# Fast algorithms for slow moving asteroids: constraints on the distribution of Kuiper Belt Objects

## TL;DR

This paper presents a GPU-accelerated algorithm capable of rapidly searching for faint moving asteroids in large astronomical datasets, leading to the discovery of new Kuiper Belt Objects and insights into their distribution.

## Contribution

The authors develop a massively parallel GPU-based algorithm for efficient asteroid trajectory searches, enabling rapid analysis of large astronomical image stacks and discovery of new Kuiper Belt Objects.

## Key findings

- Discovered 39 new Kuiper Belt Objects in survey data.
- Algorithm can search over 10^10 trajectories in under a minute.
- Results align with existing models of Kuiper Belt inclination distribution.

## Abstract

We introduce a new computational technique for searching for faint moving sources in astronomical images. Starting from a maximum likelihood estimate for the probability of the detection of a source within a series of images, we develop a massively parallel algorithm for searching through candidate asteroid trajectories that utilizes Graphics Processing Units (GPU). This technique can search over 10^10 possible asteroid trajectories in stacks of the order 10-15 4K x 4K images in under a minute using a single consumer grade GPU. We apply this algorithm to data from the 2015 campaign of the High Cadence Transient Survey (HiTS) obtained with the Dark Energy Camera (DECam). We find 39 previously unknown Kuiper Belt Objects in the 150 square degrees of the survey. Comparing these asteroids to an existing model for the inclination distribution of the Kuiper Belt we demonstrate that we recover a KBO population above our detection limit consistent with previous studies. Software used in this analysis is made available as an open source package.