Free Access
Issue
A&A
Volume 597, January 2017
Article Number A132
Number of page(s) 8
Section Interstellar and circumstellar matter
DOI https://doi.org/10.1051/0004-6361/201628696
Published online 18 January 2017

© ESO, 2017

1. Introduction

The definition of transitional disks is heavily debated in the literature. Espaillat et al. (2014) defined transitional disks as objects that exhibit almost no near-IR excess, yet harbor a strong mid- and far-IR excess. The former suggests that the inner regions have been cleared of material, forming a hole in the disk. Strom et al. (1989) suggested that they are a transition stage in the evolution from an optically thick disk extending towards the star into a dispersed low-mass disk. Disks that have a near-IR excess but a dip in the mid-IR emission can be interpreted as a two-disk system with a gap in between (Espaillat et al. 2012). They are sometimes referred to as pre-transitional disks (Espaillat et al. 2007).

A key question for studying these objects is how their inner region is cleared out. Several mechanisms have been proposed for this. As a consequence of viscosity in disks, they are expected to become optically thin as they accrete (Alexander et al. 2014), but this is a slow process. Photoevaporation, where material on the surface of the disk is heated strongly by the UV or X-ray radiation from the central star, can cause an outflow of material from the disk (Alexander et al. 2014). This cuts off the supply of disk material from the outer disk, making it possible to clear out the inner disk as the material quickly accretes onto the star. A substantial sample of transitional disks, however, show inner holes that are too large together with accretion rates that are too high to be explained by photoevaporation alone (Owen et al. 2011). Furthermore, disk winds driven by magnetohydrodynamic turbulance can also play an important role in the dispersal of disks (Suzuki & Inutsuka 2009). It is also possible to create gaps in the disk by dynamical interaction with single (e.g., Pinilla et al. 2012; de Juan Ovelar et al. 2013) or multiple massive objects (e.g., Zhu et al. 2011; Dodson-Robinson & Salyk 2011; Dong et al. 2015). The main candidate for this type of clearing is a planetary body that carves a hole by sweeping up material as it moves through the disk. The transitional disks are thought to be an important stage in understanding the formation of these planets, and several promising canditates for planets within disks have been observed, e.g., HD 100546 (Quanz et al. 2013; Currie et al. 2015), HD 169142 (Reggiani et al. 2014), and LkCa 15 (Kraus & Ireland 2012; Sallum et al. 2015).

A significant sample of transitional disks are shown to have a cavity in the submm (Andrews et al. 2011). Recently however, comparisons of high-resolution near-IR observations with submm images have shown a possible number of transitional disks with near-IR emission extending into the submm cavity (e.g., Dong et al. 2012), which suggests a decoupling of the distribution of both small and large dust grains. In some cases the cavities at both wavelengths have been spatially resolved, indeed showing that the small dust grains can move in closer to the star than the large dust grains (e.g., Muto et al. 2012; Garufi et al. 2013; Grady et al. 2013; Follette et al. 2013).

The transitional disk RX J1615.3-3255 (from here on referred to as RXJ1615) was first detected by Henize (1976). RXJ1615 is located in the constellation Lupus and has been kinematically tied to a young (~1 Myr old) subgroup of the Lupus association at a distance of 185 pc (Makarov 2007). It was identified as a weak-line T Tauri star by Krautter et al. (1997), based on optical spectroscopy. Spitzer IR observations, showed the first evidence of an inner hole in the disk by performing a fit to the SED, designating it a transitional disk (Merín et al. 2010).

Andrews et al. (2011) performed high-resolution 880 μm observations and created a disk model that fits both the spectral energy distribution (SED) and their visibilities. Their data shows a decrease in the intensity close to the center, a low density cavity out to a radius of 30 AU. The disk is relatively flat and massive, ~12% of the stellar mass. Because of the large size of the gap and the disk mass, they find that the disk is most likely cleared dynamically by tidal interactions with a low-mass brown dwarf or giant planet companion on a long-period orbit.

In this paper, we present new H-band scattered light images of RXJ1615 and reproduce the disk model from Andrews et al. (2011) based on submm interferometry and the SED in order to study the spatial distribution of the large versus small dust grains in this disk.

2. Observations and data reduction

Our observations were obtained with the HiCIAO instrument (Tamura et al. 2006) of the Subaru telescope as part of the 16th run of the Strategic Explorations of Exoplanets and Disks with Subaru (SEEDS) survey on July 5, 2012. The images were taken in the H-band (1.6 μm) using a combination of the HiCIAO quad Polarimetric Differential Imaging (qPDI) and Angular Differential Imaging (ADI) modes. In order to explore structures close to the star, no coronographic mask was used. A summary of the observations and the details of the data are given in Table 1.

