Issue |
A&A
Volume 519, September 2010
|
|
---|---|---|
Article Number | A26 | |
Number of page(s) | 10 | |
Section | Stellar structure and evolution | |
DOI | https://doi.org/10.1051/0004-6361/201014910 | |
Published online | 08 September 2010 |
Milli-arcsecond images of the Herbig Ae star HD 163296
S. Renard1 - F. Malbet1 - M. Benisty2 - E. Thiébaut3 - J.-P. Berger4,1
1 - Laboratoire d'Astrophysique de Grenoble, CNRS-UJF UMR5571, BP 53,
38041 Grenoble, France
2 - INAF - Osservatorio Astrofisico di Arcetri, Largo E. Fermi 5, 50125
Firenze, Italy
3 - Centre de Recherche Astrophysique de Lyon, CNRS-UCBL-ENSL UMR5574,
69561 St-Genis-Laval, France
4 - European Southern Observatory, Alonso de Cordova, 3107, Vitacura,
Chile
Received 30 April 2010 / Accepted 15 June 2010
Abstract
Context. The very close environments of young stars
are the hosts of fundamental physical processes, such as planet
formation, star-disk interactions, mass accretion, and ejection. The
complex morphological structure of these environments has been
confirmed by the now quite rich data sets obtained for a few objects by
near-infrared long-baseline interferometry.
Aims. We gathered numerous interferometric
measurements for the young star HD 163296 with various
interferometers (VLTI, IOTA, KeckI and CHARA), allowing for
the first time an image independent of any a priori model to be
reconstructed.
Methods. Using the Multi-aperture image
Reconstruction Algorithm (MiRA), we reconstruct images of
HD 163296 in the H and K
bands. We compare these images with reconstructed images obtained from
simulated data using a physical model of the environment of
HD 163296.
Results. We obtain model-independent H
and K-band images of the surroundings of
HD 163296. The images detect several significant features that
we can relate to an inclined asymmetric flared disk around
HD 163296 with the strongest intensity at about
4-5 mas. Because of the incomplete spatial frequency coverage,
we cannot state whether each of them individually is peculiar in any
way.
Conclusions. For the first time, milli-arcsecond
images of the environment of a young star are produced. These images
confirm that the morphology of the close environment of young stars is
more complex than the simple models used in the literature so far.
Key words: instrumentation: interferometers - techniques: image processing - stars: pre-main sequence - stars: individual: HD 163296
1 Introduction
The process of star formation triggered by the collapse and fragmentation of a molecular cloud leads to the birth of a young star surrounded by a circumstellar disk and outflows. The disks are believed to be the place where the planets form (Boss 1997; Mayer et al. 2002), and are composed of a mixture of gas and dust with a wide range of grain composition (Henning & Meeus 2009). The standard picture of the close environment of pre-main sequence stars is so far limited to a quasi-stationary accreting disk partially reprocessing the irradiation from the central protostar with potential planetary gaps opened by newly formed planets. Some of the accreted material is ejected by means of bipolar outflows but their precise origin has not yet been identified. Most of the models are presently assumed to be symmetric around the star rotation axis and stationary. However hydrodynamical turbulence, gravitational waves, magneto-rotational instabilities, vortices and thermal instabilities occurring on the AU-scale are known to play a major role in star and planet formation (e.g., Balbus & Hawley 1991). The close environments of young stars are therefore not expected to be as simple as they are currently modeled, but the observational measurements do not provide tight enough constraints to unambiguously identify strong departures from axisymmetrical models.
The photometric and spectroscopic observations obtained with very modest spatial resolution are usually integrated over a subarcsecond field of view which corresponds to several tens of AUs at the distance of the closest star formation regions (140 pc). Observations at the scale of 1 AU and below correspond to 7 milli-arcsec (mas) angular scale and requires therefore optical long-baseline interferometry. However, even if long-baseline optical interferometry is capable of reaching very high angular resolution, the observations are usually limited to a small number of measurements (see Millan-Gabet et al. 2007, for a review). With the advent of interferometers with more than two telescopes and with significantly high spectral resolution (e.g., VLTI/AMBER, CHARA/MIRC), the number of interferometric observations has significantly increased allowing the first images to be reconstructed with aperture synthesis techniques. Images of stellar surfaces (e.g., Zhao et al. 2009; Monnier et al. 2007; Haubois et al. 2009), binaries (e.g., Kraus et al. 2009; Zhao et al. 2008), or circumstellar shells around evolved stars (e.g., Le Bouquin et al. 2009) have been obtained mostly for objects brighter than the brightest young stars. In the young stellar object field, we are at a comparable stage to that reached 40 years ago when the first 3 antennas of the VLA became operational producing the first radio-interferometry images (Hogg et al. 1969). We report the first attempt to reconstruct an image of a circumstellar disk around a young star using mostly AMBER/VLTI interferometric data.
