Issue |
A&A
Volume 507, Number 2, November IV 2009
|
|
---|---|---|
Page(s) | 901 - 910 | |
Section | Stellar structure and evolution | |
DOI | https://doi.org/10.1051/0004-6361/200912551 | |
Published online | 15 September 2009 |
A&A 507, 901-910 (2009)
HD 172189: another step in furnishing one of the best laboratories known for asteroseismic studies
O. L. Creevey1,2 - K. Uytterhoeven1,3 - S. Martín-Ruiz4 - P. J. Amado4 - E. Niemczura5 - H. Van Winckel6 - J. C. Suárez4 - A. Rolland4 - F. Rodler1,2 - C. Rodríguez-López4,7,8 - E. Rodríguez4 - G. Raskin6,9 - M. Rainer10 - E. Poretti10 - P. Pallé1,2 - R. Molina11 - A. Moya4 - P. Mathias12 - L. Le Guillou6,9,13 - P. Hadrava14 - D. Fabbian1,2 - R. Garrido4 - L. Decin6 - G. Cutispoto15 - V. Casanova4 - E. Broeders6 - A. Arellano Ferro11 - F. Aceituno4
1 - Instituto de Astrofísica de Canarias,
38200 La Laguna, Tenerife, Spain
2 -
Departamento de Astrofísica, Universidad de La Laguna,
38205 La Laguna, Tenerife, Spain
3 -
Laboratoire AIM, CEA/DSM-CNRS-Université Paris, Diderot;
CEA,IRFU, SAp, centre de Saclay, 91191
Gif-sur-Yvette, France
4 -
Instituto de Astrofísica de Andalucía (CSIC),
Camino bajo de Huétor 50,
18080 Granada, Spain
5 -
Astronomical Institute, Wrocaw University, Kopernika 11, 52-622
Wroc
aw, Poland
6 -
Instituut voor Sterrenkunde, Celestijnenlaan, 200D, 3001 Leuven, Belgium
7 -
Laboratoire d'Astrophysique de Toulouse-Tarbes, Université de Toulouse, CNRS,
31400 Toulouse, France
8 -
Universidad de Vigo, Departamento de Física Aplicada,
Campus Lagoas-Marcosende, 36310 Vigo, Spain
9 -
Mercator Telescope, Observatorio del Roque de los Muchachos,
Apartado de Correos
474, 38700 Santa Cruz de La Palma, Spain
10 -
INAF-OABrera, Osservatorio Astronomico di Brera, via E. Bianchi 46, 23807 Merate, Italy
11 -
Instituto de Astronomía, Universidad Nacional Autónoma de Mexico, Apdo. Postal 70-264, 04510 Mexico D.F., Mexico
12 -
UNS, CNRS, OCA, Campus Valrose, UMR 6525 H. Fizeau, 06108 Nice Cedex 2, France
13 -
UPMC Univ. Paris 06, UMR 7585, Laboratoire de Physique Nucléaire et
des Hautes Énergies (LPNHE), 75005 Paris, France
14 -
Astronomical Institute, Academy of Sciences,
Bocní II 1401, 141 31 Praha 4,
Czech Republic
15 -
INAF Catania Astrophysical Observatory,
via S. Sofia 78, 95123 Catania, Italy
Received 20 May 2009 / Accepted 27 August 2009
Abstract
HD 172189 is a spectroscopic eclipsing binary system with a
rapidly-rotating pulsating
Scuti component. It is also a member of the open cluster
IC 4756. These combined characteristics make it an excellent
laboratory for asteroseismic studies.
To date, HD 172189 has been analysed in detail photometrically but not
spectroscopically. For this reason
we have compiled a set of spectroscopic data
to determine the absolute
and atmospheric parameters
of the components.
We determined the radial velocities (RV) of both components using
four different techniques.
We disentangled the binary spectra using KOREL, and performed the
first abundance analysis on both disentangled spectra.
By combining the spectroscopic results and the photometric data,
we obtained the component masses,
1.8 and 1.7
,
and radii, 4.0 and 2.4
,
for
inclination
,
eccentricity e = 0.28, and orbital period
days.
Effective temperatures of 7600 K and
8100 K were also determined.
The measured
are 78 and 74 km s-1, respectively,
giving rotational periods of 2.50 and 1.55 days for the components.
The abundance analysis shows
[Fe/H] = -0.28 for the primary (pulsating) star, consistent
with observations of IC 4756.
We also present an assessment of the different analysis techniques
used to obtain the RVs and the global parameters.
Key words: stars: binaries: spectroscopic -
stars: fundamental parameters - stars: oscillations - stars: variables:
Sct - stars: abundances - Galaxy: open clusters and associations: individual: IC 4756
1 Introduction
HD 172189 (=BD +53 864, V = 8.85 mag,
38
37.6
,
,
J2000)
has the combined characteristics of being an
eclipsing and spectroscopic binary, pulsating star, and
member of a cluster
(Martin 2003; Martín-Ruiz et al. 2005 - MR05 hereafter;
Costa et al. 2007; Ibanoglu et al. 2009 - I09 hereafter).
Each of these provide unique constraints that allow
us to test stellar evolution theories in an independent form:
a) an eclipsing spectroscopic binary system is fundamental for
determining the
absolute global parameters of both stars and the system with precision;
b) a pulsating star allows us to use the oscillation frequencies to probe
the interior of the star, thereby also determining the
evolutionary state;
c) cluster membership has the distinct advantage that the properties such
as age, metallicity, and distance can be well-determined.
Given the constraints imposed by the cluster membership and the
binary system on the mass, age, and metallicity of the pulsating star,
the observed seismic frequencies can be used
to test and improve the current asteroseismic models.
For example, as both components are rapidly rotating
with periods of 2.50 and 1.55 days, (see Sect. 5),
we can
investigate the effects of rotation, such as the mixing of elements
and transport of angular momentum.
Several theories exist regarding rapid rotation, but as yet,
observations have not been able to confirm any of these hypotheses.
