A&A 382, 157-163 (2002)
DOI: 10.1051/0004-6361:20011623
E. Poretti1 - D. Buzasi2 - R. Laher3 - J. Catanzarite4 - T. Conrow5
1 - Osservatorio Astronomico di Brera, Via Bianchi 46,
23807 Merate, Italy
2 -
Department of Physics, 2354 Fairchild Drive, US Air Force Academy,
CO 80840, USA
3 -
SIRTF Science Center, California Institute of Technology, MS 314-6,
Pasadena, CA 91125, USA
4 -
Interferometry Science Center, California Institute of
Technology, MS 100-22, Pasadena, CA 91125, USA
5 -
Infrared Processing and Analysis Center, California Insitute of
Technology, MS 100-22, Pasadena,
CA 91125, USA
Received 16 October 2001 / Accepted 7 November 2001
Abstract
The bright variable star Tau was monitored with the star camera
on the Wide-Field Infrared Explorer satellite. Twelve independent
frequencies were detected down to the 0.5 mmag amplitude level.
Their reality was investigated by searching for them using
two different algorithms and by some internal checks: both procedures
strengthened our confidence in the results.
All the frequencies are in the range
10.8-14.6 cd-1. The histogram of the frequency spacings
shows that 81% are below 1.8 cd-1; rotation may thus play a role
in the mode excitation.
The fundamental radial mode is not observed, although it is expected to occur
in a region
where the noise level is very low (55
mag). The rms residual is about
two times lower than
that usually obtained from successful ground-based
multisite campaigns. The comparison of the results of previous campaigns
with the new ones establishes the amplitude variability of some modes.
Key words: methods: data analysis - techniques: photometric - stars:
individual:
Tau -
stars: oscillations - stars: variable:
Sct
Soon after launch in March 1999, the primary science instrument onboard
the Wide-Field Infrared Explorer (WIRE) satellite failed due to loss
of coolant. However, it proved possible to begin an asteroseismology program
using the 52-mm aperture star camera. A few bright stars were
monitored
with the
SITe CCD in a bandpass approximately equivalent to
V+R; further details about the orbit, the detector and the raw data
reduction can be found in Buzasi et al. (2000) and Buzasi (2000).
The prospect of future space-based asteroseismology missions ( COROT,
MONS, MOST)
has increased interest in
bright variable stars, a bit neglected in the past in favour of the 6-8 mag stars better-suited to differential photoelectric photometry
from the ground.
Tau thus constituted both a good scientific target and a useful test for
asteroseismology from space.
Tau was monitored from August 2 to 21, 2000;
the original dataset consists of 1049155 points. The typical
time interval between two consecutive measurements is 0.5 s,
resulting in
an over-sampling of the light variability.
As the luminosity
of
Tau varies by a negligible amount in one minute or so,
we grouped the data in 60-s bins, obtaining a dataset
composed of 8958 normal points.
The average value of the 8958 standard deviations
yields us the
observational error on a single 0.5-s integration, i.e. 5.9 mmag.
As the mean level is 13091.09 ADU and the gain is
15
ADU,
the resulting photon noise is 2.4 mmag on a single 0.5-s integration.
As the observational error is more than twice the photon noise, it is
evident that other error sources are introduced by the
frame reading process.
The binning procedure we adopted reduced the error to about 0.5 mmag (standard error of the mean).
The orbital period of the WIRE satellite is 5741 s.
The interruption of about 3480 s (duty cycle 40%) in each orbit
simulates a night/day effect which originates in the spectral window shown
in Fig. 1, dominated by the aliases at 15.05 cd-1.
Since the pulsational content of
Tau is expected to be very dense and confined to a small frequency
range, it is a great advantage to have the alias region very far from
that range. The data span an interval of about 18.5 d,
giving a frequency resolution of about 0.05 d-1.
![]() |
Figure 1:
Window function of the ![]() |
Open with DEXTER |
The changing observational conditions (varying temperature, scattered light, etc.) caused by the satellite orbit, the jitter of the stellar image on the detector (a problem accentuated by the lack of a flat field) and the short duty cycle are expected to introduce systematic deviations. As a consequence, in our analysis we considered the frequencies we detected at the orbital value (15.05 cd-1), the duty cycle (26.19 cd-1) and f<1 cd-1 as spurious terms originated by these effects. The term at low frequency is also detected in the power spectrum of the coordinates of the stellar centroid and hence no doubt is left as to its instrumental origin.