In this study, we present reconstructed images of the young
star HD 163296 (MWC 275), an isolated Herbig Ae star
(HAe) of
spectral type A1, with a 30
luminosity, and a
2.3
mass located at 122+17-13 pc
(Montesinos
et al. 2009; Natta et al. 2004; van den
Ancker et al. 1998).
In scattered light (Grady
et al. 2000) and at millimeter wavelengths
(Mannings & Sargent 1997),
a disk has been detected on large scales, traced out
to 540 AU. The CO millimeter line observations have revealed a
large-scale inclined disk in Keplerian rotation probably
evolving towards a debris disk phase (Isella
et al. 2007).
HD 163296 also exhibits an asymmetric outflow
perpendicular to the disk, with a chain of six Herbig-Haro knots
(HH409) tracing the history of mass loss (Devine et al. 2000; Wassell
et al. 2006). The emission of the innermost regions,
observed in far-UV emission
lines, have been attributed to optically thin gas accreting onto the
stellar surface, a magnetically confined wind, or shocks at the base of
the jet (Deleuil
et al. 2005; Swartz et al. 2005).
HD 163296 has been observed with several interferometers (see Benisty et al. 2010,
B10 hereafter).
Using the largest set of interferometric data of a young star, we
present here the
first reconstructed images of a complex young stellar object.
The article is organized as follow. Sect. 2 describes the image reconstruction method and the methodology employed to extract the best reconstructed image. Section 3 presents the reconstructed images obtained in the H and K bands and their analysis using simulated data generated from inner disk models. In Sect. 4, we describe the choices made during the image reconstruction process, and discuss the physical meaning of the features seen in the image, as well as the consequences for the models commonly used. Finally, Sect. 5 summarizes our results and provides some perspectives for the future.
2 Image reconstruction
2.1 Image reconstruction by MiRA
The principle of interferometry is to interfere coherently the light
coming
from a single astronomical source from two or more independent
telescopes
(Malbet
& Perrin 2007; Lawson 2000). An interferometer
measures a complex number
referred to as the visibility. According to the
Van Cittert-Zernicke
theorem, this complex visibility, ,
is the Fourier
transform of the object brightness distribution at the spatial
frequency of
the observations, given by the projected baseline in units of
wavelength
(
). The visibility amplitude, V,
is related to the
spatial extent of the emission, while the phase,
,
provides the location of the photocenter. However, the requested
infrastructure to carry out optical interferometry is complex and has
led to a limitation in the number of
telescopes (Baldwin &
Haniff 2002). The main consequence is to provide a sparse
sampling of the spatial frequencies, the so-called (u,v)
plane. Moreover, the
absolute value of the phase
is lost due to atmospheric turbulence that randomly modifies it.
However, by adding the phases of the fringes measured for each baseline
over a 3-telescope configuration, one can measure an
additional quantity, the closure phase, which is
insensitive to the
atmospheric disturbance (Monnier et al. 2006; Monnier 2003).
The closure phase
includes part of the Fourier phase information, and is related to the
global
asymmetry of the emission: a point-symmetric object has a zero closure
phase. The main observables are therefore the squared visibility
amplitudes, V2, and the
closure phases (CP).
The objective of the image reconstruction is to numerically
retrieve an
approximation of the true brightness distribution of the source given
the
interferometric measurements. To account for the data, the Fourier
transform
of the sought image should fit the measured complex visibilities.
However,
due to the sparse (u,v) coverage,
the image reconstruction problem is ill-posed as there are more
unknowns, e.g., the pixels of the image, than
measurements. Additional prior constraints are therefore required to
supplement the available data and retrieve a unique and stable
solution. A
very general solution is to define the optimal image to be the solution
to the optimization problem (Thiébaut 2005; Thiébaut
& Giovannelli 2009):
where



- Minimization of the likelihood term
, which enforces agreement of the sought image with the data. In practice, this term is derived from the noise statistics. For instance, it is the
of the data for Gaussian statistics.
- Minimization of the regularization
term
, which favors images that are the simplest or the smoothest according to a priori assumptions.

![]() |
Figure 1: Reconstructed images of HD 163296 in the H (left) and K bands (right), after a convolution with a Gaussian beam at the interferometer resolution. The colors are scaled to the squared root of the intensity with a cut corresponding to the maximum expected dynamic range (see text for details). The blue ellipse traces the location of the main secondary blobs, and the green dot-dashed ellipse corresponds to the location of the rim in the B10 model, with its width given by the green dashed ellipses. North is up and east is left. The sub-panel in the right corner of each plot indicates the Gaussian beam at the interferometer resolution, applicable to Figs. 3, 4, and 6. |
Open with DEXTER |
Many different algorithms have been developed to solve the image
reconstruction problem from optical interferometry data (e.g., Cotton
et al. 2008; Thiébaut & Giovannelli 2009).
In this paper, we use the Multi-Aperture Image Reconstruction Algorithm
(MiRA; by Thiébaut 2008).
