High-resolution Keck I spectroscopy of Galactic halo post-asymptotic giant branch stars

Absolute and differential abundance analyses have been performed from high-resolution, high signal-to-noise ratio optical (Keck I) spectra for three evolved Galactic halo stars, namely PG 1704 + 222, HD 341617 and LSIV -0401. Their derived atmospheric parameters indicate that all three objects are undergoing a post-asymptotic giant branch (post-AGB) phase of evolution. A differential abundance analysis reveals HD 341617 as having a mild carbon deficiency of 0.74 dex, possibly due to the star having evolved off the AGB before the onset of the third dredge-up. Although such carbon underabundances are typical of hot post-AGB objects, the same trend is not observed in PG 1704 + 222, where the carbon abundance is found to be consistent with those derived for nitrogen and oxygen. Hence, a dredge-up scenario need not be invoked to explain the chemical composition of PG 1704 + 222. For LSIV -0401 no iron deficiency is apparent relative to magnesium and silicon, and hence a gas- dust separation event in the AGB progenitor need not be invoked for this star.

High-resolution spectroscopic observations of post-asymptotic giant branch candidates from the Edinburgh-Cape Survey

High spectral resolution ( R similar to 40 000) and signal-to-noise optical spectra, obtained at the Very Large Telescope ( VLT), are presented for three post-asymptotic giant branch ( AGB) candidates selected from the Edinburgh-Cape ( EC) Faint Blue Object Survey. The stellar atmospheric parameters and chemical compositions, derived using sophisticated non-local thermodynamic equilibrium calculations, reveal that EC 14102-1337 and EC 20068-7324 are both in an evolved post-horizontal branch ( HB) evolutionary state. However, EC 11507-2253 is most likely a post-AGB star.

High-resolution spectroscopy of globular cluster post-Asymptotic Giant Branch stars

We present model atmosphere analyses of high resolution Keck and VLT optical spectra for three evolved stars in globular clusters, viz. ZNG-1 in M 10, ZNG-1 in M 15 and ZNG-1 in NGC 6712. The derived atmospheric parameters and chemical compositions confirm the programme stars to be in the post- Asymptotic Giant Branch (post-AGB) evolutionary phase. Differential abundance analyses reveal CNO abundance patterns in M 10 ZNG-1, and possibly M 15 ZNG-1, which Suggest that both objects may have evolved off the AGB before the third dredge-up occurred. The abundance pattern of these stars is similar to the third class of optically, bright post-AGB objects discussed by van Winckel (1997). Furthermore, M 10 ZNG-1 exhibits a large C underabundance (with Delta[C/O] similar to -1.6 dex), typical of other hot post-AGB objects. Differential Delta[alpha/Fe] abundance ratios in both M 10 ZNG-1 and NGC 6712 ZNG-1 are found to be approximately 0.0 dex, with the Fe abundance of the former being in disagreement with the cluster metallicity of M 10. Given that the Fe absorption features in both M 10 ZNG-1 and NGC6712 ZNG-1 are well observed and reliably modelled, we believe that these differential Fe abundance estimates to be secure. However, our Fe abundance is difficult to explain in terms of previous evolutionary processes that Occur oil both the Horizontal Branch and the AGB.

Iron abundances of B-type post-asymptotic giant branch stars in globular clusters: Barnard29 in M13 and ROA5701 in ωCen

High-resolution optical and ultraviolet (UV) spectra of two B-type post-asymptotic giant branch (post-AGB) stars in globular clusters, Barnard29 in M13 and ROA5701 in ?Cen, have been analysed using model atmosphere techniques. The optical spectra have been obtained with FEROS on the ESO 2.2-m telescope and the 2d-Coudé spectrograph on the 2.7-m McDonald telescope, while the UV observations are from the Goddard high-resolution spectrograph on the Hubble Space Telescope (HST). Abundances of light elements (C, N, O, Mg, Al and S) plus Fe have been determined from the optical spectra, while the UV data provide additional Fe abundance estimates from FeIII absorption lines in the 1875-1900 Å wavelength region. A general metal underabundance relative to young B-type stars is found for both Barnard29 and ROA5701. These results are consistent with the metallicities of the respective clusters, as well as with previous studies of the objects. The derived abundance patterns suggest that the stars have not undergone a gas-dust separation, contrary to previous suggestions, although they may have evolved from the AGB before the onset of the third dredge-up. However, the Fe abundances derived from the HST spectra are lower than those expected from the metallicities of the respective clusters, by 0.5 dex for Barnard29 and 0.8 dex for ROA5701. A similar systematic underabundance is also found for other B-type stars in environments of known metallicity, such as the Magellanic Clouds. These results indicate that the FeIII UV lines may yield abundance values which are systematically too low by typically 0.6 dex and hence such estimates should be treated with caution.

Chemistry in anisotropic asymptotic giant branch winds

We have constructed a model for chemistry in the outflow of an asymptotic giant branch (AGB) star, using a spheroidal anisotropy in density, after that used by Jura. The predicted distributions of a selection of representative species are shown, and it is suggested that the abundance distributions observed by interferometry in IRC + 10216 may be the result of directional variation in outflow velocity.

Ruling out a massive asymptotic giant-branch star as the progenitor of supernova 2005cs

We calculate the predicted UBVRIJHK absolute magnitudes for models of supernova progenitors and apply the result to the case of supernova 2005cs. We agree with previous results that the initial mass of the star was low, around 6 to 8 M-circle dot. However, such stars are thought to go through a second dredge-up to become asymptotic giant branch (AGB) stars. We show that had this occurred to the progenitor of 2005cs it would have been observed in JHK pre-explosion images. The progenitor was not detected in these bands and therefore we conclude that it was not an AGB star. Furthermore, if some AGB stars do produce supernovae they will have a clear signature in pre-explosion near-infrared images. Electron-capture supernovae are thought to occur in AGB stars, hence the implication is that 2005cs was not an electron-capture supernova but was the collapse of an iron core.

Behavior-Based branch prediction by dynamically clustering branch instructions

Conditional branches frequently exhibit similar behavior (bias, time-varying behavior,...), a property that can be used to improve branch prediction accuracy. Branch clustering constructs groups or clusters of branches with similar behavior and applies different branch prediction techniques to each branch cluster. We revisit the topic of branch clustering with the aim of generalizing branch clustering. We investigate several methods to measure cluster information, with the most effective the storage of information in the branch target buffer. Also, we investigate alternative methods of using the branch cluster identification in the branch predictor. By these improvements we arrive at a branch clustering technique that obtains higher accuracy than previous approaches presented in the literature for the gshare predictor. Furthermore, we evaluate our branch clustering technique in a wide range of predictors to show the general applicability of the method. Branch clustering improves the accuracy of the local history (PAg) predictor, the path-based perceptron and the PPM-like predictor, one of the 2004 CBP finalists.

Clustered indexing for branch predictors

As a result of resource limitations, state in branch predictors is frequently shared between uncorrelated branches. This interference can significantly limit prediction accuracy. In current predictor designs, the branches sharing prediction information are determined by their branch addresses and thus branch groups are arbitrarily chosen during compilation. This feasibility study explores a more analytic and systematic approach to classify branches into clusters with similar behavioral characteristics. We present several ways to incorporate this cluster information as an additional information source in branch predictors.