We present new moderate-resolution near-infrared spectroscopy of three CVs obtained using GNIRS on Gemini-North. These spectra covered three 13CO bandheads found in the K-band, allowing us to derive the isotopic abundance ratios for carbon. We find small 12C/13C ratios for all three donor stars. In addition, these three objects show carbon deficits, with AE Aqr being the most extreme ([C/Fe] = −1.4). This result confirms the conjecture that the donor stars in some long-period CVs have undergone considerable nuclear evolution prior to becoming semi-contact binaries. In addition to the results for carbon, we find that the abundance of sodium is enhanced in these three objects, and the secondary stars in both RU Peg and SS Cyg suffer magnesium deficits. Explaining such anomalies appears to require higher mass progenitors than commonly assumed for the donor stars of CVs.

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We use adaptive mesh refinement cosmological simulations to study the spatial distribution and covering fraction of absorption in the circumgalactic medium (CGM) as a function of projected virial radius and azimuthal angle. We compare these simulations to an observed sample of 53 galaxies from the Multiphase Galaxy Halos Survey. Using Mockspec, an absorption-line analysis pipeline, we generate synthetic quasar absorption-line observations of the simulated CGM. To best emulate observations, we studied the averaged properties of 15,000 “mock samples,” each of 53 sight lines having a distribution of and sight-line orientation statistically consistent with the observations. We find that the covering fraction obtained for the simulated galaxies agrees well with the observed value for the inner halo ( ) and is within 1.1σ in the outer halo ( ), but is underproduced within . The observed bimodal distribution of the covering fraction with azimuthal angle, showing a higher frequency of absorption along the projected major and minor axes of galaxies, is not reproduced in the simulations. Further analysis reveals the spatial-kinematic distribution of -absorbing gas is dominated by outflows in the inner halo mixed with an inflowing gas that originates from farther out in the halo. Though the CGM of the individual simulated galaxies exhibits spatial structure, the flat azimuthal distribution occurs because the individual simulated galaxies do not develop a CGM structure that is universal from galaxy to galaxy.

A key assumption in quasar absorption line studies of the circumgalactic medium (CGM) is that each absorption component maps to a spatially isolated "cloud" structure that has single valued properties (e.g. density, temperature, metallicity). We aim to assess and quantify the degree of accuracy underlying this assumption. We used adaptive mesh refinement hydrodynamic cosmological simulations of two 𝑧 = 1 dwarf galaxies and generated synthetic quasar absorption-line spectra of their CGM. For the Si 𝜆1260 transition, and the C 𝜆𝜆1548, 1550 and O 𝜆𝜆1031, 1037 fine-structure doublets, we objectively determined which gas cells along a line-of-sight (LOS) contribute to detected absorption. We implemented a fast, efficient, and objective method to define individual absorption components in each absorption profile. For each absorption component, we quantified the spatial distribution of the absorbing gas. We studied a total of 1,302 absorption systems containing a total of 7,755 absorption components. 48% of Si , 68% of C , and 72% of O absorption components arise from two or more spatially isolated "cloud" structures along the LOS. Spatially isolated "cloud" structures were most likely to have cloud-cloud LOS separations of 0.03𝑅 𝑣𝑖𝑟 , 0.11𝑅 𝑣𝑖𝑟 , and 0.13𝑅 𝑣𝑖𝑟 for Si , C , and O , respectively. There can be very little overlap between multi-phase gas structures giving rise to absorption components. If our results reflect the underlying reality of how absorption lines record CGM gas, they place tension on current observational analysis methods as they suggest that component-by-component absorption line formation is more complex than is assumed and applied for chemical-ionisation modelling.