Table 1

Summary of the observations and the obtained data.

2.1. Data reduction

We performed the data reduction following the standard description for handling PDI data to obtain the Stokes parameters using cycles of four different angular positions of the Wollaston prism (Hinkley et al. 2009). All images were destriped and corrected for warm and bad pixels, distortion, and instrumental polarization. The images were then derotated to account for the ADI observation mode and photometrically calibrated using data of the standard star HD 203856 observed in the open use program on July 5, 2012.

2.2. Bad images

During the data reduction process, we noticed that the quality between exposures varied. This is evidenced in Fig. 1, where we show the FWHM of the stellar light after the distortion correction step. Although the atmospheric attenuation during the night should not have been a problem, the seeing did get above 1′′ for a large part of the night. The adaptive optics or not easily able to correct for this, which might explain the variation in the point spread function (PSF) of the exposures. In order to try to resolve the cavity found by Andrews et al. (2011), we wanted to keep our inner working angle as small as possible. We therefore removed all data where the PSF FWHM is larger than 16 pixels (0.152 arcsec). This effectively meant losing half of the data, bringing the integration time down from 7.5 min (15 waveplate cycles) to 4 (8 waveplate cycles), which significantly reduced our signal-to-noise, but decreased our inner working angle from ~33 AU to ~24 AU.

thumbnail Fig. 1

FWHM in different images. Each line represents a different qPDI channel.

Open with DEXTER

3. Results

thumbnail Fig. 2

Polarized intensity map (left) and signal-to-noise map (right). The red contours show the S/N> 3 region, the green cross denotes the stellar position and the magenta circle gives the inner working angle of 33 AU. The region inside the inner working angle is masked. The plot gives the brightness profile along the disk major axis to which we fitted power-law profiles (black lines). The fitted power-law exponents are given in the plot with 1σ uncertainties.

Open with DEXTER

Using the Stokes Q and U images obtained from the data, we determined the polarized intensity using (1)The resulting polarized intensity map is given in the left panel of Fig. 2, where the brightness profile along the major axis of the disk is given inside the plot. Power-law fits to both sides are shown in the plot as black lines. The disk has a relatively shallow radial profile along the major axis, with power-law indices of −1.17 ± 0.09 and −1.4 ± 0.1, compared to the range of 1.7 to 5 found in other disks (Kusakabe et al. 2012; Muto et al. 2012). As a conservative estimate for the errors on the polarized intensity we used the standard deviation between images of different waveplate cycles, divided by the square root of the number of images. Dividing the polarized intensity by the error then gives the signal-to-noise map shown in the right panel of Fig. 2. As can be seen in both figures, we clearly detected the extended disk emission with a signal-to-noise of ~2–6.

Table 2

Physical parameters measured using an ellipsoid fit.

From the polarized intensity image we estimated a few physical parameters of the RXJ1615 disk and summarize them in Table 2. For the position angle (PA), we fitted an ellipsoid using the Image Reduction and Analysis Facility (IRAF1) package. Assuming an infinitely flat disk, we obtained the inclination angle (i) from the ratio of the major and minor axis of the disk. The uncertainties in these parameters are determined by the IRAF ellipsoid fitting routine. We defined the outer radius (Rout) as the distance from the stellar position along the major axis at which the S/N drops below 3. We note that the outer radius of 68 ± 12 AU is smaller than was found from the submm observations of Andrews et al. (2011; ~115 AU). At large distances, the low surface brightness of the disk can be expected to disappear into the noise and therefore our measurement is likely underestimating the true outer radius of the disk. Our inner working angle of 33 AU does not allow for the exploration of the inner 30 AU cavity. However, when decreasing the inner working angle to 24 AU by removing the bad images, as described in Sect. 2.2, we still do not see signs of a depletion in the inner 30 AU of the disk. Although the large dust grains (~mm size) are depleted in the gap (as evidenced by the submm data), this could signify that the small dust grains (1 μm size) either still survive or that they have a smaller cavity size than the large grains. The latter was also seen in other transitional disks, e.g., SAO 206462 (Muto et al. 2012; Garufi et al. 2013), MWC 758 (Grady et al. 2013), and SR21 (Follette et al. 2013). However, our inner working angle of 24 AU is too close to the 30 AU cavity radius of Andrews et al. (2011) to be certain from this dataset.

