Individual stars in the Local Group

The stellar chemical abundances of the various galactic components (disk, bulge, halo, globular clusters) in galaxies of diverse masses and morphologies provide crucial information against which to test theories of galaxy formation and evolution (e.g. Helmi et al. 2006). Chemical abundances of evolved and metal-rich stars are extremely difficult, if not impossible, to investigate in the optical bands, due to the severe molecular blanketing and blending of the absorption features. Instead, the near-IR spectra of evolved stars (red giants and supergiants) display a wealth of prominent absorption features that are sensitive indicators of the abundances of key elements such as iron, carbon, and oxygen, as well as of various other a-elements such as calcium, magnesium, silicon, and titanium (Larsen et al. 2006; Rich et al. 2005; Origlia etal. 1997,1999,2006). At the maximum spectral resolution achieved by JWST with the NIRSpec (R ~ 2,700), many of these absorption features

Teff = 3,600 K, log g = 0.5, % = 2 km s-1, [M/H] = 0.0

Teff = 3,600 K, log g = 0.5, % = 2 km s-1, [M/H] = 0.0

1.0 0.8 0.6 0.4

rf^x

- V it 'ir

(r tf. it if

- Fe ii

ll

Mg

Mg

l

----[M/H] = +0.5 -

~ i i . .

F

| [M/H] = -0.5 J

1.180

1.190 1.200

Wavelength (|m)

1.210

1.180

1.190 1.200

Wavelength (|m)

1.210

Figure 23.2. A model of the near-IR spectrum for a red giant star with Teff = 3600 K and Solar abundances, smoothed to the maximum spectral resolution of NIRSpec. The effect of varying the abundances by ±0.5 dex is also shown.

are clearly separated and can be used to determine metallicities and relative elemental abundances. This is illustrated in Figure 23.2, where the model of the near-IR spectrum of a typical red giant star is convolved with the maximum spectral resolution achieved by NIRSpec. The same figure also shows the depth variation of the various stellar features on changing the abundances of all elements by ±0.5 dex. With such a spectral resolution, the elemental abundances can be inferred with an accuracy of ±0.2 dex, provided that the signal-to-noise ratio is high enough (>20). Thanks to the high sensitivity achieved by JWST with NIRSpec, it will be possible to derive detailed metallicities and abundance patterns for individual stars in all galaxies within the Local Group. As an example, a giant star near the tip of the red giant branch (RGB) at the distance of M31 has an apparent magnitude of KAB = 22; in this case NIRSpec will achieve a signal-to-noise ratio of 20 per resolution element in only two hours of integration at R ~ 2,700. With the micro-shutter array (MSA) it will be possible to obtain simultaneously spectra of about 100 stars in the bulge/disk/halo of M31; with the IFU it will be possible to obtain spectra of all giant stars in any globular cluster (GC) of M31, except possibly for their innermost region, where stellar crowding will deliver only integrated information of the GC cores (note that the IFU field of view is nicely matched to the size of GCs at the distance of M31).

NIRCam will be able to trace global metallicities of large numbers of stars by determining the location (and in particular the slope) of the RGB on the magnitude-color diagram MK versus J - K. Indeed, the slope of the RGB ridge on this diagram correlates tightly with the stellar metallicity (Valenti et al. 2004, 2005). An accurate determination of its slope requires the RGB to be sampled at or below, the horizontal branch (i.e. stars with MK ~ -3). In principle the sensitivity achieved by the NIRCam would allow us to measure the RGB slope even at the distance of the Virgo cluster. However, the angular resolution of JWST will allow us to resolve individual stars only in galaxies within the Local Group. At the distance of M31, only a few minutes of integration will be required to measure the RGB slope in a single exposure, with an unprecedented photometric accuracy. Therefore, NIRCam will be able to survey large stellar fields in several galaxies within the Local Group, identifying RGB slopes for several thousand stars, thus identifying metallicity variations from object to object and gradients within individual systems.

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