- Title Information
- Title
- A Next Generation Analysis Pipeline for 21cm Epoch of Reionization Studies
- Name:
Personal
- Name Part
- Kerrigan, Joshua
- Role
- Role Term:
Text
- creator
- Name:
Personal
- Name Part
- Pober, Jonathan
- Role
- Role Term:
Text
- Advisor
- Name:
Personal
- Name Part
- Tucker, Gregory
- Role
- Role Term:
Text
- Reader
- Name:
Personal
- Name Part
- Dell'Antonio, Ian
- Role
- Role Term:
Text
- Reader
- Name:
Corporate
- Name Part
- Brown University. Department of Physics
- Role
- Role Term:
Text
- sponsor
- Origin Information
- Copyright Date
- 2019
- Physical Description
- Extent
- 13, 130 p.
- digitalOrigin
- born digital
- Note:
thesis
- Thesis (Ph. D.)--Brown University, 2019
- Genre (aat)
- theses
- Abstract
- The Epoch of Reionization (EoR) is a period during the history of the Universe that as of today has been largely unconstrained by cosmological measurements. The most promising probe of reionization, the 21cm emission of neutral hydrogen, is unfortunately difficult to observe. Measurements of the 21cm reionization signal are performed using low-frequency wide-field radio interferometers. The difficulty in detecting the weak 21cm signal is further compounded by instrumental and astrophysical limitations. In an effort to overcome these issues, I present four key results. First I look at applying a hybrid foreground avoidance strategy for retaining sensitivity in the presence of Galactic and extragalactic foregrounds. I then introduce a novel method for identifying radio frequency interference (RFI) in interferometric visibilities using a Deep Fully Convolutional Neural Network (DFCN). Following this, I perform sky calibration on preliminary Hydrogen Epoch of Reionization Array (HERA) observations using the Fast Holographic Deconvolution (FHD) interferometry simulation software which provides an independent validation of the default HERA processing and calibration pipeline. Finally, I demonstrate a Convolutional Neural Network (CNN) for 21cm parameter estimation and uncertainty propagation on simulated 21cm cosmological volumes.
- Subject
- Topic
- Machine Learning
- Subject (fast)
(authorityURI="http://id.worldcat.org/fast", valueURI="http://id.worldcat.org/fast/00880600")
- Topic
- Cosmology
- Subject (fast)
(authorityURI="http://id.worldcat.org/fast", valueURI="http://id.worldcat.org/fast/01087196")
- Topic
- Radio astronomy
- Subject (fast)
(authorityURI="http://id.worldcat.org/fast", valueURI="http://id.worldcat.org/fast/02002936")
- Topic
- Epoch of reionization
- Subject
- Topic
- 21cm
- Language
- Language Term (ISO639-2B)
- English
- Record Information
- Record Content Source (marcorg)
- RPB
- Record Creation Date
(encoding="iso8601")
- 20190603
- Identifier:
DOI
- 10.26300/gd9x-ms58
- Access Condition:
rights statement
(href="http://rightsstatements.org/vocab/InC/1.0/")
- In Copyright
- Access Condition:
restriction on access
- Collection is open for research.
- Type of Resource (primo)
- dissertations