Deriving photospheric parameters and elemental abundances for a sample of stars showing the FIP effect
aa r X i v : . [ a s t r o - ph . S R ] J un Contrib. Astron. Obs. Skalnat´e Pleso , 287 – 292, (2019) Deriving photospheric parameters and elementalabundances for a sample of stars showing theFIP effect
B. Seli , , L. Kriskovics and K. Vida Konkoly Observatory, Research Centre for Astronomy and Earth Sciences,Hungarian Academy of Sciences, 1121 Budapest, Konkoly Thege Mikl´os ´ut15-17, Hungary E¨otv¨os University, Department of Astronomy, 1518 Budapest, Pf. 32,Hungary
Received: October 31, 2018; Accepted: January 21, 2019
Abstract.
One puzzling question in solar physics is the difference betweenelemental abundances in the photosphere and the corona. Elements with lowfirst ionization potential (FIP) can be overabundant in the corona comparedto the photosphere under certain circumstances. The same phenomenon hasbeen observed on a handful of stars, while a few of them show the inverseeffect. But not all the stars in the original sample had precise photosphericabundances derived from optical spectra, so for some the solar values wereadopted. In this work we make homogeneous abundance measurements fromoptical spectroscopy.We collected spectra of 16 stars showing the FIP effect with the 1-m RCCtelescope of Konkoly Observatory, with resolution of λ/ ∆ λ ∼
21 000. We de-termine the fundamental astrophysical parameters ( T eff , log g , [ M/H ], ξ mic , v sin i ) and individual elemental abundances with the SME spectral synthesiscode using MARCS2012 model atmosphere and spectral line parameters fromthe Vienna Atomic Line Database (VALD). Key words:
Stars: abundances – Stars: atmospheres – Stars: fundamentalparameters – Techniques: spectroscopic
1. Introduction
When working on X-ray spectra, solar physicists found a discrepancy betweenthe abundances of several elements compared to the known photospheric values.In the solar corona, elements with low first ionization potential (FIP) are en-hanced by approximately a factor of 4 (Laming, 2015, and references therein).This phenomenon – the FIP effect – was later observed on a handful of stars.The magnitude of the effect shows a spectral type dependence, for stars coolerthan K5 the inverse FIP effect was observed, where the low FIP elements aredepleted in the corona.However, for some of these stars the photospheric composition is unknownor the available data were collected from several different sources. Substituting88
B. Seli, L. Kriskovics and K. Vida
Table 1.
The observed sample. Mean S/N was calculated with the DER SNR algo-rithm (Stoehr et al., 2008).star number of S/N star number of S/Nspectra spectraEK Dra 17 77 β Com 5 140EQ Peg A 24 39 ǫ Eri 42 100EV Lac 23 23 κ Cet 20 113GJ 338 A 31 69 ξ Boo A 5 124GJ 338 B 27 66 ξ Boo B 5 58Sun 3 99 π UMa 6 14370 Oph A 5 122 π Ori 40 15170 Oph B 15 80 χ Ori 35 105 the stellar elemental composition with the solar abundance pattern makes itimpossible to determine whether the coronal abundances are caused by the FIPeffect or if those elements are just over/underabundant in that particular star.In this work we present new fundamental parameters and elemental abundancesderived from new homogeneous optical measurements for stars that are knownto show the FIP effect.