Some examples of these unproved theories include understanding
the interplay between rapid rotation and convective cores, enabling
the transport of angular momentum both poleward and in the radial
direction (Featherstone et al. 2007),
or the existence
of an overshoot boundary layer between the convective core and the
radiative region, where mixing of nuclear elements can influence
main sequence lifetimes (Brun et al. 2004).
Such theories can be confirmed from detailed seismic modeling,
once the global parameters of the pulsating star have been determined.
Since HD 172189 was discovered to be a binary system
by Martin (2003),
several groups have shown a keen interest in this object.
Dedicated photometric campaigns (Amado et al. 2006, MR05,
Costa et al. 2007, I09)
have begun to reveal the true nature of this system,
and several
oscillation
frequencies have been documented from the time series of the
Scuti star.
This system
is moreover a selected target
of the asteroseismic core program of the CoRoT satellite
mission (Baglin et al. 2006a,b; Michel et al. 2008),
and has been continuously observed from space
in white light for about 150 days from April to September 2008,
with the aim of interpreting the pulsations.
With the prospects of using the observed oscillation frequencies to
study the internal structure of the star, we have compiled
spectroscopic data taken in 2005 and 2007 from various sources with the
aim of determining some spectroscopic properties of the system, to
facilitate the future analysis of this star.
We determine the radial velocities (RVs) of the individual components using
various techniques (Sect. 3)
to subsequently
solve for the orbital parameters of the sytem, while also
providing an assessment of the methods employed (Sect. 4).
We combine the RV data with photometric data and
present
a full orbital and
component solution for this object (Sect. 5).
We subsequently disentangle the spectra (Sect. 6),
estimate the effective temperatures
using the
disentangled spectra, and using
synthetic spectra (Sect. 7)
and perform the first abundance analysis of this object
(Sect. 8).
Discussion and conclusions then follow.
Before beginning our analysis, we briefly review the literature of both
HD 172189 and IC 4756.
One of the first references to HD 172189 and IC 4756 can be found in Graff (1923), where HD 172189 is named star 83 and has V=8.69. Later, Kopff (1943) published an analysis (star 93, V = 8.86 mag), using a referenced tentative spectral typing of A6 from Wachmann (1939). Photoelectric observations of IC 4756 were then carried out in 1964 in Lowell Observatory (Alcaino 1965), with the purpose of determining the distance and the absorption of the cluster as well as to establish a criterion for membership. This author determined from the measured V = 8.73 mag and the colour-colour diagram, that HD 172189 (Alcaino star 10) most likely was not a member of the cluster, however, stated that proper motions would be needed to confirm this. They determined a distance modulus of 8.2 mag corresponding to 437 pc, and an age of 820 Myr for IC 4756. Herzog et al. (1975) subsequently determined the proper motions of 464 stars in the field of this cluster and estimated a probability of 89% of HD 172189 (Herzog 205) being a member of the cluster, while Missana & Missana (1995) obtained a 91% probability based on proper motions and the position of the star.
Schmidt & Forbes (1984) measured a of 69 km s-1,
where i is the inclination of the rotation axis (assumed
to be the same for both stars and equal to the inclination of the orbital
plane).
The spectral type has been somewhat discordant in the literature,
probably due to its binary nature later discovered by
Martin (2003).
Adding the fact that spectral typing of A stars can be difficult and
that both components of this (at least) double system
(see Sect. 9)
are rapidly rotating,
it is not a surprise that different authors
have arrived at several inconsistent results:
A6 V (Wachmann 1939; Herzog et al. 1975),
A7 III (Schmidt & Forbes 1984),
A6 III or A4 III (Dzervitis 1987),
A2 V (Costa et al. 2007), and
A6 (I09).
Schmidt (1978) measured Strömgren photometry of the system:
,
(b-y) = 0.258 mag,
m1 = 0.123 mag,
c1 = 1.055 mag, and estimated
E(b-y) = 0.15.
Using the de-reddenned quantities and the tables from Cox (2000), HD 172189
appears to be of spectral type late B or early A.
The range of these spectral types clearly imposes little constraint on
,
luminosity
and gravity
.
With the available photometric data of the eclipsing binary system
(MR05; Amado et al. 2006; Costa et al. 2007), extra
constraints can be imposed
on some of the fundamental parameters.
Very recently, I09 published combined
photometric and spectroscopic data with estimates of global parameters.
They suggested that the system has component masses
of
and
.
The cluster has an age of roughly 1 Gyr
(Alcaino 1965; Mermilliod & Mayor 1990).
The two components are rapidly rotating in a non-synchronous fashion,
and the orbit is quite eccentric, indicating that the stars
are not interacting
and are most likely detached MS stars. Furthermore,
the suggested MS turn-off mass for IC 4756 is 1.8-1.9
(Mermillod & Mayor 1990).
Table 1: Summary of spectroscopic observations.
2 Spectroscopic observations
The spectroscopic observations used in this work are summarised in Table 1, and the following subsections describe the observation, reduction, and calibration of the spectra taken at the various observatories. All of the spectra were subsequently barycentric corrected.
2.1 Aurelie data
A total of 14 spectra of HD 172189 were obtained in a time span of
10 nights from 15 to 25 June 2005 with the Aurélie
spectrograph, mounted on the 1.52 m telescope, at Observatoire de
Haute Provence (OHP), France. The instrument has a grating of
1800 lines/mm, providing a spectral resolution
000.
The spectral range used was 4528-4675 Å/4468-4542 Å,
with exposure times of 1200/1500, or 3600 s.
As there is no pipe-line reduction available, we used
standard IRAF (Tody 1986) reduction procedures.
The continuum normalisation was performed manually by fitting a
cubic spline.
Typical signal-to-noise ratio (SNR) values of the spectra are 55-63.
2.2 FIES data
The FIES data were obtained during an observation run of a separate object
in July 2007 using the 2.5 m NOT telescope at the Observatorio
del Roque de los Muchachos.
The FIbre-fed Échelle Spectrograph (FIES) is
a cross-dispersed high-resolution échelle spectrograph.
We used the medium-resolution setup with
.
The spectral range is 3640-7455 Å, with a maximum
efficiency of 9% at 6000 Å.
