Issue |
A&A
Volume 506, Number 1, October IV 2009
The CoRoT space mission: early results
|
|
---|---|---|
Page(s) | 189 - 201 | |
Section | Stellar structure and evolution | |
DOI | https://doi.org/10.1051/0004-6361/200811510 | |
Published online | 01 April 2009 |
The CoRoT space mission: early results
Pulsation modes in rapidly rotating stellar models based on the self-consistent field method
D. R. Reese1 - K. B. MacGregor2 - S. Jackson2 - A. Skumanich2 - T. S. Metcalfe2
1 - Department of Applied Mathematics,
University of Sheffield,
Hicks Building,
Hounsfield Road,
S3 7RH,
Sheffield, UK
2 -
High Altitude Observatory, National Center for Atmospheric Research,
Boulder, CO 80307, USA
Received 12 December 2008 / Accepted 23 March 2009
Abstract
Context. New observational means such as the space missions CoRoT and Kepler and ground-based networks are and will be collecting stellar pulsation data with unprecedented accuracy. A significant fraction of the stars in which pulsations are observed are rotating rapidly.
Aims. Our aim is to characterise pulsation modes in rapidly rotating stellar models so as to be able to interpret asteroseismic data from such stars.
Methods. A new pulsation code is applied to stellar models based on the self-consistent field (SCF) method.
Results. Pulsation modes in SCF models follow a similar behaviour to those in uniformly rotating polytropic models, provided that the rotation profile is not too differential. Pulsation modes fall into different categories, the three main ones being island, chaotic, and whispering gallery modes, which are rotating counterparts to modes with low, medium, and high
values, respectively. The frequencies of the island modes follow an asymptotic pattern quite similar to what was found for polytropic models. Extending this asymptotic formula to higher azimuthal orders reveals more subtle behaviour as a function of m and provides a first estimate of the average advection of pulsation modes by rotation. Further calculations based on a variational principle confirm this estimate and provide rotation kernels that could be used in inversion methods. When the rotation profile becomes highly differential, it becomes more and more difficult to find island and whispering gallery modes at low azimuthal orders. At high azimuthal orders, whispering gallery modes, and in some cases island modes, reappear.
Conclusions. The asymptotic formula found for frequencies of island modes can potentially serve as the basis of a mode identification scheme in rapidly rotating stars when the rotation profile is not too differential.
Key words: stars: oscillations - stars: rotation
1 Introduction
New observational means are and will be collecting stellar pulsation data with unprecedented accuracy. The space mission CoRoT has considerably lowered the detection threshold for pulsation modes, thus allowing photometric observation of solar-like pulsations in stars other than the Sun and increasing the number of detected modes in early-type stars. The forthcoming space mission Kepler will add a wealth of pulsation data by observing a large number of stars for a period of four years. Other projects include the space mission PLATO as well as ground-based networks such as SONG.
Stellar pulsations yield valuable information on the internal structure of stars which can be used to constrain stellar evolution models. Although a great deal of success has been achieved in probing the internal structure of the Sun and of a number of other stars, a number of difficulties arise for rapidly rotating stars. Indeed, rapid stellar rotation introduces a number of phenomena which considerably complicate their modelling and the study of their pulsation modes. These include centrifugal deformation, gravity darkening, baroclinic flows and various forms of turbulence and transport phenomena (e.g. Rieutord, 2006b). As a result, the internal structure of these stars remains difficult to probe.
Traditionally, the effects of rotation on pulsation modes have been
modelled using the perturbative approach. In this approach, rotation is taken
into account through corrections which are added to the non-rotating solutions.
The underlying assumption in this method is that the rotation rate, ,
can be treated as a small parameter, thus enabling one to develop the
perturbative corrections as a power series in
.
Such series can be
extended to first (Cowling & Newing 1949; Ledoux 1951), second (Saio 1981;
Gough & Thompson 1990; Dziembowski & Goode 1992) or third order in
(Soufi et al. 1998;
Karami et al. 2005). A natural question to ask is up to what rotation rate is this
approach valid. This remained an open question until Reese et al. (2006) applied
a non-perturbative two-dimensional approach to calculating acoustic pulsations
in polytropic stellar models and compared the results with perturbative
calculations. Their results showed that perturbative methods remain valid only
for values which are lower than the rotation rate of many early-type stars.
Further comparisons between the two approaches include those by
Lovekin & Deupree (2008), in which more realistic models were used but at a lower
accuracy, and Ouazzani et al. (2009), in which the effects of avoided crossings
are included in the perturbative calculations.
Due to the limitations of the perturbative method, a number of recent
studies have focused on modelling the effects of rapid rotation on stellar
acoustic pulsations using a two-dimensional approach. Espinosa et al. (2004)
studied the effects of rapid rotation on frequency multiplets in models with a
uniform density and also briefly discussed pulsations of realistic models. They
showed how rotation leads to highly non-uniform multiplets and causes the
frequencies of adjacent modes to pair up, thus providing a tentative explanation
for observed close frequency pairs (Breger & Pamyatnykh, 2006).
Lignières et al. (2001) studied pulsation modes in a uniform density
spheroid using a perturbative method and two different numerical approaches.
This was done in order to validate their two-dimensional numerical method before
applying it to more realistic models. Their work was followed by
Lignières et al. (2006), Reese et al. (2006) and Reese et al. (2008a) who did the first