2. Data
We selected our target stars showing the FIP effect from Table 2 in Laming(2015). We excluded objects that are not visible from Hungary, as well as fainttargets (fainter than V ∼ m ) to ensure sufficient S/N. Our final observedsample consists of 16 main-sequence stars with spectral types ranging from F6to M3. The full list can be seen in Table 1.Observations were made with the 1-m RCC telescope of Konkoly Observa-tory, equipped with an echelle spectrograph with λ/ ∆ λ ∼
21 000 mean resolu-tion. The observations were carried out in March, June, August and November2017. The quality of most spectra is sufficient for spectral synthesis, while forthe fainter stars we have to combine spectra collected on the same night toensure a high enough S/N.Data reduction was carried out with the standard IRAF tasks. A ThArspectral lamp was used for wavelength calibration. 28 echelle orders were ex-tracted from each image uniformly, but we restrict our analysis to the 5000–7000 ˚A wavelength range, because below 5000 ˚A the S/N gradually decreaseswhile the region after 7000 ˚A is dominated by telluric absorption lines. eriving photospheric parameters and elemental abundances for a sample of stars showing the FIP effect
3. Spectral synthesis
We used the Spectroscopy Made Easy (SME) code (Valenti & Piskunov, 1996)with MARCS2012 model atmosphere to calculate the necessary parameters fromthe continuum normalized spectra. We downloaded spectral line data from theVienna Atomic Line Database (VALD; Piskunov et al., 1995) using the “extractstellar” option.Before fitting the individual elemental abundances, the fundamental param-eters of the stars are needed. These are effective temperature ( T eff ), surfacegravity (log g ), metallicity ([M/H]), microturbulence ( ξ mic ) and projected rota-tional velocity ( v sin i ). Another necessary parameter is macroturbulent velocity( ξ mac ), but since it is hard to disentangle the contribution of ξ mac from the otherline broadening effects, we chose to apply the following empirical relation fromValenti & Fischer (2005) rather than fitting ξ mac : ξ mac = 3 . T eff − /
650 (1)The following initial parameters were used: log g = 4 . M/H ] = 0 dex, ξ mic = 1 km s − , v sin i = 20 km s − and T eff inferred from spectral type. In general, no reasonable fit can be achieved ifwe iterate all parameters at once, so we fit them in the following order: first ξ mic and v sin i simultaneously, then T eff , then [ M/H ] and ξ mic . After this step we fitlog g with a line list containing only the Na D and Mg b lines, since their strongline wings are more sensitive to gravity. Then we proceed by downloading a newline list from VALD with the parameters derived so far. With this we fit T eff once again, then [ M/H ]. The results can be seen in Table 2, and Figure 1 showsan example of the observed and synthetic spectrum of π Ori.After these steps we fit the individual elemental abundances (along with[
M/H ]), namely C, Na, Mg, Al, Si, S, Ca, Ti, Mn, Fe, Ni and Ba. Some in-teresting elements whose coronal abundance can be derived from X-ray spectrahave no transitions in the observed wavelength range, so their abundances can-not be determined. The result can be seen in Figure 2 for 8 stars from thesample. While most elements show no deviation from the solar scale, there isa clear Ba enhancement for all these stars. According to D’Orazi et al. (2009)young stars tend to have higher Ba abundance, based on empirical results. Allstars appearing in Figure 2 are younger than the Sun with the oldest one being β Com with age of ∼ B. Seli, L. Kriskovics and K. Vida no r m a li ze d f l ux l [Å] Figure 1.
Observed (black) and synthetic (red) spectrum of π Ori near the Mg triplet.
SME is robust enough to give almost identical results for all spectra collectedfrom the same star on the same night. This means that the standard deviationscalculated from multiple observations are small (e.g. 5 K in T eff ) and can only beused for consistency check. So the uncertainties of the derived parameters have tobe obtained by different means, for example by seeing how much each parametercan be altered before it affects the determination of the other parameters duringthe fit. The expected average uncertainties are 50 K in T eff , 0.1 dex in log g ,0.1 dex in [ M/H ], 0.3 km s − in ξ mic and 3 km s − in v sin i .After comparing our results with available literature data, it seems thatour log g values are usually lower by ∼ g modifies the final abundances by ∼ T eff results in ∼ − change in ξ mic gives ∼
4. Conclusion
It appears that a metre-class telescope equipped with a mid-high resolutionspectrograph is enough to determine elemental abundances for bright enoughstars with the spectral synthesis method. We have collected spectra of 16 starsthat show the FIP effect, and carried out the abundance analysis for 8 of them.The remaining stars are the fainter ones with noisier spectra, so for them the eriving photospheric parameters and elemental abundances for a sample of stars showing the FIP effect
Table 2.
Fundamental parameters derived from the spectra.star T eff log g [ M/H ] ξ mic v sin i [K] [dex] [dex] [km s − ] [km s − ]EK Dra 5780 4.46 − .
06 1.32 21.2 β Com 5980 4.37 − .
