths with, at most, some mild rolling hills and uneven terrain. From Italy's gentle Maremma coast to Vermont's colorful birch forests, discover new landscapes at a comfortable pace, savoring exceptional cuisine along the way.
Join us for some craic agus ceoil (fun and music) while exploring the windswept bluffs, verdant farmland, and little-known islands of western Ireland.
France's austere northern coast enchants with its white coastal cliffs, towering cathedrals, shimmering tidal flats, and fragrant apple orchards.
Discover what makes this region Italy's ultimate destination for food and wine as you explore the birthplace of the Slow Food movement.
In a rural landscape of working farms, rolling hills, old-growth forests, and picture-perfect villages, you'll enjoy the many colors of New England's autumn spectacle.
Walk apace with history on this Irish adventure, as you meander between coastal marvels and inland wonders. Ice Age landmarks and medieval sites coexist with modern pleasures in colorful towns.
Van Gogh landscapes, sweeping ridge-top vistas, and gorgeous Provençal villages await on this walking adventure through the Alpilles and Lubéron Mountains.
Savor a stay in Cape Town, where you encounter the region's distinct floral kingdom, before exploring an iconic game reserve on foot.


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Q: How to create a textformfield with listTile that looks enabled So I got a listtile that can use a function on tap and the textformfield.
How do I make it look like enabled but still prevent people from changing the value?
I tried FocusNode but it also disabled on onTap function.
ListTile(
    TextFormField(
    enabled: false,
    validator: (val) {
    if (val.isEmpty)
    return 'Please enter something';
    },
    controller: _controller,
    ),
onTap: () => _doSomething(),
)

A: You can wrap your TextFormField in an IgnorePointer:
ListTile(
  onTap: () => _doSomething(),
  title: IgnorePointer(
    child: TextFormField(
      controller: _controller,
      validator: (val) {
        if (val.isEmpty)
          return 'Please enter something';
      },
    ),
  ),
)

redpajama_set_name: RedPajamaStackExchange


and want to sell/give/pay me to take it off your hands.
my busa just not as easy as it used to be.....im getting old and need a sensible bike.
I'm gonna be moving house soon so I need to get rid of a few bikes. I'll try to get round to getting some pictures taken this week.
Took a spin down there today...got what was probably the best non BK i've ever tasted.., cup of coffee and a scone...and it was all free...happy out..
Last edited by Jack stowage; 7th April 2019 at 04:55 PM.
Its a potential line of business for these guys if they did track days out foreign.