In order to confirm the nature of the scattered light, it is possible to look at the direction of the polarization vector. The polarization angle is defined as (2)We overplot this angle on the polarized intensity in Fig. 3, where the angle of the ticks denotes the polarization angle. In the disk region along the major axis most ticks are aligned in a direction perpendicular to the direction towards the stellar position, which is a clear sign that we are indeed looking at light scattered from the star through the disk. We note, however, that the polarization angle is not aligned perpendicular to the radial direction along the minor axis of the disk, and thus a polarized halo might be affecting the observation data (Hashimoto et al. 2012). This could affect our derivation of the outer radius, position angle and inclination of the disk and could also explain why we find a significantly larger inclination angle than Andrews et al. (2011).

thumbnail Fig. 3

Polarization angle map overlayed on a block averaged version of PI. The angle of the yellow ticks gives the polarization angle.

Open with DEXTER

4. Comparison with models

Andrews et al. (2011) created a disk model of RXJ1615 that fits both the spectral energy distribution (SED) and their observed submm visibilities. In order to see if this same model also agrees with the scattered light observations, we used the Monte Carlo three-dimensional continuum radiative transfer code MCFOST (Pinte et al. 2006) to reproduce the Andrews et al. (2011) disk model and simulate an H-band image. The code traces the path of individual packages of photons that propagate through the disk. The photons can undergo scattering, absorption, and re-emission events. The main sources of radiation are thermal emission from dust in the disk and photospheric emission from the star. The thermal emission is assumed to be isotropic and depends only on the temperature, density, and opacity of the disk material. The stellar emission is governed by the stellar photospheric spectrum. Photon packages that manage to escape the computation grid are used to calculate the SED and create the simulated H-band image.

4.1. Disk models

The Andrews et al. (2011) model has three main zones consisting of an inner and outer disk and a puffed up wall at the rim of the outer disk with a gap between the inner and outer disk that has been cleared of material (see Fig. 4).

The density structure of the disk follows a Gaussian profile, (3)where H denotes the scale height. We assume that the dust follows the same vertical distribution as the gas. The disk flaring is characterized by the flaring exponent β(4)where r0 is a reference radius and H0 the corresponding scale height at that radius. The surface density profile follows either a power-law distribution (inner disk) (5)or a tapered edge distribution (outer disk) (6)characterized by the surface density exponent ϵ. The parameter Rc in Eq. (6) denotes the characteristic radius at which the exponential term in the distribution becomes important. The dust grain population follows a power-law distribution in grain size ranging from the smallest size amin to the largest amax as n(s) ∝ a-3.5 and we use Draine astronomical silicates (Draine & Lee 1984).

In the outer disk, we allow for dust settling of the large dust grains onto the midplane of the disk (Dullemond & Dominik 2004). To mimic this effect, we assume two separate dust populations with different reference scale heights. The flaring index is kept constant throughout the disk. In order to reproduce the SED with MCFOST, we had to tweak some of the parameters adpted by Andrews et al. (2011), e.g., Teff was decreased by 150 K, the inner disk dust mass was increased by a factor of 10, and the wall dust mass was decreased by a factor of 100. The full details of the model are given in Table 3. To investigate the effect of different small dust grain distributions on the produced scattered light, we also explore two other models. One is the same as the Andrews et al. (2011) model but without the wall of intermediate sized dust grains at the inner rim of the outer disk. The other is a thin single disk model that fits the SED (no effort was made to fit details such as the Si feature at 10 micron). In this model the scale height is similar to that of the outer disk in the Andrews et al. (2011) model, but the disk extends closer to the star and small and large dust grains are well mixed throughout the disk. The parameters of this model can also be found in Table 3. All three resulting SEDs are shown in Fig. 5, where the photometric fluxes were de-reddened using the CCM law (Cardelli et al. 1989) with AV = 0.4 and RV = 5 (see Table A.1 in the Appendix).

thumbnail Fig. 5

SED of the disk models. The black dashed line shows the stellar SED from the output of MCFOST. The model parameters are given in Table 3. The references for the photometric data points from the literature are given in the legend. The values of the uncorrected fluxes from the literature can be found in Table A.1.

Open with DEXTER

Table 3

Model parameters.