MiRA is capable of dealing with any available interferometric data
(complex visibilities, squared visibilities, closure phases, etc.), and
has been successfully used to process real data
(e.g., Lacour
et al. 2008; Haubois et al. 2009;
Le
Bouquin et al. 2009; Lacour et al.
2009).
When phases are missed because of the atmospheric turbulence, the MiRA
algorithm can directly fit the available interferometric observables
without explicitly rebuilding the missing phases. Finally, one can
choose the most effective of various regularization methods integrated
into MiRA for the type of object observed and check the effect of the
regularization on the resulting image. MiRA directly attempts to solve
the problem in Eq. (1)
using an iterative non-linear optimization
algorithm (Thiébaut 2002).
Because of the missing phases, the function to be minimized is not
however convex thus has several local minima. The final image is
therefore determined by the data, the choice of the regularization (and
its level), and the initial image.
2.2 Methodology used in this work
Systematic tests have been performed on the MiRA algorithm by Renard et al. (in prep.; RTM10 hereafter) in which images of ten astrophysical objects were reconstructed, for different (u,v) coverages and signal-to-noise ratios. Twelve regularizations were tested and images were reconstructed for a set of weight factors

- The total variation regularization (Strong & Chan 2003), which minimizes the total norm of the image gradient, is the best regularization method in most of the cases.
- The weight factor
depends, within one order of magnitude, on neither the amount of data, the signal-to-noise ratio, nor the object type, but only on the type of the regularization used. Each regularization has its best value for
.


Once the parameters of the image reconstruction process are set, the images can be reconstructed. The solutions are not straightforward to analyze because of artifacts caused by the image reconstruction process or the quality of the data set, e.g., voids in the (u,v) plane, error bars. There are no objective criteria to distinguish between the actual structures from the object and the artifacts caused only by the data structure. We therefore performed a comparative analysis between our results and the results obtained from simulated data from the B10 model for HD 163296. To do so, we simulated fake data sets, using the B10 model and the same (u,v) plane and errors as in the real data set. Image reconstruction was also performed for the simulated data in the same conditions and compared to the image model. This comparative method is important to understand what could be trusted in the actual reconstructed images and what could not.
2.3 Interferometry data set
The principal characteristics of the data set is summarized in this section. A more detailed description is given in the Appendix A. HD 163296 was observed with several interferometers. The large data set comprises H and K-band data from VLTI (Benisty et al. 2010), IOTA (Monnier et al. 2006), Keck-I (Monnier et al. 2005), and CHARA (Tannirkulam et al. 2008). This data set represents the largest set of interferometric data available so far for a young stellar object. Since a trade-off has to be found between enough data to pave the (u,v) plane and the wavelength dependency of the observed object, we decided to reconstruct two different images, one in H and one in K band, using all the spectral channels available in each band i.e. assuming the object to be grey in each band (see Sect. 4.2 for further discussion).
3 Results and first image analysis
3.1 Reconstructed images in the H and K bands
![]() |
Figure 2: Contours of the reconstructed images of HD 163296 in the H ( left) and K bands ( right), after a convolution with a Gaussian beam at the interferometer resolution. The contours vary linearly between the minimum cut corresponding to the maximum expected dynamic range and the image maximum, with a step around 0.1. |
Open with DEXTER |
Using the methodology described in Sect. 2.2, we reconstruct the images of HD 163296 in the H and K bands. To produce a rendu similar to that usually used in radio-interferometry, we convolve all the resulting images with a Gaussian beam at the interferometer resolution defined by the (u,v) plane. The resulting images are plotted in Fig. 1 with a color scale and in Fig. 2 with linear contours. As the minimum cut, we use the level corresponding to the expected dynamic range (see Sect. 4.1 for the discussion on how to compute this value).
![]() |
Figure 3: Reconstructed images of the B10 model of HD 163296 in the H ( left) and K bands ( right). The dashed green ellipse corresponds to the location of the rim in this model. The models used are presented in the upper left corner. Same conventions as in Fig. 1. |
Open with DEXTER |
At first look, the spot representing the star is unambiguous and
corresponds to the maximum of the images in the two bands. Around this
central spot, one can see many secondary blobs. In the next section, we
will discuss the level of confidence in these blobs by comparing
them to the results obtained on simulated data from the B10
model. The
main secondary blobs are concentrated in the center of the image
around the brightest spot at a distance of smaller than
4-5 mas. To show the location of these secondary blobs, an
ellipse is drawn using a dashed blue line in Figs. 1
and 2
with a semi-major axis of 4.5 mas, an
inclination of 55
,
and a position angle of
155
.
When considering their repartition along
the ellipse, we find that they are less numerous at the bottom of the
ellipse. The percentage of flux in these blobs is around
30% in the K band and 24% in the H
band.
