A&A 399, 789-794 (2003)
DOI: 10.1051/0004-6361:20021832
F. Moreno1 - L. M. Lara1 - J. J. López-Moreno1 - O. Muñoz1 - A. Molina1,2 - J. Licandro3
1 - Instituto de Astrofísica de Andalucía, CSIC,
PO Box 3004, 18080 Granada, Spain
2 -
Departamento de Física Aplicada,
Universidad de Granada, 18071 Granada, Spain
3 -
Isaac Newton Group of Telescopes
& Instituto de Astrofísica de Canarias,
PO Box 321, 38700 Santa Cruz de La Palma, Tenerife, Spain
Received 9 October 2002 / Accepted 29 November 2002
Abstract
A numerical method to compute cometary dust tail brightnesses
has been developed. The method, analogous in many ways to the
inverse Monte Carlo method proposed by Fulle (1989),
has been applied
to red continuum images of comet C/1999 T1 McNaught-Hartley obtained
by Lara et al. (2002). The time and
size dependence of the particle terminal velocities, the size
distribution functions, and the dependence with time of the power index
of the size distribution have been derived. The best fits to the
observed isophote fields are obtained for highly anisotropic dust grain
ejection velocities. The power indexes of the time-dependent dust
size distributions show small values, particularly shortly after
perihelion is reached, in which a minimum of -5.5 in the power index of the
size distribution function is found, suggesting the apparition of
small particles. Our results are in line
with previous results by Fulle (1992) relating a systematic
decrease of size distribution power index and dust ejection isotropy
as the comet age increases. We also derived the dust mass loss rates and
the
quantity as a function of time, providing evidence that
these two quantities do not have to be correlated if the size
distribution and the dust ejection velocity are both time-dependent, in
accordance with the results by Fulle (2000) for comet 46/P
Wirtanen.
Key words: comets: general - comets: individual: C/1999 T1 McNaught-Hartley
The theory of the morphology of dust tails as a tool to study the dust environment of comets is based on an early mechanical theory which goes back to the nineteenth century with Bessel. The theory was subsequently improved by many others such as the Russian astronomer Feodor A. Bredikhin (see e.g. Festou et al. 1993). Using this mechanical theory, Finson & Probstein (1968a) presented a method to derive information on the size distribution, production rate, and size- and time-dependent velocities of the grains leaving the inner coma. The technique was successfully applied to comet Arend-Roland (Finson & Probstein 1968b). The method was, however, not free from simplifying assumptions, such as the isotropic dust ejection, the hypersonic approximation, and the linear expansion of the dust shells. Fulle (1989) proposed a new method based on the sampling of grains, computing rigorously their orbital motion, and avoiding the simplifying hypothesis above mentioned. The orbit of the dust grain is defined by the keplerian motion resulting from its initial velocity in the solar gravity field reduced by the pressure of solar radiation. Fulle has applied his method to many comets (e.g., Fulle 1989; Fulle et al. 1992; Fulle et al. 1998b).
We have recently envisaged a Monte Carlo method to compute energy fluxes impinging on cometary comae surrounded by dust, including the effects of polarization of light (Moreno et al. 2002). Our purpose is to have a tool to extract complementary information on the physical properties of cometary grains and the grain velocities in the coma vicinity with the interpretation of dust tail images, by building a numerical method similar to that by Fulle (1989). The model is described here, along with its application to a set of images of comet McNaught-Hartley 1999 T1 as obtained by Lara et al. (2002).
