Joann Jones Email and Phone Number

The cosmic microwave background (CMB) can be described as a snapshot of the early Universe. It provides us with essential information on the origin and evolution of the Universe. Using the CMB, we are able to place constraints on the current standard model of cosmology, 𝚲CDM. Conventionally, 𝚲CDM treats the Universe as statistically homogeneous and isotropic, i.e. the same in every location and in every direction. However, there are several unexpected features of the large scale fluctuations in the CMB that are inconsistent with statistical isotropy. These are referred to as the large-scale anomalies. Each of these anomalies has a small chance of occurring (1/100 - 1/10000) , but are often individually excused as statistical flukes. In this project, we seek to answer the question of whether or not these anomalies are correlated. In particular, we are interested in the lack of large-angle correlation, the odd-parity preference, the quadrupole-octupole alignment, and the hemispherical asymmetry anomalies. We find that the anomalies we have considered are uncorrelated in the tails of their distributions, meaning that their joint probability is significantly lower. We find a 3e-8 chance of 𝚲CDM reproducing our CMB. This provides strong evidence against the existence of statistical isotropy in our Universe. Check out my first author paper here: https://arxiv.org/abs/2310.12859

I am part of a research group studying dark matter candidates using machine learning and a zooniverse project. https://www.zooniverse.org/projects/macrodarkmatter/countertop-dark-matter

I am a Spartan Ambassador at Case Western Reserve University. I connect with admitted students and answer any questions they may have, providing them with student insight into life at CWRU, specifically within the Physics and Astronomy departments. My job is to make admitted students feel comfortable and happy about joining the CWRU community.

I instructed children during an Astronomy camp on several topics including stars, galaxies, black holes, and dark matter.

High energy particles, such as relativistic electrons, enter the Earth's magnetic field through solar wind. Relativistic electron precipitation (REP) occurs when these high energy electrons precipitate off of the magnetic field lines and fall to Earth's atmosphere. Precipitation bands are a longer duration form of REP. They contribute significantly to rapid loss of electrons from the outer Van Allen radiation belt, yet their origins are still unclear. In this study, we develop an algorithm to automatically detect precipitation bands observed by the Solar, Anomalous, and Magnetospheric Particle Explorer (SAMPEX) satellite (1992-2012) using an unsupervised machine learning technique called a self-organizing-map (SOM). The results from this study will be followed by a statistical analysis of precipitation bands to better understand the radiation belt dynamics.