AVIATOR: Morphological object reconstruction in 3D. An application to dense cores. (arXiv:1912.01005v1 [astro-ph.IM])

<a href="http://arxiv.org/find/astro-ph/1/au:+Hasenberger_B/0/1/0/all/0/1">B. Hasenberger</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Alves_J/0/1/0/all/0/1">J. Alves</a>

Reconstructing 3D distributions from their 2D projections is a ubiquitous

problem in various scientific fields, particularly so in observational

astronomy. In this work, we present a new approach to solving this problem: a

Vienna inverse-Abel-transform based object reconstruction algorithm AVIATOR.

The reconstruction that it performs is based on the assumption that the

distribution along the line of sight is similar to the distribution in the

plane of projection, which requires a morphological analysis of the structures

in the projected image. The output of the AVIATOR algorithm is an estimate of

the 3D distribution in the form of a reconstruction volume that is calculated

without the problematic requirements that commonly occur in other

reconstruction methods such as symmetry in the plane of projection or modelling

of radial profiles. We demonstrate the robustness of the technique to different

geometries, density profiles, and noise by applying the AVIATOR algorithm to

several model objects. In addition, the algorithm is applied to real data: We

reconstruct the density and temperature distributions of two dense molecular

cloud cores and find that they are in excellent agreement with profiles

reported in the literature. The AVIATOR algorithm is thus capable of

reconstructing 3D distributions of physical quantities consistently using an

intuitive set of assumptions.

Reconstructing 3D distributions from their 2D projections is a ubiquitous

problem in various scientific fields, particularly so in observational

astronomy. In this work, we present a new approach to solving this problem: a

Vienna inverse-Abel-transform based object reconstruction algorithm AVIATOR.

The reconstruction that it performs is based on the assumption that the

distribution along the line of sight is similar to the distribution in the

plane of projection, which requires a morphological analysis of the structures

in the projected image. The output of the AVIATOR algorithm is an estimate of

the 3D distribution in the form of a reconstruction volume that is calculated

without the problematic requirements that commonly occur in other

reconstruction methods such as symmetry in the plane of projection or modelling

of radial profiles. We demonstrate the robustness of the technique to different

geometries, density profiles, and noise by applying the AVIATOR algorithm to

several model objects. In addition, the algorithm is applied to real data: We

reconstruct the density and temperature distributions of two dense molecular

cloud cores and find that they are in excellent agreement with profiles

reported in the literature. The AVIATOR algorithm is thus capable of

reconstructing 3D distributions of physical quantities consistently using an

intuitive set of assumptions.

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