accurate calculations of p-modes in rapidly rotating polytropic models. They
investigated the limits of the perturbative approach, studied disk averaging
factors which intervene in mode visibility, compared the effects of the
centrifugal and Coriolis forces and found an empirical formula which
characterises the structure of the frequency spectrum for low degree modes. At
the same time, Lignières & Georgeot (2008) and Lignières & Georgeot (2009) applied ray
dynamics to the study of acoustic modes in rotating polytropic models. They
classified modes into several categories, the main ones being island,
chaotic, and whispering gallery modes which are rotating counterparts to
modes with low, intermediate, and high
values, where
is the
harmonic degree and m the azimuthal order. They showed that each category
has its own frequency organisation and provided an explanation
involving travel time integrals for the empirical formula found in
Lignières et al. (2006) and Reese et al. (2008a). Finally, Lovekin & Deupree (2008) and
Lovekin et al. (2009) studied p-modes with low radial orders in realistic models
from Deupree (1990) and Deupree (1995) with both uniform and
differential rotation. They investigated how frequencies and the large and small
separations vary with uniform or differential rotation and compared their
calculations with a perturbative approach.
Before being able to interpret pulsation modes in observed stars, more progress
is needed in understanding the effects of rotation on pulsation modes. Indeed,
although a number of important results have been established for p-modes in
polytropic models, these need to be extended to more realistic models. The
calculations involving more realistic models have currently been limited to
small mode sets and the analysis has not been pushed far enough to see whether
similar results apply. In what follows, we calculate pulsation modes, using the
numerical method developed in Lignières et al. (2006) and Reese et al. (2006), in
realistic models of rapidly rotating stars based on the self-consistent field
(SCF) method (Jackson et al. 2005; MacGregor et al. 2007). In particular, we investigate
whether a similar mode classification exists in these models, whether a similar
empirical formula applies to frequencies of modes with low
values, and
quantify the effects of using a differential profile. The next section deals
with the SCF method and the models it produces. The following section explains
the pulsation equations, the numerical method used for calculating the pulsation
modes and a number of tests to validate the method. Afterwards,
Sects. 3 and 4
describe the results for models with mildly and strongly differential rotation,
respectively. Our conclusions are summarised in Sect. 5.
2 Stellar models based on the SCF method
The SCF method is an iterative procedure for solving the equations that govern the structure of a conservatively rotating star. The basic approach underlying the method is to alternately solve Poisson's equation to derive the 2D shapes of equipotential surfaces, and the equations of mass, momentum, and energy conservation to obtain the 1D profiles of thermodynamic quantities along a radius in the rotational equatorial plane. As described in detail in Jackson et al. (2005), this procedure yields a sequence of models which, under most circumstances, converges to a model that satisfies all the equations for a prescribed internal rotation law.
The method was first developed and used 40 years ago to compute uniformly and
differentially rotating polytropic stellar models (Ostriker & Mark, 1968).
Although subsequently extended through the incorporation of more realistic input
physics (Jackson, 1970), application of the method was limited to massive
stars, a consequence of convergence difficulties encountered in lower mass
models with sufficiently high values of the central mass concentration
(see, e.g., Clement, 1978). This problem was addressed and remedied
through a reformulation of the method in which the normalised distributions of
thermodynamic quantities and the central values of those quantities are adjusted
in separate iterative loops. The new SCF method has been implemented in
a code that utilises up-to-date input physics. The opacities are obtained from
the tables of OPAL opacities computed by Rogers & Iglesias (1992) and from tables of
low-temperature opacities compiled by Alexander & Ferguson (1994), using interpolation
subroutines written by Vandenberg (1983). The equation of state for the
stellar material is calculated according to the formula of Eggleton et al. (1973),
and the nuclear energy generation rates for hydrogen burning are from
Caughlin & Fowler (1988), with the treatment of electron screening effects from
Graboske et al. (1973) for the case of equilibrium abundances of CNO isotopes.
Energy transport in sub-photospheric convective envelopes is treated using a
standard mixing-length model (see, e.g., Kippenhahn et al., 1967), in which the
local gravitational acceleration
is replaced by the value of
as reduced by the local centrifugal acceleration, averaged over
equipotential surfaces. For the models utilised in the pulsation mode
computations described in subsequent sections, a value of 1.9 was adopted for
the ratio of the mixing length to the pressure scale height. The method and the
code are both robust and rapidly convergent, and have been thoroughly tested and
validated through such applications as the interpretation of interferometric
observations of rapid rotators like the Be star Achernar (Jackson et al., 2004, and references
therein) and an examination of the effects of differential rotation
on the structure of stars less massive than 2
(MacGregor et al., 2007).
Models computed using the SCF method are chemically homogeneous, ZAMS
models with the following abundance fractions by weight of H, He, and heavy
elements: X=0.7112, Y=0.27, and Z=0.0188. The rotation profile is imposed
beforehand and is conservative, i.e. the centrifugal force derives from a
potential. As a result, the stellar structure is barotropic - different
thermodynamic quantities remain constant along lines of constant total
(centrifugal plus gravitational) potential. The rotation profile used in the
present calculations was:
where s is the distance from the rotation axis,







