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Baltic Astronomy, vol. 14, XXXXXX, 2005.

SPECTRAL ANALYSIS OF sdB-He STARS FROM THE SDSS

A. Ahmad , C. Winter and C. S. Jeffery Armagh Observatory, Col lege Hil l, Armagh BT61 9DG. N. Ireland. Received 2005 July 28 Abstract. We present spectral classification and physical parameters of a sample of "helium-rich" sdB-He stars from spectra obtained from the SDSS archive. The spectral classification was carried out using an automated neural network and the physical parameters were derived using LTE model atmospheres. The results indicate that most of these stars are not typical He-sdB stars but rather are normal sdB stars with slight helium enrichment. This is most likely a result of the use of a different definition of "helium-rich" in the initial SDSS classification to that used more widely in the field. Key words: stars: chemically peculiar - stars: early-type - subdwarfs - stars: fundamental parameters 1. INTRODUCTION Subluminous B stars form the dominant population of faint blue stars in our Galaxy down to a limiting magnitude of B 16. These so-called subdwarf B (sdB) stars are thought to be low-mass core helium burning stars with a thin hydrogen envelope. The surfaces of sdB stars are predominantly helium-deficient due to diffusion and gravitational settling. However, a small number have extremely helium-rich atmospheres. The evolution of these "helium-rich subdwarf B" (HesdB) stars has recently been the sub ject of much debate involving both single and binary star evolution. Only a very small fraction (5%) of sdB stars identified in previous surveys of faint blue stars like the Palomar Green survey (Green et al. 1986) and the Edinburgh Cape survey (Kilkenny et al. 1997) are helium-rich. A small number of stars discovered amongst the many thousand hot subdwarfs in the recent Quasar survey the Sloan Digital Sky Survey (SDSS) have been reported to show strong helium lines and labelled `sdB-He' (Harris et al. 2003). In this study we used an artificial neural network (ANN) to classify spectra of sdB-He stars from the SDSS and to derive fundamental atmospheric parameters. The aim was to determine whether sdB-He stars are similar to He-sdB stars. This would increase the number of known helium-rich subdwarfs for further studies.

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2. DATA MINING Where available, reduced spectra were manually extracted from the SDSS Data Release server using coordinates listed in Harris et al. (2003). The spectra were then normalized using the continuum provided in the fits file. The normalized spectra were then classified and parameterised. It should be noted that the spectra analysed here are moderate resolution (3° and have a typical signal-to-noise A) (S/N ) ratio of 40 3. CLASSIFICATION We have classified the SDSS sdB-He sample onto the MK-like system defined by Drilling et al. (2000). As the hot subdwarfs do not fall within the scope of the original MK system, Drilling et al. (2000) have extended and refined the earlier work of Drilling (1996) and Jeffery et al. (1997) to construct a three-dimensional MK-like classification scale for these stars. This scale is based upon Table 1. Classifications of the SDSS sdB-He a sample of spectra from a sample as determined by the ANN. Error esti- number of sources, covering mates are 2 subtypes for spectral type, 1 sub- the wavelength region 4050 A A. class for luminosity, and 4 subclasses for the 4900° at a resolution of 2.5° It defines a spectral type runhelium class. ning from sdO1 to sdA, analName [SDSS J+] nHe ANN Classification ogous to MK spectral classes, and uses luminosity classes IV VIII, where most hot subdwarfs have a luminosity class VII. A helium class has been introduced, which runs from `He0' to `He40', based on H, HeI, and HeII line strengths. As our intention is to classify large quantities of spectra obtained from digital sky surveys such as the SDSS, we have trained an artificial neural network (ANN) to perform classifications onto the Drilling et al. (2000) scale. The ANN is a feed-forward back propagation network with an input layer of 901 nodes, two hidden layers of 5 nodes each, and an output layer of 3 nodes from which is obtained the spectral type, luminosity class, and helium class values determined by the network. The ANN was trained for 700 iterations on the same set of hot standards used by Drilling et al. (2000), with the spectra having been velocity corrected and resampled onto a uniform wavelength grid of 4050 4950° at a dispersion of of 1° per A A pixel. 09 11 12 12 13 13 13 13 14 14 14 15 15 15 40 38 43 54 17 45 46 57 15 39 45 27 29 42 44.08+00 40.69-00 46.38+00 10.86-01 45.80+01 45.24-00 35.68-00 07.35+01 56.68-00 17.64+01 14.93+00 08.31+00 05.62+00 38.43-00 47 35 25 04 04 06 18 04 58 02 02 33 21 37 59 31 34 08 50 41 04 54 14 51 49 08 37 58 0.16 0.01 0.05 0.01 0.01 0.15 0.09 0.36 0.21 0.01 0.02 0.45 0.06 0.07 sdB0VIII:He23 sdB3V:He1 sdB1V:He23 sdB3III:He5 sdB0VI:He3 sdO9VII:He21 sdA2IV:He0 sdO6VII:He30 sdB8VI:He14 sdB6V:He3 sdB1VII:He11 sdO9VIII:He35 sdO9VII:He10 sdA2III:He2

