# Automated, context-free assignment of asymmetric rotor microwave spectra

**Authors:** Lia Yeh, Lincoln Satterthwaite, David Patterson

arXiv: 1812.06221 · 2019-06-26

## TL;DR

The paper introduces RAARR, an automated algorithm that rapidly assigns asymmetric rotor microwave spectra, even for complex mixtures, without prior molecular data, significantly advancing spectral analysis efficiency.

## Contribution

The novel RAARR algorithm automates the assignment of asymmetric rotor spectra using energy conservation constraints, handling mixtures and unestimated constants efficiently.

## Key findings

- Successfully assigned 15 experimental spectra, including 5 new species.
- Automatically assigned multiple mixture components in 9 cases.
- Operates in about 100 seconds, demonstrating high speed and accuracy.

## Abstract

We present a new algorithm, Robust Automated Assignment of Rigid Rotors (RAARR), for assigning rotational spectra of asymmetric tops. The RAARR algorithm can automatically assign experimental spectra under a broad range of conditions, including spectra comprised of multiple mixture components, in about 100 seconds or less. The RAARR algorithm exploits constraints placed by the conservation of energy to find sets of connected lines in an unassigned spectrum. The highly constrained structure of these sets eliminates all but a handful of plausible assignments for a given set, greatly reducing the number of potential assignments that must be evaluated. We successfully apply our algorithm to automatically assign 15 experimental spectra, including 5 previously unassigned species, without prior estimation of molecular rotational constants. In 9 of the 15 cases, the RAARR algorithm successfully assigns two or more mixture components.

## Full text

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## Figures

5 figures with captions in the complete paper: https://tomesphere.com/paper/1812.06221/full.md

## References

30 references — full list in the complete paper: https://tomesphere.com/paper/1812.06221/full.md

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Source: https://tomesphere.com/paper/1812.06221