Interests: Exoplanets and Instrumentation. Specifically direct-imaging or 'High Contrast Imaging' (HCI).
In descending chronological order, the following entries are somewhat informal descriptions of what I've been pursuing. If you find yourself curious to know more, I've attached links below each section's image (when appropriate).
On the right is a gif of me making a He-Ne laser parallel for an interferometer setup.
Currently working on exoplanet vetting using data from the James Webb Space Telescope (JWST). Working with Prof. Andrew Skemer (UCSC) within Dr. Aarynn Carter's (STScI) Sub-Jupiter exoplanet group.
By analyzing the colors (spectra), shape, and motion of planet canidates within our 2024 JWST data and comparing each source to similar data from years prior, we can determine whether or not each canidate is truly 'bound' to their host star. A source following similar motion to its host across time is the first indicator that it may be a planet (instead of say, a background star). The biggest challenge (so far) with this project is working with data originating from wildly different instruments. Hubble data has different documentation and parameters compared to Keck, ELT, and JWST.
On the left is an example of what is meant by a direct image of an exoplanet; the white star in the middle represents where the host star once was (its light here was removed using coronagraphic and post-processing techniques), and the bright orange-ish blob being the planet. Exoplanets are so far away that they appear to be single point sources of light, meaning no clouds or large features like rings can be seen. making their nature difficult (and exciting) to uncover.
Interned at Lawrence Livermore National Laboratory's (LLNL) Germanium Detector Lab with Dr. Morgan Burks.
Primarily worked on creating a map of Magneisum (Mg) abundances across Mercury's nothern hemisphere, using data from the gamma-ray spectrometer that flew on the MESSENGER (2004) mission. Analyzed binary/XML data from the NASA PDS website by creating python code to apply Gaussian fitting methods. Also got to work on building and testing an engineering model of the upcoming Dragonfly mission's gamma-ray spectrometer, which will fly to Saturn's larget moon, Titan, in 2028 to search for life. Learned a lot about vaccum sealing, crystal annealing, and dealing with calibrated spacecraft data.
On the right, an image of an oscilloscope and gamma-ray spectrometer. Oscilloscopes are used to read out signal with the resulting datasets used in final analysis. Gamma-ray spectrometers (located to the right of the oscilloscope) are covered in a thin layer of gold to reflect away any stray light, helping to keep its insides at very low temperatures. This is crucial for space-based missions existing in hot environments, such as around the planet Mercury.
Exoplanet imaging is made near-impossible due to the stark difference in brightness of an exoplanet as compared its host star. One method used to eliminate starlight from exoplanet images is a post-processing method called 'Reference Differential Imaging,' or RDI. by using a 'reference image,' aka a lone star with similar spectral type and magnitude to the star hosting a planet, we can subtract away stray starlight leftover after imaging a exoplanet containing system using coronagraphic methods. However, in the era of JWST, there are several cases where one may want to use a 'reference image' containing multiple, or binary, sources. This could be a bounded binary star system, or a star and background galaxy.
For this project I created simulations of RDI (Reference Differential Imaging) imaging with JWST's NIRCam (Near InfraRed Camera) to explore and analyze the effects of binary sources on contrast limits. I primarly used a package called panCAKE, created by Dr. Aarynn Carter (who mentored me for this project). Since this is an unexplored area of RDI imaging, a lot of effort on this project went into creating analysis methods that act in line with current direct-imaging industry standards.
In addition to this project serving as my undergraduate thesis at UCSC, I had a great pleasure of presenting this research at SPIE: Astronomical Telescopes and Instrumentation held in Yokohama, Japan, back in June 2024. On the left is a link to my first-author publication for this work.
Interned for Lawrence Livermore National Laboratory's AO system LLAMAS. Observed ~60 nights at Lick Observatory's Nickel Telescope using LLAMAS, performing live data analysis during experimentation/testing of the system. When not observing, I learned about real-time computing (RTC) and worked on optical allignment and calibration. Used Python and IDL to carry out these responsibilities. Occassionally completed side-projects like programming a custom humidity sensor, and making a terminal interface (decision-tree) for interacting with dual-piezoelectic motion motors.
When light from astronomical objects is observed using ground-based telescopes, it is degraded by to Earth's atmosphere. Atmospheric turbulence (the same as felt on an airplane) has detrimental effects on the quality of astronomical data. AO is a technology implemented into telescopes to help counteract atmospheric turbulence by predicting and correcting for it on extremely short time scales. On the right is a picture of the Nickel telescope, located in San Jose, CA.