4.2. Simulated H-band image

From MCFOST, we get Stokes Q and U images for the three disk models, which we converted to polarized intensity images of the model as it would be seen at a distance of 185 pc. Convolving this image with a point spread function (PSF) then allows for a better comparison of the model with the data. There is no data available of a PSF reference star observed on the same night, preventing the development of an accurate PSF model. To still enable a qualitative comparison, we used the polarized intensity profile along the minor axis of the disk from our observations as a PSF estimate. This assumes that the disk is unresolved along the minor axis. We then fitted a double Gaussian to the mean of both sides of this profile (a broad component with FWHM = 0.184 arcsec and a narrow component with FWHM = 0.039 arcsec). The resulting convolved H-band image of the Andrews et al. (2011) model is shown in Fig. 6.

thumbnail Fig. 6

Simulated H-band polarized intensity image of the Andrews et al. (2011) model convolved with a two-component Gaussian PSF with FWHM = 0.183 arcsec for the broad component and FWHM = 0.038 arcsec for the narrow one. The scales are identical to Fig. 2 for comparison. The green cross gives the stellar position and the magenta circle denotes the inner working angle from our observations.

Open with DEXTER

The extent of the emission is similar to our observations (~100 AU), but the model clearly produces a much higher signal. This is also evident from the radial profile of the polarized intensity along the major axis of the disk (Fig. 7). Because the wall has a large surface area, it can be expected to produce a lot of scattered light (Thalmann et al. 2010). As can be seen from the radial profile, however, removing the wall only slightly lowers the polarized intensity signal. Instead, most of the emission comes from the inner rim at the edge of the outer disk (30 AU) and is then smeared out by the PSF. The thin single disk model reduces the polarized intensity by a factor of ~2–4, bringing it down to a factor of a few from the observed polarized intensity in the outer ~50 AU of the disk. Even though this model has almost the same scale height as the outer disk in the Andrews et al. (2011) model, its inner radius is much smaller (2.7 AU vs. 30 AU), also making the exposed surface area at the rim smaller (H = 0.03 AU vs. 0.76 AU) and thus reducing the scattered light intensity. This suggests that, although the large grain distribution in RXJ1615 has a cavity out to 30 AU consistent with the 880 μm observations, the small dust grains likely extend closer to the star.

However, this does not have to be the only option for bringing down the polarized intensity. A large inner rim much closer to the star could potentially cast a shadow and thus prevent the stellar light from scattering on the disk behind it (Dong et al. 2012). Such a wall would have to be massive enough because, as we can see from our models, most of the light passes directly through the wall and scatters on the rim of the disk behind it instead. A more massive wall would block more stellar light, but would also affect the shape of the SED. Another possibility would be to change the properties of the dust grains (e.g., lowering the grain albedo or different dust type mixtures) or reducing the amount of small particles in the disk. The thin single disk model simply uses astronomical silicate grains with a minimum grain size of 0.005 μm, which give an albedo of 0.74 and a polarizability of 0.17. Changing amin affects both of these quantities. As can be seen from the dashed line in Fig. 7, changing the minimum dust grain size to amin = 1μm lowers the polarized intensity of the thin single disk model to the same level as we observe. In this case the albedo and the polarizability decrease to 0.63 and 0.12, respectively. However, when increasing the minimum grain size even further to 3 μm, the albedo keeps decreasing as expected (0.57), but the polarizability rises again to much higher values (0.66), therefore increasing the disk polarized intensity again above observed values. The current (low) level of polarized intensity suggests that the dust in the disk has already undergone significant processing compared to the ISM. However, more observations at different frequencies and modeling are required before firm conclusions can be drawn.

thumbnail Fig. 7

Radial profile along the major axis of the simulated disk H-band PI images for the different models compared to our observations.

Open with DEXTER

5. Conclusion

We presented the first H-band scattered light observations of the transitional disk RX J1615.3-3255. We detected the disk in scattered light, finding an outer radius of 68 ± 12 AU. Outside our 24 AU inner working angle, we find no signs of the central depletion in the disk that was previously found in the submm. This could suggest a smaller cavity size for the small grains, but the observations are limited by low signal-to-noise and a large inner working angle. A detailed comparison with several disk models based on fits to the SED and submm visibilities suggests that the small dust grain population is radially decoupled from the large grains. The small dust grains appear to be present closer to the star than the large grains and the dust in the disk has possibly undergone significant processing compared to the ISM. Future higher spatial resolution and higher sensitivity observations (e.g., VLT SPHERE) are required to provide more detailed information on the distribution of the small dust grains in this disk.


1

IRAF is distributed by National Optical Astronomy Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., under cooperative agreement with the National Science Foundation.

