A differentiable and optimizable 3D model for interpretation of observed spectral data cubes

TL;DR

This paper introduces a differentiable 3D model that interprets spectral data cubes of prestellar cores, enabling efficient optimization to infer physical and chemical properties from observed molecular spectra.

Contribution

A novel differentiable 3D geometrical model for spectral data cubes that allows direct optimization and interpretation of prestellar core observations.

Findings

The model successfully reproduces observed spectral features.

Asymmetry in density and velocity is necessary to match observations.

Application to L1544 reveals detailed core structure.

Abstract

Molecular spectral cubes of prestellar cores encode the information on the physical and chemical properties of these objects along the line of sight. To retrieve this information, we need an interpretable model that reproduces the observed spectra. We designed a differentiable 3D geometrical model that produces synthetic observations from the parameterized density and velocity fields, and that can be efficiently optimized to reproduce the real data cubes. The model has been applied to p-NH2D and N2D+ spectral cubes in the prestellar core L1544. The optimized model suggests that to reproduce the observed velocity difference between p-NH2D and N2D+ in L1544, an asymmetric structure in density and velocity is necessary.