Separate wavelength calibrator exposures of
thorium-argon (ThAr) were obtained.
During each of the 5 nights of observations,
either 2 or 3 spectra of HD 172189 were taken with exposure times
of 600 s. We used
the FIEStool
reduction software (Stempels 2004
)
to calibrate the wavelength
and reduce the spectra.
This tool is optimised for FIES data, although
the reduction is standard and calls IRAF to perform some of the
tasks.
SNR values around 5720 Å are
70.
2.3 FRESCO data
From May - August 2005 a total of 21 spectra of HD 172189 were observed with the FRESCO échelle spectrograph, attached to the 91 cm telescope of the Fracastoro Mountain Station at Catania Astrophysical Observatory (CAO), Sicily, Italy. The FRESCO spectra, with a resolution

2.4 FEROS data
The Fiber-fed, Extended Range, Échelle Spectrograph (FEROS), mounted at the 2.2 m ESO/MPI telescope at La Silla (ESO), Chile, has a resolution of

2.5 FOCES data
Observations at the observatory of Calar Alto in Almeria, Spain, during 10 nights in May-June 2007 were carried out both in visitor and in service mode. The full optical range with a resolution of

3 Determination of radial velocities
As both components of the system are rapidly rotating, the spectral lines are broadened, making it difficult to identify individual lines Doppler-shifted due to the orbital motion. In fact, most profiles are merged and line profile variations due to pulsations are clearly present making complicated and delicate the determination of the RVs. For these reasons, we used the following independent methods to determine the RVs, described in the next subsections:
- LSD+GAU: fitting a double-Gaussian function to the least-squares deconvolution (LSD) profiles (Donati et al. 1997, 1999). The central positions of the Gaussian functions are the RVs of each component;
- LSD+MM: calculating the first moments (Aerts et al. 1992) from the LSD profiles;
- IRAF: using the IRAF task FXCOR with a synthetic non-broadened template and then using the DEBLEND function to compute the RVs;
- KOREL: disentangling the spectra using the programme KOREL (Hadrava 1995), and determining the RVs by fitting the observed spectra with the superposition of the Doppler-shifted disentangled spectra.
![]() |
Figure 1:
Least-squares deconvolution (LSD) profile (open circles)
calculated
at phase 0.93 (based on
|
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3.1 Least-squares deconvolution
To make optimised use of the common information available in all
spectral lines, we deconvolved several hundreds of individual lines by
comparison with synthetic masks, into a single ``correlation'' profile
with a significantly increased SNR, using the least-squares
deconvolution (LSD) method (Donati et al. 1997, 1999)
(cf. Fig. 1).
The synthetic line
masks contain lines from the VALD database
(Piskunov et al. 1995; Ryabchikova et al. 1999;
Kupka et al. 1999).
We used the values of
K and
dex (see Sect. 7)
for the spectral template.
Varying the effective temperature with
or 500 K and the gravity
with
or 0.1 dex
did not affect the central positions of the
LSD profiles significantly.
The fitted RV values obtained from using different templates was
used to estimate the error on the RVs.
The LSD profiles were calculated by
taking into account all elements, apart from He and H, in the regions
4380-4814 Å and 4960-5550 Å.
This involved deconvolving about 3000,
2600, 2200, 1525, or 250 lines for the FEROS, FIES, FRESCO,
FOCES, and Aurelie spectra, respectively, and resulted in
profiles with SNR of
1100-3300, 500-1700, 400-2000, 400-1200, and 200-700.
The LSD line profiles did not all have a continuum level at 1.0, so
they were
subsequently normalised, followed by a rescaling to homogenise the
profiles obtained with different instruments (see description in
Uytterhoeven et al. 2008). The velocity steps of the LSD profiles
were 2 km s-1 (FIES, FEROS and FOCES), 2.3 km s-1 (Aurelie), and 7.8 km s-1 (FRESCO). We note that systematic
instrumental RV offsets of the order of 1.5 km s-1 are most
likely present (see Uytterhoeven et al. 2008). However,
due to the small amount of datapoints per dataset,
we currently are not
able to quantify and subsequently correct for these
instrumental differences.
3.2 Double-Gaussian fit to the LSD profile
To determine the RVs of each component we fit a
double-Gaussian function
to each LSD profile.
We initially fixed the widths of the Gaussians while fitting the
central positions (the RVs) and the amplitudes, and subsequently allowed
all of the Gaussian parameters to be fit.
Cut-off values in the velocity axis were used for each fit
because the broad wings
of the Gaussian profiles do not accurately match the LSD profiles.
Figure 1 shows an example of an LSD profile when
both components are near maximum separation at orbital
phase 0.93 (based on reference eclipse minimum of HJD
2452914.644 days, and orbital period
days from MR05).
The deformations in the profiles are most likely due to pulsations,
and this inhibits the accuracy of the RV.
The dotted vertical lines
delimit the region that was fitted.
The solid curve shows the Gaussian fit, and the dashed curve shows the
rest of this function for further velocity values.
The model is fit several times using various cut-off values, and
using several LSD profiles which are calculated from different
spectral templates.
The RVs are defined as the mean values of these fits, with the standard
deviations defining the errors.
The RVs corresponding to this spectrum are denoted by the
vertical continuous lines.
This method worked well when the components in the LSD
profiles were sufficiently
separated, hence RVs at conjunction are not available using this method.
3.3 First normalised moments
Another tool to obtain RVs for the primary and secondary
components from the LSD profiles is to calculate the first
normalised moments (
,
e.g. Aerts et al. 1992).
At quadrature the velocity profiles of
the primary and secondary stars are well separated.
In these orbital phases we determined the integration boundaries,
within which to
calculate
,
from the individual Gaussian
profiles for the primary and secondary components
described in Sect. 3.2.
Close to conjunction, the velocity contributions
of the primary and secondary stars are blended,
which complicates the definition of the profile boundaries.
Therefore, we assumed a fixed width of the component profiles,
derived from the spectra in elongation phase.
The moments were calculated by determining
one of the integration borders, and calculating
the other border assuming a fixed profile width.
