L. M. Freyhammer1,2
- H. Hensberge 1 - C. Sterken 2,
- K. Pavlovski 3
- A. Smette 4,5,
- S. Ilijic 6
1 - Royal Observatory of Belgium, Ringlaan 3, 1180 Brussels,
Belgium
2 -
OBSS/WE, Vrije Universiteit Brussel, Pleinlaan 2,
1050 Brussels, Belgium
3 -
Department of Physics, University of Zagreb, Bijenicka
32, 10000 Zagreb, Croatia
4 -
Institut d'Astrophysique et de Géophysique, Université de
Liège, 17 Allée du 6 Août, 4000 Liège, Belgium
5 -
European Southern Observatory, Casilla 19001, Alonso de
Cordova 3107, Vitacura, Santiago, Chile
6 -
Faculty of Electrical Engineering
and Computing, Department of Applied Physics,
University of Zagreb, Unska 3, 10000 Zagreb, Croatia
Received 24 June 2004 / Accepted 28 August 2004
Abstract
HD 92024 is a member of the open cluster NGC 3293; it is the only
eclipsing binary system with a
component known in the southern
hemisphere. This paper presents the first spectroscopic analysis of the
single-lined binary and provides an orbital analysis based on recent
high-resolution spectroscopy and photometry. A procedure to derive orbital
elements with minimal influence of the pulsational line-profile variations
on the radial velocities is applied, and we find the stellar masses to be
and
respectively,
and radii of
,
.
The temperatures are
K and
K. The surface gravity values of
and
indicate that the binary consists of
an evolved early B-type primary and a late-B main sequence companion.
The resulting distance
kpc and systemic velocity -16
km s-1 confirm cluster membership.
Theoretical stellar models indicate an age of 10-13 Myr,
somewhat higher than the literature value for the brightest members
of NGC 3293.
Key words: stars: binaries: eclipsing - stars: binaries: spectroscopic - stars: early-type - techniques: spectroscopic
HD 92024 (V381 Car, SpT. B1 III,
)
is the only known
component
in an eclipsing binary in the southern hemisphere. The star is a
member of the young open cluster NGC 3293 where it was registered as #5 by Feast
(1958). He determined the cluster's radial velocity to be
-14
1.8
and identified the star as a radial velocity variable with
a range of 52
.
The distance modulus to NGC 3293 is
(=2750
250 pc, Baume et al. 2003) and the cluster shows
differential reddening.
Balona (1977) discovered the
light variations of HD 92024 and
the eclipsing nature was found by Engelbrecht & Balona (1986, EB86
hereafter) who determined an ephemeris based on extensive photometric
B-band observations relative to NGC 3293-20. They detected two
oscillation frequencies,
f1=5.640
and f2=7.669
,
but the f2 frequency is ambiguous
due to a 1
alias. Engelbrecht (1986) re-analysed the EB86
photometry and detected a third frequency f3=7.17
.
Jerzykiewicz &
Sterken (1992, JS92 hereafter) obtained uvby photometry over 5 years
and confirmed the frequencies f1 and f3, or the latter's 1
alias. By
combining their observations with those of EB86 they derived an orbital
period of
with a primary minimum of light at
HJD
.
The present paper deals with the orbital elements of the binary system using recent high-resolution spectroscopy and photometry including new eclipse observations. In Sect. 2 the observations and data reduction are described. Section 3 gives the ephemeris and the period analysis of the photometry, and Sect. 4 shows the spectroscopic analysis leading to the orbital elements. In Sect. 5 the photometric analysis with the Wilson-Devinney code is given. Finally, the stellar dimensions and evolutionary stage are presented and discussed in Sect. 6, before concluding in Sect. 7.
Table 1: Photometric indices and data for HD 92024 (P) and comparison stars. Sources: Kaltcheva (2003) and Shobbrook (1983, for C1).
Table 2: rms scatter of the PMT magnitude differences (mmag) between comparison stars. N is the number of differential measurements.
An additional two hours of CCD observations were obtained in Apr 2001 (JD 2 452 009) using the Danish 1.54-m telescope with DFOSC (2k ![]() |
Figure 1: The blue light curve before ( top) and after ( bottom) prewhitening the frequencies f1,f2,f3. The four different datasets are indicated. |
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Table 3:
Logbook of the spectroscopic observations of HD 92024. Dates,
incl. Julian date (=HJD-2 400 000), indicate start of night in UT.
