Thesis
Building a citizen science project to investigate IceCube data analysis
Master of Science (M.S.), Drexel University
Jun 2023
DOI:
https://doi.org/10.17918/00001705
Abstract
The IceCube Neutrino Observatory is a neutrino detector at the South Pole that has 5160 optical sensors that observe light deposited by incoming particles interacting with the Antarctic ice. IceCube utilizes advanced machine learning algorithms to classify the topology of these different signals and determine the direction and energy of the incident particle. These classifications can be used to effectively reconstruct events and aid in IceCube's goal of determining sources of astrophysical neutrinos. Name that Neutrino (NtN) is a citizen science project in which users from the general public can view and classify simulated IceCube events. NtN was developed in order to explore the capability of laypeople to classify these events and make comparisons to the classifications made by machine learning techniques. Over a three-month period from March 2023 to May 2023, NtN had 1,000 registered volunteers perform over 64,000 classifications of 4,273 events. With the results from this project, we compare the performance of people and machine learning in the task of classifying IceCube event topologies. Possible outstanding issues for future iterations of this project are examined.
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Details
- Title
- Building a citizen science project to investigate IceCube data analysis
- Creators
- Elizabeth Hilda Stern Warrick
- Contributors
- Christina Love (Advisor)Naoko Kurahashi Neilson (Advisor)
- Awarding Institution
- Drexel University
- Degree Awarded
- Master of Science (M.S.)
- Publisher
- Drexel University; Philadelphia, Pennsylvania
- Number of pages
- vii, 27 pages
- Resource Type
- Thesis
- Language
- English
- Academic Unit
- College of Arts and Sciences; Physics; Drexel University
- Other Identifier
- 991020876803404721