Acknowledgments

We thank The Netherlands Foundation for Scientific Research support through the VICI grant 639.043.006. F.Me. acknowledges funding from ANR of France under contract number ANR-16-CE31-0013.

References

  1. Alexander, R., Pascucci, I., Andrews, S., Armitage, P., & Cieza, L. 2014, Protostars and Planets VI, 475 [Google Scholar]
  2. Andrews, S. M., Wilner, D. J., Espaillat, C., et al. 2011, ApJ, 732, 42 [NASA ADS] [CrossRef] [Google Scholar]
  3. Bessell, M. S. 1979, PASP, 91, 589 [NASA ADS] [CrossRef] [Google Scholar]
  4. Cardelli, J. A., Clayton, G. C., & Mathis, J. S. 1989, ApJ, 345, 245 [NASA ADS] [CrossRef] [Google Scholar]
  5. Cohen, M., Wheaton, W. A., & Megeath, S. T. 2003, AJ, 126, 1090 [NASA ADS] [CrossRef] [Google Scholar]
  6. Currie, T., Cloutier, R., Brittain, S., et al. 2015, ApJ, 814, L27 [NASA ADS] [CrossRef] [Google Scholar]
  7. de Juan Ovelar, M., Min, M., Dominik, C., et al. 2013, A&A, 560, A111 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  8. Dodson-Robinson, S. E., & Salyk, C. 2011, ApJ, 738, 131 [NASA ADS] [CrossRef] [Google Scholar]
  9. Dong, R., Hashimoto, J., Rafikov, R., et al. 2012, ApJ, 760, 111 [NASA ADS] [CrossRef] [Google Scholar]
  10. Dong, R., Zhu, Z., & Whitney, B. 2015, ApJ, 809, 93 [NASA ADS] [CrossRef] [Google Scholar]
  11. Draine, B. T., & Lee, H. M. 1984, ApJ, 285, 89 [NASA ADS] [CrossRef] [Google Scholar]
  12. Dullemond, C. P., & Dominik, C. 2004, A&A, 421, 1075 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  13. Espaillat, C., Calvet, N., D’Alessio, P., et al. 2007, ApJ, 670, L135 [NASA ADS] [CrossRef] [Google Scholar]
  14. Espaillat, C., Ingleby, L., Hernández, J., et al. 2012, ApJ, 747, 103 [NASA ADS] [CrossRef] [Google Scholar]
  15. Espaillat, C., Muzerolle, J., Najita, J., et al. 2014, Protostars and Planets VI, 497 [Google Scholar]
  16. Evans, II, N. J., Allen, L. E., Blake, G. A., et al. 2003, PASP, 115, 965 [NASA ADS] [CrossRef] [Google Scholar]
  17. Follette, K. B., Tamura, M., Hashimoto, J., et al. 2013, ApJ, 767, 10 [NASA ADS] [CrossRef] [Google Scholar]
  18. Garufi, A., Quanz, S. P., Avenhaus, H., et al. 2013, A&A, 560, A105 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  19. Grady, C. A., Muto, T., Hashimoto, J., et al. 2013, ApJ, 762, 48 [NASA ADS] [CrossRef] [Google Scholar]
  20. Hashimoto, J., Dong, R., Kudo, T., et al. 2012, ApJ, 758, L19 [NASA ADS] [CrossRef] [Google Scholar]
  21. Henize, K. G. 1976, ApJS, 30, 491 [NASA ADS] [CrossRef] [Google Scholar]
  22. Hinkley, S., Oppenheimer, B. R., Soummer, R., et al. 2009, ApJ, 701, 804 [NASA ADS] [CrossRef] [Google Scholar]
  23. Kraus, A. L., & Ireland, M. J. 2012, ApJ, 745, 5 [NASA ADS] [CrossRef] [Google Scholar]
  24. Krautter, J., Wichmann, R., Schmitt, J. H. M. M., et al. 1997, A&AS, 123, 329 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  25. Kusakabe, N., Grady, C. A., Sitko, M. L., et al. 2012, ApJ, 753, 153 [NASA ADS] [CrossRef] [Google Scholar]
  26. Lommen, D. J. P., van Dishoeck, E. F., Wright, C. M., et al. 2010, A&A, 515, A77 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  27. Makarov, V. V. 2007, ApJ, 658, 480 [NASA ADS] [CrossRef] [Google Scholar]
  28. Merín, B., Brown, J. M., Oliveira, I., et al. 2010, ApJ, 718, 1200 [NASA ADS] [CrossRef] [Google Scholar]
  29. Muto, T., Grady, C. A., Hashimoto, J., et al. 2012, ApJ, 748, L22 [NASA ADS] [CrossRef] [Google Scholar]
  30. Owen, J. E., Ercolano, B., & Clarke, C. J. 2011, MNRAS, 412, 13 [NASA ADS] [CrossRef] [Google Scholar]
  31. Padgett, D. L., Cieza, L., Stapelfeldt, K. R., et al. 2006, ApJ, 645, 1283 [NASA ADS] [CrossRef] [MathSciNet] [Google Scholar]
  32. Pinilla, P., Benisty, M., & Birnstiel, T. 2012, A&A, 545, A81 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  33. Pinte, C., Ménard, F., Duchêne, G., & Bastien, P. 2006, A&A, 459, 797 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  34. Quanz, S. P., Amara, A., Meyer, M. R., et al. 2013, ApJ, 766, L1 [NASA ADS] [CrossRef] [Google Scholar]
  35. Reggiani, M., Quanz, S. P., Meyer, M. R., et al. 2014, ApJ, 792, L23 [NASA ADS] [CrossRef] [Google Scholar]
  36. Sallum, S., Follette, K. B., Eisner, J. A., et al. 2015, Nature, 527, 342 [NASA ADS] [CrossRef] [Google Scholar]
  37. Strom, K. M., Strom, S. E., Edwards, S., Cabrit, S., & Skrutskie, M. F. 1989, AJ, 97, 1451 [NASA ADS] [CrossRef] [Google Scholar]
  38. Suzuki, T. K., & Inutsuka, S.-I. 2009, in AIP Confer. Ser. 1158, eds. T. Usuda, M. Tamura, & M. Ishii, 161 [Google Scholar]
  39. Tamura, M., Hodapp, K., Takami, H., et al. 2006, in SPIE Conf. Ser., 6269, 62690V [Google Scholar]
  40. Thalmann, C., Grady, C. A., Goto, M., et al. 2010, ApJ, 718, L87 [NASA ADS] [CrossRef] [Google Scholar]
  41. Wahhaj, Z., Cieza, L., Koerner, D. W., et al. 2010, ApJ, 724, 835 [NASA ADS] [CrossRef] [Google Scholar]
  42. Zhu, Z., Nelson, R. P., Hartmann, L., Espaillat, C., & Calvet, N. 2011, ApJ, 729, 47 [NASA ADS] [CrossRef] [Google Scholar]