Column 3 lists the observers: Sterken (S), Hensberge (H) and Freyhammer (F).
N is the number of spectra obtained that night,
is the mean integration time (s), "Ins''
indicates instrument used (FEROS or ECHELEC) and S/N denotes the range of
signal-to-noise at 4500 Å. The last column gives the orbital phase
interval covered that night.
We intend in Paper II to study the
oscillations by exploiting
the full wavelength range in these spectra
for information on line-profile variations. Therefore, a considerable effort
was now put into improving the reduction of the FEROS spectra beyond the
limitations of the standard FEROS pipeline. The main concern was
to ensure consistency between all spectra by imposing a differential data
reduction procedure, assuring correct order merging, removing
time-dependent vignetting and blaze function variations before combining
the orders, and by avoiding the introduction of time-dependent effects from
the calibration unit into the spectra. Technical details are given in
Hensberge (2001) and Hensberge et al. (2004).
During the order-merging process, the spectra were
rebinned to
,
partly in anticipation of the
cross-correlation velocity analysis.
23 spectra were obtained during five nights in 1989 with the
ECHELEC spectrograph, also on the ESO 1.5-m, covering the range
4390-4715 Å. ECHELEC is a Littrow echelle spectrograph (
)
with a grism as cross disperser. It was equipped with a thinned
backside-illuminated RCA CCD with 1024
640 pixels.
In view of their long integration times, low S/N and small wavelength
coverage, we reduced the ECHELEC spectra in the standard way using
MIDAS routines. Instead of a reduction with more dedicated
software (see Verschueren & Hensberge 1990; Verschueren
et al. 1997, for details), an a posteriori correction
derived from comparison to the FEROS spectra was then applied (see Hensberge et al. 2004) to minimise possible systematic errors from blemished CCD columns and improper order merging.
Some systematic variability remains in the light curves after prewhitening, so the frequency solution may be incomplete, but the residuals no longer critically obstruct analysis of the eclipses. The reduction of scatter by the prewhitening, inside as well as outside the eclipses, is apparent from Table 4 where our SAT data are compared to the EB86 measurements. It is seen that after prewhitening, the rms errors are comparable for data in- and outside of the eclipses as well as for the EB86 and the SAT data, indicating that the frequency analysis (based on out-of-eclipse data alone) predicts the pulsational light variations inside and outside the eclipses equally well. A closer look at the nightly light curves revealed that, as explained well by constructive interference of the frequencies, the EB86 data have higher pulsational amplitudes than the recent SAT observations. This explains the higher scatter in the EB86 data prior to the prewhitening.
Table 4:
The effect of prewhitening frequencies in the SAT b light curve,
with comparison to the B light curves by EB86. The statistical uncertainty
in the errors ()
is 10% as derived from observations.
In the prewhitened uvby light curves, Fig. 2, we notice a
small orbital eccentricity because the secondary minimum occurs
slightly later than half an orbital period after the primary.
During secondary eclipse (full occultation by the
primary)
a minor blueing of the light is seen, clearest in u-b.
The fact that Table 4 shows similar levels of scatter
during the eclipses for light curves over 18 years, and that the old data
fit nicely inside the secondary eclipse's shape as given by the recent
SAT light curves, suggests absence of any significant apsidal motion.
A test for apsidal motion from partly
covered primary and secondary minima, using the SAT data and the
EB86 and JS92 data, also showed that the timing, duration and depth of
the eclipses are stable within the quality level of the available
photometry. The light curves show that the centre of the
secondary minimum is 1.4 h off from the half-period phase.
Based on our SAT data alone, the change in orbital period needed to
position the secondary eclipse exactly half a period from the primary
is 0.11 days. Such a large change is discrepant with the period
determined from the SAT data (even for their 120-days baseline).
The large recent dataset on its own is thus incompatible with the
circular orbit assumed by EB86. Their assumption at that time was logical,
as they did only cover ingress of the secondary eclipse.
A refined ephemeris (Table 5) was then calculated from the
blue light curve. Using the procedure by Lafler & Kinman
(1965) for a fine grid of test periods centered on the period
by EB86, the orbital period was improved to
.
