Inspecting spectra with sound: proof-of-concept & extension to datacubes

Abstract

We present a novel approach to inspecting galaxy spectra using sound, via their direct audio representation ('spectral audification'). We discuss the potential of this as a complement to (or stand-in for) visual approaches. We surveyed 58 respondents who use the audio representation alone to rate 30 optical galaxy spectra with strong emission lines. Across three tests, each focusing on different quantities measured from the spectra (signal-to-noise ratio, emission-line width, & flux ratios), we find that user ratings are well correlated with measured quantities. This demonstrates that physical information can be independently gleaned from listening to spectral audifications. We note the importance of context when rating these sonifications, where the order examples are heard can influence responses. Finally, we adapt the method used in this promising pilot study to spectral datacubes. We suggest that audification allows efficient exploration of complex, spatially-resolved spectral data.