Abstract This paper introduces the Wide-band Asp-Clean ( WAsp ) algorithm, a novel scale-sensitive image reconstruction method tailored for wide-band imaging applications. This algorithm is particularly beneficial for thermal noise-limited imaging with aperture synthesis telescopes, where joint spatio-frequency modeling of the sky brightness distribution is critical. The WAsp algorithm replaces the use of the MS-Clean algorithm in the Multi-scale Multi-Term Multi-Frequency Synthesis algorithm with the Asp algorithm, which itself has been improved for both imaging and runtime performance. With the high sensitivity of current and next-generation telescopes, spatio-frequency modeling on a scale-sensitive basis becomes crucial for ensuring that residuals align with the noise model across the frequency band. Although existing wide-band scale-sensitive algorithms have demonstrated superior performance over scale-insensitive counterparts, they often suffer from well-documented deficiencies, leading to significant wide-scale residuals in Stokes- I at low levels and consequently significant relative errors in spectral index maps. The WAsp algorithm addresses these limitations while maintaining computational efficiency. The implementation can be configured to support narrowband and wide-band scale-sensitive imaging, spectral-cube imaging applications, and joint single-dish and interferometer imaging. To demonstrate improved imaging performance, we show a comparison with existing algorithms via carefully developed simulations for stress-testing the algorithms. We also present results from its application to real-world wide-band data, underscoring its effectiveness in practical imaging scenarios.
Hsieh et al. (Mon,) studied this question.
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