A detailed description of the observations and data reduction is given
by Lara et al. (2002). Briefly, the
two post-perihelion images
of comet C/1999 T1 analyzed here were obtained
on 2001 January 26, 06:34 UT, and 2001 February 5, 05:24 UT through a red
continuum filter on a CCD camera at the
Observatorio del Teide IAC80 telescope. The comet reached perihelion on
13.47 December 2000 (MPC 42106).
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Figure 1: Images of comet C/1999 T1 obtained on January 26 and February 5, 2001. The images are oriented to the (M,N) coordinate system and resampled as to have a resolution of 4080 km/pixel and 4060 km/pixel on Jan. 26 and Feb. 5, respectively. |
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As in Fulle (1989), we consider a
sample of
dust grains, where
Nt is the number of samples in the time interval of dust ejection,
is the number of samples in size and Ns is the number of grains
of a given size uniformly distributed on a dust shell ejected at
time t. We set
200. The grain velocity is given by:
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(1) |
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(2) |
Once derived the orbital elements of the dust grain according to its
size and velocity, its position at a time t is derived, and then it is
projected on the photographic coordinate system (M,N) (Finson &
Probstein 1968a, 1968b). The Monte
Carlo
procedure involves 8106 particles. To obtain the modeled
image densities
we followed Fulle (e.g. Fulle 1989;
Fulle et al. 1992; Fulle et al. 1998b). The size of
the particles
involved (or, equivalently, their
value) are defined by the
syndyne-synchrone network. The largest
value at each dust
grain
ejection time is defined by the syndyne crossing the synchrone at the
image edge, and the smallest
value is simply the largest one
divided by the number of samples in size (
). The integration time
ends at the observation time of the image and starts at a time where the
contribution to the tail density is negligible The fit of the dust tail
involves the inversion of the oversampled linear system AF=I, where
A is the kernel matrix containing the model dust tail (i.e., the
surface density of the sampling particles integrated over t and
,
F is the
output vector, which contains the time-dependent
distribution, and I is the
observed surface brightness of the image in the selected (M,N)region. Since the kernel matrix A is often sparse and ill-conditioned,
a regularizing condition is usually added to the system
(Fulle 1989). The condition (in the least square fit sense)
imposed by Fulle (1989)
has the physical meaning of constraining the size distribution to be
slowly time-dependent and the dust production rate to depend on the
inverse square of the heliocentric distance. From the water production
rates reported so far, this canonical law concerning gas production is
strongly violated: the water production rate has been reported to be
a factor of 2.8 higher on
Jan. 13, 2001 (at heliocentric distance,
AU), than on
Dec. 28, 2000 (
AU)
(see Schleicher et al. 2001, IAUC 7558, and Conrad & Chaffee 2001,
IAUC 7578). Also, as stated by
Jockers (1997),
it is not clear what the regularization does to the model. For the
present application, we have therefore preferred not to include
any regularizing condition. From the vector F we obtained
the
and time-dependent distribution from which we obtained
the size distribution (Finson & Probstein 1968a).
The method should be applied to a sequence of calibrated images obtained
during a few days apart. In this case, two images are available,
although they are separated about 10 days in time. In addition, the
image of January 26, 2001 is quite distorted by the presence of field stars.
We have therefore preferred to apply the method only to the image of
February 5 first, and give the maximum weight to the parameters derived
with that single observation. After that, we modeled
the image of January 26, and then, we compare the results obtained for
the two observations.
Figure 2 shows the grain diameter range to which the
solutions for the images on the two dates aforementioned are related
(for an assumed density of g cm-3). Our approach was to
model first the image of February 5, 2001.
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Figure 2: The grain diameter to which the solutions of the inverse Monte Carlo procedure are related for the images of January 26, 2001 (filled circles), and February 5, 2001 (open circles). |
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Figure 3:
Upper panel: observed (solid contours) and reconstructed (dotted
contours) isophote field for the February 5, 2001 image, for isotropic
ejection velocity
conditions (
![]() ![]() ![]() ![]() |
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We have tried all the possible k -
combinations
for k=2, 4, and 6, and
(highly
anisotropic ejection), 90
(hemispherical ejection), and
180
(isotropic ejection), with a large number of trial velocity
functions v(t). We quantified the goodness of the fits as given by
,
where
and
are the observed and modeled images, the sum being
extended
to all the pixels (M,N) included in the region under analysis. The
best fits correspond to those having the largest ejection anisotropy,
,
with little influence of the assumed k. The best
fits for
give
,
while
the best fits for isotropic or hemispherical ejections give
about
,
roughly a factor of 3 larger than
those corresponding to
the anisotropic case. Two examples of the reconstructed images are
shown in Figs. 3 and 4.
