2018
DOI: 10.3847/1538-4357/aaab63
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Characterizing the Variable Dust Permeability of Planet-induced Gaps

Abstract: Aerodynamic theory predicts that dust grains in protoplanetary disks will drift radially inward on comparatively short timescales. In this context, it has long been known that the presence of a gap opened by a planet can alter the dust dynamics significantly. In this paper, we carry out a systematic study employing long-term numerical simulations aimed at characterizing the critical particle-size for retention outside a gap as a function of particle size and for various key parameters defining the protoplaneta… Show more

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Cited by 102 publications
(112 citation statements)
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“…), dust filtration is found to be more efficient when the gap is deep and narrow, resulting in a higher pressure gradient at the outer edge of the gap (Weber et al. ). In general, the more massive a planet is, the smaller the particles that can reach the inner edge of the gap (Weber et al.…”
Section: Discussionmentioning
confidence: 99%
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“…), dust filtration is found to be more efficient when the gap is deep and narrow, resulting in a higher pressure gradient at the outer edge of the gap (Weber et al. ). In general, the more massive a planet is, the smaller the particles that can reach the inner edge of the gap (Weber et al.…”
Section: Discussionmentioning
confidence: 99%
“…In general, the more massive a planet is, the smaller the particles that can reach the inner edge of the gap (Weber et al. ). Hence, a growing planet is expected to filter more particles over time, a trend opposite to expectations brought forward by our data.…”
Section: Discussionmentioning
confidence: 99%
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“…In addition, our solutions make a number of symmetry assumptions (most notably azimuthal symmetry) and full 3D calculations will be required to understand the dynamics induced by the back-reaction. This however requires sophisticated gas and dust simulations, the tools for which have only recently begun to be developed (Gonzalez et al 2017;Ricci et al 2018;Humphries & Nayakshin 2018;Hutchison et al 2018;Weber et al 2018).…”
Section: Limitations Of the Modelmentioning
confidence: 99%