With my students Jerrick Wee, Nilotpal Chakraborty, and Jiayun Wang, all amazing Yale-NUS students who took my general observational astronomy course, we wrote an Astrophysical Journal paper which appeared in 2019. Jerrick was the primary author, and it was a study of the nearby supernova 2017cbv which occurred in the galaxy NGC 5643. A study of this sort, made possible by the Yale 1-meter telescope and ANDICAM camera, which enabled us to derive the brightness profile for the Type Ia supernova in its early stages. We also were able to provide a valuable example of how smaller telescopes that can respond quickly to time-variable astrophysics events can contribute significantly to astronomy.

Our team was able to derive early-time optical and infrared photometry covering the rise and fall of the supernova over 68 days. Key findings include a broad light curve with a decline rate parameter ∆m15(B) = 0.88, negligible host galaxy reddening, and a distance modulus of 30.49, corresponding to a distance of approximately 12.58 Mpc. The study utilized two numerical models, SALT2 and SNooPy, for analyzing the light curves and determining the supernova’s properties. The photometric data and model analysis contribute to understanding the intrinsic properties and distances of Type Ia supernovae, which are crucial for cosmological distance measurements and the precision of the Hubble constant.

Our paper is significant for several reasons, which are described below:

1. Refinement of Cosmological Distance Measurements: The precise photometric data and distance modulus calculation for SN 2017cbv enhance the accuracy of Type Ia supernovae as “standard candles.” This improvement is vital for cosmological studies that rely on these objects to measure vast cosmic distances and refine the Hubble constant, which describes the rate of expansion of the universe. Accurate distance measurements are crucial for developing a more precise cosmological model and understanding the universe’s expansion history.
2. Insights into Supernova Mechanics: The detailed light curves, especially the broad light curve with a secondary maximum in the near-infrared, provide critical data on the physical processes governing Type Ia supernovae explosions. By comparing these observations with theoretical models, such as SALT2 and SNooPy, the study contributes to a better understanding of the progenitor systems, explosion mechanisms, and the role of different channels (e.g., single-degenerate and double-degenerate scenarios) in Type Ia supernovae formation.
3. Improvement in Photometric Techniques: The paper demonstrates the effectiveness of combining optical and near-infrared photometry to reduce uncertainties in extinction calculations. This approach helps to account for dust extinction more accurately, which is a significant source of error in supernova observations. Improved photometric techniques directly enhance the reliability of supernova measurements, benefiting a wide range of astrophysical research areas that depend on precise luminosity and distance estimates.
4. Contribution to Low-Redshift Supernova Data: By providing detailed observations of a nearby (low-z) supernova, this study fills a gap in the existing supernova data, which is often dominated by high-redshift (high-z) events. Low-redshift supernovae are crucial for anchoring the cosmic distance ladder and calibrating the absolute magnitudes of supernovae used in high-redshift cosmological studies. This calibration is essential for minimizing systematic errors in determining cosmological parameters.
5. Cross-Validation with Other Distance Indicators: The accurate distance measurement to SN 2017cbv allows for cross-validation with other independent distance indicators, such as Cepheid variables and the Tip of the Red Giant Branch (TRGB) method. Such cross-checks are essential for ensuring consistency across different methods and improving the robustness of the overall distance scale.

(note: This summary was developed with assistance from ChatGPT 4o).