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Home / Featured Cars / Wally Shatkus' Bill Von Esser Von T
Wally Shatkus' Bill Von Esser Von T
by Joseph Alig and Stephen "Spike" Kilmer
Wally has collected and gathered just about every part needed to return Von T back to original. Here is Von T in its current streetable form. (Photo Courtesy Wally Shatkus)
Chicago is fortunate to have Wally Shatkus. He has preserved much of that area's automotive past.
As a kid, Wally was intrigued by a hot rod named Von T. It was constructed by the legendary Bill Von Esser who also owned and operated the once-famous Von Esser's Speed Shop.
"When I was around ten years old, I would do anything I could to get a grownup to take me to the indoor custom and rod shows around the Chicago area. I even convinced my Cub Scout leader to take our whole troop. It was the first time I laid eyes on this white T-bucket dipped in chrome.
Von Esser speed parts are a rare commodity these days. Bill was known to stamp his name on everything he sold even if it was made by another manufacturer. (Photo Courtesy Wally Shatkus)
"In the 1990s, I read an article in Rod & Custom by Pat Ganahl based on tracking down the cars from your childhood that made an impact on you. It inspired me to start searching for a car with some history. I happened to be flipping through the pages of Auto Trader and a car from my past jumped out at me. I checked my collection of old car magazines and I found one picture in Car Craft to compare it to. It had to be the 1960s show rod built by the once famous speed shop in my local area. Upon seeing the street rod, I questioned the owner about specific parts and finally he spit out that it was once Von T. He was embarrassed to admit that he had sanded off all the gold-leaf VonT lettering. I feel as if Von T had California heritage and if it were resurrected, it would be a big deal.
"Von T's construction began in 1959 and was refined over a number of years until it was completely finished by Bill Von Esser in 1963. It sported a 6-71 belt-driven blower and radical mechanical fuel injection by Scott. Von T had a 4-speed manual, chromed transmission, and radiator. The meticulous frame and suspension was constructed by famous midget race car builder Max Reichenbach.
"The only place where there are visible welds on the car is on the header flanges. Bill Von Esser used to hype kids up at the car shows by telling them, 'If you can find a visible weld, I'll give you $50.' He would have kids at the shows crawling all over Von T.
"Bill was a crafty self promoter and loved to stamp his name on everything he sold, even parts from other makers such as Edelbrock. People often paid more money for speed parts with the Von Esser name because it had a mystique about it. He sold everything from racing equipment to custom car accessories like ripple-disc hubcaps. Bill was very successful and when he passed away at a fairly young age in 1974 he housed two Ferraris and Von T in his garage.
"Bill Von Esser's nephew Jimmy Cimmer ended up owning the car years after its heyday. He added a roll bar and disc brakes. It showed up right across the street from my house one day at a car show in the Chicago suburbs. There were a bunch of guys hanging around and I wanted to ask what 'Von T' meant but I didn't want to look like a punk kid in front of those guys. I couldn't bring myself to talk to them. From there the car changed hands a number of times and that was the last I saw of it until I was lucky enough to track it down.
When Von T was originally built using a Scott fuel injection and blower it boasted 550 hp to the rear slicks. Von T allured google-eyed customers as a rolling advertisement of Von Esser's finest speed equipment. (Photo Courtesy Wally Shatkus)
"At the moment, Von T is in a semi-restored drivable state with an automatic transmission. My goal is to restore it to its original show condition of 1963 but I'm having too much fun driving it. The car has most of its original chrome, but some of the nickel has worn through in places. There was even a plastic model kit that you could purchase and build to resemble Von T."
Wally has documented many more amazing stories for the rest of us to enjoy. Finding Von T is a big deal to us and we share his passion! Wally will be the first to tell you, it is about preserving the legacy of hot rodding.
Bill was the consummate marketer and his decals were visible on the most successful race cars of the day. (Photo Courtesy Wally Shatkus)
Taken from Joseph Alig and Stephen "Spike" Kilmer's East vs. West Showdown: Rods, Customs & Rails (published 2012)


My family has been on a banana kick lately so there haven't been too many over-ripe bananas in the basket on my counter recently.
This week I tried to outsmart them and I bought way too many bananas than we could possibly eat before they over ripened. By the end of the week, I finally had a few leftovers for banana muffins. (Yea) I had been itching to try a new recipe that I had found on www.the-girl-who-ate-everything.com and these bananas were the perfect opportunity to try out a new recipe.
I decided to make my muffins into minis because I hadn't made any mini muffins in a while. (Pretty scientific, right?) Much to my delight, these muffins came out moist and cinnamony and delicious. The crunchy streusel topping just puts these muffins over the top.
Combine flour, baking soda, baking powder and salt.
Mix together bananas, sugar, egg, melted butter, vanilla and cinnamon.
Spoon batter into greased mini muffin tins.
Combine brown sugar, flour and cinnamon in food processor. Cut in butter and pulse until crumbly.
Bake 10 minutes at 375.


The Personal Transformation Wellness Group staff of counselors have a passion for helping you and your family move forward through challenges and make progress to achieve goals.
We offer a full range of mental health and behavioral services and our primary focus is to provide quality mental health services to adults, adolescents, children, couples, and families.
We strive to deliver a superior level of care with the help of highly experienced and trained mental health care providers, and we are committed to improving the quality of life of our clients.