This method is sensitive to the profiles,
including any deformations due to
pulsations. In Fig. 1 the RVs
corresponding to this
spectrum are denoted by the vertical dashed lines
showing an offset of a few km s-1 from the values of LSD+GAU.
3.4 IRAF FXCOR
FXCOR cross-correlates the observed spectra with a template
spectrum in the Fourier domain. In our case, the merged (one-dimensional)
spectra of HD 172189 were cross-correlated with a
Kurucz synthetic spectrum computed with the approximate physical
parameters of the components of the binary, i.e.,
K and 7500 K,
and solar abundance.
The range of the spectrum used for the cross-correlation was
between 5000 and 6500 Å, avoiding the two regions most affected
by telluric absorption lines. The object spectra were filtered in the
Fourier domain with a bandpass filter according to the
resolution of the data. Most information in the Fourier spectrum is
above a certain wavenumber which was computed to take into account the
resolution of our data. The Fourier transform of the spectrum was then
multiplied by a ramp function which starts rising at wavenumber 10,
reaches 1 at 20, starts falling at 2500 and reaches 0 again at 4500.
The cross-correlation functions (CCF) were then calculated.
Two examples of the CCFs at different orbital phases
are shown in Fig. 2.
Gaussian functions were subsequently fitted to the CCFs,
using the full CCF profile (later referred to as IRAF
),
and next using only the upper 50% of the CCF (later referred to as IRAF),
resulting in much better central Gaussian fits.
![]() |
Figure 2: Cross-correlation profiles (CCF) of the observed spectra with a template spectrum at two different orbital phases (solid curves). The dashed curve is a double-Gaussian fit at phase 0.76, obtained by fitting the upper 50% of the profiles. |
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3.5 Disentangling of spectra
KOREL is a FORTRAN based code that fits time series of observed spectra of a multiple stellar system in the Fourier wavelength domain, to decompose them into mean spectra of each component, and simultaneously finds the best estimate of the orbital parameters (Hadrava 1995). It also calculates RVs of all components by fitting each exposure as a superposition of the disentangled spectra. We use the recent version KOREL08 to find RVs with a sub-pixel precision (cf. Hadrava 2009).As the spectral lines are broad and hence more likely blended with nearby lines, we carefully chose several wavelength regions where the orbital motion could be clearly observed. We have chosen regions containing different numbers of spectral lines: 4537-4595 Å, 4931-4995 Å, 4975-5038 Å, 5300-5368 Å, 5506-5577 Å, and 6340-6357 Å. We only used the data from FEROS, FIES, and FOCES because these provided the highest SNR as well as allowing sufficient spectral resolution for the combined data set.
Each spectral region was disentangled independently converging the
following parameters:
periastron epoch, eccentricity e, longitude of periastron ,
semi-amplitude of the radial velocity curve of the primary component KA,
and mass ratio
(=
MB/MA).
The orbital period
was held fixed to the constant 5.71098 days (MR05),
because the spectral data can not improve this
previous determination.
Also, note that the systemic velocity
is not obtained from
disentangling, because KOREL does not use any spectrum template.
To determine the optimal orbital parameters, we inspected
both the residual value of the KOREL fit as well as the
extracted RV curves. However, broad spectral profiles
enlarge the range of acceptable orbital values considered as
``good fits''.
For each of the spectral regions we obtain a set of RV measurements.
![]() |
Figure 3: Fit of the observed spectra by KOREL disentangling. The circles are the observations while the solid curves are the superimposed RV Doppler-shifted disentangled spectra (y-shifted for clarity). |
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Figure 3 shows the observed spectra (circles) for the spectral region 4546-4585 Å at orbital phases 0.98 (eclipse) and 0.1 (separated). The solid curve is the sum of the individual disentangled primary and secondary spectra, but x-shifted by their RVs at the appropriate orbital phase and, for maintaining clarity, we also vertically shift the phase = 0.1 spectrum.
4 Orbital parameters based on RVs
From each of the methods explained in Sect. 3 we obtain a set
of RV measurements.
In order to obtain the orbital parameters of the binary system we
fit
each set separately
using the standard radial velocity
equations. The results are summarised in Table 2,
where the orbital period is fixed at 5.70198 days (MR05),
T0 is the
offset in days from the defined primary minimum, and
is the reduced
value. For the LSD+MM method
we have SNR values instead of observational error measurements, so the
value is not comparable with the other methods.
The uncertainties quoted are the standard
formal uncertainties calculated from the fitted parameters and using the
observational errors given for each RV data point.
The results for KOREL are obtained by weight
combining all of the RV measurements
from the individual spectral profiles, and subsequently fitting using the
standard equations, while the uncertainties reflect the variation in the
fitted orbital parameters from the different spectral regions.
These are the RV data that were later used for the simultaneous
photometric and spectroscopic analysis (Sect. 5).
We also analysed the published RVs from I09, who had used standard
IRAF procedures to determine these. The results are given under heading I09.
![]() |
Figure 4: Phased radial velocity solution (dotted curve) obtained using the parameters from Table 2 under the column heading KOREL. The RVs obtained by the individual methods are also shown. The dashed lines delimit orbital phase at 0 and 1. |
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Table 2: Spectroscopic orbital solutions based on fitting the radial velocities obtained using different data fitting methods, explained in Sect. 3.
We define the primary component as the more massive star. The primary is the star that shows the deeper LSD or CCF profiles as well as the line-profile variations due to pulsations (see Sect. 9).
Figure 4 shows the phased radial velocity data
from each of the methods: LSD+MM (crosses), IRAF (diamonds),
LSD+GAU (squares),
and KOREL (triangles - we have included a weighted average
shift of
-28.02 km s-1 for clarity).
The dotted curve shows the radial velocity solution
given by the parameters using KOREL and shifting it vertically by
.
All of the methods presented return values of e, ,
T0 and
consistent with each other (Table 2).
There is, however, a variation among the fitted values
of KA and KB. This is due to the sensitivity of the
various methods used
to extract the radial velocities.
Two possible reasons that affect the determination of the RVs
are (1) the effect of the pulsations on the spectral profiles, and
(2) line-broadening due to rotation making it difficult to accurately
determine RVs (especially at conjunction).