09 0.92 13.3 ǫ Eri 5150 4.32 − .
07 0.91 12.8 κ Cet 5780 4.39 − .
01 0.83 12.5 ξ Boo A 5670 4.56 − .
16 1.32 14.1 π UMa 5880 4.39 − .
18 0.98 16.9 π Ori 6320 4.37 − .
12 1.06 20.0 χ Ori 5940 4.44 − .
10 0.54 17.2 spectral synthesis will be more challenging. In the future we also plan to gatherthe available X-ray abundances to recalculate the FIP bias for these stars.
Acknowledgements.
Authors are grateful to Konkoly Observatory, Hungary, forhosting two workshops on Elemental Composition in Solar and Stellar Atmospheres(IFIPWS-1, 13–15 Feb, 2017 and IFIPWS-2, 27 Feb–1 Mar, 2018) and acknowledge thefinancial support from the Hungarian Academy of Sciences under grant NKSZ 2018 2.The authors acknowledge the Hungarian National Research, Development and Innova-tion Office grant OTKA K-113117 and the Lend¨ulet grant LP2012-31 of the HungarianAcademy of Sciences. KV is supported by the Bolyai J´anos Research Scholarship ofthe Hungarian Academy of Sciences. This work has made use of the VALD database,operated at Uppsala University, the Institute of Astronomy RAS in Moscow, and theUniversity of Vienna. Authors are grateful to Borb´ala Cseh for her helpful suggestionsrelated to Ba stars.
References
D’Orazi, V., Magrini, L., Randich, S., et al., Enhanced Production of Barium in Low-Mass Stars: Evidence from Open Clusters. 2009,
Astrophys. J. , , L31, DOI:10.1088/0004-637X/693/1/L31Laming, J. M., The FIP and Inverse FIP Effects in Solar and Stellar Coronae. 2015, Living Reviews in Solar Physics , , 2, DOI: 10.1007/lrsp-2015-2Piskunov, N. E., Kupka, F., Ryabchikova, T. A., Weiss, W. W., & Jeffery, C. S.,VALD: The Vienna Atomic Line Data Base. 1995, Astron. Astrophys., Suppl. , ,525Stoehr, F., White, R., Smith, M., et al., DER SNR: A Simple & General SpectroscopicSignal-to-Noise Measurement Algorithm. 2008, , 505Valenti, J. A. & Fischer, D. A., Spectroscopic Properties of Cool Stars (SPOCS). I.1040 F, G, and K Dwarfs from Keck, Lick, and AAT Planet Search Programs. 2005, Astrophys. J., Suppl. , , 141, DOI: 10.1086/430500 B. Seli, L. Kriskovics and K. Vida −0.4 0 0.4 0.8 1.2 C Na Mg Al Si S Ca Ti Mn Fe Ni Ba [ X / H ] EK Dra −0.4 0 0.4 0.8 1.2 C Na Mg Al Si S Ca Ti Mn Fe Ni Ba [ X / H ] b Com−0.4 0 0.4 0.8 1.2 C Na Mg Al Si S Ca Ti Mn Fe Ni Ba [ X / H ] e Eri −0.4 0 0.4 0.8 1.2 C Na Mg Al Si S Ca Ti Mn Fe Ni Ba [ X / H ] k Cet−0.4 0 0.4 0.8 1.2 C Na Mg Al Si S Ca Ti Mn Fe Ni Ba [ X / H ] x Boo A −0.4 0 0.4 0.8 1.2 C Na Mg Al Si S Ca Ti Mn Fe Ni Ba [ X / H ] p UMa−0.4 0 0.4 0.8 1.2 C Na Mg Al Si S Ca Ti Mn Fe Ni Ba [ X / H ] p Ori −0.4 0 0.4 0.8 1.2 C Na Mg Al Si S Ca Ti Mn Fe Ni Ba [ X / H ] c Ori
Figure 2.
Elemental abundances relative to the solar values (derived in this work).Error bars shown are multiplied by 10 for illustration purposes.Valenti, J. A. & Piskunov, N., Spectroscopy made easy: A new tool for fitting observa-tions with synthetic spectra. 1996,
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