Equation (1) corresponds to a rotation profile in which the rotation rate decreases with s. Such profiles can be used to construct highly distorted configurations. Indeed, the stellar core can be made to rotate quite rapidly since the local break-up velocity is larger than at the equator. This type of model was used to try to explain Achernar's extreme oblateness (Jackson et al., 2004). The SCF method can also produce models with a rotation rate that increases with distance from the rotation axis. This resembles somewhat the solar rotation profile in which the rotation rate increases with decreasing latitude in the convection zone (Schou et al. 1998; Thompson et al. 2003).
2.1 The pulsation equations
In order to derive the set of equations which govern acoustic pulsation modes
in a differentially rotating star, we start by representing the differential
rotation by a permanent background flow
.
In what
follows, we will work with cylindrical coordinates
and their
associated unit vectors
.
We write out the Eulerian perturbation
to various equations, starting with Euler's equation, and only keep first order
linear terms:
where quantities with the subscript ``o'' are equilibrium quantities, and those without a subscript Eulerian perturbations. The quantity


![]() |
= | ![]() |
(3) |
![]() |
= | ![]() |
(4) |
![]() |
= | ![]() |
(5) |
where we have assumed an



where we have assumed an



In terms of

The Eulerian perturbation to Poisson's equation is simply:
where G is the gravitational constant. These equations are then supplemented by the adiabatic relation between the pressure and density perturbations which takes on the following form:
where






2.2 Non-dimensional form
These equations are then put into non-dimensional form using the following length, density and pressure scale factors:![]() |
(12) |
where the subscript ``c'' refers to the centre of the star, and


![]() |
(13) |
Based on these scale factors, all of the above equations remain the same as in dimensional form, except for Poisson's equation where a non-dimensional factor

2.3 Spheroidal geometry
In order to achieve higher accuracy when solving these equations numerically, a coordinate system which follows the shape of the star is introduced. This new coordinate system

for
![$\zeta \in [0,1]$](/articles/aa/full_html/2009/40/aa11510-08/img75.png)




for
![$\zeta \in [1,2]$](/articles/aa/full_html/2009/40/aa11510-08/img81.png)






Another possibility would be to base the radial coordinate on the
equipotentials. This has the advantage of simplifying the pulsation equations
because terms such as
and
vanish.
However, this requires using numerical rather than analytical differentiation
when calculating terms with radial derivatives such as
,
thereby reducing
the accuracy of the results. Furthermore, the regularity conditions
in the centre of the star become more complicated as the equipotentials
do not in general become circular towards the centre.
Based on the coordinate system presented above, the continuity
equation becomes:
Euler's equation takes on the following form:
the adiabatic relation is given by:
and Poisson's equation takes on the following form:
where







![]() |
= | ![]() |
|
![]() |
(23) | ||
![]() |
= | ![]() |
(24) |
The above expressions are obtained by using tensorial expressions for the differential operators which intervene and working them out explicitly. Furthermore, the components to the velocity are written on the following basis:
![]() |
(25) |
where




Equations (17-22) were completed with a number of boundary conditions which ensure that the solution remains regular in the centre, the Lagrangian pressure perturbation vanishes on the stellar surface and the perturbation to the gravitational potential goes to zero at an infinite distance from the star.
![]() |
Figure 1:
Evolution of various forms of the frequency error with
|
Open with DEXTER |
2.4 Numerics
The above equations were then projected onto the spherical harmonic basis in the
same way as was done in Lignières et al. (2006) and Reese et al. (2006). This is
achieved by expressing the different unknowns as a sum of scalar or vectorial
spherical harmonics multiplied by unknown radial functions, and then projecting
the equations themselves onto the spherical harmonic basis, using
Gaussian quadrature to numerically perform the integrations. The resultant
system is an infinite system of coupled ordinary differential equations in terms
of the radial variable
which is truncated at a maximal harmonic degree
.
The solution to this system yields the radial functions used
in the harmonic decomposition of the different unknowns.
This system of ordinary differential equations is discretised using one of three
methods: a spectral method based on Chebyshev polynomials, finite differences or
a polynomial spline-based method. In the latter two cases, the order
can be adjusted. When applying these methods, the stellar model is
interpolated onto either a higher resolution uniform grid or a Chebyshev
Gauss-Lobatto collocation grid using cubic spline interpolation. For the
spectral method, this is analogous to what was done in Dintrans & Rieutord (2000) in
which a
CESAM model was interpolated onto the same type of
collocation grid before being used to calculate gravito-inertial modes.
After discretisation, the eigenvalue problem is in algebraic form:
where
and
are
square matrices. With a suitable choice of variables, these matrices can be
made real, thereby reducing the computational cost. Also, pulsation modes are
either symmetric or anti-symmetric with respect to the equator, so that only
spherical harmonics of the same parity are needed to describe them. The problem
is then solved numerically using the Arnoldi-Chebyshev algorithm (e.g.
Chatelin, 1988) around different target frequencies, called frequency
shifts. In what follows, most of the calculations have been done using a
4th order finite difference approach. The angular resolution was
typically
and the radial resolution
.
2.5 Accuracy of the calculations
Various tests can be used to assess the accuracy of the calculations. A first
test consists in following the evolution of the frequency error as a function of
the radial and angular resolution. The solid lines in Fig. 1 show
the evolution of the relative error on the numerical frequency for two modes in
a 25
model uniformly rotating at
of the break-up rotation
rate, using the frequencies calculated at highest resolution as references. The
first two panels apply to an
mode and the other two to
(see Sect. 3 for the definition
of
). As is evident from the figure, the stability of the numerical
frequencies is very good, especially for the angular resolution where spectral
convergence seems to be achieved.
The right two panels of Fig. 2 of Reese et al. (2008b) show similar curves for a
pulsation mode in a 1.8
star rotating uniformly at
of the
break-up rotation rate. In this case the results were not as good. As explained
in Reese et al. (2008b), evaluating the error in this case was not entirely
straightforward due to difficulties in identifying the correct mode at different
resolutions. Indeed, at such high rotation rates, regular modes interact much
more with chaotic ones thus distorting their geometric features. Furthermore,
the amount of interaction between the different modes seems to depend on the
numerical resolution.
Although the problem is expressed in terms of real matrices and
frequencies are searched for around real target frequencies, complex conjugate
solutions sometimes appear. For instance, two of the calculations in the panel
to the far right of Fig. 1 (at
and
)
correspond
to complex solutions. The imaginary parts are most likely due to numerical
inaccuracies as these solutions are replaced by real solutions at other
numerical resolutions. Their relative magnitude (
)
suggests a comparable accuracy on the corresponding frequencies.
Another test consists in applying a variational formula on the eigenmodes to
yield an independent value for the frequency. According to the variational
principle, the error on the ``variational frequency'' is proportional to the
square of the error on the eigenmode, thus minimising its effect provided it is
sufficiently small (Christensen-Dalsgaard & Mullan, 1994). By comparing this value
to the original (numerical) frequency, it is possible to estimate the accuracy
of the calculation. In what follows, we calculated variational frequencies
using the following formula which is only valid for uniform rotation:
where