With the
method of Kwee & van Woerden (1956) applied on data in primary
eclipse, our new ephemeris becomes
![]() |
Figure 2: Prewhitened y and u-b light- and colour curves (see text). The binary model from Sect. 5 is superimposed. |
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Figure 3:
The model orbit from RV differences (full line), compared with RVs
from cross-correlations with a template (thick lines). For ![]() |
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The FEROS spectra reveal substantial line-profile variations (LPVs) despite
the exposure time being one tenth of the pulsational cycle. In many cases
the local line depth changes more than a factor of 2 within 70
from the
line-centre during a pulsation cycle, while producing variable subcomponent
line-structure. No secondary spectrum is seen.
To aid in the spectroscopic analysis, two composite spectra were made from FEROS spectra with orbital (model) shifts eliminated: a "103-spectrum composite'', made by averaging all FEROS spectra, and a "narrow-line spectrum composite'' averaged over 10 spectra having similar deep and narrow line profiles. The 103-spectrum composite has S/N = 1000 and is shown in its full extent with line identifications in Hensberge et al. (2004).
Figure 3 shows the final orbit with strings of nightly RVs
superimposed with thick lines. These RVs were obtained by cross-correlating
the FEROS spectra with an average spectrum constructed from all spectra
compensated for nightly orbital shifts. While the orbital radial velocity at
most changes 7
in a single night, the velocity fields may shift the RVs
up to 14
,
which could bias the orbital parameter determination. The
option to eliminate a large part of this bias by averaging over a single night,
or a pulsation cycle, is not attractive since night-to-night bias remains due
to the multi-periodicity, and only in the most recent observing run was the star
monitored continuously.
Therefore, we decided to follow an alternative approach to minimise the
impact of pulsational line-shifts. We refer to this method as
matched-profile RV differences, because the orbit will be derived
from the difference in radial velocity between pairs of spectra
and
for different times
t selected to have similar line profiles. For all possible pairs of
combinations (
), we compute correlations as:
![]() |
Figure 4:
Selection of matching pairs (fat dots) among all combinations for the
criteria (see text): linear cutoff (line), pair elements separated
>4.5 h in
time,
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For the correlations, we found after some tests that the RV information from
the adopted region 4209-4733 Å could not be improved by adding data at
other wavelengths. From the 5253 possible combinations of FEROS spectra,
80 pairs passed our test of line-profile similarity. Figure 4
(big symbols) shows the selected matches for the criteria: linear cutoff
(dashed line),
|ti-tj|>4.5 h,
and
.
These criteria were optimised to eliminate spectral
mismatch while preserving a good phase coverage. The difference of the two
spectra in each matched pair (corrected for orbital shift) was below 5% in
local line-profile mismatch for the He I 4471 Å line, and
typically far less, while the mismatch for disordered pairs was above 30%.
In order to include the ECHELEC spectra, suffering a larger smearing of the
LPVs due to longer exposure time, we averaged up to three consecutive FEROS
spectra as matching templates. The similarity was judged subjectively as it
is evidently less stringent for the noisier ECHELEC spectra.
In total, we selected 101 RV differences for pairs of 107 different orbital
phases. Using an iterative procedure, we optimised the four parameters:
radial-velocity semi-amplitude ,
eccentricity e, time of
periastron passage
,
and periastron longitude
,
by
a least-squares fit to the differential RV measurements for an eccentric
Keplerian orbit,
Table 5: Orbital elements for HD 92024.
Table 6:
Orbital elements from SBOP fitting to RVs made by
cross-correlation of all spectra with the 103-spectrum composite
(cf. Table 5).
.
The
fitting was made for all RVs (Col. 2) and for nightly averages (Col. 3).
In the last column
is rescaled to single velocity
measurements for comparison purposes.
How reliable is the solution in Table 5 compared to classical
orbit-fitting methods? The input RV differences could be seriously affected
by pulsational velocity effects only if constructive interference would mimic
a given line profile shape closely (98% of the RV difference pairs had
already been rejected!) but produce a Doppler shift. In Table 6
two alternative orbit solutions are given for RVs from cross-correlation
of the FEROS and ECHELEC spectra with the 103-spectrum composite. Solutions
for all RVs (Col. 2) and for nightly RV averages (Col. 3) are found using
SBOP (Etzel 1985). The FEROS data were given twice the
weights of the ECHELEC data, and the number of spectra defining the nightly
average was taken into account. The main difference of the SBOP
solutions from our solution is the marginally higher velocity amplitude that
would lead to a 15% increase in the mass function. The fact that the
scatter of the solutions in Table 6 is markedly higher
than for the RV differences (
)
gives support to our method
and shows, a posteriori, that our reliability concern expressed above is
unimportant.
