Impact Probability Under Aleatory And Epistemic Uncertainties

TL;DR

This paper introduces a method to estimate upper bounds on impact probabilities of hazardous asteroids considering both aleatory and epistemic uncertainties, demonstrated through Apophis risk assessment.

Contribution

It provides a novel approach to quantify impact risk bounds under epistemic uncertainties using statistical distributions of physical properties.

Findings

Upper bound impact probability for 2036 keyhole: 5×10⁻⁵

Upper bound impact probability for 2068 keyhole: 1.6×10⁻⁵

Method accounts for wide range of physical property distributions

Abstract

We present an approach to estimate an upper bound for the impact probability of a potentially hazardous asteroid when part of the force model depends on unknown parameters whose statistical distribution needs to be assumed. As case study we consider Apophis' risk assessment for the 2036 and 2068 keyholes based on information available as of 2013. Within the framework of epistemic uncertainties, under the independence and non-correlation assumption, we assign parametric families of distributions to the physical properties of Apophis that define the Yarkovsky perturbation and in turn the future orbital evolution of the asteroid. We find ${\rm IP}\leq 5\times 10^{-5}$ for the 2036 keyhole and ${\rm IP}\leq 1.6\times 10^{-5}$ for the 2068 keyhole. These upper bounds are largely conservative choices due to the rather wide range of statistical distributions that we explored.