Inside the ellipse, the central spot is not point-like. In the Hband, the central spot is extended, while in the K band the energy is spread into two close separated spots. The emission does not decrease slowly from the central spot towards the exterior but instead shows a rapid decay before increasing again when crossing the ellipse to finally decrease at large distances. We also note that the ellipse and the central spots are not exactly centered, although this result may not be relevant.
3.2 Comparison with simulated images from models
![]() |
Figure 4: Reconstructed images of a geometrical model of HD 163296 with only a star plus a Gaussian ring in the H ( left) and K bands ( right). The dashed green ellipse corresponds to the location of the rim in this model. The models are presented in the upper left corner. Same conventions as in Fig. 1. |
Open with DEXTER |
To analyze the artifacts in the images, we use
the model of HD 163296 presented in B10 (see the bottom right
squares of
Fig. 3
for the H and K-band models) to
simulate images with the same conditions as the actual ones.
The model is composed of a star (producing 30% and
14% of the flux in the H and K
bands, respectively, estimated from spectral energy distribution
fitting), a dust rim located
at 0.45 AU (3.6 mas)
representing 16% (36%) in the H (K)
band
and a bright inner disk, from 0.1 to 0.45 AU, contributes to
the remaining emission. The reconstructed images of the model from
simulated
data with the same (u,v) coverage
and the same error bars as the real
data are shown in Fig. 3 for the
H and K bands.
The analysis of the reconstructed images of the model in the K band illustrates that the following structures are well retrieved by the image reconstruction process:
- The dust rim, which is clearly visible at the right location and appears as a somewhat blobby ellipse. We checked that by changing the (u,v) plane filling, the blob location changes but remains aligned along the ellipse.
- The energy inside the disk, which is more spread than if there was only the star inside the dust rim in the model (see below). This emission between the star and the rim represents the bright inner disk.
- The skewness of the dust rim is visible in the reconstructed images: the bottom part of the blobby ellipse has less flux than the top part.
- The star, the dust rim, and the inner disk provide
15%,
30%, and
55% of the flux, respectively. We emphasize that these values are in close agreement with the model.
In the H band, the dust rim disappears in the reconstructed image as a ring of blobs, but still seems to define the outer boundary of the object. The main reasons are that the rim represents only 16% of the flux to be compared with 36% in the K band, and, that the angular resolution is not high enough in the H band data compared to the K band data (with the CHARA very long baselines). For the dust rim to be seen in the H band, we would need data on longer baselines and higher dynamics in the reconstructed image (1000 at least, 2000 to be unambiguously seen). As in the K band, the bright inner disk is also present in the H band image as a large spot in the middle, which would not have existed with the star only (see below), and represents 86% of the total flux.
To demonstrate that the bright inner disk is clearly seen in the reconstructed images, i.e., that the central spot includes more energy than that from the star alone, reconstruction of a simpler model is performed. This model is the same as the B10 model but without the bright inner disk, i.e. a star surrounded by a Gaussian ring. The star fluxes in the H and K bands remain the same and the Gaussian ring accounts for 70% of the flux in the H band and 86% in the K band. Figure 4 clearly indicates that the star alone does not spread across more than over 4 pixels in the K band and 7 in the H band, which is less than in Fig. 3.
This analysis performed on existing models allows us to state which features in the reconstructed images from Fig. 1 can be trusted. We argue that the main secondary blobs present around the main central spot are real. Their spatial distribution along an ellipse and the intensity present between these peaks and the central spot are also real. However, the clumpy structure of the ring is probably not representative of the reality, but only of the actual (u,v) plane. More observations at different spatial frequencies will probably change the actual position of these peaks along the ellipse, which may be smoothed. However, we conclude that the inclination and orientation of the observed distribution of peaks along an ellipse are real. This orientation and inclination are indeed very close to the ones fitted by B10 and Tannirkulam et al. (2008), and are consistent with previous estimates at different wavelengths (Isella et al. 2007). The second feature that we think is representative of the reconstructed image is that the central spot is extended and not reduced to an unresolved point as a point-like star would be. The shape of this central spot is certainly dependent on the filling of the (u,v) plane, although the position of the centroid is certainly representative of reality.
4 Discussion
In this section, we discuss the reconstructed images.
4.1 Dynamic range
To compute the theoretical dynamical range of our image, we
use an
estimator based on the one proposed by Baldwin
& Haniff (2002)
where n is the total number of measurements,


Applying Eq. (2) to the data, a dynamic range of 780 is found in the K band. In the H band, for which there is fewer data and the error bars are slightly larger, a dynamic range of 400 is computed. Minimum cut levels of 1/780 and 1/400, respectively, are applied to all the K and H figures.