Considering the long period of the spectroscopic binary and its small error bar, it is possible to calculate the orbital phases of the WIRE run. We verified that it is located in the phase interval 0.50-0.64, where the light time correction is very small and practically constant (see Fig. 6 in Breger et al. 1989). Therefore, we have not introduced such a correction.
Figure 2 shows the light curve of Tau derived from the 8958
averaged 60-s bins: the three spurious periodicities
at 15.05 cd-1, 26.19 cd-1and f<1 cd-1 have been removed. To do that,
after having obtained a first solution we applied a least-squares
fit and then we removed the contribution of the three periodicities from the
data.
Instrumental magnitudes are
( ADU), where ADU are measured
in 0.5-s intervals. Light variability and beating phenomena are
evident.
![]() |
Figure 2:
The light curve of ![]() |
Open with DEXTER |
To detect the periodicities in the light curve,
we used the least-squares iterative sine-wave
fitting approach (Vanicek 1971). It consists of the simultaneous
least-squares
fit of n+1 sinusoids, where n represents the number
of the previously identified terms (known constituents, hereinafter
k.c.) and n+1 is the number of terms of the new trial
solution.
The reduction factor (i.e. how much the variance is reduced
by the n+1 frequency with respect to that calculated with the nfrequency solution) is given for each trial frequency in the range
0-50 cd-1. This technique
is particularly suited to the case of multiperiodic light curves because
it does not require any prewhitening of the data. Indeed, the
amplitudes and phases of the terms previously identified are
recalculated when searching for the new one, i.e. only the frequency
values of the k.c.'s are kept constant. To avoid any possible
misidentification, we refined the frequency values by a non-linear least-squares
fit after the inclusion of a new term.
Figure 3 shows the step-by-step detection by the
iterative sine-wave fittig procedure; the frequency values are listed in
Table 1.
![]() |
Figure 3:
The least-squares power spectra of the WIRE observations of
![]() |
Open with DEXTER |
One of the most critical aspects in the signal detection concerns
the decision as to which peaks in the power spectrum can
be considered as intrinsic to the star. Due to the presence of nonrandom
errors
and because of observing gaps, the prediction of statistical false-alarm
tests give answers which are generally optimistic.
To consider as real the peaks having S/N>4.0
is a conservative trade-off
used by observers (Breger et al. 1993) and justified from a theoretical
point
of view (Kuschnig et al. 1997). Therefore, we calculated
the noise by averaging the amplitudes over a 10 cd-1region centered
around the frequency under consideration; as sampling step, we used
1/20,
i.e. about 0.0025 cd-1. The S/N values calculated by
this way are listed in
Table 1.
We duplicated the analysis by using the CLEAN algorithm (Roberts et al. 1987): again we detected
the same frequencies (Fig. 4). This is not surprising,
since the spectral window
does not interact with the signal. In turn, it means that in the
case of Tau the sampling ensured by the WIRE monitoring has been very
effective.
To avoid supporting the frequency detection solely on a statistical
basis, we performed further checks.
Looking closely at the frequency values shows
that, not considering the smallest amplitude term
f12=11.72 cd-1, the shortest
separation is
13.69-13.48=0.21 cd-1. That means it is possible to
perform the frequency analysis after first subdividing the dataset into two
subsets. These frequency analyses detected the same terms as in the
whole dataset. We calculated the least-squares fits on the two subsets,
taking care not to consider the unresolved, small amplitude f12 term.
Moreover, Table 1
reports the parameters of the least-squares fit on all the
data, on the first half of the data (4367 points before HJD 2451768.5) and
on the second half of the data (4591 points after HJD 2451768.5). The average
error bars reported in Table 1 are at the
level.
Since we detected the same terms, in most of cases with the same amplitudes
and the same phases (within error bars), we are confident of the reality
of the frequencies listed in Table 1. Note also that the
f1 and the f10 terms are separated by 1.006 cd-1; to resolve them
by single-site ground observation would prove a very hard task.
Formal errors (as derived from the least-squares fit) are of the
order of 10-4 cd-1for the highest amplitude terms and a few 10-3 cd-1
for the others.
