Methodology

Choosing a Candidate

In the first stage of our project, we identified high-probability exoplanet candidates by analyzing key features in TESS reports: relative flux graph, signal-to-noise ratio (SNR), and occultation number. For relative flux, a U-shaped flux curve suggests a planet transit, while a V-shape may indicate a variable star. An SNR above 50 is key for clarity in our observations and an occultation difference or transit difference under 5 sigma is ideal to rule out multiple-body systems. Candidates also needed a radius under 20 for it to plausibly be a planet. An Rp/Rstar ratio near 0.1 for the flux dip is required to be detectable. To ensure observability from the Leuschner Telescope in Lafayette, CA, we needed an RA between 8–12 hours and DEC between 5–70 degrees. We prioritized candidates with multiple monthly transits that lasted under six hours to increase observation opportunities.

Observation

Having chosen our candidate, we began observing transits. We observed three times, with two of them being full transits. In addition to the potential candidate we found, we also spent a night observing the candidate from last year, “Sundialia.”

On observation nights, we set up the Leuschner Telescope to focus on the exoplanet we were observing. For transits, we took 120-second exposures. We also took darks and bias frames, typically around 10 to 20 of each. During sunset or sunrise, we took flats, as this is the only time they can be taken (about 15 minutes after either), so we captured them before or after observing the transit. The dome that houses the Leuschner Telescope has an auto-adjustment feature that moves when the telescope moves to follow the target. Due to programming errors, during two of our observations, it did not work, so we had to manually rotate the dome to prevent it from blocking the telescope.

Data Analysis

Air Mass Correction

For our air mass correction computation we first needed to convert from flux to magnitudes using the conversion:

and then used the Kasten-Young formula to find the air mass at the given zenith-angle:

This fit is more ideal for our observations as it can account for altitudes approaching 10 degrees and our last observation remained within a relatively low altitude threshold throughout the transit. With this, the first-order correction becomes:

With our k value being set to roughly 0.25-0.4, or the average V-band extinction for earth on a clear or dusty night respectively.

Generating the Light Curve

To create our light curve, we took three types of calibration frames along with the light exposures: flat frames (to correct vignetting and dust), dark frames (to subtract hot or cold pixels), and bias frames (to calibrate the sensor). We uploaded the FITS files using the glob package and converted them into 2D NumPy arrays. We subtracted the bias and dark frames from the light exposures and divided by the flat frames to get a clean image of our star. We manually recorded the coordinates of the target and reference stars, then performed aperture photometry by summing pixel values in a given radius and subtracting the background. We calculated the background noise (σ) and SNR for error bars. Finally, we divided the star’s flux by that of the reference star and plotted the result over time to produce our light curve.

Conclusion

Based on our observations and analysis, we found evidence that our candidate star (TIC 348756659) very likely has an exoplanet orbiting around it. The transit depth, shape, and timing we measured are consistent with predictions from TESS data, supporting the classification of the observed object as planet. However, additional observations are necessary to further reduce uncertainties and fully, officially confirm their planetary status according to standard follow-up protocols. Our results demonstrate that ground-based observations with modest equipment can play a valuable role in exoplanet confirmation efforts.

Future Work

While we successfully observed one full transit for our candidate, more observations are needed to reduce statistical uncertainties and strengthen the confirmation of their planetary status before the findings can be reported to the authorities. In future work, we aim to monitor additional transit events to improve our light curve precision and enable more detailed modeling of the exoplanets' orbits and physical properties. We are also aiming to further refine our code and re-evaluate our existing data, looking at all visible bodies in the frame to see if we can aid in the discovery of new objects of interest in the future.

Published Research Poster

References

1. “TESS Project Pipeline.” MIT — https://tev.mit.edu

2. “Leuschner Observatory.” UC Berkeley Department of Astronomy

3. NASA — “How We Find and Characterize Exoplanets” — https://science.nasa.gov/exoplanets/how-we-find-and-characterize/

4. Las Cumbres Observatory — “Transit Method” — https://lco.global/spacebook/exoplanets/transit-method/

5. Kasten, F. & Young, A. T. “Revised Optical Air Mass Tables and Approximation Formula” — https://pubmed.ncbi.nlm.nih.gov/20555942/