Highlights - Volume 495-3 (March I 2009)

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HIGHLIGHTS: this week in A&A

Volume 495-3 (March I 2009)


In section 6. Interstellar and circumstellar matter

“Models of turbulent dissipation regions in the diffuse interstellar medium”, by B. Godard, E. Falgarone, and G. Pineau des Forêts, A&A 495, p. 847

The authors demonstrate that intermittent structures in the form of magnetized vortices produce detectable chemical signatures on scales of about 100 AU in turbulent molecular clouds flows. Using detailed chemical models, they find that neutral-ion friction to be the principal mechanism in these dissipative regions. The paper provides evidence that spectroscopic diagnostics are available to study the energetics of the smallest scales in turbulent shear flows in interstellar environments. 


In section 1. Letters

“Pluto's lower atmosphere structure and methane abundance from high-resolution spectroscopy and stellar occultations”, by E. Lellouch, B. Sicardy, C. de Bergh, H.-U. Kaufl, S. Kassi, and A. Campargue, A&A 495, p. L17

Although it has been demoted from the planet rank recently, Pluto is definitely an interesting object, one with an atmosphere that has been shown to vary in mass by a factor two as a result of seasonal variations. In this issue, E. Lellouch et al. determine precisely for the first time the present abundance of methane in its atmosphere with both high-resolution spectroscopic observations and occultation light-curves. Surprisingly, methane which condenses in the low-temperature atmosphere appears to be very significantly supersaturated, a sign that the atmosphere is very clean and devoid of condensation nuclei. The observations are useful to understand the seasonal evolution of Pluto's atmosphere.

In section 13. Astronomical instrumentation

“Maximum-likelihood detection of sources among Poissonian noise”, by I.M. Stewart, A&A 495, p. 989

Present X-ray observatories operate in a relatively low-exposure regime and exhibit Poissonian noise at background flux levels. The author examines a maximum likelihood (ML) technique for detecting compact sources in such datasets, and uses Monte Carlo simulations to show that ML compares favorably with a variety of source detection methods and that it also has several practical advantages. This paper provides a common and optimal framework for the data analysis community, in a presentation style that balances mathematical rigor with common sense.


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© Astronomy & Astrophysics 2009