4.2 Use of the spectral information
![]() |
Figure 5: Combination of the reconstructed images of HD 163296 in a two-color image (H band in green, K band in red). The blue ellipse traces the location of the main secondary blobs of the K-band emission. The sub-panels indicate the Gaussian beam at the interferometer resolution used in the convolution. |
Open with DEXTER |
The decision to present one reconstructed image in the H and one in the K band results from different tests made on the B10 model. A trade-off has to be made between ensuring that we have enough data to pave the (u,v) plane and the wavelength dependency expected from circumstellar disks. Because of the intrinsic chromaticity of the object, we prefer to reconstruct two separated images in the H and K bands, otherwise two separated visibilities, sampling different emitting regions, may correspond to the same spatial frequency. We show in Fig. 5 the combination of both reconstructed images that illustrate complementary features.
For each band, we used all the data points in the different spectral channels, assuming implicitly the object to be grey in each separated band. Compared to the model, this method produces images with fewer artifacts than when reconstructing a single broadband image with the average data for all spectral channels. The (u,v) plane is indeed far more filled taking into account all the wavelengths, because there are more spatial frequencies.
4.3 Physical consequences for the models
We emphasize that we have obtained a new type of data in the form of images reconstructed with limited assumptions. The analysis of the results described in Sect. 3.2 is useful for distinguishing artifacts caused mainly by the shape of the (u,v) plane from what we infer to be true features. In this section, we highlight the new information provided by these images, but are also aware that these new pieces of evidence have to be handled with great care.
The ellipse described by the successive blobs in the
reconstructed
image at a distance of 4-5 mas from the center of the image
and
underlined by a blue dot-dashed line in Figs. 1
and 2
certainly traces an external ring. The
characteristics of this ring are not exactly the same as the rim found
in the B10 model plotted with a green dashed line in
Figs. 1
and 2.
The
radius of the ring is 0.55 AU instead of AU
in the
B10 model, the inclination is 55
instead of
,
and the position angle is 155
instead of
.
The intensity is close to that of the model with 30% of the total flux
instead of 36%. The location of the blobs differs a little bit between
the H and K bands:
those in the H-band image are closer to the center
of the image than those in
the K-band image. This behavior could be explained
by a temperature gradient in the disk, which has a tendency to move the
peak of intensity closer to the center for the shorter wavelengths. We
probably also need data on longer baselines (equivalent to the K-band
CHARA data) to resolve unambiguously the external ring in the H-band
image. This bright ring is not clear evidence of a physical rim, which
was proposed by
Dullemond et al. (2001).
We propose that this feature instead traces an
enhancement of the intensity caused by a change in the opacity in the
disk probably due to sublimation of dust.
We assume that the number of blobs along this ellipse is representative of the azimuthal distribution of the intensity. Following B10 who in their analysis proposed a model of a rim with a skewed distribution of intensity along the ring (see Fig. 4), we assume that the distribution of light along the blue ellipse indicates that the actual ring of light is less luminous in the south-west direction than in the north-east direction at least in the K-band image. In the H-band image, there are blobs around the central spot that do not appear in the reconstructed image of the model. Does this mean that there is more flux in the external ring than expected? Is the skewness factor more important because the blobs appeared at one side only? Does the presence of blobs in the south part of the ellipse rather than in the north in the K-band image have some significance? To remain on solid ground, we assume that the intensity varies along the distribution of blobs, but do not have definitive data to determine the magnitude of this effect. The departure from the axisymmetry may be caused by an inclined surface of the disk or even a strong dust opacity change.
The energy detected within the ellipse is certainly real: as explained in Sect. 3.2, the central region, which contains about 70% of the flux, certainly does not originate in a single unresolved star but from an extended source. These results independently confirm the conclusions of B10, without using any model. Indeed, B10 were unable to fit the visibilities at higher spatial frequencies without introducing some continuous emission in the space between the rim and the star. They called this region the inner disk. We do not know whether the shape of this central source in the K-band image in the form of two spots is real or not, since in the simulated image this central source also seems to be decomposed into 3 single sources, which were not present in the model. It might be only the effect of the (u,v) plane coverage, but we cannot exclude too that it might be due to a hot spot in the disk, although we should in principle then see it in the two images. The reconstructed images cannot help us to determine the origin of the inner disk emission, and ascertain whether it comes from hot gas or very refractory grains. These unknowns may be solved by combining high resolution spectroscopic observations in the near-infrared with advanced models that self-consistently compute the emission of both dust and gas.
Finally, it remains unclear whether the non-zero value of the closure phases found by B10 is caused by the contribution from the inner disk not being exactly centered with the external ring. This might be the case when the disk surface is flaring and the system is seen with non-zero inclination. If the curvature of the surface of the disk probed by our images is large enough, then the ellipses tracing equal distances to the star will be shifted in the polar direction.
4.4 Consequences on the image reconstruction
Since image reconstruction in optical interferometry remains in its infancy, only a too sparse (u,v) coverage is available to reconstruct an unambiguous image of a complex object and analyze it without the help of the model-fitting technique. Repeated comparisons between the model and the reconstructed image have to be performed to avoid over-interpreting the structures in the images. However, in all these cases, the image reconstruction technique remains the only technique able to perform model-independent analysis of the data and is a powerful tool to give more credits to the models, derive tighter constraints, or even reveal unexpected structures.