The dashed lines in Fig. 1 show the relative difference between the numerical and variational frequencies. As can be seen in the figure, these differences are much larger than the variations caused by modifying the resolution. A third set of curves, the dotted lines, show the relative error on the variational frequencies when using the variational frequency at highest resolution as a reference. From these, we deduce that the variational frequencies do converge to a specific value, but at a slower rate than the numerical frequencies, which is the opposite of what we would expect from the variational principle. Furthermore, the limit of the variational frequencies is different than that of the numerical frequencies, as can be seen from the dashed curves. Such a discrepancy can occur if the models are not in perfect hydrostatic equilibrium due typically to numerical inaccuracies. Indeed, hydrostatic equilibrium is implicitly assumed when deriving the variational formula, and deviations from this state will tend to produce errors which are independent of the resolution of the eigenfunctions. Nonetheless, these discrepancies remain small when the rotation rate is not too close to break-up and probably affect the different modes in a similar way for a given model so that the analysis in the rest of the article is not likely to be affected.
![]() |
Figure 2:
Comparison of a pulsation mode calculated using finite differences
(left), a spectral method (centre), and polynomial
splines (right) to discretise the equations in the radial
direction. These and other similar plots show a meridional
cross-section of the Eulerian pressure perturbation divided by
the square root of the background density profile so as to
bring out near surface regions. The difference on the frequencies is
less than |
Open with DEXTER |
Finally, a last test consists in applying different numerical techniques to
calculate the eigenmodes and seeing if they give similar results.
Figure 2 shows such a comparison. The mode on the left is
calculated using 4th order finite differences in the radial
direction, the one in the middle a spectral method based on Chebyshev
polynomials and the one on the right 4th order polynomial splines.
The angular resolution was very similar for the three cases and the radial
resolution went from
for the calculation based on Chebyshev
polynomials to
for the spline-based calculation. As can be seen in
the figure, the three calculations yield very similar results, and the
corresponding frequencies are less than
Hz apart.
Furthermore, as will be explained later on, some pulsation modes were
calculated using the Lagrangian displacement rather than the Eulerian velocity
perturbation. When comparing the two methods, differences on the frequencies
are very small for m=0 and can be larger for
(for example,
for the mode represented in
Fig. 11, right panel), thereby providing yet another
verification on the pulsation mode calculations.
Overall, these tests indicate a good numerical stability both with respect to the numerical resolution and the choice of numerical method. The tests on the variational principle, on the other hand, show that some numerical difficulties remain, possibly resulting from a loss of precision on the stellar models. Furthermore, the accuracy is not as good when the rotation rate approaches break-up, as shown in Reese et al. (2008b). Before doing accurate comparisons with actual observations, these difficulties will need to be addressed. Nonetheless, these are not expected to change the basic behaviour of the pulsation modes nor the results in following sections.
3 Uniform or nearly uniform rotation profile
3.1 Mode classification
As was stated above, Lignières & Georgeot (2008) and Lignières & Georgeot (2009) have
previously shown that for rotating polytropic models, pulsation modes fall into
the following main categories: island, chaotic, and whispering gallery
modes. We have found that a similar classification also applies to pulsation
modes in SCF models with uniform or mildly differential rotation (at least up to
,
which, based on Eq. (1), gives an equatorial
rotation rate which is
of the polar rotation rate).
Figure 3 compares pulsation modes from both types of models.
As can be seen in the figure, corresponding modes with an analogous geometric
structure are also present in SCF models.
![]() |
Figure 3:
A comparison between pulsation modes in polytropic models and models
based on the SCF method. The same three categories apply in both cases as can
be seen by the analogous geometric structure. The quantum numbers |
Open with DEXTER |
3.2 Quantum numbers for island modes
As was also the case for polytropic models, it is possible to introduce a new
set of quantum numbers
based on the geometry of
island modes (see lower left plot in Fig. 3). These quantum
numbers then intervene in a new asymptotic formula which describes the frequency
organisation of these modes:
where