Detection of the faint secondary spectrum may be feasible through spectral
disentangling of the components as e.g. done by Holmgren et
al. (1999). In view of the faintness of the secondary spectrum,
for a B8V star according to the present analysis (see final results,
Tables 11 and 12), its strong hydrogen lines offer
the best chance for detection. Still, their signature will only be on the
1-1.5% level of the total flux. Clearly, detection attempts can only be
efficient after proper consideration of line variability linked to the
pulsations of the primary. Therefore, the spectroscopy presently only
constrains the stellar masses through the mass function f(M)
With static line-profile models (without velocity fields), spectral line-width
only provides an upper limit on the rotation rate. Balona's (1975)
value of 122
represents the straightforward interpretation of the average
line width. Using our narrow-line spectrum composite results in a significantly
lower estimate. From the
- FWHM relation for B0.5-1.5III-IV stars by
Slettebak (1975), the He I 4471 Å line indicates a
projected rotational velocity
.
Using synthetic line profiles, a
similar value
is found from the Si III triplet around
4568 Å.
The uncertainty estimate of 20
reflects the influence from the LPVs as
judged from the deviation of the narrow-line composite's line shape
from a rotational profile.
The stellar radius, determined from the duration of the eclipses,
requires a rotational velocity of
,
if
synchronised with orbit. Synchronisation can therefore not be firmly excluded.
Table 7:
EW-measurements for HD 92024 FEROS spectra and in model lines for
different
temperatures and abundances. The second column lists helium abundance for the
helium lines (using
)
and metal abundance for selected metal
lines (
), while Cols. 3-5 give corresponding model EWs for three
different temperatures. The last columns give EWs for the two composite
spectra, combined from all 103, and from 10 similar spectra.
Theoretical spectra, calculated using the non-LTE line-formation
package DETAIL/SURFACE (Butler & Giddings 1985), were
rotationally broadened through convolution with the rotation profile from Gray
(1976) to 40-100
in steps of 10
.
These models, available
from another investigation, were for: surface gravities
and 4.0,
K in steps of 1000 K, solar helium abundance, and
metal abundances
.
Additional spectra were made with hydrogen and helium lines available for
,
and helium abundances
and -0.15.
A turbulence velocity of 2
was assumed.
In order to estimate the uncertainty introduced by using static models, the analysis was applied to the 103-spectrum composite, as well as to the narrow-line spectrum composite. Fortunately, the EW of these lines does not vary substantially in contrast to their profiles as seen in Table 7 that lists the most important lines used in the analysis. EWs were measured by integrating the average absorption over observed and synthetic profiles of selected lines.
The width of the Balmer lines is consistent with
(Sect. 5), but their line cores are more shallow than those of
the synthetic models, probably due to the broadening of the observed profiles by the LPVs.
The determination of temperature involves to some extent the abundance
of the species producing the temperature-sensitive lines. Mathys et al.
(2002) reported normal abundances for six bright stars in NGC 3293.
They find a marginal overabundance of helium (0.15) and, as is usual for
early B-stars (e.g. Daflon et al. 2001), subsolar metal
abundance with typically
to -0.2. From ultraviolet IUE
spectra, Daszynska et al. (2003) derived solar metallicity
for a subsample of the cluster's
stars.
In the temperature range of early B-stars, lines of ionised helium fade
quickly with decreasing temperature, while lines of neutral helium slowly
become stronger. The only detected He II line is 4686 Å.
For solar helium abundance, ionised helium poses an upper limit to
which is at face value incompatible with the lower limit due to neutral
helium. Therefore subsolar helium abundances were also tested and gave
compatible temperature estimates for
and
= 25 000-26 000 K (Table 7). This also applies for
lines such as He I 4471 Å and He I 4713 Å for
which EW measurements are not listed because of interfering weak blends.
The marginally subsolar helium abundance is likely an artifact of the
simplified modelling done, and verification is outside the scope of this paper.
The Si IV lines are quite temperature-sensitive at the
current temperature range, as opposed to the insensitivity of the
Si III lines. The 25 000-27 000 K range is acceptable for
Si IV for a reasonable range in abundances (solar to subsolar). We note that the Si III lines are somewhat stronger than
expected from static models, again indicating the need for detailed modelling
in Paper II. Carbon and nitrogen lines do not constrain the temperature more
than helium and silicon do, and their relative strengths support the
conclusions derived from these:
K.
