===== Local models/mocks =====
These mock data give positions and velocities for stars in and around the Solar neighbourhood, relevant for recovering the local Galactic potential and e.g. dark matter content.
==== Simple 1D data sampled from a distribution function of vertical energy ====
These first data assume a 1D population with precisely zero "tilt" term. The velocities are sampled from a 1D distribution function assuming $f \equiv f(E_z)$ as in [[http://adsabs.harvard.edu/abs/1989MNRAS.239..571K|Kuijken & Gilmore 1989]]. This should be an easy test, but highlights:
* The importance of systematic errors due to over-restrictive assumptions about the potential;
* The role of sampling - i.e. how many stars are needed for what type of error;
* The importance of having different populations split by chemistry (and the errors introduced if we get this wrong);
* The importance of sampling high or low as compared to the disc plane; and
* The role of uncertainties in the baryonic mass model
We use a disc model:
$\nu(z) = \exp(-z/z_0)$
and vertical force law:
$K_z = -\left[\frac{K z}{\sqrt{z^2 + D^2}} + 2Fz\right]$
The vertical velocity dispersion (assuming no tilt) can be derived from the Jeans equations:
$\sigma_z^2(z) = \frac{1}{\nu(z)} \int_0^z \nu(z') K_z(z') dz' + \frac{\sigma_z^2(0)\nu(0)}{\nu(z)}$
where $\sigma_z^2(0) = -\frac{1}{\nu(0)} \int_0^\infty \nu(z') K_z(z') dz'$ sets the velocity dispersion at $z = 0$. However, we do not use this. Instead, we use the distribution function:
$f(E_z) = -\frac{1}{\pi}\int_{E_z}^{\infty} \frac{\mathcal{F}(\Phi) d\Phi}{\sqrt{2(\Phi - E_z)}}$
where:
$\mathcal{F} = \frac{1}{z_0}\frac{\nu}{K_z}$
This is made more numerically tractable by the trigonometric substitution:
$\Phi = E_z \sec^2\theta$
which gives:
$f(E_z) = \frac{-\sqrt{2 E_z}}{\pi} \int_{0}^{\pi/2} \sec^2\theta \mathcal{F}(\theta,E_z) d\theta$
We set up several models by drawing stars from the above distribution function. These are detailed in the following table.
^ Model ^ Parameters ^ Data files ^ Plots ^
| Simple | z_0 = 0.4\,{\rm kpc}; K = 1500; F = 267.65; D = 0.18; n_* = 10^4; \Delta z_{\rm bin} = 0.05\,{\rm kpc}| {{:data:simplenu_sigz_bin.dat}} {{:data:simplenu_sigz.dat}} {{:data:simplenu_sigz_raw.dat}} | {{:data:simple.png?200}} |
| Simplelow | As Simple, above, but with n_* = 10^3 | {{:data:simplelownu_sigz_bin.dat}} {{:data:simplelownu_sigz.dat}} {{:data:simplelownu_sigz_raw.dat}} | |
| Simple2 | z_0 = 0.9\,{\rm kpc}; otherwise as Simple, above| {{:data:simple2nu_sigz_bin.dat}} {{:data:simple2nu_sigz.dat}} {{:data:simple2nu_sigz_raw.dat}} | {{:data:simple2.png?200}} |
| High | As Simple2, above, but with z_0 = 0.65\,{\rm kpc}; data cut on 2 < z < 4 kpc; just ~500 stars; and \Delta z = 0.25\,{\rm kpc} | {{:data:highnu_sigz_bin.dat}} {{:data:highnu_sigz.dat}} {{:data:highnu_sigz_raw.dat}} | {{:data:high.png?200}} |
where n_* is the number of stars, and \Delta z_{\rm bin} is the bin size (for the binned data).
The data files are as follows:
* simplenu_sigz_bin.dat :: Binned data: z [{\rm kpc}], \nu(z), \nu_{\rm err}(z), \sigma_z(z) [{\rm km/s}], \sigma_{z,{\rm err}}(z)
* simplenu_sigz.dat :: Smooth model
* simplenu_sigz_raw.dat :: Raw particle data in [z,v_z]
* simple.png :: Plots of the above.
The system of units is kpc, Msun, km/s. Converting the vertical force to a surface density ({\rm M}_\odot\,{\rm pc}^{-2}) via the Poisson equation (assuming no rotation curve contribution), we have:
\Sigma_z(z) = \frac{|K_z|}{2\pi G_1}
where:
G_1 = 6.67 \times 10^{-11} \times 1.989\times 10^{30} / 3.086\times 10^{19}. In the above system of units, the "baryonic" contribution \Sigma_b = K = 55.53 {\rm M}_\odot\,{\rm pc}^{-2}.