Table 1 gives the values of these parameters for selected SCF
models as well as for a polytropic model. The parameters were calculated from a
sparse frequency set and are therefore subject to some error. The ranges
on the quantum numbers are
,
and
.
Furthermore, due to difficulties in mode identification, the
parameters given for the most rapidly rotating models
must be
taken with caution. Nonetheless, a second calculation based on a more complete
mode set shows that these values provide a reasonable estimate for 2 of the
models (see following section). The true value or range of values for the
rotation rate,
,
is also provided and shows a
posteriori that
does approximately correspond to the
rotation rate.
Table 1: Parameters for the asymptotic formula Eq. (27).
As was noted in Reese et al. (2008a), the ratio
decreases for increasing rotation rates. Using
in the non-rotating case (Tassoul, 1980), and
the relationships between
,
and
,
given in Reese et al. (2008a), one finds a theoretical
value of 2 for
when
.
Since the values in Table 1 are much smaller, the ``small''
frequency separation is no longer small but comparable with the large frequency
separation, as was also observed in Lignières et al. (2006) and
Lovekin et al. (2009).
In the last column, the standard deviation between the asymptotic and numerical
frequencies is given. It is defined as follows:
![]() |
(28) |
where




3.3 High azimuthal orders
The results presented so far were based on pulsation modes with azimuthal orders between -2 and 2. However, island modes also exist for high values of m as is illustrated in Fig. 4. As can be seen in the figure, high misland modes have an analogous structure to their low m counterparts except that they are much closer to the equator. This is similar to the behaviour of sectoral modes in non-rotating stars.
![]() |
Figure 4: Two island pulsation modes, one with a low m value ( left) and the other with a high m value ( right). Although the basic structure remains the same, the mode with a high azimuthal order is concentrated much closer to the equator. This is analogous to what happens with sectoral modes in non-rotating stars when m increases. |
Open with DEXTER |
![]() |
Figure 5:
Pulsation frequency spectrum in a uniformly ( left panel) and
differentially ( right panel) rotating model. The radial order |
Open with DEXTER |
Figure 5 shows two pulsation frequency spectra with
to 20,
to 1 and m=-10 to 10. The left
plot is for a uniformly rotating model and the right one corresponds to
differential rotation. The symbols represent the numerical frequencies and the
continuous lines are a least-squares fit based on the following formula:
The term







Table 2: Parameters for the asymptotic formula Eq. (29).
Table 2 gives the values of the different parameters used to
fit the frequency spectra in Fig. 5. Comparing these
values with those in Table 1 shows reasonable agreement,
provided one compares
and
with
and
,
respectively,
where the expressions
comes from a Taylor expansion of
Eq. (29) around m = 0. Although the average deviations are
larger in this table, Eq. (29) is a better fit to the
frequencies than Eq. (27). The reason for this apparent
contradiction is because the frequency sets used in Table 2
cover a larger range of m values. Applying Eq. (27) to these
expanded sets would yield
and 0.088 for the uniformly and
differentially rotating models, respectively.
An important difference between the two formulae, is that contrary to
what is suggested by Eq. (27), the azimuthal dependence is
different for
and
modes. A likely cause is the
fact that pulsation modes are closer to the equator at high m values. This
would then modify the path which intervenes in the time integrals used to
calculate
,
when working with ray dynamics
(Lignières & Georgeot, 2008). As a result, a physically more relevant formula for the
frequencies would include a
term which depends on mrather than an azimuthal term which depends on
.
Of course, a
quantitative calculation based on ray dynamics is needed to support this
explanation.
It is also interesting to look at what happens when
is increased to
a large value. Figure 6 compares 4 sets of pulsation
frequencies corresponding to
,
40, 50 and 60. The symbols
represent the numerical frequencies and the continuous lines a fit based on
Eq. (29). The frequencies are given in a co-rotating
frame and have been shifted so that the different curves are at 0 for
.
Plotting the frequencies as a function of
rather than m causes the curves associated with the high
order frequencies to overlap and reduces the difference between these curves and
the
curve. These results suggest that as
goes to
infinity, the azimuthal dependence of the co-rotating frequencies can be
described by a law of the form
where fis a function and
.
![]() |
Figure 6:
Four sets of pulsation frequencies in a co-rotating frame in
which
|
Open with DEXTER |
![]() |
Figure 7:
The
|
Open with DEXTER |
3.4 An effective rotation rate
Of particular interest is the parameter
.
In the
uniformly rotating case, the term
represents, to first
order, the advection of the modes by stellar rotation. The value given
for
in Table 2 is quite close to the
true rotation rate and only differs by
,
this difference probably
resulting from the Coriolis force. In the differentially rotating case,
can also be interpreted as an estimate of the
advection of the pulsation modes by stellar rotation. The parameter
would then be an average of the rotation rate in which
the weighting depends on the structure of the pulsation modes. We will refer to
as an effective rotation rate. We can then use
Eq. (1) to calculate the position
where
is equal to
for the differentially rotating
model. This is represented by the thick vertical line in
Fig. 7 for the numerical value given in
Table 2. The hashed region on either side of this line is
an estimate of the error on this position using the difference between
and
from the uniformly rotating
model as a guide.
As can be seen from Fig. 7,
is located
towards the outer regions of the star. This means that
,
when viewed as an average of the rotation profile, has a stronger weighting in
these outer regions. This seems logical from the point of view of ray dynamics
because a sound wave travelling along a ray path will spend most of its time in
the outer regions of the star where the local sound velocity is lower. As a
result, it will spend more time being advected by rotation in that region rather
than in an inner region. Sound-travel times along ray paths have already been
used to establish an asymptotic expression for rotational kernels of high order
p-modes in spherical stars (Gough, 1984).
One of the best ways to confirm these ideas in a quantitative way is to
apply a variational formula which is valid for differential rotation. Such a
formula has been established in Lynden-Bell & Ostriker (1967). Here we give a
different and somewhat simpler expression which is only valid for conservative
rotation profiles:
where