We compared our narrow-line spectrum composite to ECHELEC spectra of the
binary
Sco (HD 147165, SpT. B1 III), which has
a
primary with
K,
(mean
values, vander Linden & Butler 1988). The two stars showed
almost identical spectra in the wavelength region 3900-4065 Å,
having similar line widths and strengths. This indicates that they
have essentially the same temperature.
Table 8: Velocity shifts for selected lines in the 103-spectrum composite. Error estimates are deduced from fitting same profiles with different fitting parameters (see text), and the listed shifts are means of the three measurements. Laboratory wavelengths are from Martin et al. (1999). Last column: comments on line strength and profile.
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Figure 5: Two-dimensional power spectra for wavelength regions centered on the Si III 4553 Å ( left) and O II 4596 Å ( right) lines. Owing to insufficient data sampling, strong aliasing makes the significant frequencies appear "smeared''. The three photometric frequencies are indicated ("-''). Note the similarity of the periodicities for the two lines. |
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Figure 6:
Summed power spectrum from the combined O II 4596 Å
and Si III 4553 Å regions ( top). The three photometric
frequencies are indicated with dotted lines. The two lower panels
show the power spectra with respectively one (7.1651
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As a quick test of the efficiency of combining more regions, we used the FEROS
spectra shifted in wavelength to eliminate the orbital shifts. Two different,
relatively strong lines O II 4596 Å and
Si III 4553 Å, were selected and power spectra were computed with
Period98 for bins corresponding in size to 5.5
.
With only 103
spectra, obtained in two short periods of 4-12 days duration and separated
by one year, strong 1, 0.091, 0.003
aliases are unavoidable and limit
the usefulness of the dataset. As seen in Fig. 5, the three
photometric frequencies
f1, f2, f3 (indicated with bars) are prominent
for both line regions. f1 is, however, not unambiguous due to
aliasing from the other two frequencies. Contrary to the photometry,
f3 has highest power. Also notice the higher power for the
stronger Si-line, and that most information is contained inside
Å.
Then, by summing the power spectra for regions with the highest power,
we combine the information in both line-regions to obtain the
summed
one-dimensional periodogram in Fig. 6 (top). Significant
periodicities for all photometric frequencies are seen,
but the strong aliases make unique detections of frequencies
impossible in spite of the strongly enhanced S/N in the periodogram.
We then successively prewhitened the detected frequencies
f3=7.1651
and
f2=6.6640
,
while keeping only frequency fixed during the calculations (as
amplitude and phase vary among and in the lines). The results are
inserted in the lower two panels in the figure.
Due to the substructure of the window function related to the 1-year
baseline, several alias frequencies (e.g. 7.159, 7.162 and 7.165
)
appear with the same power, and any one of these leads to
phase diagrams similar to the ones presented in Fig. 7.
The bottom panel in Fig. 6 with the periodogram for
both frequencies prewhitened still has power at 5.6597, 6.6620 and
12.8655
.
The 5.6597
frequency is probably an alias of f2,
or f1 combined with the alias of the 6.6640
frequency.
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Figure 7:
Integrated-flux variations, in units of normalised flux per pixel,
inside a 5-bin wide core region of Si III 4553 Å. The panels
show phase diagrams for each of the detected pulsational periods, each
successive
one after prewhitening for the previous one above. Sinusoidal fits are
superimposed for the individual frequencies. The panels show the
monochromatic input light curve phased with
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The wavelength-dependent amplitudes and phases of the frequencies
complicate the construction of phase plots corresponding to
Fig. 6. As a simple demonstration of the phased
pulsation modes, Fig. 7 shows phase diagrams
for variations of the integrated normalised flux inside a 5-bin (0.34-Å) wide
core region of Si III 4553 Å; the phases correspond to
(a) and, with f3 prewhitened,
(b). The residuals of f3, f2 prewhitened (panel c)
have rms = 0.011, while a similar region in the continuum, 8 Å blue-ward
of the Si-line, has 0.0051. This rms difference is partly due to the candidate
frequencies seen in Fig. 6 (bottom panel), for which
Fig. 7 (c) shows the phase of the 12.8655
frequency.
