2018
DOI: 10.1051/0004-6361/201731627
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A study of dust properties in the inner sub-au region of the Herbig Ae star HD 169142 with VLTI/PIONIER

Abstract: Context. An essential step to understanding protoplanetary evolution is the study of disks that contain gaps or inner holes. The pretransitional disk around the Herbig star HD 169142 exhibits multi-gap disk structure, differentiated gas and dust distribution, planet candidates, and near-infrared fading in the past decades, which make it a valuable target for a case study of disk evolution. Aims. Using near-infrared interferometric observations with VLTI/PIONIER, we aim to study the dust properties in the inner… Show more

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Cited by 14 publications
(13 citation statements)
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“…Our rings are at a similar location to the ∼ 100 mas (∼ 11 AU) ring and asymmetry found by Ligi et al (2018). The location of our inner disc (r d ) is at 0.11 AU (0.96 mas), which is slightly beyond the radius of 0.07 AU found by Chen et al (2018) from their modelling of the inner disc.…”
Section: Summary Of Hd 169142 Resultssupporting
confidence: 82%
“…Our rings are at a similar location to the ∼ 100 mas (∼ 11 AU) ring and asymmetry found by Ligi et al (2018). The location of our inner disc (r d ) is at 0.11 AU (0.96 mas), which is slightly beyond the radius of 0.07 AU found by Chen et al (2018) from their modelling of the inner disc.…”
Section: Summary Of Hd 169142 Resultssupporting
confidence: 82%
“…The uncertainties of the parameters are estimated with the bootstrapping method. The best-fit model parameters for the 2011-2013 observations (Chen et al 2018 observations could be due to a simultaneous slight fading of the innermost ring, but could also be related to observational uncertainty.…”
Section: A Scenario Of Dust Evolutionmentioning
confidence: 97%
“…The model reproduces the observations within the formal uncertainties, accounting for the steep drop of visibility at the short baselines with the outer ring at ∼0.3 au. For comparison, our previous model of the 2011-2013VLTI/PIONIER observations (model 2012-2013Chen et al 2018) is also listed.…”
Section: Modeling the 2019 Data Setmentioning
confidence: 99%
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