We present Spitzer 10-34 $\mu{\rm m}$ spectroscopic observations of the diffuse gas in the inner region of the star-forming region IC 348 of the Perseus Molecular Cloud. We find evidence for the strongest mid-IR bands of common molecules as H 2, OH, H 2O, CO 2, and NH 3 and of several carbonaceous molecules which may play an important role in the

Stellar spectral classification has been highly useful in the study of stars. While there is a currently accepted spectral classification system for carbon stars, the subset of hydrogen-deficient carbon (HdC) stars has not been well described by such a system, due predominantly to their rarity and their variability. Here we present the first system

In the last decade, growing evidence has emerged supporting a non-universal stellar initial mass function (IMF) in massive galaxies, with a larger number of dwarf stars with respect to the Milky Way (bottom-heavy IMF). However, a consensus about the mechanisms that cause IMF variations is yet to be reached. Recently, it has been suggested that

Wide-field time-domain photometric sky surveys are now finding hundreds of eclipsing white dwarf plus M dwarf binaries, a population encompassing a wealth of information and potential insight into white dwarf and close binary astrophysics. Precise follow-up observations are essential in order to fully constrain these systems and capitalize on the

Many binary companions to the central stars of planetary nebulae (PNe) are found to be inflated, perhaps indicating that accretion onto the central star might occur during the planetary nebula (PN) phase. The discovery of a handful of nova eruptions and supersoft X-ray sources inside PNe supports this hypothesis. In this paper, we investigate the

Recent cosmological analyses rely on the ability to accurately sample from high-dimensional posterior distributions. A variety of algorithms have been applied in the field, but justification of the particular sampler choice and settings is often lacking. Here, we investigate three such samplers to motivate and validate the algorithm and settings