In Fig. 3 results are shown for the case of isotropic ejection
velocities, and in Fig. 4 for highly anisotropic
ejection velocities. It
is clear how the fit improves and the noise in the
reconstruction decreases in the anisotropic case. On
the other hand, the size dependence of the ejection velocity is very
weakly constrained, as we could find very similar values of
for a given
independently of the value of k, after
modifying the velocity profile accordingly. The best fit for the
time-dependent velocity function is shown in Fig. 5.
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Figure 4:
Upper panel: observed (solid contours) and reconstructed (dotted
contours) isophote field for highly anisotropic ejection
conditions (
![]() ![]() ![]() ![]() |
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Figure 5: The time dependence of the dust ejection velocity as derived for the February 26, 2001 image. |
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Figure 6:
Upper panel: observed (solid contours) and reconstructed (dotted
contours) isophote field for highly anisotropic ejection
conditions (
![]() ![]() ![]() ![]() |
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Once obtained the best fit for the February 5 image, we proceed to the
application of the inverse Monte Carlo method to the January 26
image. Our
approach was to consider, in principle, the same size and time-dependent
velocity profile as for the
best fitted image of February 5. With those input data, the resulted
reconstruction
for the January 26 image is shown in Fig. 6. The
resulting fit gives
,
which
indicates
that the fit is nearly as good as that obtained for the February 5 image. This
shows the consistency of the inverse Monte Carlo method in the sense
that the same particle time- and size-dependent velocity function can
give good fits for two images obtained 10 days apart. To ensure
the robustness of the method, we should find, in addition, the same
time-dependence of the power index of the derived size distribution
functions. This condition may not be completely satisfied, as the grain
sizes to which the solutions are related are not exactly the same for
both dates (see Fig. 2), and the derived power index may
well have a strong size dependence (e.g. McDonnell et al. 1991)
in addition to the time
dependence. Nevertheless, the agreement between both cases is good, as
Fig. 7 shows. As can be seen, only the time range -10 to
+58 days since perihelion is shown. For earlier times, the power index
could not be estimated reliably. The wide dispersion in the power
indexes may be related to the fact of not applying any regularizing
constraint to the system AF=I, as that condition has the physical
meaning of constraining
the size distribution to be slowly time-dependent, as
stated in the previous section.
The power indexes show in fact a strong
time dependence having a minimum close to -5.5 shortly after perihelion
and increasing to values near -3 several days before
and after perihelion is reached. Fulle
(1989) also found a
similar behavior in comets C/1962 III and C/1973 XII, in which there
also appeared a population of small particles after perihelion, and in
comet C/1996B2, in which there
also appeared a strong drop in the size distribution power index about
20 days before perihelion
(Fulle 1997), accompanied by a strong drop in the dust mass
production rate. The
time-dependent velocity function shows a maximum about 10 days after
perihelion, and displays a similar behavior to that found by Fulle et
al. (1992) for the dynamically old comet C/1988 V.
We have also calculated the time-dependent dust loss rates and the quantity (A'Hearn et al. 1984) from the two observations. The
quantity, which has linear dimensions, is the product
of the single scattering albedo of the
dust particles (A) times the fraction of the observed field filled by the
grains (f) times the radius of the diaphragm around the comet nucleus
position (
). When the brightness of the coma is proportional to
this quantity is independent of the radius of the aperture
used. These
quantities were computed in our model according to the formulae given e.g. in
Fulle (1998a), and are shown in Fig. 8. With the
exception of the point near t=-17 days, the results
derived from the two images are in good agreement in
both the dust loss rates and the
quantity.
The quantity
can be interpreted as the
radius of the equivalent dust disk of unitary albedo which scatters the
same light as the observed coma, and must not be directly related to a
dust loss rate, as clearly demonstrated by Fulle (2000) in
his analysis of comet 46/P Wirtanen. As
can be seen in Fig. 8, the derived dust loss rates and the
quantity are not correlated after perihelion, showing a
clear anticorrelation at times t>+15 days since perihelion
passage. The explanation resides in the time evolution of the size
distribution function (Fulle 2000).
