Large molecules in the envelope surrounding IRC+10216

A new chemical model of the circumstellar envelope surrounding the carbon-rich star IRC+10216 is developed that includes carbon-containing molecules with up to 23 carbon atoms. The model consists of 3851 reactions involving 407 gas-phase species. Sizeable abundances of a variety of large molecules including carbon clusters, unsaturated hydrocarbons and cyanopolyynes have been calculated. Negative molecular ions of chemical formulae and C _n H (7 n 23) exist in considerable abundance, with peak concentrations at distances from the central star somewhat greater than their neutral counterparts. The negative ions might be detected in radio emission, or even in the optical absorption of background field stars. The calculated radial distributions of the carbon-chain C _n H radicals are looked at carefully and compared with interferometric observations.     

NCCN in TMC-1 and IRC+10216

We employ quantum chemical calculations using the CBS-RAD ('Complete Basis Set – Radicals') technique on the C₂N₂H potential energy surface to show that the reaction of HNC with CN is a viable and plausible route to NCCN in cold astrophysical environments. We use detailed chemical kinetic models to predict the abundance of NCCN in TMC-1 and IRC+10216. Radio-astronomical detection of NCCN is precluded by its lack of a dipole moment. We discuss other prospects for its observation in interstellar and circumstellar environments, by space-borne infrared spectroscopy, indirectly by detection of the NCCNH⁺ ion, or inferentially by detection of its higher-energy, polar isomer CNCN.     

Sinusoidal variables from the Tycho Epoch Photometry Annex

The Tycho Epoch Photometry Annex A, a data base of photometry of more than 34 000 bright stars, has been searched for periodic variable stars with approximately sinusoidal light curves. Advantage was taken of special properties of the observing programme (photometry in two wavebands, availability of repeated measurements) to use simple but efficient variable selection criteria. Details of 70 strong candidate variables are presented.     

Sulphur-bearing carbon chains in IRC+10216

We have updated the chemical model of IRC+10216 developed by Millar, Herbst & Bettens to include recent routes to the formation of sulphuretted hydrocarbons. The routes are based on a quantum chemical study of the S+C₂H system. In addition, we have altered the parent species for sulphur to reflect new observational results. We find that the model calculations give excellent agreement with the observed column densities, and discuss the significance of these reactions to the formation of species as yet unobserved and to dark interstellar clouds.     

A model of diffuse Galactic radio emission from 10 MHz to 100 GHz

Understanding diffuse Galactic radio emission is interesting both in its own right and for minimizing foreground contamination of cosmological measurements. cosmic microwave background experiments have focused on frequencies ≳10 GHz, whereas 21-cm tomography of the high-redshift universe will mainly focus on ≲0.2 GHz, for which less is currently known about Galactic emission. Motivated by this, we present a global sky model derived from all publicly available total power large-area radio surveys, digitized with optical character recognition when necessary and compiled into a uniform format, as well as the new Villa Elisa data extending the 1.42-GHz map to the entire sky. We quantify statistical and systematic uncertainties in these surveys by comparing them with various global multifrequency model fits. We find that a principal component based model with only three components can fit the 11 most accurate data sets (at 10, 22, 45 and 408 MHz and 1.42, 2.326, 23, 33, 41, 61, 94 GHz) to an accuracy around 1–10 per cent depending on frequency and sky region. Both our data compilation and our software returning a predicted all-sky map at any frequency from 10 MHz to 100 GHz are publicly available at http://space.mit.edu/home/angelica/gsm .     

Automated classification of variable stars for All-Sky Automated Survey 1–2 data

With the advent of surveys generating multi-epoch photometry and the discovery of large numbers of variable stars, the classification of these stars has to be automatic. We have developed such a classification procedure for about 1700 stars from the variable star catalogue of the All-Sky Automated Survey 1–2 (ASAS 1–2) by selecting the periodic stars and by applying an unsupervised Bayesian classifier using parameters obtained through a Fourier decomposition of the light curve. For irregular light curves we used the period and moments of the magnitude distribution for the classification. In the case of ASAS 1–2, 83 per cent of variable objects are red giants. A general relation between the period and amplitude is found for a large fraction of those stars. The selection led to 302 periodic and 1429 semiperiodic stars, which are classified in six major groups: eclipsing binaries, 'sinusoidal curves', Cepheids, small amplitude red variables, SR and Mira stars. The type classification error level is estimated to be about 7 per cent.     

Observations of flat-spectrum radio sources at λ850 μm from the James Clerk Maxwell Telescope – I. 1997 April to 2000 April

Calibrated data for 65 flat-spectrum extragalactic radio sources are presented at a wavelength of 850 μm, covering a three-year period from 1997 April. The data, obtained from the James Clerk Maxwell Telescope using the SCUBA camera in pointing mode, were analysed using an automated pipeline process based on the Observatory Reduction and Acquisition Control–Data Reduction ( orac–dr ) system. This paper describes the techniques used to analyse and calibrate the data, and presents the data base of results along with a representative sample of the better-sampled light curves.     

Finding outlier light curves in catalogues of periodic variable stars

We present a methodology to discover outliers in catalogues of periodic light curves. We use a cross-correlation as the measure of 'similarity' between two individual light curves, and then classify light curves with lowest average 'similarity' as outliers. We performed the analysis on catalogues of periodic variable stars of known type from the MACHO and OGLE projects. This analysis was carried out in Fourier space and we established that our method correctly identifies light curves that do not belong to those catalogues as outliers. We show how an approximation to this method, carried out in real space, can scale to large data sets that will be available in the near future such as those anticipated from the Panoramic Survey Telescope & Rapid Response System (Pan-STARRS) and Large Synoptic Survey Telescope (LSST).