In the uniformly rotating case, the term that corresponds to the
advection of pulsation modes by rotation is ,
which is contained in the
first integral. By analogy, we can define an effective rotation rate for the
differentially rotating case as follows:
![]() |
(31) |
Solving for

where
When








![]() |
Figure 8:
A plot of the kernel associated with the
|
Open with DEXTER |





![]() |
Figure 9:
Different measures of the effective rotation rate. The solid and
dotted curves show an average over m and -m of
|
Open with DEXTER |
![]() |
Figure 10: The left figure corresponds to a chaotic mode and the right one to what appears to be a whispering gallery mode in SCF models with a highly differential rotation profile. No island modes are shown as they seem to have disappeared in the models (for low m). |
Open with DEXTER |
![]() |
Figure 11: The two figures corresponds to pulsation modes with a high azimuthal order in models with a highly differential profile. The left figure corresponds to a whispering gallery mode and the right one to an island mode. As can be seen in these plots, pulsation modes become less chaotic with increasing azimuthal order. |
Open with DEXTER |
This naturally leads on to the idea of applying inversion theory to
probe the rotation profile using the rotational kernels defined in
Eq. (33). The quantity
is readily available from
observations, once an accurate mode identification has been done. Furthermore,
it turns out that
is a
very good approximation to
,
at least in the example
considered above, thereby allowing the use of linear inversion theory. These
kernels will, nonetheless, need to refined so as to include the effects of the
Coriolis force.
4 Highly differential rotation
When the rotation profile becomes highly differential, the stellar structure becomes more and more deformed and the polar regions can, in some cases, become concave. These polar concavities result from the particular choice of rotation profile as expressed in Eq. (1) since they do not appear in models where the rotation rate increases with distance from the rotation axis. This deformation naturally affects the structure and organisation of pulsation modes. Figure 10 shows a chaotic and what appears to be a whispering gallery mode in models where the rotation profile is very differential. No island modes are shown as they seem to have disappeared. In the more distorted configurations, even whispering gallery modes become difficult to find. Instead, most of the modes are of a very chaotic nature.
One way to counteract the effects of stellar distortion is to increase the azimuthal order m. Indeed, increasing the azimuthal order causes the pulsation modes to become closer to the equator and move away from the poles where stellar deformation is strongest. As can be seen in Fig. 11, highly regular whispering gallery modes exist even in the most deformed configurations. Also, for models with less distortion, it is possible to find some island modes. Nonetheless, such modes are not likely to be visible in stars due to disk averaging effects. Therefore, if stars reach this degree of distortion, it will be very challenging to interpret their pulsation spectra.
5 Conclusion
As has been shown in this paper, results concerning pulsation modes in rapidly
rotating polytropic models can be generalised to more realistic models based on
the self-consistent field method (Jackson et al. 2005; MacGregor et al. 2007) provided the
rotation profile is not too differential. In particular, pulsation modes fall
into different categories, island, chaotic and whispering gallery
modes, each with their own characteristic geometry, in full agreement with
previous calculations based on ray dynamics (Lignières & Georgeot 2008;
Lignières & Georgeot 2009). The frequencies of the island modes obey the same type of
asymptotic formula as those in polytropic models although a more careful
investigation of their m-dependence reveals a more complex behaviour than was
previously established. This type of formula potentially provides a promising
way of identifying pulsation modes in rapidly rotating stars, especially at high
radial orders where the agreement between formula and frequency is very good
(Reese et al., 2009). Of course, when applying this formula to
observations, one should restrict themselves to modes with low
and
m values, because cancellation effects reduce the visibility of modes with
more nodes on the surface. As a result, the approximate form given by
Eq. (27), which is valid for low m values, is sufficiently
accurate.
A useful by-product of the asymptotic formula is an estimate of the effective rotation rate which gives the average advection of modes by rotation when the rotation profile is mildly differential. The obtained value indicates a stronger weighting near the surface, where the local sound velocity is smaller. This goes hand in hand with the intuitive picture based on ray dynamics that a sound wave is most advected in those regions where it spends the most time. A rigorous calculation based on a variational principle yields rotation kernels which confirm this picture and help provide effective rotation rates similar to the one obtained in the asymptotic formula, apart from the effects of the Coriolis force on the frequencies. These rotation kernels could then be used in inversion methods to probe the rotation profile.
When the rotation profile is highly differential, pulsation modes tend to be predominantly chaotic, probably as a result of the star's geometric distortion. Increasing the azimuthal order counteracts this effect by drawing the pulsation modes closer to the equator thereby causing regular whispering gallery modes, and in some cases, island modes, to reappear. Nonetheless, such modes are not likely to be visible due to disk averaging effects thus making pulsation spectra in such stars difficult to interpret.
Acknowledgements
The authors wish to thank the referee for valuable suggestions and comments which helped to improve this article. Many of the numerical calculations were carried out on the Altix 3700 of CALMIP (``CALcul en MIdi-Pyrénées'') and on Iceberg (University of Sheffield), both of which are gratefully acknowledged. D.R.R. gratefully acknowledges support from the UK Science and Technology Facilities Council through grant ST/F501796/1, and from the European Helio- and Asteroseismology Network (HELAS), a major international collaboration funded by the European Commission's Sixth Framework Programme. The National Center for Atmospheric Research is a federally funded research and development center sponsored by the US National Science Foundation.
Appendix A: Pulsation equations based on the Lagrangian displacement
In order to derive Euler's equation in terms of the Lagrangian displacement,
we begin with Eq. (13) of Lynden-Bell & Ostriker (1967) and calculate its Eulerian
perturbation in an inertial frame:
where