If we inspect Fig. 1 we see that the double-Gaussian function cannot correctly reproduce the shape of the LSD profile. In fact, due to the wiggles or variations in the line, the actual center of the Gaussian could be shifted slightly to the right or the left. We have highlighted the center positions derived using the LSD+GAU and LSD+MM methods with the continuous and dashed vertical lines. In this figure it can also be seen that the latter method is sensitive to the minima of the deepest variations in both the primary and secondary profiles. In this case, it results in smaller absolute values of the RVs than the former method. By inspecting these profiles by eye, it is very difficult to distinguish which is the true orbital motion RV.
For phases between 0.35 and 0.7 we begin to see
blending of the component profiles using both CCFs and LSD methods.
Hence
the resulting RVs between these phases will not be as accurate.
For example, the deviations of the RVs using the LSD+MM method
from the fitted RV curve in Fig. 4
are explained most likely by
the sensitivity of this method to the deformations in the line profiles
induced by pulsations.
In Fig. 2 we show the CCF calculated using IRAF procedures at two different orbital phases. For phase = 0.76 we have also plotted the Gaussian fits. Again, it is difficult to extract an accurate RV value because the lines are so broad and due to the variations (wiggles) in the CCFs. These values were obtained using the upper 50% of the CCF (although we draw the full analytical profile).
By inspecting the profiles of all of the available spectra (and CCFs or
LSDs) it is not possible to distinguish between shifts
of a few km s-1, and it is these shifts that cause the differences
in the fitted values of KA and KB of 6 km s-1 shown in Table 2.
The last method used to extract the RVs was KOREL. We choose this as the best solution because it is robust against broadened/blended lines, it simultaneously fits the orbital solution (comparing all of the spectra at the same time), and it is independent of spectral templates. These are the RVs that are subsequently used for the simultaneous photometric and spectroscopic light curve fitting.
5 Combined analysis of photometric and spectroscopic data
In order to obtain a consistent photometric and RV solution for this
system, we combine the RV data with an extensive photometric data set (MR05).
We include photometry
from some more recent (2005 and 2007) observational campaigns with
the twin Danish 6-channel
photometer at the 1.5 m and the 0.9 m
telescopes at
San Pedro
Martír, and Sierra Nevada Observatories (data reduced in the same
manner as MR05).
We also include photometric data from the P7 photometer mounted
on the Flemish Mercator telescope at the Roque de los Muchachos Observatory
(see Rufener 1964, 1985, for reduction procedure).
In total there are more than 4000 photometric measurements obtained in each of the four
Strömgren filters, spanning more than 3700 days, and 70 out-of-eclipse
data points in the Geneva UBB1B2VV1 filter system.
We used PHOEBE
(PHysics Of Eclipsing BinariEs) (version 0.31a, Prsa & Zwitter 2005)
and FOTEL (Hadrava 1990) to model these data, however the latter was used
mainly to confirm the results.
PHOEBE is a user-friendly
software based on the Wilson-Devinney (WD) code (2007 v. of
Wilson & Devinney 1971).
5.1 Photometric indices
Using out-of-eclipse measurements, we calculated the Strömgren indices. We obtain (b-y) = 0.262 mag, m1 =0.134 mag, and c1=1.058 mag. The de-reddenned indices were obtained using the method described in Philip et al. (1976), these are E(b-y) = 0.158 mag, (b-y)0 = 0.104 mag, m0 = 0.184 mag, and c0 = 1.026 mag. If we compare these values to Crawford (1979) we obtain spectral type A6V or A7V. These values correspond to a single star with a mass range of between 1.7 and 1.9

5.2 PHOEBE
We started our fitting by varying




We modelled the stars as a
detached system
assuming a radiative albedo for both stars
equal to 1 and
gravity darkening values of
gA = gB = 1.
We also attempted to model the data using the semi-detached configuration,
however, most of the parameters did not converge.
The
model parameters from the best fit are given in Table 3.
The errors are derived using
PHOEBE. The velocities
are determined from spectroscopy
(see Sect. 8) allowing the derivation of the
rotational periods
.
Table 3: Component and orbital results from simultaneous photometric and velocity light curve fitting with PHOEBE.
6 Disentangling of spectra
The disentangled spectra were obtained by imposing the orbital solution from KOREL shown in Table 2. The used version of KOREL is limited in resolution to 4000 points. However, in most cases it was quicker and more stable to work on 2000 points at a time, over wavelength regions of about 100 Å. For this we had to rebin the spectra at the appropriate resolution and carefully choose the endpoints of the regions where there was continuum, while also ensuring that overlapping spectral regions are present to facilitate the merging of all of the wavelength regions.We attempted to disentangle the spectra in the
wavelength range from 4600 to 5800 Å because this region is most
sensitive to abundances.
However, we only obtained reliable results for 100 Å-length
spectral regions
between 4976-5627 Å.
Unfortunately, this implies that a spectroscopic determination
of
from the Balmer lines is not
possible from the disentangled spectra:
a better orbital phase coverage and higher SNR spectra are needed in
order
to disentangle
these regions correctly.
Spectra from binary systems normalised to 1 contain no information about the relative light contributions of each of the individual spectra. We used the literature values from I09 ( LA = 0.61 and LB = 0.39 where LA + LB = 1), and the fitted luminosities given by our composite photometric and spectroscopic analysis ( LA = 0.69 and LB = 0.31, Sect. 5) to obtain the fractional contributions to the total light. We shifted the output spectra to continuum 0, scaled the individual spectra by their corresponding fractional luminosity, and shifted the spectra again to 1 to obtain the disentangled individual spectra.
7 Spectroscopic determination of
Once the spectra were disentangled, we proceeded to obtain the LSD profiles of the
individual disentangled spectra (Sect. 3.1), in order to estimate










As the disentangled renormalised spectra depend on the assumed luminosity
ratio of both components, we performed a few tests
to investigate how these results depend on this
imposed value.