In the future, two aspects of the image reconstruction will be important:
- 1.
- The homogeneity of the (u,v) plane: thanks to several tests on the B10 model, we found that the global blobby aspect of the reconstructed image is almost certainly caused by the non-homogeneity of the (u,v) plane. Indeed the reconstructed images from a homogeneous (u,v) plane are smoother. The holes in the (u,v) plane correspond to blobby or point-like structures in the reconstructed images, and the baselines for the observations have to be carefully chosen to map the (u,v) plane as homogeneously as possible.
- 2.
- The quality of the measurements: the number of data points and their associated errors can clearly determine the dynamic range of the image. A larger number of data points and smaller error bars are needed to improve the dynamics of the image.
![]() |
Figure 6: Reconstructed image of the B10 model in the K band, using a synthetic (u,v) plane obtained with 3 quadruplets (A0-K0-G0-I1, D0-H0-G1-I1, E0-G0-H0-I1) at VLTI and the CHARA baselines (S1-W1, W1-W2, S2-W2, E1-W1, E2-S2, S2-W1). |
Open with DEXTER |
5 Conclusion
Since the renewal of optical interferometry in the mid-70's, imaging using aperture synthesis between different telescopes has been attempted for all possible astrophysical topics following the path opened by radio-interferometry with the Very Large Array. Unfortunately, optical interferometry requires precisions in the optical path delay 103 to 105 smaller than in the radio domain and therefore the development of large optical arrays has been slower. Although images of stellar surfaces or binaries have been obtained, no synthetic images have so far been possible at the milli-arcsecond scale of complex young stellar objects.
This paper is the first one attempting to reconstruct images of the close environment of a young star independent of any a priori model by gathering many interferometric measurements on the young star HD 163296 with various interferometers (VLTI, IOTA, KeckI, and CHARA). Using the Multi-Aperture Image Reconstruction Algorithm (MiRA), we have reconstructed images of HD 163296 in the H and K bands. The quality of the images compares well to those obtained 40 years ago with the first three antennas of the Very Large Array. To assess the reality of the features that are present, we have compared these images with images obtained from simulated data using the best known physical model of the environment of HD 163296 and reconstructed with the same conditions of (u,v) plane and noise.
Those model-independent H and K-band images of the surrounding of HD 163296 reveal several significant features that we can relate to the presence of an inclined asymmetric disk around HD 163296. We also detect a pre-eminent intensity at the location of dust sublimation above a structure extending from the central source with some differential effect along the azimuth that is not necessarily related to a puffed-up inner rim. Together with a slight offset of the central source compared to this bright ring, we proposed this to be the signature of the flared surface of a disk with a discontinuity caused by a opacity change.
These images confirm that the morphology of the close environment of young stars is more complex than the simple models used in the literature. We have also shown that having a more uniform (u,v) plane coverage and higher measurement accuracies should help us to obtain higher quality images in the future.
AcknowledgementsThe authors are grateful to the different institutions that trusted them in giving them guaranteed observing time with the VLTI to perform the first image of a complex young stellar object: CNRS through its national programs (ASHRA and PNPS), INAF and the AMBER consortium. This research has made use of NASA's Astrophysics Data System service, of the Jean-Marie Mariotti Center (JMMC) resources of the SIMBAD database, operated at CDS, Strasbourg, France, and of the Yorick, a free data processing language written by D. Munro (http://yorick.sourceforge.net). M.B. acknowledges fundings from INAF (grant ASI-INAF I/016/07/0).
Appendix A: The data set in detail
Table A.1: Log of the data used for the image reconstruction.
![]() |
Figure A.1: (u,v) plane coverage of the data used for the image reconstruction in spatial frequencies for the H ( left) and K ( right) bands. The different interferometers are plotted in different colors and symbols. |
Open with DEXTER |
![]() |
Figure A.2: Squared visibilities ( up) and closure phases ( bottom) in the H ( left) and K ( right) bands. The different interferometers are plotted in different colors and symbols. |
Open with DEXTER |
![]() |
Figure A.3: Squared visibilities in the H ( left) and K ( right) bands for the VLTI/AMBER data. The different colors and symbols correspond to different baseline position angle ranges. |
Open with DEXTER |
Appendix B: The effect of the regularization weight
The systematic tests performed in RTM10 shows that a weight factor
can be
associated with a regularization term to within an order of
magnitude. In this appendix, we illustrate the effect of the
factor on
the reconstructed images, therefore determining the influence
of
and demonstrating that
is the best value.
