Interests: Instrumentation and exoplanets. 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.
I am currently a 1st year graduate student, advised by Dr. Kate Jackson, primarily located at NRC Herzberg in British Columbia, Canada; I'm academically affilated with the University of Victoria.
Working on developing a "non-linear Curvature Wavefront Sensor" (nlCWFS) for the REVOLT adaptive optics (AO) testbed on our local 1.4 meter McKellar telescope (see right). Presently, I've been creating simulations of our nlCWFS using a popular astronomy optics package called HCIPy, created by Emiel Por. After publishing my simulation work, I will be designing and building a nlCWFS for REVOLT, planning to have it on-sky for my PhD thesis (~2029).
nlCWFS is a type of wavefront sensor used in AO to gain extreme sensitivity to a wide range of atmospheric turbulence "modes," particularly higher-order modes. nlCWFS is unique in that it requires concurrent images before and after the pupil plane, unlike other pupil-plane based wavefront sensors such as a pyramid WFS, which only collects wavefront information once. nlCWFS requires a variety of new issues to be taken into consideration. For instance, having to use near-field propagation equations, the usage of multiple optical planes, the latter of which requires a weird optical design, making it difficult to develop a working nlCWFS.
In 2025, after completing my B.S. in astrophysics, I was hired as an exoplanet researcher for the University of California Observatories, working on exoplanet vetting using data from the James Webb Space Telescope (JWST). I worked with Prof. Andrew Skemer (UCSC) within Dr. Aarynn Carter's (STScI) Sub-Jupiter exoplanet group.
I presently still work in the group to this day, working when I can on the project below, with plans to publish a paper in early 2027.
By analyzing the colors (spectra), shape, and motion of planet candidates within our JWST data and comparing each source to similar data from years prior, we can determine whether or not each candidate is truly 'bound' to their host star. A source following a 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 handling suspicious 'little red dots,' which look exactly like exoplanets, and yet are completely unplanetary in nature. If you're curious about these new objects discovered with JWST, I reccomend checking out the paper linked on the left.
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 Magnesium (Mg) abundances across Mercury's northern 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. I 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 largest moon, Titan, in 2028 to search for life! Learned a lot about vacuum 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 signals with the resulting datasets used in the 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 to its host star. One method used to eliminate starlight from exoplanet images is a post-processing method called 'Reference Differential Imaging,' or RDI. Using a 'reference image,' aka a lone star with a similar spectral type and magnitude to the star hosting a planet (aka the 'science target').By subtracting the reference target from the science target, we subtract away stray starlight left after imaging an exoplanet-containing system (with the image being taken using coronagraphic methods). However, in the era of the James Webb Space Telescope (JWST), there are several cases where one may want to use a 'reference image' containing multiple (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 primarily 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 align with current direct-imaging industry standards.
In addition to this project serving as my undergraduate thesis at UCSC, I had the great pleasure of presenting this research at SPIE: Astronomical Telescopes and Instrumentation held in Yokohama, Japan, back in June 2024, which resulted in a first-author publication. 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 alignment and calibration. Used Python and IDL to carry out these responsibilities. Occasionally completed side projects like programming a custom humidity sensor and making a terminal interface (decision tree) for interacting with dual-piezoelectric motion motors.
When light from astronomical objects is observed using ground-based telescopes, it is degraded by 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.