![]() |
(A.2) |
Simplifying Eq. (A.1) yields:
This is the same equation as what is used in Lovekin et al. (2009). If one uses the following relationship between


it is possible to show that Eqs. (6) and (A.3) are equivalent.
In terms of the coordinate system described in Sect. 2.3,
Euler's equation takes on the following explicit form:
where

![]() |
(A.8) |
the adiabatic relation,
![]() |
(A.9) |
and Poisson's equation,
![]() |
(A.10) |
which in spheroidal geometry are:
0 | = | ![]() |
|
![]() |
(A.11) | ||
0 | = | ![]() |
|
![]() |
(A.12) | ||
0 | = | ![]() |
(A.13) |
Using this set of equation yields the same modes and similar frequencies as using the system of equations based on the Eulerian velocity perturbation


References
- Alexander, D. R., & Ferguson, J. W. 1994, ApJ, 437, 879 [NASA ADS] [CrossRef] (In the text)
- Bonazzola, S., Gourgoulhon, E., & Marck, J.-A. 1998, Phys. Rev. D, 58, 104020 [NASA ADS] [CrossRef] (In the text)
- Breger, M., & Pamyatnykh, A. A. 2006, Mem. Soc. Astron. Ital., 77, 295 [NASA ADS] (In the text)
- Caughlin, G. R., & Fowler, W. A. 1988, Atomic Data and Nuclear Data Tables, 40, 283 [NASA ADS] [CrossRef] (In the text)
- Chatelin, F. 1988, Valeurs propres de matrices (Paris: Masson) (In the text)
- Christensen-Dalsgaard, J. 2003, Lecture Notes on Stellar Oscillations, http://astro.phys.au.dk/~jcd/oscilnotes/ (In the text)
- Christensen-Dalsgaard, J., & Mullan, D. J. 1994, MNRAS, 270, 921 [NASA ADS] (In the text)
- Clement, M. J. 1978, ApJ, 222, 967 [NASA ADS] [CrossRef] (In the text)
- Cowling, T. G., & Newing, R. A. 1949, ApJ, 109, 149 [NASA ADS] [CrossRef] (In the text)
- Deupree, R. G. 1990, ApJ, 357, 175 [NASA ADS] [CrossRef] (In the text)
- Deupree, R. G. 1995, ApJ, 439, 357 [NASA ADS] [CrossRef] (In the text)
- Dintrans, B., & Rieutord, M. 2000, A&A, 354, 86 [NASA ADS] (In the text)
- Dziembowski, W. A., & Goode, P. R. 1992, ApJ, 394, 670 [NASA ADS] [CrossRef] (In the text)
- Eggleton, P. P., Faulkner, J., & Flannery, B. P. 1973, A&A, 23, 325 [NASA ADS] (In the text)
- Espinosa, F., Pérez Hernández, F., & Roca Cortés, T. 2004, in Helio- and Asteroseismology: Towards a Golden Future, ESA SP-559: SOHO 14, 424 (In the text)
- Gough, D. O. 1984, Roy. Soc. London Philos. Trans. Ser. A, 313, 27 [NASA ADS] [CrossRef] (In the text)
- Gough, D. O., & Thompson, M. J. 1990, MNRAS, 242, 25 [NASA ADS] (In the text)
- Graboske, H. C., Dewitt, H. E., Grossman, A. S., & Cooper, M. S. 1973, ApJ, 181, 457 [NASA ADS] [CrossRef] (In the text)
- Jackson, S. 1970, ApJ, 161, 579 [NASA ADS] [CrossRef] (In the text)
- Jackson, S., MacGregor, K. B., & Skumanich, A. 2004, ApJ, 606, 1196 [NASA ADS] [CrossRef] (In the text)
- Jackson, S., MacGregor, K. B., & Skumanich, A. 2005, ApJS, 156, 245 [NASA ADS] [CrossRef] (In the text)
- Karami, K., Christensen-Dalsgaard, J., Pijpers, F. P., Goupil, M.-J., & Dziembowski, W. A. 2005, [arXiv:astro-ph/0502194] (In the text)
- Kippenhahn, R., Weigert, A., & Hofmeister, E. 1967, Meth. Comp. Phys., 7, 129 (In the text)
- Ledoux, P. 1951, ApJ, 114, 373 [NASA ADS] [CrossRef] (In the text)
- Lignières, F., & Georgeot, B. 2008, Phys. Rev. E, 78, 016215 [CrossRef] (In the text)
- Lignières, F., & Georgeot, B. 2009, A&A, 500, 1173 [NASA ADS] [CrossRef] [EDP Sciences] (In the text)
- Lignières, F., Rieutord, M., & Valdettaro, L. 2001, in Semaine de l'Astrophysique Francaise, ed. F. Combes, D. Barret, & F. Thévenin, SF2A-2001, 127 (In the text)
- Lignières, F., Rieutord, M., & Reese, D. 2006, A&A, 455, 607 [CrossRef] [EDP Sciences]
- Lovekin, C. C., & Deupree, R. G. 2008, ApJ, 679, 1499 [NASA ADS] [CrossRef] (In the text)
- Lovekin, C. C., Deupree, R. G., & Clement, M. J. 2009, ApJ, 693, 677 [NASA ADS] [CrossRef] (In the text)
- Lynden-Bell, D., & Ostriker, J. P. 1967, MNRAS, 136, 293 [NASA ADS] (In the text)
- MacGregor, K. B., Jackson, S., Skumanich, A., & Metcalfe, T. S. 2007, ApJ, 663, 560 [NASA ADS] [CrossRef] (In the text)
- Ostriker, J. P., & Mark, J. W.-K. 1968, ApJ, 151, 1075 [NASA ADS] [CrossRef] (In the text)
- Ouazzani, R.-M., Goupil, M.-J., Dupret, M.-A., & Reese, D. 2009, in 38th Liège International Astrophysical Colloquium, submitted (In the text)
- Reese, D. 2006, Ph.D. Thesis, Université Toulouse III - Paul Sabatier, http://tel.archives-ouvertes.fr/tel-00120334 (In the text)
