1. Pigmentation Pattern Recreation in Reaction-Diffusion Systems using Realistic Bounds
Annie Cloonan, Agnes Scott College
Research into the application of reaction-diffusion models to understand natural systems has uncovered its novel capability to mechanistically recreate realistic animal pigmentation patterns. Reaction-diffusion systems, first proposed by Alan Turing in 1952, describe the rate of change of the concentrations of substances by their interactions and diffusions in space. The complex spatial periodic patterns created by the model develop autonomously through the random perturbations of an initially homogeneous equilibrium state, and have been found to correspond to numerous natural phenomena, including animal pigmentation. With the implementation of a reparameterized version of the system, we use silhouettes of various species as spatial bounds to create GPU simulations of the development of their pigmentation patterns in their natural shape. We study the relationship between the features of an animal’s surface and its developed pigmentation pattern complexity. We also analyze variations in the parameters, which produce a wide range of pigmentation patterns associated with different species of animal. Our analysis allows for biological and mathematical insight into the core mechanisms of general animal pattern development.
2. Exploring the Properties of Astrophysical Neutrino Events with the IceCube Neutrino Observatory in Antarctica
Sarah Foess, University of Alabama
I work with the IceCube Neutrino Observatory in the geographic South Pole, which collects data on high-energy neutrino events as they pass through the detector. By working with this collected data, I am able to process different properties of each high-energy event such as type, time between consecutive like-type events, and frequency of all events to make conjectures about particle behavior and origin.
3. Improving Optical Lattice Clock Stability by Quantifying EMCCD Camera Noise Sources
Melanie Frolich, Florida International University
The EMCCD (electron-multiplying charge coupled device) camera has found widespread use in a variety of fields from developmental biology, to astronomy and optical physics. The various sources of noise, including readout noise, dark current, and clock induced noise, and their contribution to the total noise of the camera can be characterized in order to find the total Signal-to-Noise Ratio (SNR) of the camera. Through investigation and analysis of a variety of parameters of the camera’s use (light source, exposure time, gain, and temperature) the camera setup that yields the highest value of SNR can be chosen for the given experimental setup, leading to more accurate and precise experimental results. These analyses will ultimately serve the goal of improving the noise within the collected fluorescence spectroscopy data of a strontium clock experiment through replacement of the current EMCCD camera. Improvements in the strontium clock means improvements in many related areas that heavily rely on the precise measurement of time, such as GPS systems, space travel, and overall ability to measure new phenomena.
4. Probing the Likelihood of New Physics with JWST
Martine Maggi, University of North Georgia
Via observation of high redshift galaxies near the epoch of reionization (~13.6 billion years ago), the James Webb Space Telescope (JWST) is potentially capable of settling an open debate in astrophysics with important implications to our understanding of the Standard Model: a determining measurement of the primordial helium abundance. The relative proportion of helium created during Big Bang Nucleosynthesis (BBNS) is a byproduct of the rate of expansion of the early Universe, as is the number of neutrinos flavors. At present, the primordial helium abundance must be extracted and inferred from sources younger than the epoch of reionization which leads to large uncertainty in the resulting determination of the primordial helium abundance. An uncertain primordial helium abundance predicted a non-integer number of neutrino flavors which obviously cannot occur in nature. This project aims to set expectations for JWST’s ability to determine the primordial helium abundance from direct observation with enough accuracy to substantiate sufficient evidence for or utterly refute the existence of a fourth flavor of neutrino. The spectral synthesis code CLOUDY is used to produce spectra from simulated primordial HII regions with variations in helium abundance which are then redshifted and fed into the online JWST simulation software. The output spectra of the simulation is then compared to the actual to determine accuracy. At the present stage of this research, the JWST output spectra is fairly accurate, boding well for astronomers embroiled in the debate father primordial helium abundance and confirmation of 3 neutrino flavors.
5. Study of the Structure and Evolutionary History of the Milky Way
Ashley Meglino, University of North Florida
This research project was in the field of Galactic archeology, which is the area of astrophysics that examines stars in the Milky Way in order to study the history and evolution of the Galaxy. There have recently been significant advancements in spectroscopic surveys and astrometry, thus providing a greater understanding of the chemical abundances and dynamics of stars. With that, the goal of this research project was to study the age-resolved physical structure and chemical abundance trends in the Galaxy’s disk. Using python, we took stellar data from the APOGEE spectroscopic survey and from Gaia and started by creating two plots displaying the structure of the disk. The first plot showed the inside-out and upside-down formation trends that many other previous studies have also found. The second plot contained evidence of the Gaia-Sausage-Enceladus (GSE) merger that happened in the Galaxy’s past. To further study this GSE merger, we created a heatmap of the current chemical abundance distribution of stars in the disk. The idea was to determine whether this distribution fits in a single-infall or two-infall chemical evolution model, which each provide different theories of how the Galaxy evolved chemically over time. We determined that the data fit the single-infall model. Therefore, we concluded from the research that evidence of the GSE merger can be seen in the age-resolved physical structure of the Galaxy and that the present-day chemical abundances can be explained without significant impact from the GSE merger.
6. Implementation of machine learning models for prediction of primary gamma-ray emissions from thermal neutron capture reactions
Ana Pereira, Florida State University
The National Nuclear Data Center (NNDC) at Brookhaven National Laboratory maintains a dedicated effort towards providing easy access of reliable and evaluated nuclear data. Nuclear data includes features describing the lifetime, mass, types of decays, and energies related to a nuclide. Using the Evaluated Gamma-ray Activation File (EGAF), Evaluated Nuclear Structure Data File (ENDSF), and NuDat, the goal of this project is to employ machine learning (ML) methods to predict primary gamma ray emissions from isotopes which have undergone neutron capture at thermal incident energies. A neutron capture reaction is identified by the formation of a residual nucleus composed by the projectile neutron and the target isotope. This new system is presumed to be formed at an excited state of the compound nucleus and undergoes a sequence of gamma ray emissions as a mean of de-excitation, eventually reaching its ground state. To comprehend the cascade of emissions, it is most significant to understand the first steps in the decay: the primary emissions. Instead of using standard theoretical nuclear models, training classification and regression models using machine learning algorithms with experimental data can allow for the machine to predict primary gamma ray emission probabilities missing in data sets with greater accuracy. We have produced such models, but none with desired accuracy. We will continue to consider adding features, fine-tune models, and produce ‘physics informed’ ML. Upon successful project completion the NNDC will be able to provide more precise capture gamma-ray spectra in evaluated libraries.
7. Plasma Processing on Superconducting RF Cavities for Ion Linacs
Zhihan Wei, Georgia Institute of Technology
At Argonne National Laboratory, maintaining and cleaning the Argonne Tandem Linac Accelerating System (ATLAS) cavities is a labor-intensive task. The process involves disassembling the cryostats and removing the cavities to undergo the cleaning process. This project aims to utilize plasma processing to develop an in-situ maintenance process in order to mitigate field emission in RF cavities. The presentation will showcase the experimental setup and initial plasma ignition testing conducted in the 172 MHz Half-Wave Resonator (HWR) cavity. In the future, we aim to perform plasma ignition tests on ATLAS Quarter-Wave Resonator (QWR) cavities and eventually conduct cold testing on the ATLAS cavities, with the goal of implementation on ATLAS within one to two years.