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Figure 7:
Power index as a function of time for the size distribution
functions derived for the image of January 26 (filled circles) and
February 5 (open circles). The error bars represent ![]() |
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The dust mass loss rates were computed assuming an albedo of
,
and should be rescaled for other values of the
albedo. The dust loss rate shows a marked departure from the rh-2law, a consequence of the rejection of the regularizing condition, but
still it does show a maximum just before perihelion and a
strong decline with heliocentric distance in both pre- and
post-perihelion. Our dust loss rates can
be compared with the gas loss rates
derived from other observations. The water production rate has been
found to increase with heliocentric distance from
s-1, as reported by Schleicher et al. (2001, IAUC
7558) on Dec. 28, 2000 (
AU) and on Jan. 2, 2001,
to
s-1 on Jan. 13, 2001 (
AU) (Mumma et al. 2001,
IAUC 7578) or to
s-1 also on Jan. 13, 2001, as reported by
Conrad & Chaffee (2001, IAUC 7578). This gives a range of gas loss
rates of
g s-1 to
g
s-1. Our dust mass loss rates range from about
to
105 g s-1 in the same period, giving dust-to-gas
ratios much smaller than 1. This result is different to
the previous results by Fulle (e.g. Fulle 1997), who found
dust-to-gas ratios in excess of 1 for all comets analyzed with his
inverse dust tail model. Regarding the quite different time
evolution of the mass loss rate and the
parameter, an exactly
opposite behavior to that of the dust loss rate would be
found if we were considering the
quantity as a measure of the
dust loss rate, as its tendency is, as the water production rate,
also to increase between
Dec. 28, 2000, and Jan. 13, 2001. This illustrates the inconsistency in
assessing variations of dust-to-gas ratios with heliocentric
distance when the quantity
is used as a measure of
the dust production rate.
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Figure 8:
Upper panel: time dependence of the quantity ![]() |
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The Monte Carlo procedure allows to compute the individual orbit of each
sampled grain, being possible to compute the total dust grain
mass ejected that remains in bound orbits, and the minimum size of those
particles contributing to the
zodiacal dust cloud. Our calculations reveal that the total dust mass ejected
is about
g, from which
2-3% of that mass will remain in bound orbits in the Solar
System. This has to be
considered as a lower limit, since the solutions always refer to a limited
size and time range. The minimum diameter of those grains injected
into the Solar System is found to be 0.34 mm.
Numerical dust tail models can give important information concerning the
dust component of comets such as the
time-dependent size distribution, the ejection velocity of the grains
as a function of time and its degree of spatial anisotropy, and the dust
mass loss rate. We have built a Monte Carlo model on the same
grounds of that described by Fulle (1989), and we have applied it to
the long-period comet C/1999 T1. The model produces good fits to the
tail isophotes only when the anisotropy of the ejected grains is very
high, a result that seems to be common to dynamically old comets, as suggested
by Fulle (1992). The low time-averaged power index of the
dust size distribution found for C/1999 T1 (
)
also supports that
conclusion.
The calculation of the time-dependent
quantity and the dust
mass loss rate from the numerical model allowed us to conclude that both
parameters are not always correlated, in agreement with the analysis of
Fulle (2000) of comet 46/P Wirtanen. Specifically, for comet
C/1999 T1, the dust mass loss rate and the
quantity are almost
anticorrelated at times t>+15 days since perihelion passage. Thus,
the
parameter cannot be directly related to a dust loss rate, unless the size
distribution and the dust ejection velocity are independent of
time, physical conditions that hardly occur in practice.
The total dust mass injected into bound orbits in the Solar System is
calculated from the
Monte Carlo procedure to be about
kg. This should be
considered as a lower limit, due to the limited dust size range employed in
the calculations. Also, the minimum size of those particles contributing to the
zodiacal dust cloud is found to be 0.34 mm in diameter.
Acknowledgements
This work was supported by contracts PNE-001/2000-C-01 and AYA-2001-1177.