All the data | First half of the data | Second half of the data | |||||||||
Frequency | Frequency | S/N | Amplitude | Phase | Amplitude | Phase | Amplitude | Phase | |||
[cd-1] | [![]() |
[mmag] | [rad] | [mmag] | [rad] | [mmag] | [rad] | ||||
f1 | 13.6972 | 158.532 | 9.8 | 6.50 | 5.01 | 6.56 | 5.01 | 6.45 | 5.00 | ||
f2 | 14.3213 | 165.756 | 7.8 | 3.22 | 3.72 | 3.20 | 3.73 | 3.21 | 3.73 | ||
f3 | 13.2294 | 153.118 | 7.5 | 2.51 | 1.23 | 2.87 | 1.21 | 2.18 | 1.27 | ||
f4 | 11.7718 | 136.248 | 5.8 | 1.47 | 3.73 | 1.22 | 3.98 | 1.89 | 3.68 | ||
f5 | 12.8331 | 148.531 | 5.7 | 1.45 | 0.15 | 1.46 | 0.17 | 1.48 | 0.12 | ||
f6 | 13.4870 | 156.099 | 6.1 | 1.32 | 5.12 | 1.32 | 5.15 | 1.30 | 5.02 | ||
f7 | 10.8613 | 125.709 | 5.8 | 1.07 | 5.68 | 1.11 | 5.70 | 0.99 | 5.61 | ||
f8 | 12.4043 | 143.568 | 5.3 | 0.83 | 4.98 | 0.81 | 5.10 | 0.92 | 4.95 | ||
f9 | 14.6104 | 169.102 | 4.7 | 0.72 | 2.94 | 0.53 | 3.11 | 0.91 | 2.86 | ||
f10 | 12.7031 | 147.027 | 5.1 | 0.68 | 3.92 | 0.54 | 3.96 | 0.76 | 3.90 | ||
f11 | 12.1274 | 140.363 | 4.5 | 0.55 | 1.40 | 0.35 | 1.05 | 0.73 | 1.51 | ||
f12 | 11.7278 | 135.739 | 4.4 | 0.55 | 0.99 | - | - | - | - | ||
Average errors (2![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
![]() |
|||||
Residual rms | 1.45 mmag | 1.36 mmag | 1.49 mmag |
We conclude that we have identified 12 independent terms in the WIRE light
curve of Tau, down to 0.5 mmag half-amplitude level. This is the same
limit reached on FG Vir,
the
Sct star best studied from the ground. However, it should
be noted that for FG Vir this threshold was obtained by combining 3
different campaigns
(one of which was a multisite one involving six observatories for
40 d) spanning 10 years (Breger et al. 1998).
It should also be noted that the residual rms of only 1.5 mmag is much smaller
than that obtained from multisite ground-based campaigns; it is the
limit sporadically reached in ground observatories located in very good
photometric sites.
To demonstrate the goodness of the least-squares solution,
Fig. 5 shows the 12-term fit of the normal points in a part of the
WIRE light
curve where beating is evident: as it can be seen, the agreement
between observations and fit is excellent.
Figure 5 also shows the
characteristic sampling of the WIRE time-series.
![]() |
Figure 4:
The CLEANed power spectrum of the WIRE observations of
![]() |
Open with DEXTER |
![]() |
Figure 5: The fit of a part of the WIRE light curve where beating is evident. The residual rms of the fit is 1.5 mmag. |
Open with DEXTER |
Breger et al. (1989) used the following
stellar parameters of Tau:
K. These values are
very similar to those adopted by Torres et al. (1997).
After applying the bolometric correction (Straizys & Kuriliene 1981),
we can introduce them in the equation (Breger 2000)
![]() |
(1) |
Kennelly & Walker (1996) reported spectroscopic observations of Tau;
in addition to f1, they also detected
a high-degree mode at 16.0 cd-1. Around that value, the noise level in our
residual
power spectrum is 0.12 mmag and no significant peak stands up.
If the term reported by Kennelly & Walker is real,
then the lack of detectable amplitude variation
in the WIRE photometric series implies that
cancellation effects are very effective on the integrated flux, thus
confirming the high
degree of this mode.
The stability and the lifetime of the modes is an open point in
asteroseismology.
As Tau was observed in the past, we can compare the previous results with
the new ones. Breger et al. (1987) identified the f3, f6, f1 and
f2
terms. Breger et al. (1989) added a fifth term, i.e. f9. Li et al. (1997)
confirmed these five terms, but claimed evidence for amplitude variability
not
reported by Breger et al. (1989).
It is immediately obvious that the relative strengths of the modes have
changed.
In the WIRE dataset
f1 is by far the term with the largest amplitude, while it is only the
third-largest in Breger et al. (1989) and the fifth-largest in Li et al.
(1997). The largest amplitude term
is f3 in Breger et al. (1989) and f6 in Li et al. (1997). Note that
the
1 cd-1 alias interaction is possible only between f1 and f10 and,
marginally, between f5 and f7. Also taking into account that the main
results from Breger et al. were obtained from
a multisite campaign, the observed changes strengthen the hypothesis
of an amplitude variability rather than an interaction between aliases.
