Publication of an article on advanced Monte Carlo sampling for the estimation of asteroid impact probability

Earth is subject to frequent impacts by small meteoroids and asteroids that orbit the Sun in Earth’s neighbourhood, causing periodic close encounters with our planet with a chance of impacting it.  In a paper recently published in Celestial Mechanics and Dynamical Astronomy by Matteo Romano, Matteo Losacco, Camilla Colombo, and Pierluigi Di Lizia, we propose advanced Monte Carlo sampling methods such as Line Sampling and Subset Simulation to estimate the probability of an impact between an asteroid and the Earth.

The paper describes the two methods (schematised in the pictures above) in detail and compares their accuracy and efficiency both with standard Monte Carlo techniques and between them. This was done by studying different Near-Earth Asteroids whose orbits present close approaches with our planet with different levels of impact probability.

The results show that the two methods perform better than standard Monte Carlo as the expected probability level decreases. In particular, Line Sampling can obtain a more accurate estimation using the same number of propagations, while Subset simulation is able to reduce the number of propagations required for the same accuracy level.

The paper is accessible in open access at Check it out!