![]() |
Figure B.1:
Reconstructed images of HD 163296 in the K
band from simulated data of the B10 model (up) and
from the real data (bottom), for
3 different values of the weight factor |
Open with DEXTER |
The upper part of Fig. B.1
presents the reconstructed
images from the B10 model in the K band for
3 different values of the
weight factor
(1000, 100, 10). When comparing them to the model (see
the upper left corner of Fig. 3), the
following information can be extracted:
- In the left part of Fig. B.1, the image is too regularized, meaning that too much weight is put on the regularization term and not enough on the data. The reconstructed image is too smooth and several structure are not visible, because of the lack of distinction between the external ring and the internal disk.
- In the right part of Fig. B.1, the image is insufficiently regularized, meaning that too much weight has been placed on the data. The reconstructed image is far more blobby than the original and the flux in the internal disk starts to disappear.
- The ideal weight factor is shown in the middle part of Fig. B.1. In this figure, all the different characteristics of the model are presented and it seems to provide the best reconstruction between the three.
References
- Balbus, S. A., & Hawley, J. F. 1991, ApJ, 376, 214 [NASA ADS] [CrossRef] [Google Scholar]
- Baldwin, J. E., & Haniff, C. A. 2002, Phil. Trans. R. Soc. London, Ser. A, 360, 969 [Google Scholar]
- Benisty, M., Natta, A., Isella, A., et al. 2010, A&A, 511, A74 (B10) [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Boss, A. P. 1997, Science, 276, 1836 [NASA ADS] [CrossRef] [Google Scholar]
- Cotton, W., Monnier, J., Baron, F., et al. 2008, in SPIE Conf. Ser., 7013 [Google Scholar]
- Deleuil, M., Bouret, J., Catala, C., et al. 2005, A&A, 429, 247 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Devine, D., Grady, C. A., Kimble, R. A., et al. 2000, ApJ, 542, L115 [NASA ADS] [CrossRef] [Google Scholar]
- Dullemond, C. P., Dominik, C., & Natta, A. 2001, ApJ, 560, 957 [NASA ADS] [CrossRef] [Google Scholar]
- Grady, C. A., Devine, D., Woodgate, B., et al. 2000, ApJ, 544, 895 [Google Scholar]
- Haubois, X., Perrin, G., Lacour, S., et al. 2009, A&A, 508, 923 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Henning, T., & Meeus, G. 2009, in Physical Processes in Circumstellar Disks around Young Stars, ed. P. J. V. Garcia, Theoretical Astrophysics Series (Chicago: University Press), in press [arXiv:0911.1010] [Google Scholar]
- Hogg, D. E., MacDonald, G. H., Conway, R. G., & Wade, C. M. 1969, AJ, 74, 1206 [NASA ADS] [CrossRef] [Google Scholar]
- Isella, A., Testi, L., Natta, A., et al. 2007, A&A, 469, 213 [CrossRef] [EDP Sciences] [Google Scholar]
- Kraus, S., Weigelt, G., Balega, Y. Y., et al. 2009, A&A, 497, 195 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Lacour, S., Meimon, S., Thiébaut, E., et al. 2008, A&A, 485, 561 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Lacour, S., Thiéaut, E., Perrin, G., et al. 2009, ApJ, 707, 632 [NASA ADS] [CrossRef] [Google Scholar]
- Lawson, P. R., 2000, Principles of Long Baseline Stellar Interferometry [Google Scholar]
- Le Bouquin, J., Lacour, S., Renard, S., et al. 2009, A&A, 496, L1 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Malbet, F., & Perrin, G. 2007, New Astron. Rev., 51, 563 [NASA ADS] [CrossRef] [Google Scholar]
- Mannings, V., & Sargent, A. I. 1997, ApJ, 490, 792 [NASA ADS] [CrossRef] [Google Scholar]
- Mayer, L., Quinn, T., Wadsley, J., & Stadel, J. 2002, Science, 298, 1756 [NASA ADS] [CrossRef] [PubMed] [Google Scholar]
- Millan-Gabet, R., Malbet, F., Akeson, R., et al. 2007, Protostars and Planets V, 539 [Google Scholar]
- Monnier, J. D. 2003, Rep. Progr. Phys., 66, 789 [Google Scholar]
- Monnier, J. D., Millan-Gabet, R., Billmeier, R., et al. 2005, ApJ, 624, 832 [NASA ADS] [CrossRef] [Google Scholar]
- Monnier, J. D., Berger, J., Millan-Gabet, R., et al. 2006, ApJ, 647, 444 [NASA ADS] [CrossRef] [Google Scholar]
- Monnier, J. D., Zhao, M., Pedretti, E., et al. 2007, Science, 317, 342 [NASA ADS] [CrossRef] [PubMed] [Google Scholar]
- Montesinos, B., Eiroa, C., Mora, A., & Merín, B. 2009, A&A, 495, 901 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Natta, A., Testi, L., Neri, R., Shepherd, D. S., & Wilner, D. J. 2004, A&A, 416, 179 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Strong, D., & Chan, T. 2003, Inverse Problems, 19, S165 [NASA ADS] [CrossRef] [Google Scholar]