![]() |
Figure 6: The residual least-squares power spectrum obtained considering the 12 terms as k.c.'s; the predicted position of the unobserved radial fundamental mode is indicated as a dashed line. The reduction factor indicates how much the variance is reduced by the 13-th frequency with respect to that calculated with the 12-frequency solution. |
Open with DEXTER |
We also performed some simulations by introducing
an artificial drift of the f1 amplitude to verify what threshold
can originate a discernible effect.
We found that a spurious peak near f1appears for a linear drift as large as 0.08 mmag d-1, i.e for an
amplitude variability attaining 12% of the full amplitude of f1.
Looking at Fig. 6 we can see that only a minor
peak is visible at 13.23 cd-1 and no peak is close to the highest amplitude
term
f1=13.697 cd-1. The only pair suggestive of the presence of
amplitude variability is that composed of the f12 and
f4 terms (see Table 1). However, the relative amplitude
variability of the small amplitude f4 term would have to be very large
to produce such an effect, and that seems unlikely.
Therefore, we cannot infer any significant amplitude variability
of the detected terms
over the 18.5-d baseline covered by the WIRE observations.
It should be noted that some
Scuti stars do
display amplitude variability on this timescale (XX Pyx, Handler et al.
1998).
![]() |
Figure 7: Histograms of the frequency spacings between all the frequency pairs (12 independent modes). |
Open with DEXTER |
The frequency distribution of the modes
can be very different from one
Scuti star to the next (see Fig. 4
in Poretti 2000).
Tau displays a single bunch of frequencies, whose
average value makes
Tau more similar to
to 4 CVn rather than XX Pyx; in any case, there is
no hint of two bunches of frequencies as in FG Vir. The investigation of
regularities in the frequency spacing distribution can supply details about
the stellar structure. Figure 7 shows the histogram of the
differences
between all the frequency pairs; there is no particular peak, and
81% of spacings are concentrated below 1.8 d. Below this limit, the
distribution is smooth; the more recurrent spacing is about 0.70 d.
Breger et al. (1989) concluded that the rotational splitting alone was not
able to explain the frequency spectrum they observed in the second multisite
campaign. They predicted that adjacent m values would be separated by
![]() |
(2) |
The results obtained on Tau demonstrated the powerful capability
of a small instrument measuring stars from space, especially considering
that this particular use was unplanned.
In fact, the WIRE monitoring reported here puts
Tau among
the best studied
Sct stars, i.e. among stars intensively observed
from ground by a large use of telescopes and manpower.
The detection of the 12 terms having full-amplitude at the mmag level
lowered the rms residual down to 1.5 mmag, i.e. about three times the observational
error of the time series constituted by the 8958 normal points. Even admitting
other possible instrumental sources of errors,
that means that very probably undetected terms are again hidden in the light
curve; since they should have very small amplitude, they may be
very numerous. Therefore,
Sct stars are confirmed as particularly
interesting targets for asteroseismology.
The interaction between spurious terms and signal is a
further complication: the spurious terms
can be removed only on the basis of a step-by-step analysis and
a careful evaluation of their effect on the physical ones.
In the specific case of
Tau, we had no problems with the f=26.19 cd-1 and f<1 cd-1 terms,
since they are far away from the frequencies where the signal is observed.
However,
f=15.05 cd-1, i.e. the term introduced by the
orbital period, masks from us a region where signal could be observed.
From a physical point of view, WIRE monitoring demonstrates us that Tau is an
interesting
Sct star, showing numerous excited modes
(and likely many more have not been detected yet) and amplitude
variability. As we detected excited
terms only in a narrow interval, it is very probable that
they originate from the primary component only.
The only drawback of the WIRE dataset is its relatively poor frequency
resolution
compared to ground-based multi-site efforts,
though this does not constitute a serious problem for the generally well separated
frequencies of Tau. However, close pairs of frequencies are observed
when going down to smallest amplitude: the requirement to achieve good frequency
resolution is essential to the success of future asteroseismological space missions.
Acknowledgements
We gratefully acknowledge the support of Harley Thronson, Phillipe Crane, Daniel Golombek, and Joe Bredekamp at NASA Headquarters for making this use of WIRE possible. The hard work of many people, including the WIRE operations and spacecraft teams at GSFC and the timeline generation team at IPAC, was essential to the success of this project. While it is impractical to single out everyone who contributed, we would particularly like to thank Carol Lonsdale at IPAC and David Everett and Patrick Crouse at GSFC for their efforts above and beyond the call of duty.