Including the latter candidate frequency and adding asymmetry terms
in the fit to f3 and f2 only lowers the residual rms to 0.0010, while
selecting the best alias peaks from the dataset itself
results in an rms = 0.0079. The lower scatter in the continuum window suggests
the presence of more low-amplitude pulsation modes.
We emphasise that all frequencies other than f3 and f2 are ambiguous
in the preliminary spectroscopic analysis presented here.
For the reasons mentioned we will not try to interpret the prewhitened periodogram further than f3 and f2. More important is the significant reduction of noise in the summed power spectrum, showing the feasibility of the method.
The primary's temperature
was fixed to the spectroscopic
value. Bolometric limb darkening coefficients were interpolated in the
tables of Van Hamme (1993): 0.620 (primary) and 0.699 (secondary).
The linear limb darkening coefficients for each
component and passband were fixed to the values calculated by
Diaz-Cordoves et al. (1995):
We tested for orbital eccentricity with the blue light curve and the RVs,
however without weights the RVs had little influence on the solution (107:2262
points). By adjusting
and phase shift d
and then optimising
the size of the orbital semi-major axis
and the mass
ratio q, we got a solution with slightly higher periastron longitude than
from the spectroscopy but again with eccentricity.
We then compared individual solutions for the 5 uvby and blue light
curves, without the RV data but with the orbital parameters a, q fixed.
The agreement was good with less than 2% differences in stellar potentials
and same inclination (85
6
0
4). Because the uvby data gave
results consistent with those from the blue (B+b) light curve,
we did not use the latter in the following part of the photometric analysis.
The unknown mass ratio was evaluated with DC for a grid of different
values of q while optimising the other parameters for each value.
The minimum value of
was then found at
by
using second-degree polynomial interpolation along the q axis. This result
is in agreement with all light curves and the mass ratio was fixed to this
value in the further analysis. Direct confirmation from the spectrum of the
secondary is required, though, before the formal accuracy of q can be
determined. In view of the limited number of RV data compared to photometric
data, appropriate weights were defined to recover with WD the
and e values in Table 5. These weights were hereafter applied
in the remaining analysis. The inclination value was slightly affected by the
inclusion of weights and was optimised with the photometry to
.
DC was then used to evaluate individual light curves with model RVs,
keeping now also periastron longitude, eccentricity, and inclination fixed. The final adopted results of the WD analysis are listed in
Table 9. Introduction of atmosphere models by Kurucz (1993)
brought the u band results in line with those of the other bands; in
particular
was now the same to within 500 K for all passbands.
The geometry, through the stellar potentials and the radii indicating absence
of deformation, also agrees well. The model light curves, superimposed in
Fig. 2, reproduce the colour change during secondary eclipse,
and also reflection effects outside the eclipses seem required.
The rms values of individual solutions given at
the bottom of Table 9 are for the photometry, and the associated
photometric residuals are shown in Fig. 8. Considering
that the eclipse light changes are 2-8 times larger than the pulsations, it
is satisfying that all residuals are smaller than half the pulsation amplitudes
(worst case).
Residuals for the spectroscopy were evaluated by subtracting the 101 measured
RV differences from those predicted by the WD model. This indicated an
rms of 2.6
per pair element.
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Figure 8: Residuals of the uvby light curves from the DC solution with the geometry free (Table 9). Dotted lines delimit the start and end of both eclipses. From top to bottom: y,b,v,u. |
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Table 9:
Wilson-Devinney binary model solutions for the 4 light curves and model
RVs for HD 92024.
.
Assumed were e=0.028,
,
q=0.20,
25 500 K and
.
Stellar radii
are in units of the orbital semi-major axis a.
are the normalised
(
)
light contributions at
phase 0.25. Last row gives number of observations for light curves
and RVs.
The errors listed in Table 9 are output from WD and should
only serve as lower limits on the true errors. Errors for a subset of key
parameters were therefore examined in more detail:
,
,
i and
were changed in turn in grids of test
values, while for each value the other parameters were optimised. Acceptable
parameter values are those occurring in the subspace of allowed
(see Eq. (12) in
Hensberge et al. 2000), where
and
are the random and systematic contributions. The factor
1.056 defines the 95% confidence level, assuming that the
sum is
built up from residuals due to random errors in the data as well as from
systematic contributions, and that only the term due to random errors increases
when there is a slight deviation from the best-fit solutions. In our case, systematic
contributions are primarily due to the influence of the pulsations. Despite
our carefulness, they strongly dominate the residuals in the photometry
(Fig. 8). For the light curves, the residuals of the
best-fit model have an rms of 5 mmag, while the expected (theoretical) random
noise should only contribute an rms of 3 mmag (b-band). We note that the
best-fit values for the individual potentials, contrary to their ratio, are
strongly correlated with the inclination i. Hence, we list in
Table 10 the large uncertainty in
and
from the corresponding uncertainty in i, as well as the
small uncertainty in
.
