We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the solar system, exploring the transient optical sky, and mapping the Milky Way. LSST will be a large, wide-field ground-based system designed to obtain repeated images covering the sky visible from Cerro Pachón in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg 2 field of view, a 3.2-gigapixel camera, and six filters (ugrizy) covering the wavelength range 320-1050 nm. The project is in the construction phase and will begin regular survey operations by 2022. About 90% of the observing time will be devoted to a deep-wide-fast survey mode that will uniformly observe a 18,000 deg 2 region about 800 times (summed over all six bands) during the anticipated 10 yr of operations and will yield a co-added map to r∼27.5. These data will result in databases including about 32 trillion observations of 20 billion galaxies and a similar number of stars, and they will serve the majority of the primary science programs. The remaining 10% of the observing time will be allocated to special projects such as Very Deep and Very Fast time domain surveys, whose details are currently under discussion. We illustrate how the LSST science drivers led to these choices of system parameters, and we describe the expected data products and their characteristics.

Analysis of emission lines in gaseous nebulae yields direct measures of physical conditions and chemical abundances and is the cornerstone of nebular astrophysics. Although the physical problem is conceptually simple, its practical complexity can be overwhelming since the amount of data to be analyzed steadily increases; furthermore, results depend crucially on the input atomic data, whose determination also improves each year. To address these challenges we created PyNeb, an innovative code for analyzing emission lines. PyNeb computes physical conditions and ionic and elemental abundances and produces both theoretical and observational diagnostic plots. It is designed to be portable, modular, and largely customizable in aspects such as the atomic data used, the format of the observational data to be analyzed, and the graphical output. It gives full access to the intermediate quantities of the calculation, making it possible to write scripts tailored to the specific type of analysis one wants to carry out. In the case of collisionally excited lines, PyNeb works by solving the equilibrium equations for an n-level atom; in the case of recombination lines, it works by interpolation in emissivity tables. The code offers a choice of extinction laws and ionization correction factors, which can be complemented by user-provided recipes. It is entirely written in the python programming language and uses standard python libraries. It is fully vectorized, making it apt for analyzing huge amounts of data. The code is stable and has been benchmarked against IRAF/NEBULAR. It is public, fully documented, and has already been satisfactorily used in a number of published papers.

A set of software tools has been developed for the IRAF/STSDAS environment to derive the physical conditions in a low-density (nebular) gas given appropriate diagnostic emission line ratios; and line emissivities given appropriate emission line uxes, the electron temperature (T e) and density (N e). The package is based on the ve-level atom program developed by De Robertis, Dufour and Hunt (1987), but it includes diagnostics from a greater set of ions and emission lines, most particularly those in the satellite ultraviolet that are now observable. Two of the applications make use of a 3-zone nebular model to derive T e and N e simultaneously in separate zones of low-, intermediate-, and high-ionization. These applications are useful for calculating nebular densities and temperatures directly from the traditional diagnostic line ratios, either to provide some reasonable input parameters for a more complicated physical model, or to calculate ionic abundances (or other quantities) within some simplifying assumptions. Examples of the utility of these diagnostics for real nebulae are presented.

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Hydrogen depleted environments are considered an essential requirement for the formation of fullerenes. The recent detection of C 60 and C 70 fullerenes in what was interpreted as the hydrogen-poor inner region of a post-final helium shell flash Planetary Nebula (PN) seemed to confirm this picture. Here, we present evidence that challenges the current paradigm regarding fullerene formation, showing that it can take place in circumstellar environments containing hydrogen. We report the simultaneous detection of Polycyclic Aromatic Hydrocarbons (PAHs) and fullerenes towards C-rich and H-containing PNe belonging to environments with very different chemical histories such as our own Galaxy and the Small Magellanic Cloud. We suggest that PAHs and fullerenes may be formed by the photochemical processing of hydrogenated amorphous carbon. These observations suggest that modifications may be needed to our current understanding of the chemistry of large organic molecules as well as the chemical processing in space.