A deep analysis for New Horizons' KBO search images

TL;DR

This paper applies a FPGA-based detection method to analyze Subaru HSC images from the New Horizons mission, successfully identifying 84 Kuiper Belt Object candidates in datasets from 2020-2021.

Contribution

It demonstrates the adaptation of a fast-moving object detection method for slow-moving KBOs in astronomical survey data, expanding detection capabilities.

Findings

Detected 84 KBO candidates in the datasets analyzed.

Validated the method's effectiveness for slow-moving object detection.

Provided publicly available datasets with identified candidates.

Abstract

Observation datasets acquired by the Hyper Suprime-Cam (HSC) on the Subaru Telescope for NASA's New Horizons mission target search were analyzed through a method devised by JAXA. The method makes use of Field Programmable Gate arrays and was originally used to detect fast-moving objects such as space debris or near-Earth asteroids. Here we present an application of the method to detect slow-moving Kuiper Belt Objects (KBOs) in the New Horizons target search observations. A cadence that takes continuous images of one HSC field of view for half a night fits the method well. The observations for the New Horizons Kuiper Belt Extended Mission (NH/KEM) using HSC began in May 2020, and are ongoing. Here we show our result of the analysis of the dataset acquired from May 2020 through June 2021 that have already passed the proprietary period and are open to the public. We detected 84 KBO candidates in the June 2020 and June 2021 datasets, when the observation field was close to opposition.