We scaled each of the disentangled spectra arbitrarily, and
proceeded to
identify the best
for each of the ``synthetic'' spectra in the same manner as above
(as double-blind tests).
The results were again quite insensitive to the value of
,
while
the derived values of
were consistent with results of 7500-7750 K for the primary,
and 8000-8250 K for the secondary.
This test showed that the identified
were not obtained from
the imposed luminosity ratio of the stars,
but rather the shape of the spectra.
MR05 obtained an effective temperature ratio
(TB/TA) of
1.05 (secondary/primary), in agreement with our result,
while I09 obtained a hotter temperature for the primary component
than for the secondary (
).
We also directly compared composite rotationally-broadened RV- and
-shifted Kurucz synthetic spectra to the best SNR observations
near maximum elongation
phase.
We used templates spanning temperatures of 7000-8500 K and
of
3.5-4.5 dex.
Figure 5 shows the observations (grey) compared to various
templates (black) for the temperature-sensitive H-
line.
As shown in this figure, the best fitted temperatures are
7500-7750 and 8000-8250 K for primary and secondary star, respectively.
(The
values used are 3.5.)
![]() |
Figure 5:
Composite rotationally broadened RV- and |
Open with DEXTER |
8 Abundance analysis
We determined the abundances of both components using
the disentangled renormalised spectra.
We compared the results with both values of luminosity fraction,
and the final abundances varied
slightly, but within the quoted errors.
Our analysis follows the methodology presented in
Niemczura & Poubek (2006)
and
relies on an efficient spectral synthesis based on
a least-squares optimization algorithm (Bevington 1969;
Takeda 1995).
This method allows the simultaneous
determination of various parameters associated with stellar spectra and
consists of minimizing the deviation between the theoretical flux
distribution and the observed one.
The atmospheric models used for the synthethic spectra determination
were computed with the line-blanketed LTE ATLAS9 code
(Kurucz 1993), which handles line opacity with the
opacity distribution function.
The synthetic spectra were computed with the SYNTHE code (Kurucz 1993).
Both codes were ported to GNU/Linux by Sbordone (2005).
The identification of stellar lines and the abundance analysis
were performed on a line list we constructed based on
VALD
data (Kupka et al. 2000, and references therein).
The shape of the synthetic spectrum depends on the
stellar parameters such as
,
,
,
microturbulence
,
RV
and relative abundances of the elements.
The effective temperature and surface gravity were not determined
during the iteration
process but were considered as fixed input ones
(
and
= 4.0/4.0 for primary/secondary
components),
while
= 2 km s-1
was adopted.
All of the other above-mentioned parameters can be determined
simultaneously because they produce detectable and different
spectral signatures.
The theoretical spectrum was fitted to the normalised observed one in
small regions, until the results converged.
The obtained chemical element abundances, relevant errors with the
adopted solar abundances
(Grevesse et al. 2007) are given
in Table 4.
The errors are calculated as
where
is the
standard deviation of the individual element abundance,
and
denote the
variation of abundance for
K and
.
For those elements where only one line was used to estimate
the abundance, the
error is
.
Table 4: The abundances of chemical elements for the primary and secondary stars.
![]() |
Figure 6: The disentangled observed primary spectrum (open circles), and the theoretical fitted spectrum (solid) obtained using the abundances from Table 4. |
Open with DEXTER |
Apart from the errors in
and
,
several systematic
errors
are likely affecting the derived abundances.
For example, fixing
,
the restriction of the disentangling
technique
to the spectral range of 4976-5672 Å
and the imposed luminosity
ratio all contribute to these sytematic errors.
In addition to this,
the adopted atmospheric models and the
atomic data (in particular the oscillator strengths)
also contribute.
We are also not taking NLTE effects into account, which are
crucial for a number of spectral lines of several elements
(see e.g. Asplund 2005; Fabbian et al. 2006, 2009).
However, we have estimated that for the neutral C lines used here,
the NLTE corrections are negligible (private comm. Fabbian).
Moreover, even for other chemical elements we can safely assume that
the differential NLTE effects between the primary and secondary
stars are
small and hence can not explain the differences for some of the
elements between the two stars.
Figure 6 shows a region of the primary disentangled
spectrum (circles) and
the theoretical fitting to it (solid curve)
which is obtained using the abundances from Table 4.
The chemical composition of the primary star is slightly
sub-solar, judging
from the Fe content, while
the secondary star shows enhanced abundances
(see Fig. 7).
The derived rotational velocities
are =
km s-1 and
km s-1 for primary and secondary component respectively,
based on a comparison between
the spectra with broadened
theoretical profiles.
Coupling these values with the results for
and i
from Table 3, we
derive the following rotational periods:
days for the primary star
and
days for the secondary.
![]() |
Figure 7:
Abundances of the primary (filled circles) and
secondary (open circles) stars
compared to the adopted solar values.
The bars represent errors of |
Open with DEXTER |
We have also performed a comparison abundance analysis based on a detailed
line abundance approach using the MOOG code.
The full procedure is described in Arellano Ferro et al. (2001) and
Giridhar & Arellano Ferro (2005).
The number of elements analysed is smaller than those shown in
Table 4, but the overall Fe abundance and the indication that
the secondary component is iron rich is consistent with our previous result.
This analysis yielded the best results when
of 7750 and 8000 K,
and
of 3.0 and 3.5
were adopted for primary and secondary, respectively.
9 Discussion
9.1 Orbital and System parameters
From the spectroscopic and the combined photometric and spectroscopic
analysis we obtain system parameters that are in agreement:
e = 0.29,
and
(this result is compatible with
taking the error into account, and this value
indicates that the resulting offset in days from eclipse/conjunction
coincides with the input value from MR05).
When we compare our results with the only other published system
parameters by I09, we find that I09 obtain from their combined
photometric and spectroscopic analysis a lower
value of the eccentricity (e=0.19).
When we fit their data using our RV
solution method, we obtain e = 0.25,
and
T0 = -0.4. However, when we use
and T0=-0.1 as fixed values we obtain
a
value that increases
by less than 1 (i.e. less than 1
),
indicating that this solution is also plausible with their
data.
