Automated Classification of Stellar Spectra: Where Are We Now?

We briefly review the work of the past decade on automated classification of stellar spectra and discuss techniques which show par­ticular promise. Emphasis is placed on Artificial Neural Network and Principle Component Analysis based techniques, due both to our greater familiarity with these and to their rising popularity. As an example of the abilities of current techniques we report on our automated classification work based on the visual classifications of N. Houk (Michigan Spectral Catalogue, Vol. 1 - 4, 1975, 1978, 1982, 1988)

Automated classification of stellar spectra - I. Initial results with artificial neural networks

We have initiated a project to classify stellar spectra automatically from high-dispersion objective prism plates. The automated technique presented here is a simple back propagation neural network and is based on the visual classification work of Houk. The plate material (Houk’s) is currently being digitized, and contains « 105 stars down to K æ 11 at æ 2-Â resolution from « 3850 to 5150 Â. For this first paper in the series, we report on the results of 575 stars digitized from 6 plates. We find that even with the limited data set now in hand we can determine the temperature classification to better than 1.7 spectral subtypes from B3 to M4. Our current sample size provides insufficient training set material to generate luminosity and metallicity classifications. Our eventual aims in this project are (1) to create a large and homogeneous digital stellar spectral library; (2) to create a well-understood and robust automatic classification algorithm which can determine temperatures, luminosities and metallicities for a wide variety of spectral types; (3) to use these data, supplemented by deeper plate material, for the study of Galactic structure and chemical evolution; and (4) to find unusual or new classes of objects

Automated Classification of Stellar Spectra: Where Are We Now?

We briefly review the work of the past decade on automated classification of stellar spectra and discuss techniques which show par­ticular promise. Emphasis is placed on Artificial Neural Network and Principle Component Analysis based techniques, due both to our greater familiarity with these and to their rising popularity. As an example of the abilities of current techniques we report on our automated classification work based on the visual classifications of N. Houk (Michigan Spectral Catalogue, Vol. 1 - 4, 1975, 1978, 1982, 1988)

Penetrators for in situ subsurface investigations of Europa

We present the scientific case for inclusion of penetrators into the Europan surface, and the candidate instruments which could significantly enhance the scientific return of the joint ESA/NASA Europa-Jupiter System Mission (EJSM). Moreover, a surface element would provide an exciting and inspirational mission highlight which would encourage public and political support for the mission. Whilst many of the EJSM science goals can be achieved from the proposed orbital platform, only surface elements can provide key exploration capabilities including direct chemical sampling and associated astrobiological material detection, and sensitive habitability determination. A targeted landing site of upwelled material could provide access to potential biological material originating from deep beneath the ice. Penetrators can also enable more capable geophysical investigations of Europa (and Ganymede) interior body structures, mineralogy, mechanical, magnetic, electrical and thermal properties. They would provide ground truth, not just for the orbital observations of Europa, but could also improve confidence of interpretation of observations of the other Jovian moons. Additionally, penetrators on both Europa and Ganymede, would allow valuable comparison of these worlds, and gather significant information relevant to future landed missions. The advocated low mass penetrators also offer a comparatively low cost method of achieving these important science goals. A payload of two penetrators is proposed to provide redundancy, and improve scientific return, including enhanced networked seismometer performance and diversity of sampled regions. We also describe the associated candidate instruments, penetrator system architecture, and technical challenges for such penetrators, and include their current status and future development plans