Probabilistic distribution functions
Jun Yan Lau, James Binney
TL;DR
This paper introduces a probabilistic framework for modeling observed clusters using distribution functions as random variables, providing a canonical coordinate system for consistent weighting of these functions.
Contribution
It develops a novel probabilistic approach and identifies a canonical coordinate system for distribution functions, enabling more consistent modeling of system excitation.
Findings
A system of canonical coordinates for distribution functions is established.
Distribution functions are modeled as random variables to quantify excitation.
A consistent weighting scheme for distribution functions is proposed.
Abstract
Observed clusters should be modelled by considering the distribution function to be a random variable that quantifies the degree of excitation of the system's normal modes. A system of canonical coordinates for the space of DFs is identified so DFs can be weighted in a consistent way.
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