Abstract
All surveys include observational biases, which makes it impossible to directly compare properties of discovered trans-Neptunian Objects (TNOs) with dynamical models. However, by carefully keeping track of survey pointings on the sky, detection limits, tracking fractions, and rate cuts, the biases from a survey can be modelled in Survey Simulator software. A Survey Simulator takes an intrinsic orbital model (from, for example, the output of a dynamical Kuiper belt emplacement simulation) and applies the survey biases, so that the biased simulated objects can be directly compared with real discoveries. This methodology has been used with great success in the Outer Solar System Origins Survey (OSSOS) and its predecessor surveys. In this chapter, we give four examples of ways to use the OSSOS Survey Simulator to gain knowledge about the true structure of the Kuiper Belt. We demonstrate how to statistically compare different dynamical model outputs with real TNO discoveries, how to quantify detection biases within a TNO population, how to measure intrinsic population sizes, and how to use upper limits from non-detections. We hope this will provide a framework for dynamical modellers to statistically test the validity of their models.
Highlights
The orbital structure, size frequency distribution, and total mass of the trans-Neptunian region of the Solar System is an enigmatic puzzle. Fernandez (1980) described an expected distribution for this region based on the mechanisms for the delivery of cometary material into the inner Solar System
In the Outer Solar System Origins Survey (OSSOS) project we demonstrate the effectiveness of this approach by managing to track essentially all trans-Neptunian Objects (TNOs) brighter than the flux limits of the discovery sequences
While the methodology presented here is specific to the OSSOS Survey Simulator, by measuring on sky pointings, magnitude limits, and tracking fractions, a Survey Simulator can be built for any survey
Summary
The orbital structure, size frequency distribution, and total mass of the trans-Neptunian region of the Solar System is an enigmatic puzzle. Fernandez (1980) described an expected distribution for this region based on the mechanisms for the delivery of cometary material into the inner Solar System. Other recent results for Kuiper belt subpopulations include Schwamb et al (2009), who use Monte Carlo sampling to estimate detectability of Sedna-like orbits, and Parker (2015), who uses an approximate Bayesian computation approach to account for unknown observation biases in the Neptune Trojans. Each of these methods relies on backing out the underlying distributions from a detected sample. We hope this chapter provides an outline for others to follow
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