A Well-Characterized Survey for Centaurs in Pan-STARRS1

TL;DR

This paper develops a method to quantify the selection function of wide-field surveys, applies it to Pan-STARRS1 to discover and analyze Centaurs, and demonstrates the effectiveness of HelioLinC3D as a discovery algorithm for large-scale surveys.

Contribution

It introduces a systematic approach to characterize survey selection functions and applies HelioLinC3D to Pan-STARRS1, revealing new Centaurs and validating the algorithm's utility.

Findings

Discovered 9 new Centaurs in Pan-STARRS1 data.

Estimated an intrinsic Centaur population of approximately 21,400.

Confirmed high completeness of the Pan-STARRS1 discovery pipeline.

Abstract

To prepare for the upcoming Legacy Survey of Space and Time, we develop methods for quantifying the selection function of a wide-field survey as a function of all six orbital parameters and absolute magnitude. We perform a HelioLinC3D search for Centaurs in the Pan-STARRS1 detection catalog and use a synthetic debiasing population to characterize our survey's selection function. We find nine new objects, including Centaur 2010 RJ$_{226}$, among 320 real objects, along with $\sim$70,000 debiasing objects. We use the debiasing population to fit a selection function and apply the selection function to a model Centaur population with literature orbital and size distributions. We confirm the model's marginal distributions but reject its joint distribution, and estimate an intrinsic population of 21,400$^{+3,400}_{-2,800}$ Centaurs with $H_r < 13.7$. The discovery of only nine new objects in archival data verifies that the Pan-STARRS discovery pipeline had high completeness, but also shows that new linking algorithms can contribute even to traditional single-tracklet surveys. As the first systematic application of HelioLinC3D to a survey with extensive sky coverage, this project proves the viability of HelioLinC3D as a discovery algorithm for big-data wide-field surveys.