The ratio of the temperatures is reflected by the depth of the shallow
total eclipse and may be sensitive to the systematic residuals after the
prewhitening. Therefore, we computed the rms error in the depth when offsets
for light curves from different nights are taken explicitly into account, and
also performed WD solutions using only subsets of the same light curve.
We conclude that the uncertainty in the eclipse depth is 2 mmag, or a change
of 1000 K in temperature of the secondary, slightly higher than the 770 K
indicated by the analysis of acceptable
subspace (95% conf. level).
Table 10 also lists the means of the relative radii, with
WD errors.
Some of the advantages of a simultaneous solution for multiple passbands are
that one avoids inconsistencies among solutions of individual light curves
and that the number of free parameters is reduced. For comparison, we
therefore also
performed a simultaneous uvby and RV evaluation, made for two subsets
,
,
and
,
to avoid fitting correlated parameters. The resulting
values
,
,
and also the luminosities were all in good
agreement with those of Table 9.
Consequently, we fix the geometry to the mean values in Table 9 and re-evaluate the temperature and luminosities to get the passband-dependent luminosity ratios. Table 11 presents the solution. There is good correspondence of the evaluated parameters for different passbands, seen both in potentials and sigma's for the solutions. The effective temperature range is now within 250 K, which is mainly caused by a changed temperature in the y passband.
Table 10:
Mean elements for HD 92024.
= 25 500.
Table 11:
Wilson-Devinney binary model solution for HD 92024 for fixed mean geometry
from Table 9. q = 0.20 and
K.
The resulting mean temperature is
K.
In addition to the relative radii
given in Table 9,
WD gives as output the masses
and mean radii
,
expressed in solar units, the surface gravities (cgs units) and the bolometric
magnitudes for both components. These results are given in
Table 12. Errors are based on the accuracies of the radial
velocity amplitude, the mass ratio, the relative radii and the inclination;
errors in the masses are from Sect. 4.1.
As shown by Sterken & Jerzykiewicz (1993), the Strömgren indices for the system correspond to MK type B1 III. The secondary star's temperature and surface gravity from the dynamical analysis (Table 12) correspond (Lester et al. 1986) to indices c0=0.658, m0=0.118, which, according to Crawford's (1978) average parameters are equivalent to MK type B8V. When taking the uncertainty in temperature and gravity into account, the possible types of the secondary are B7V-B9V.
Using bolometric corrections from Flower (1996), we derive
the absolute magnitudes from the bolometric magnitudes output by WD.
As given in the table, they correspond to a systemic distance of
kpc, in excellent agreement with the cluster distance estimate
by Baume et al. (2003).
Table 12:
Astrophysical data for HD 92024.
is assumed, and
kg
and
m3 kg-1 s-2 are from Seidelmann
(1992). Bolometric corrections are from Flower (1996).
![]() |
Figure 9:
The positions of the components of HD 92024 in an evolutionary
diagram for ![]() ![]() ![]() |
Open with DEXTER |
Acknowledgements
Part of this research was carried out in the framework of the "IAP P5/36'' project of the Belgian Federal Science Policy, and was supported by the Belgian Fund for Scientific Research (FWO) and the Flemish Ministry for Foreign Policy, European Affairs, Science and Technology, under contract BIL 01/2. Support from the project "Structure and evolution of stars - new insight from eclipsing binaries and pulsating stars'' by the Danish National Science Research Council is acknowledged. We thank Jens Viggo Clausen, Erik Heyn Olsen and Bodil Helt for their invaluable guidance in planning and retrieving the SAT data, the ESO staff for assistance during the observations, and C. Papadaki and M. Y. Bouzid for some SAT observations obtained in a combined observing effort. We wish to thank the referee Prof. P. Harmanec for constructive criticism and useful comments which all improved the paper. We have made use of the Simbad database, operated by the CDS, Strasbourg, France, the ESO-MIDAS and NOAO-IRAF software, and the Wilson-Devinney code.