Kevin Diep was born and raised on Oahu. He graduated from McKinley High School in 2017. He recently graduated from University of Hawaii, Manoa in 2021 with a Bachelors of Science in Astrophysics and Mathematics. He is currently interested in learning some computer science skills. In his free time he enjoys playing video games, reading manga, watching anime, and hanging out with his friends.
Home Island: O’ahu
High School: McKinley High School, HI
Institution when accepted: University of Hawaii at Manoa
Akamai Project: Automating Fried’s Parameter Storage
Project Site: W. M. Keck Observatory (Keck) – Waimea, Hawai‘i Island HI
Mentor: Sam Ragland
Ground-based astronomical observations are distorted by turbulence in Earth’s atmosphere. Large telescopes use adaptive optics (AO) systems to apply corrections to wavefront errors, thereby reducing distortion and improving telescope resolution. Our project is an essential part of the W.M Keck Obervatory’s ongoing effort to upgrade their AO system by replacing its current licensed commercial software with an open-source alternative. The goal is to write a Python script to estimate and archive turbulence parameters for the Keck All-sky Precision Adaptive Optics (KAPA) project. Utilizing a collection of scripts called P3, we use existing images from actual observation and compute an estimation of seeing parameter for every image. We validate our estimations by comparing the results with Maunakea weather station’s MASS/DIMM data and existing on-sky turbulence parameter data. We plot the Fried parameter r0 of our P3 estimation vs MASS/DIMM values and vs. classic estimation for each image, then create a line of best fit for the observation night. From the fitting, we extract an error term and correlation coefficient to perform a statistic test for agreement. In addition, we included a functionality to plot of the MASS profile as a brief check for data irregularities. Our algorithm can automate calculation and storage of the estimation for multiple observation nights within a single run.