Improving the accuracy of solar system small body period derivation through de-aliasing and survey cadence

Kramer, Daniel Robert (2023) Improving the accuracy of solar system small body period derivation through de-aliasing and survey cadence. Masters thesis, Northern Arizona University.

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Abstract

Currently, deriving small body rotation periods is one of the most challenging problems in small body astronomy. An added challenge is that data from ground-based surveys have to overcome the day-night cadence of the Earth, which causes aliasing. I used real data from the Zwicky Transient Facility (ZTF) and synthetic data from the Legacy Survey of Spaceand Time (LSST), several ways were tried to improve the match rate of derived small body periods to their physical state. The two main ways were (1) removing cadence based aliasing solutions after a survey has acquired observations and (2) finding a cadence for a survey that results in the highest match percentage, each of them comprising their own paper. In my first paper, I used four different methods — three from the literature and a new one that we developed — were examined that remove aliases to improve the accuracy of period-finding algorithms. We investigate the effectiveness of these methods in decreasing the fraction of aliased period solutions by applying them to the ZTF and the LSST Solar SystemProducts Database (SSPBD), a synthetic LSST small body dataset, asteroid datasets. We find that the VanderPlas method had the worst accuracy for each survey. The mask and our newly proposed window method yields the highest accuracy when averaged across both datasets. However, the Monte Carlo method had the highest accuracy for the ZTF dataset, while for SSPDB, it had lower accuracy than the baseline where none of these methods are applied. Where possible, detailed de-aliasing studies should be carried out for every survey with a unique cadence. In my second paper, I used simulations of LSST to determine the best cadence for deriving small body rotation periods. LSST has already made simulations of LSST observations using different cadences to try to determine which one is the best for many different science cases. However, these science cases do not address the derivation of small body rotation periods. We implanted synthetic asteroids in 141 different simulations, all 139 version v2.1 simulations and two from the version 1.7/v1.7.1 simulations, to determine the best and worst cadences for rotation period derivation. We found that cadences with long exposures (small errors) and cadences that repeatedly observe one field had the best derived period match rate. Conversely, short exposures and non-repeated fields had the worst match rate. We also examined the match rate as a function of survey length to examine when periods would be successfully derived. We found, with a minimum observation cut, that at least 90% of the year ten match rate is achieved in year 1. We also found that the match rate does not plateau, meaning that a longer survey would result in higher match rates. My work in this thesis leads to several lines of future investigation: (1) Develop methods for removing pseudo-aliases, (2) Develop a “confidence” metric for period solutions, (3) testing the de-aliasing methods and the effects of cadence on period derivation on stellar and non-sinusoidal sources, and (4) analyzing the difference between the real LSST period results and the synthetic.

Item Type:	Thesis (Masters)
Publisher’s Statement:	© Copyright is held by the author. Digital access to this material is made possible by the Cline Library, Northern Arizona University. Further transmission, reproduction or presentation of protected items is prohibited except with permission of the author.
Keywords:	Small body rotation; Periodicity' Zwicky Transient Facility; Legacy Survey of space and Time
Subjects:	Q Science > QB Astronomy
NAU Depositing Author Academic Status:	Student
Department/Unit:	Graduate College > Theses and Dissertations College of Engineering, Informatics, and Applied Sciences > School of Informatics, Computing, and Cyber Systems
Date Deposited:	15 May 2025 22:19
Last Modified:	15 May 2025 22:19
URI:	https://openknowledge.nau.edu/id/eprint/6147

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