- Swartz, D. A., Drake, J. J., Elsner, R. F., et al. 2005, ApJ, 628, 811 [NASA ADS] [CrossRef] [Google Scholar]
- Tannirkulam, A., Monnier, J. D., Millan-Gabet, R., et al. 2008, ApJ, 677, L51 [NASA ADS] [CrossRef] [Google Scholar]
- Thiébaut, E. 2002, in SPIE Conf. Ser. 4847, ed. J.-L. Starck, & F. D. Murtagh, 174 [Google Scholar]
- Thiébaut, E. 2005, in NATO ASIB Proc. 198: Optics in astrophysics, ed. R. Foy, & F. C. Foy, 397 [Google Scholar]
- Thiébaut, E. 2008, in SPIE Conf. Ser. 7013 [Google Scholar]
- Thiébaut, É., & Giovannelli, J.-F. 2009, 2010, ISPM, 27, 970 [Google Scholar]
- van den Ancker, M. E., de Winter, D., & Tjin A Djie, H. R. E. 1998, A&A, 330, 145 [NASA ADS] [Google Scholar]
- Wassell, E. J., Grady, C. A., Woodgate, B., Kimble, R. A., & Bruhweiler, F. C. 2006, ApJ, 650, 985 [NASA ADS] [CrossRef] [Google Scholar]
- Zhao, M., Gies, D., Monnier, J. D., et al. 2008, ApJ, 684, L95 [NASA ADS] [CrossRef] [Google Scholar]
- Zhao, M., Monnier, J. D., Pedretti, E., et al. 2009, ApJ, 701, 209 [NASA ADS] [CrossRef] [Google Scholar]
All Tables
Table A.1: Log of the data used for the image reconstruction.
All Figures
![]() |
Figure 1: Reconstructed images of HD 163296 in the H (left) and K bands (right), after a convolution with a Gaussian beam at the interferometer resolution. The colors are scaled to the squared root of the intensity with a cut corresponding to the maximum expected dynamic range (see text for details). The blue ellipse traces the location of the main secondary blobs, and the green dot-dashed ellipse corresponds to the location of the rim in the B10 model, with its width given by the green dashed ellipses. North is up and east is left. The sub-panel in the right corner of each plot indicates the Gaussian beam at the interferometer resolution, applicable to Figs. 3, 4, and 6. |
Open with DEXTER | |
In the text |
![]() |
Figure 2: Contours of the reconstructed images of HD 163296 in the H ( left) and K bands ( right), after a convolution with a Gaussian beam at the interferometer resolution. The contours vary linearly between the minimum cut corresponding to the maximum expected dynamic range and the image maximum, with a step around 0.1. |
Open with DEXTER | |
In the text |
![]() |
Figure 3: Reconstructed images of the B10 model of HD 163296 in the H ( left) and K bands ( right). The dashed green ellipse corresponds to the location of the rim in this model. The models used are presented in the upper left corner. Same conventions as in Fig. 1. |
Open with DEXTER | |
In the text |
![]() |
Figure 4: Reconstructed images of a geometrical model of HD 163296 with only a star plus a Gaussian ring in the H ( left) and K bands ( right). The dashed green ellipse corresponds to the location of the rim in this model. The models are presented in the upper left corner. Same conventions as in Fig. 1. |
Open with DEXTER | |
In the text |
![]() |
Figure 5: Combination of the reconstructed images of HD 163296 in a two-color image (H band in green, K band in red). The blue ellipse traces the location of the main secondary blobs of the K-band emission. The sub-panels indicate the Gaussian beam at the interferometer resolution used in the convolution. |
Open with DEXTER | |
In the text |
![]() |
Figure 6: Reconstructed image of the B10 model in the K band, using a synthetic (u,v) plane obtained with 3 quadruplets (A0-K0-G0-I1, D0-H0-G1-I1, E0-G0-H0-I1) at VLTI and the CHARA baselines (S1-W1, W1-W2, S2-W2, E1-W1, E2-S2, S2-W1). |
Open with DEXTER | |
In the text |
![]() |
Figure A.1: (u,v) plane coverage of the data used for the image reconstruction in spatial frequencies for the H ( left) and K ( right) bands. The different interferometers are plotted in different colors and symbols. |
Open with DEXTER | |
In the text |
![]() |
Figure A.2: Squared visibilities ( up) and closure phases ( bottom) in the H ( left) and K ( right) bands. The different interferometers are plotted in different colors and symbols. |
Open with DEXTER | |
In the text |
![]() |
Figure A.3: Squared visibilities in the H ( left) and K ( right) bands for the VLTI/AMBER data. The different colors and symbols correspond to different baseline position angle ranges. |
Open with DEXTER | |
In the text |
![]() |
Figure B.1:
Reconstructed images of HD 163296 in the K
band from simulated data of the B10 model (up) and
from the real data (bottom), for
3 different values of the weight factor |
Open with DEXTER | |
In the text |
Copyright ESO 2010
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.