We constrained the progenitor masses for 169 supernova remnants (SNRs), eight historically observed supernovae (SNe), and the black hole formation candidate in NGC 6946, finding that they are consistent with originating from a standard initial mass function. Additionally, there were 16 remnants that showed no sign of nearby star formation consistent with a core-collapse SN, making them good Type Ia candidates. Using Hubble Space Telescope broadband imaging, we measured the stellar photometry of ACS/WFC fields in the F435W, F555W, F606W, and F814W filters, as well as WFC3/UVIS fields in F438W, F606W, and F814W. We then fitted this photometry with stellar evolutionary models to determine the ages of the young populations present at the positions of the SNRs and SNe. We then inferred a progenitor mass probability distribution from the fitted age distribution. For 37 SNRs, we tested how different filter combinations affected the inferred masses. We find that filters sensitive to Hα, [N ii], and [S ii] gas emission can bias mass estimates for remnants that rely on our technique. Using a Kolmogorov–Smirnov test analysis on our most reliable measurements, we find that the progenitor mass distribution is well matched by a power-law index of − 2.6 − 0.6 + 0.5 , which is consistent with a standard initial mass function.

Using a filter in the GROWTH Marshal based on color and the amplitude and timescale of variability, we have identified 372 objects as known or candidate cataclysmic variables (CVs) during the second year of the operation of the Zwicky Transient Facility. From the available difference imaging data, we found that 93 are previously confirmed CVs and 279 are strong candidates. Spectra of four of the candidates confirm them as CVs by the presence of Balmer emission lines, while one of the four has prominent He II lines indicative of containing a magnetic white dwarf. Gaia EDR3 parallaxes are available for 154 of these systems, resulting in distances from 108-2096 pc and absolute magnitudes in the range of 7.5-15.0, with the largest number of candidates between 10.5 and 12.5. The total numbers are 21% higher than from the previous year of the survey with a greater number of distances available but a smaller percentage of systems close to the Galactic plane. Comparison of these findings with a machine-learning method of searching all the light curves reveals large differences in each data set related to the parameters involved in the search process.

Using resolved optical stellar photometry from the Panchromatic Hubble Andromeda Treasury Triangulum Extended Region survey, we measured the star formation history near the position of 85 supernova remnants (SNRs) in M33. We constrained the progenitor masses for 60 of these SNRs, finding that the remaining 25 remnants had no local star formation in the last 56 Myr, consistent with core-collapse supernovae, making them potential Type Ia candidates. We then infer a progenitor mass distribution from the age distribution, assuming single star evolution. We find that the progenitor mass distribution is consistent with being drawn from a power law with an index of − 2.9 − 1.0 + 1.2 . Additionally, we infer a minimum progenitor mass of 7.1 − 0.2 + 0.1 M ⊙ from this sample, consistent with several previous studies, providing further evidence that stars with ages older than the lifetimes of single 8 M ⊙ stars are producing supernovae.

We have combined resolved stellar photometry from Hubble Space Telescope (HST), Spitzer, and Gaia to identify red supergiant (RSG) candidates in NGC 6946, based on their colors, proper motions, visual morphologies, and spectral energy distributions. We start with a large sample of 17,865 RSG candidates based solely on HST near-infrared photometry. We then chose a small sample of 385 of these candidates with Spitzer matches for a more detailed study. Using evolutionary models and isochrones, we isolate a space where RSGs would be found in our photometry catalogs. We then visually inspect each candidate and compare them to Gaia catalogs to identify and remove foreground stars. As a result, we classify 95 potential RSGs, with 40 of these being in our highest-quality sample. We fit the photometry of the populations of stars in the regions surrounding the RSGs to infer their ages. Placing our best candidate RSG stars into three age bins between 1 and 30 Myr, we find 27.5% of the candidates falling between 1–10 Myr, 37.5% between 10–20 Myr, and 35% between 20–30 Myr. A comparison of our results to the models of massive star evolution shows some agreement between model luminosities and the luminosities of our candidates for each age. Three of our candidates appear significantly more consistent with binary models than single-star evolution models.