text:
Hill Greene Plays Bass
website for Hilliard Greene – photo by Ken Weiss
MY THANK YOU TO JIMMY SCOTT
Negro Spirituals Performance
Bands/Projects
Solo Performances and Alone CD
"Hilliard Greene bends over his piccolo bass, tenderly. His face reminds me of Paul Robeson's — a dignified sadness, tinged with anger. For some reason, I picture a purple shawl hanging from Hilliard's shoulder. He seems to be singing with his body.
Hilliard is performing at the "Projects Room" of the Vision Festival, 2010. At first, there is a small audience, but word of his mastery spreads through the Henry Street Settlement, and the crowd grows.
Hilliard wrote all these compositions himself — except for Ornette Coleman's "Lonely Woman." This is the music I have been awaiting for decades, I find myself thinking: post-avant-garde jazz, which uses dissonance and the Music of Battle only when the soul demands, not out of habit. Hilliard's songs are brainy and populist. He could play his solos at a New York Philharmonic concert and the octogenarian music lovers would cheer. In Hilliard's music, Aretha Franklin kisses Tchaikovsky."
– Sparrow – GroundReport.com
"New York bassist Hilliard Greene is no stranger to the New York jazz scene and has been an active studio or stage player for many years in the US with Jimmy Scott as well as the musical director of his backing band The Jazz Expressions. He has also played with luminaries such as Dave Douglas, Kenny Barron, Oliver Lake, Charles Gayle, Jack Walreth, Gloria Lynne and Rashied Ali and other international artists.
This eight track CD entitled 'Alone' is just that, Hilliard playing upright bass on his own to six self penned tracks and two covers of Stanley Clarke's 'Bass Folk Tune' and Ornette Coleman's 'Lonely Woman / Kum Ba Ya'.
This is a set of wonderfully played compositions which I think is targetted at bass players and jazz connoisseurs. Hilliard is obviously a master player of his instrument and the songs cover a number jazz sub genre's with influences from contemporary, Eastern, Latin and World styles. It is the sort of CD that you would play before a master bass class and say, "Here is the yardstick, now let's see what you've got".
I have a feeling that Hilliard is a deep and conscientious musician who has created his own nirvana to integrate into this entire project and whilst I don't think it will have a general appeal to many jazz fans, it is full of rhythmically succinct ideas and takes on a similar patina to many of the great bassists which have inspired him in the past and present such as Ron Carter, Paul Chambers, Michael Henderson, Dave Holland, Eddie Gomez, Stanley Clarke, Charles Mingus, Marcus Miller, Nathan East, Jaco Pastorius and will be essential listening for bass fans."
– Wes Gillespie – Euro Club de Jazz
"Hearing this album, we can all say we could just never have imagined the bass as a solo instrument that is wholly absorbing and wholly capable with sounds that show the artist knows jazz, classical, South American, and yes, even some colors of the Japanese koto. We can say he has reinvented the bass as a solo instrument. Hill takes center stage as a first class artist, Alone."
– James Forte – Wildflower Publishers
"OK, an unaccompanied solo in a tune is one thing. A whole concert – well, that's something else entirely. The thing is, Greene can keep the listener interested – very interested – for upwards of an hour, all by himself. His new album, "Alone," is a riveting hour-plus of material, mostly originals, that stand up well as melodic compositions played with passionate dedication. There is a wide range of styles and forms, and there is no risk of boredom among the eight tunes."
– Steve Greenlee – Boston Globe
"Besides the exciting moving music, there is the amazement of the man's technique. He is a real virtuoso. Hearing this album, we can all say we could just never have imagined the bass as a solo instrument that is wholly absorbing…"
"Hill Greene created a resonating musicality, with full focus and emotional pathos… The audience was still and enraptured, as Hill Greene is a musician to watch, as well as one to listen to… Hill Greene has a bright future as Solo Bassist, Composer, Accompanist, and Music Director."
– Roberta Zlokower – RobertaOnTheArts.com
"Greene, a bass concert player. Very good (4 stars)
Hilliard Greene is an expressive double-bass player with a solid technique…Greene made of his show at Notorious a concert of refreshing features, with fiery solos developed in an explosive way at times, … His double-bass has the sonority like a guitar and continuity in his lines that seem to be pianistically inspired…A Strong presence…
… His language has in a way, a classical vocabulary that is at the same time deeply tied to the blues. There is in his music a strong conscience of the black tradition…"
– Cesar Pardines – La Nacion; Buenos Aries, Argentina (translation by Fernando Hernandez-Moros)
"…Hilliard Greene…can sound like a flamenco guitar one moment and a wailing horn the next"
– Misha Berson – Seattle Times
"…found a copy of your solo CD. I've been listening to it a great deal. It's exceptional, easily one of the best crafted solo bass CDs I've heard."
– Lou Kannenstine – Boxholder Records