Spectral analysis of sdB-He stars from the SDSS

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The results of applying the ANN to our sdB-He sample are presented in Table 1. Each spectrum was velocity corrected and resampled onto the same wavelength grid as was used for training the ANN. Error estimates (1 ) for each of the parameters determined by the ANN are 2 subtypes for spectral type, 1 subclass for luminosity, and 4 subclasses for the helium class. The spectra from Ahmad & Jeffery (2003) were also classified with the ANN to check for consistency as these have previously been manually classified by J.S. Drilling. The ANN classification with the the manual classification, within the above errors. 4. SPECTRAL ANALYSIS The physical parameters effective temperature (Teff ), surface gravity (log g ) and helium abundance (nHe ) were measured from the optical blue (4200 5000° spectra (Fig. 1) using A) the latest version of the spectral fitting code SFIT2 and grid of high-gravity LTE models (cf. Ahmad & Jeffery 2003). Note that the blue ends of the SDSS spectra are incorrectly normalized when corrected using the continuum provided by the SDSS therefore the region from 3900 4200° was not considA ered in the model fit. Given the low quality of the SDSS spectra the errors in Teff are ±1 000 K, in log g are ±0.4, and nHe are ±0.05. The sdB-He stars are plotted on the log g - Teff diagram using the derived parameters in Fig. 2. The respective helium abundances are listed in Table 1 as number fraction. From their position on the log g - Teff digram (Fig. 2), half of our sdBHe stars are too luminous to be subdwarfs, the others have a distribution typical of He-sdB stars.

Fig. 1. Optical spectra of sdB-He stars (thick line) along with best fit model. The spectrum of the He-sdB star prototype PG1544+488 is plotted on the top for comparison.

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Fig. 2. Position of sdB-He stars on the log g - T 5. CONCLUSIONS

eff

diagram.

We have classified and parameterised a set of spectra of stars identified as sdB-He in the SDSS. It is clear from both studies that most of these stars show very little helium enrichment. Half of the stars in our sample are too luminous to be subdwarfs. Out of the remaining subdwarfs only a handful are helium-rich (i.e. having nHe 0.10 or He class > 20), again pointing out the need for a homogeneous classification scheme for hot subdwarfs. REFERENCES Ahmad, A., & Jeffery, C. S. 2003, A&A, 402, 335 Drilling, J. S. 1996, in ASP Conf. Ser. 96: Hydrogen Deficient Stars, 461 Drilling, J. S., Moehler, S., Jeffery, C. S., Heber, U., & Napiwotzki, R. 2000, The Kth Reunion, 49 Green, R. F., Schmidt, M., & Liebert, J. 1986, ApJS, 61, 304 Harris, H. C., Liebert, J., Kleinman, S. J. et al. 2003, AJ, 126, 1023 Jeffery, C. S., Drilling, J. S., Harrison, P. M., Heber, U., Moehler, S. 1997, A&AS, 125, 501 Kilkenny, D., O'Donoghue, D., Koen, C., Stobie, R. S., & Chen, A. 1997, MNRAS, 287, 867