Fast Globally Optimal Catalog Matching using MIQCP

Autor: Jacob Feitelberg, Amitabh Basu, Tamás Budavári
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: The Astronomical Journal, Vol 166, Iss 4, p 174 (2023)
Druh dokumentu: article
ISSN: 1538-3881
DOI: 10.3847/1538-3881/acf5e2
Popis: We propose a novel exact method to solve the probabilistic catalog matching problem faster than previously possible. Our new approach uses mixed integer programming and introduces quadratic constraints to shrink the problem by multiple orders of magnitude. We also provide a method to use a feasible solution to dramatically speed up our algorithm. This gain in performance is dependent on how close to optimal the feasible solution is. Also, we are able to provide good solutions by stopping our mixed integer programming solver early. Using simulated catalogs, we empirically show that our new mixed integer program with quadratic constraints is able to be set up and solved much faster than previous large linear formulations. We also demonstrate our new approach on real-world data from the Hubble Source Catalog. This paper is accompanied by publicly available software to demonstrate the proposed method.
Databáze: Directory of Open Access Journals