"…(Greene's) work on the upright bass was diverse and committed. On the funk grooves, generally associated with the electric bass guitar, he was convincingly adept, wielding the larger instrument with ease. His solos, whether arco or pizzicato, used the full potential of the instrument, including choral effects and contrivances."
– Richard Mayer – Green Mountain Jazz Messenger
"Intense. Powerful. Versatile. Not for the faint-hearted. …Hill Greene showed us how it's done"
– Bass World, Journal for the International Society of Bassists
"With a technical mastery of his instrument that is nothing short of astonishing he churned through a varied and creative set full of fire, brilliance and subtlety that above all never stopped swinging."
– Bobby Shropshire – Beach Nights Entertainment Magazine – Myrtle Beach, South Carolina
"Technically and sonically, Greene's bass sounds great; his pitch is accurate even during highly technical passages played at breakneck speed, and his sound is deep and clean."
– John Kennedy – Double Bassist Magazine
"His fabulous arco bass mixes lyricism with a burning, literally ferocious desire of opening the listener's mind."
– Massimo Ricci – Touching Extremes, Italy
"Alone sounds like the culmination of one man's dedication to his instrument, the work of someone who has come a long way, and is determined to show what he can do. Classical melodies, Jazz and Folk music from around the world have been internalized by Greene who proves his talent for pizzicato and arco playing in an equal measure on unaccompanied double bass…Alone is music rooted in the human condition."
– Jeff Stockton – All About Jazz
"HILLIARD GREENE – double bass
– Massimo Ricci – Touching Extremes, Italy, January 2007
"I found his composition to be extraordinary in its depth of emotion. Hill's remarkable virtuosity and passion on his instrument and spiritual awareness was ever present throughout."
– Margot Elizabeth Meyers – Jazzimprov, 2006, NY, USA
"Hill Greene dares to release solo bass recording
For many decades the bass has ceased to be looked at as an accompaniment instrument entirely. At the same time, very few musicians dare to release solo bass recordings. Bassists like Dave Holland, Eberhard Weber, Barre Phillips and Miroslav Vitous have done that very successfully. Among those, we can add the name Hill Greene with his solo bass recording entitled "Alone".
The name Hill Greene is not that well-known even though he has played with people like Dave Douglas, Cecil Taylor, Jack Walrath, Charles Gayle and with the well-known crooner Jimmy Scott.
He has visited Greece twice to play at Half Note once with "Masters of Suspense" with Jack Walrath and with singer Pucci Jhones. In his personal career, he has released two albums as a leader of "Jazz Expressions" (the group which accompanies Jimmy Scott on his tours). Now he's adding the album alone.
"To play alone is my favorite mode of musical expression. It's risky and it needs huge effort, time, thought and practice" says Greene. Understandably, because it's not easy for one instrument, especially a monophonic instrument, to hold the interest of the listener for more than an hour. But Greene, playing with unbelievable technique, a unique passion and managing not to become monotonous since he changes moods and moves through different styles, holds undivided the attention of the listener from the beginning to the end of the album. When he's bowing, he plays with the clarity and the musicality of a cellist, and when he plays with fingers, he has a deep, warm and full-of-swing sound.
His love for the Bach Cello Suites becomes obvious in the way he arranges "Bass Folk Song" by Stanley Clarke, where he starts with melodic arco playing and develops into a recital of speed and virtuosity. He treats the second composition, "Lonely Woman", similarly. If one does not know this early piece by Ornette Coleman, which Greene combines with his own composition entitled "Kum Ba Ya" and becomes a twelve minute detailed study of the bass, one would certainly think that he has just heard a classical composition.
The same variety runs through the rest of the album which leads us from the bluesy feeling of "Home Health Aid" to the esoteric and classical mood of Iono", the folk atmosphere of "Juini", the meditative mood of "Yoyogi", the fiery speed of "Ode to A.B." and finally the detailed narration of the ballad "Samantha and Sluggo".
Even though the unique virtuosity of Hill Greene can capture the mind of the listener, what really sets him apart is his musicality, passion, and dedication to the art."
– Vangelis Aragiannis – the bimonthly magazine "Apopsi" and the daily "Ipirotikos Agon", Greece
2 thoughts on "Reviews"
Jodie Johns March 25, 2015 at 7:59 pm
I'm DJ's mother. I want to know where you are playing during the week of April 24-27th. I'll be in NYC. Are you with Nora McCarthy TRio?
Jodie Johns
hilliardgreene.com Post author March 26, 2015 at 1:47 pm
Hello Jodi,
Very nice to hear from you. Sadly I will be out of town during the time you will be here. I will return on the 28th. be well, HIll hilliardgreene@gmail.com


This beautiful coffee is a microlot finalist from the Burundi Cup of Excellence. Origin of the coffee is Kayanza province in the Gahahe region of the country.
Meticulously hand sorted and graded. The flavors you will get are Bright Citrus, Sweet Black Plum & Floral.