- Reese, D., Lignières, F., & Rieutord, M. 2006, A&A, 455, 621 [NASA ADS] [CrossRef] [EDP Sciences] (In the text)
- Reese, D., Lignières, F., & Rieutord, M. 2008a, A&A, 481, 449 [NASA ADS] [CrossRef] [EDP Sciences] (In the text)
- Reese, D., MacGregor, K. B., Jackson, S., Skumanich, A., & Metcalfe, T. S. 2008b, in SF2A-2008, ed. C. Charbonnel, F. Combes, & R. Samadi, 531 (In the text)
- Reese, D. R., Thompson, M. J., MacGregor, K. B., et al. 2009, A&A, 506, 183 [CrossRef] [EDP Sciences] (In the text)
- Rieutord, M. 2006a, EAS Publ. Ser., 21, 275 [CrossRef] (In the text)
- Rieutord, M. 2006b, in Semaine de l'Astrophysique Française, ed. D. Barret, F. Casoli, G. Lagache, A. Lecavelier, & L. Pagani, SF2A-2006, 501 (In the text)
- Rogers, F. J., & Iglesias, C. A. 1992, ApJS, 79, 507 [NASA ADS] [CrossRef] (In the text)
- Saio, H. 1981, ApJ, 244, 299 [NASA ADS] [CrossRef] (In the text)
- Schou, J., Antia, H. M., Basu, S., et al. 1998, ApJ, 505, 390 [NASA ADS] [CrossRef] (In the text)
- Soufi, F., Goupil, M.-J., & Dziembowski, W. A. 1998, A&A, 334, 911 [NASA ADS] (In the text)
- Tassoul, M. 1980, ApJS, 43, 469 [NASA ADS] [CrossRef] (In the text)
- Thompson, M. J., Christensen-Dalsgaard, J., Miesch, M. S., & Toomre, J. 2003, 41, 599 (In the text)
- Vandenberg, D. A. 1983, ApJS, 51, 29 [NASA ADS] [CrossRef] (In the text)
- Zahn, J.-P. 1974, in Stellar Instability and Evolution, ed. P. Ledoux, A. Noels, & A. W. Rodgers, IAU Symp., 59, 185 (In the text)
- Zahn, J.-P. 1993, in Les Houches Summer School Proceedings (1987), ed. J.-P. Zahn, & J. Zinn-Justin, 565 (In the text)
All Tables
Table 1: Parameters for the asymptotic formula Eq. (27).
Table 2: Parameters for the asymptotic formula Eq. (29).
All Figures
![]() |
Figure 1:
Evolution of various forms of the frequency error with
|
Open with DEXTER | |
In the text |
![]() |
Figure 2:
Comparison of a pulsation mode calculated using finite differences
(left), a spectral method (centre), and polynomial
splines (right) to discretise the equations in the radial
direction. These and other similar plots show a meridional
cross-section of the Eulerian pressure perturbation divided by
the square root of the background density profile so as to
bring out near surface regions. The difference on the frequencies is
less than |
Open with DEXTER | |
In the text |
![]() |
Figure 3:
A comparison between pulsation modes in polytropic models and models
based on the SCF method. The same three categories apply in both cases as can
be seen by the analogous geometric structure. The quantum numbers |
Open with DEXTER | |
In the text |
![]() |
Figure 4: Two island pulsation modes, one with a low m value ( left) and the other with a high m value ( right). Although the basic structure remains the same, the mode with a high azimuthal order is concentrated much closer to the equator. This is analogous to what happens with sectoral modes in non-rotating stars when m increases. |
Open with DEXTER | |
In the text |
![]() |
Figure 5:
Pulsation frequency spectrum in a uniformly ( left panel) and
differentially ( right panel) rotating model. The radial order |
Open with DEXTER | |
In the text |
![]() |
Figure 6:
Four sets of pulsation frequencies in a co-rotating frame in
which
|
Open with DEXTER | |
In the text |
![]() |
Figure 7:
The
|
Open with DEXTER | |
In the text |
![]() |
Figure 8:
A plot of the kernel associated with the
|
Open with DEXTER | |
In the text |
![]() |
Figure 9:
Different measures of the effective rotation rate. The solid and
dotted curves show an average over m and -m of
|
Open with DEXTER | |
In the text |
![]() |
Figure 10: The left figure corresponds to a chaotic mode and the right one to what appears to be a whispering gallery mode in SCF models with a highly differential rotation profile. No island modes are shown as they seem to have disappeared in the models (for low m). |
Open with DEXTER | |
In the text |
![]() |
Figure 11: The two figures corresponds to pulsation modes with a high azimuthal order in models with a highly differential profile. The left figure corresponds to a whispering gallery mode and the right one to an island mode. As can be seen in these plots, pulsation modes become less chaotic with increasing azimuthal order. |
Open with DEXTER | |
In the text |
Copyright ESO 2009
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.