Recently, Nicholls et al., inspired by in situ observations of solar system astrophysical plasmas, suggested that the electrons in H ii regions are characterized by a κ-distribution of energies rather than a simple Maxwell-Boltzmann distribution. Here, we have collected together new atomic data within a modified photoionization code to explore the effects of both the new atomic data and the κ-distribution on the strong-line techniques used to determine chemical abundances in H ii regions. By comparing the recombination temperatures (T rec ) with the forbidden line temperatures (T FL ), we conclude that κ ∼ 20. While representing only a mild deviation from equilibrium, this result is sufficient to strongly influence abundances determined using methods that depend on measurements of the electron temperature from forbidden lines. We present a number of new emission line ratio diagnostics that cleanly separate the two parameters determining the optical spectrum of H ii regions-the ionization parameter q or U and the chemical abundance, 12+log(O/H). An automated code to extract these parameters is presented. Using the homogeneous data set from van Zee et al., we find self-consistent results between all of these different diagnostics. The systematic errors between different line ratio diagnostics are much smaller than those found in the earlier strong-line work. Overall, the effect of the κ-distribution on the strong-line abundances derived solely on the basis of theoretical models is rather small.

We present a new method for inferring the metallicity (Z) and ionization parameter (q) of HII regions and star-forming galaxies using strong nebular emission lines (SEL). We use Bayesian inference to derive the joint and marginalized posterior probability density functions for Z and q given a set of observed line fluxes and an input photo-ionization model. Our approach allows the use of arbitrary sets of SELs and the inclusion of flux upper limits. The method provides a self-consistent way of determining the physical conditions of ionized nebulae that is not tied to the arbitrary choice of a particular SEL diagnostic and uses all the available information. Unlike theoretically calibrated SEL diagnostics the method is flexible and not tied to a particular photo-ionization model. We describe our algorithm, validate it against other methods, and present a tool that implements it called IZI. Using a sample of nearby extra-galactic HII regions we assess the performance of commonly used SEL abundance diagnostics. We also use a sample of 22 local HII regions having both direct and recombination line (RL) oxygen abundance measurements in the literature to study discrepancies in the abundance scale between different methods. We find that oxygen abundances derived through Bayesian inference using currently available photo-ionization models in the literature can be in good (∼30%) agreement with RL abundances, although some models perform significantly better than others. We also confirm that abundances measured using the direct method are typically ∼ 0.2 dex lower than both RL and photo-ionization model based abundances.

We present PyWiFeS, a new Python-based data reduction pipeline for the Wide Field Spectrograph (WiFeS). PyWiFeS consists of a series of core data processing routines built on standard scientific Python packages commonly used in astronomical applications. Included in PyWiFeS is an implementation of a new global optical model of the spectrograph which provides wavelengths solutions accurate to ∼0.05Å (RMS) across the entire detector. The core PyWiFeS package is designed to be scriptable to enable batch processing of large quantities of data, and we present a default format for handling of observation metadata and scripting of data reduction.

We demonstrate the long-distance transmission of an ultrastable optical frequency derived directly from a state-of-the-art optical frequency standard. Using an active stabilization system we deliver the frequency via a 146-km-long underground fiber link with a fractional instability of 3 x 10(-15) at 1 s, which is close to the theoretical limit for our transfer experiment. After 30,000 s, the relative uncertainty for the transfer is at the level of 1 x 10(-19). Tests with a very short fiber show that noise in our stabilization system contributes fluctuations that are 2 orders of magnitude lower, namely, 3 x 10(-17) at 1 s, reaching 10(-20) after 4,000 s.

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