Abstract
We recently presented a new “artificial intelligence” method for the analysis of high-resolution absorption spectra (Bainbridge and Webb, Mon. Not. R. Astron. Soc. 2017, doi:10.1093/mnras/stx179). This new method unifies three established numerical methods: a genetic algorithm (GVPFIT); non-linear least-squares optimisation with parameter constraints (VPFIT); and Bayesian Model Averaging (BMA). In this work, we investigate the performance of GVPFIT and BMA over a broad range of velocity structures using synthetic spectra. We found that this new method recovers the velocity structures of the absorption systems and accurately estimates variation in the fine structure constant. Studies such as this one are required to evaluate this new method before it can be applied to the analysis of large sets of absorption spectra. This is the first time that a sample of synthetic spectra has been utilised to investigate the analysis of absorption spectra. Probing the variation of nature’s fundamental constants (such as the fine structure constant), through the analysis of absorption spectra, is one of the most direct ways of testing the universality of physical laws. This “artificial intelligence” method provides a way to avoid the main limiting factor, i.e., human interaction, in the analysis of absorption spectra.
Highlights
Probing the variation of nature’s fundamental constants, through the analysis of absorption spectra, is one of the most direct ways of testing the universality of physical laws
This method requires evaluation before being applied to the analysis of large sets of absorption spectra. It is unknown how the accuracy of GVPFIT and Bayesian Model Averaging (BMA) is effected by the complexity of an absorption systems velocity structure
We investigate the performance of GVPFIT and BMA over a broad range of velocity structure complexities using synthetic spectra
Summary
Probing the variation of nature’s fundamental constants (such as the fine structure constant, α), through the analysis of absorption spectra, is one of the most direct ways of testing the universality of physical laws. Interactive methods for analysing high-resolution quasar spectra of heavy element absorption systems are complex and require considerable expertise. Our new method unifies three established numerical methods: a genetic algorithm (GVPFIT); non-linear least-squares optimisation with parameter constraints (VPFIT); and Bayesian Model Averaging (BMA). This method requires evaluation before being applied to the analysis of large sets of absorption spectra. It is unknown how the accuracy of GVPFIT and BMA is effected by the complexity of an absorption systems velocity structure. We investigate the performance of GVPFIT and BMA over a broad range of velocity structure complexities using synthetic spectra. By directly comparing our Universe 2017, 3, 34; doi:10.3390/universe3020034 www.mdpi.com/journal/universe
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