The average
km s-1 is consistent with the cluster radial
velocity of -25.0 km s-1(Valitova et al. 1990): providing extra
evidence of the system's membership to the cluster.
The derived value of
indicates that
if we aim to determine precise masses, we must accurately
determine the values of KA and KB.
Given that we obtain a range of about 6 km s-1 in both KA and KB this implies that the minimum mass error is already on the order of
a few tenths (if we just use the analytical calculation and the inferred
inclination).
The resulting values for
are listed in Table 2,
where it can be seen that the variation is of the order of 0.3
(all however within 3
of each other).
In Sect. 4 we already discussed the sensitivity of
each of the methods in obtaining the RVs, and we would like to
point out the difficulty of attempting to model
the type of stellar system considered here.
What hampers the precise determination of
the RVs of each component is the
significant broadening
of the spectral line profiles due to the rotation of
both stellar components, and the superimposed pulsations.
The largest differences in the results come from using the same method
(IRAF) but choosing a different cut-off region in the CCF profiles to model.
While the two-Gaussian function did not
show reasonable results for IRAF
,
an adequate 3-Gaussian fitting to the CCF seemed
to fit the profile
better indeed.
This third low amplitude component could be a sign of a
third body in the orbit.
When combining the photometric and spectroscopic data (Sect. 5)
it was difficult to arrive at a solution that (iteratively) converged
using the parameters
listed in Table 3 as free parameters.
This is most likely a result of the rapid rotation causing surface
temperature variations at different latitudes
(sometimes a difference of up to
1500 K for very rapid rotation).
The photometric light curve is distorted due to these variations,
and these effects are not taken into account in the
modeling (the assumption with PHOEBE is that
the star rotates as a rigid body, without differential
rotation).
Additionally, one of the components has visible photometric variability
on time scales of
1 h
(MR05, Amado et al. 2006; Costa et al. 2007),
and although the light curves were binned to
reduce the effects of pulsation, there are nonetheless effects that can
not be eliminated, such as those during eclipse.
We obtain component masses
of
and
for primary and secondary stars respectively,
values that are lower by
0.2
than those from I09 (2.06 and 1.87
).
Our results are consistent with the values obtained by
Mermillod & Mayor (1990) who, through a study of red giants, determined
the main sequence (MS) turn-off mass of IC 4756 to be
between 1.8 and 1.9
.
This would also be consistent with the hypothesis of the more massive
component beginning to turn off the MS, while also implying that
the secondary star is slightly
hotter than the primary.
We obtain primary and secondary
radius of
and
,
respectively,
luminosities of
and
,
and
values of
and
(see Table 3).
These values are lower than those quoted by I09, due primarily
to the lower fitted masses we obtain.
We finally fixed the values of
at 7500-7750 and 8000-8250 K respectively.
This choice is justified by the following reasons:
(a) at an earlier stage during this work, modeling the photometric
light curve produced similar answers (7560 and 8030 K) while fixing
various other parameters,
(b) modeling the light curve while fixing the
at other values
results in worse fits or non-convergence,
(c) the photometric Strömgren indices are consistent with
these ranges of values
(Sect. 5), and
(d) the spectroscopic determination of
from the LSD profiles
and synthetic spectra also arrives at these values (Sect. 7).
The primary (hotter and more massive) star is the pulsating
component that clearly shows line-profile variations.
Our data do not allow us to determine if the secondary
component is also pulsating
as the SNR is too low to detect low-amplitude variability, if any.
The results in Sect. 5 and Table 3 do not
discard the possibility of two pulsating components -
both stars lie within the Scuti instability strip close
to the blue edge (see Fig. 13 in Pamyatnykh 2000).
We have explored
various forms of determining the RVs from the 70 spectra collected
between 2005 and 2007 as well as using photometric observations spanning
over 3000 days.
Taking into account the uncertainties, our results are consistent
with the I09 ones, however, apart from the RV dataset derived with
the IRAF method, we obtained lower
masses and this would imply a downward
revision of these values to 1.8 and 1.7 .
9.2 Abundances
The resulting abundances given in Table 4 indicate for the primary component a sub-solar metal value of![$\rm [Fe/H]=-0.28$](/articles/aa/full_html/2009/44/aa12551-09/img92.png)



The abundances relative to hydrogen for the primary star are:
,
,
,
,
.
These values are comparable to Jacobson et al. (2007), who obtained
-0.15, +0.19, -0.08, -0.07,
+0.2
for IC 4756.
The results for the secondary star are
[Fe/H] = +0.4, [Si/H] = +0.4, [Ca/H] = +0.6, [Ni/H] = +0.6,
on average
0.5 dex higher than the
primary star, resulting in
enhanced abundances compared to the Sun.
Figure 7 shows the abundances
relative to the solar ones.
The enhanced abundances of the secondary star
could also be an effect of modeling a spectrum
with an inadequate normalisation from the disentangling.
Higher SNR disentangled spectra resulting
from the full orbital phase coverage would be able to confirm these
different abundances.
10 Conclusions
We analysed a set of spectroscopic data obtained between 2005 and 2007 with the aim of determining the absolute component masses, radii, luminosities, and effective temperatures of the system, as well as undertaking the first abundance analysis of the HD 172189 disentangled spectra. From a combined photometric and radial velocity analysis, we derive for the primary and secondary stars, respectively, masses of




















We applied four methods to calculate the RVs and obtained different results for each. We subsequently showed the limitations of each technique for analysing a system with two rapidly-rotating components, one of these having the additional complications of showing significant profile-variations due to pulsations. Obtaining higher SNR spectra with continuous phase coverage would help to determine the systematic differences between each of the methods.
We have disentangled the spectra of both components and determined
the rotational velocities: =
km s-1 and
km s-1.
Coupling these values with the results for
and i we obtain
rotational periods
days and
days.
We subsequently
derived a metallicity of [Fe/H] = -0.28 dex
and abundances of
[Si/H] = +0.3, [Ca/H] = -0.03,
[Ni/H] = -0.10 and
[Na/H] = +0.04 for the primary star.