Appendix A: Photometric table

Table A.1

Photometric data from the literature uncorrected for reddening.

All Tables

Table 1

Summary of the observations and the obtained data.

Table 2

Physical parameters measured using an ellipsoid fit.

Table 3

Model parameters.

Table A.1

Photometric data from the literature uncorrected for reddening.

All Figures

thumbnail Fig. 1

FWHM in different images. Each line represents a different qPDI channel.

Open with DEXTER
In the text
thumbnail Fig. 2

Polarized intensity map (left) and signal-to-noise map (right). The red contours show the S/N> 3 region, the green cross denotes the stellar position and the magenta circle gives the inner working angle of 33 AU. The region inside the inner working angle is masked. The plot gives the brightness profile along the disk major axis to which we fitted power-law profiles (black lines). The fitted power-law exponents are given in the plot with 1σ uncertainties.

Open with DEXTER
In the text
thumbnail Fig. 3

Polarization angle map overlayed on a block averaged version of PI. The angle of the yellow ticks gives the polarization angle.

Open with DEXTER
In the text
thumbnail Fig. 5

SED of the disk models. The black dashed line shows the stellar SED from the output of MCFOST. The model parameters are given in Table 3. The references for the photometric data points from the literature are given in the legend. The values of the uncorrected fluxes from the literature can be found in Table A.1.

Open with DEXTER
In the text
thumbnail Fig. 6

Simulated H-band polarized intensity image of the Andrews et al. (2011) model convolved with a two-component Gaussian PSF with FWHM = 0.183 arcsec for the broad component and FWHM = 0.038 arcsec for the narrow one. The scales are identical to Fig. 2 for comparison. The green cross gives the stellar position and the magenta circle denotes the inner working angle from our observations.

Open with DEXTER
In the text
thumbnail Fig. 7

Radial profile along the major axis of the simulated disk H-band PI images for the different models compared to our observations.

Open with DEXTER
In the text

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.