Inferring Spherical Mass Distributions Using the Projected Mass Estimator: Possibility or Pitfall?
Previous
abstract Next
abstract
- Session 22 -- Galactic Structure; Galactic Center
- Display presentation, Monday, 9, 1995, 9:20am - 6:30pm
[22.07] Inferring Spherical Mass Distributions Using the Projected Mass Estimator: Possibility or Pitfall?
J.W. Haller, F. Melia (Dept. of Physics and SO, U. of Arizona)
Various workers have applied the projected mass estimator (PME) to infer the
radial mass distribution, $M(r)$, in stellar systems ranging in scale
from the Galactic center, dwarf spheroidals, and globular cluster
systems of external galaxies. The
PME was originally used to infer the total
mass of a stellar system
according to the relation $M=f\ \times/G$ where
the factor $f$ depends on the stellar orbit distribution
(e.g., isotropic) and how co-extensive the mass distribution
is compared to the tracer population. We here examine the general
expression of the PME for a spherically symmetric
mass distribution and an arbitrary
sampling volume. For a
cylinder centered on the distribution, corresponding to
the observational case of evaluating the PME within apertures
of increasing radius $R$,
boundary terms arising from the finite sampling volume make
appreciable contributions when the aperture radius $R\rightarrow0$.
Numerical calculation and Monte Carlo simulations
demonstrate that the PME overestimates $M(r)$ by factors
of at least 3 - 4 inside the core. More importantly, the
functional form of the PME as $R\rightarrow0$ is attributable to
the factor $f=f(R)$, not the function $M(r)$.
Analytical ``$\eta$-models'' show that the PME can infer the
presence of a compact object at the center of a stellar distribution
only when its mass greatly exceeds the mass of the
cluster. Previous attempts to overcome volume
incompleteness have computed the PME within a series of concentric
annuli. Here the term giving rise to the total mass in the
case of complete volume sampling, and through which one intends to infer
$M(r)$, actually cancels out.
Thus, using the PME often gives results that resemble $M(r)$ but
this is not precisely what is being measured.
The generalized estimator
can be compared with observations if one has some model
of the mass distribution and the tracer population.
Monday
program listing