These are consistent with the results published for the
cluster IC 4756 by Jacobson et al. (2007).
The sub-solar metallicity is also consistent with the findings from I09.
The rapid rotation of both components, the non-synchronous
rotation (based on the orbital period), the eccentricity, and the
likely membership of IC 4756 suggests that the system
is still detached.
Based on the inferred age of the system of 0.8-0.9 Gyr
(Alcaino 1965; Mermillod & Mayor 1990)
we estimate that the 1.8
primary star is
moving towards the end of
its MS lifetime, when it begins to cool down and increase in
luminosity.
Mermillod & Mayor (1990) also determine that the main sequence
turn-off mass
for this cluster is 1.8-1.9
,
which agrees with this hypothesis.
In order to study the oscillations of the primary star, recently CoRot (Baglin et al. 2006a,b; Michel et al. 2008) observed HD 172189 as a primary asteroseismic target. Our analysis of this data has given a thorough insight into the nature of this object, and hence forms a solid foundation for the subsequent asteroseismic analysis. We look forward to the unravelling of the mysteries associated with this object, and to learning about the effects of rotation on the interior structure of the star from the pulsation frequencies.
Acknowledgements
The FEROS data were obtained with ESO Telescopes at the La Silla Observatory under the ESO Programme: 075-D.032. This work is partially based on observations made with the Nordic Optical Telescope, jointly operated on the island of La Palma by Denmark, Finland, Iceland, Norway, and Sweden, in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofisica de Canarias. We acknowledge Calar Alto director, Joao Alves, for authorising schedule changes and thank astronomers F. Hoyo, M. Alises and S. Pedraz and the rest of the staff for acquiring the FOCES dataset, at the Centro Astronómico Hispano Alemán (CAHA) at Calar Alto, operated jointly by the Max-Planck Institut für Astronomie and the Instituto de Astrofísica de Andalucía (CSIC). Part of this work is based on observations made with the Mercator Telescope, operated on the island of La Palma by the Flemish Community, at the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofisica de Canarias, and observations (SPM and SNO) obtained at the Observatorio de Sierra Nevada (Spain) and at the Observatorio Astronómico Nacional San Pedro Mártir (Mexico). O.L.C. is greatful to Petr Hadrava and Jirí Kubát from the Astronomical Institute in Ondrejov, Czech Republic, for their hospitality and efforts in making the First Summer School in Disentangling of Spectra a success. S.M.R. acknowledges a ``Retorno de Doctores'' contract of the Junta de Andalucía. P.J.A. acknowledges financial support from a ``Ramón y Cajal'' contract of the Spanish Ministry of Education and Science. P.H. acknowledges the support from a Czech Republic project LC06014. CRL acknowledges an Ángeles Alvariño contract under Xunta de Galicia. A.M. ackowledges financial support from a ``Juan de la Cierva'' contract of the Spanish Ministry of Education and Science. M.R., G.C., and E.P. acknowledge financial support from the Italian ASI-ESS project, contract ASI/INAF I/015/07/0, WP 03170. J.C.S. acknowledges support from the ``Consejo Superior de Investigaciones Científicas'' by an I3P contract financed by the European Social Fund and from the Spanish ``Plan Nacional del Espacio'' under project ESP2007-65480-C02-01. E.N. acknowledges financial support of the N N203 302635 grant from the MNiSW. D.F. acknowledges financial support by the European Commission through the Solaire Network (MTRN-CT-2006-035-484). We would also like to thank the anonymous referee for their constructive comments and suggestions. This research was motivated and in part supported by the European Helio- and Asteroseismology Network (HELAS), a major international collaboration funded by the European Commission's Sixth Framework Programme.
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Footnotes
- ... 2004
- Available at http://www.not.iac.es/instruments/fies/fiestool/FIEStool.html
- ...2005)
- These are available online: www.user.oat.ts.astro.it/atmos/
- ... VALD
- http://ams.astro.univie.ac.at/ vald/
- ... MOOG
- MOOG was developed by Chris Sneden, see: http://verdi.as.utexas.edu/moog.html
- ... rotation
- See the PHOEBE manual, available at http://phoebe.fiz.uni-lj.si/
- ... +0.2
- Here, Jacobson et al. used the gf values from Luck (1994).
All Tables
Table 1: Summary of spectroscopic observations.
Table 2: Spectroscopic orbital solutions based on fitting the radial velocities obtained using different data fitting methods, explained in Sect. 3.
Table 3: Component and orbital results from simultaneous photometric and velocity light curve fitting with PHOEBE.
Table 4: The abundances of chemical elements for the primary and secondary stars.
All Figures
![]() |
Figure 1:
Least-squares deconvolution (LSD) profile (open circles)
calculated
at phase 0.93 (based on
|
Open with DEXTER | |
In the text |
![]() |
Figure 2: Cross-correlation profiles (CCF) of the observed spectra with a template spectrum at two different orbital phases (solid curves). The dashed curve is a double-Gaussian fit at phase 0.76, obtained by fitting the upper 50% of the profiles. |
Open with DEXTER | |
In the text |
![]() |
Figure 3: Fit of the observed spectra by KOREL disentangling. The circles are the observations while the solid curves are the superimposed RV Doppler-shifted disentangled spectra (y-shifted for clarity). |
Open with DEXTER | |
In the text |
![]() |
Figure 4: Phased radial velocity solution (dotted curve) obtained using the parameters from Table 2 under the column heading KOREL. The RVs obtained by the individual methods are also shown. The dashed lines delimit orbital phase at 0 and 1. |
Open with DEXTER | |
In the text |
![]() |
Figure 5:
Composite rotationally broadened RV- and |
Open with DEXTER | |
In the text |
![]() |
Figure 6: The disentangled observed primary spectrum (open circles), and the theoretical fitted spectrum (solid) obtained using the abundances from Table 4. |
Open with DEXTER | |
In the text |
![]() |
Figure 7:
Abundances of the primary (filled circles) and
secondary (open circles) stars
compared to the adopted solar values.
The bars represent errors of |
Open with DEXTER | |
In the text |
Copyright ESO 2009
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