We present the pulsar_spectra software repository, an open-source pulsar flux density catalogue and automated spectral fitting software that finds the best spectral model and produces publication-quality plots. The python-based software includes features that enable users in the astronomical community to add newly published spectral measurements to the catalogue as they become available. The spectral fitting software is an implementation of the method described in Jankowski et al. (2018, MNRAS, 473, 4436) which uses robust statistical methods to decide on the best-fitting model for individual pulsar spectra. pulsar_spectra is motivated by the need for a centralised repository for pulsar flux density measurements to make published measurements more accessible to the astronomical community and provide a suite of tools for measuring spectra.

We present the first observational study of pulsars performed with the second-generation precursor stations to the low-frequency component of the Square Kilometre Array (SKA-Low): the Aperture Array Verification System 2 (AAVS2) and the Engineering Development Array 2 (EDA2). Using the SKA-Low stations, we have observed 100 southern-sky pulsars between 70–350 MHz, including follow-up observations at multiple frequencies for a selected sample of bright pulsars. These observations have yielded detections of 22 pulsars, including the lowest-frequency detections ever published for 6 pulsars, despite the modest sensitivity of initial system where the recording bandwidth is limited to ${\sim}{1}\,\mathrm{MHz}$ . By comparing simultaneous flux density measurements obtained with the SKA-Low stations and performing rigorous electromagnetic simulations, we verify the accuracy of the SKA-Low sensitivity simulation code presented in Sokolowski (2022, PASA, 39, e015). Furthermore, we perform model fits to the radio spectra of the detected pulsars using the method developed by Jankowski (2018, MNRAS, 473, 4436), including nine pulsars which were not fitted in the original work. We robustly classify the spectra into five morphological classes and find that all but one pulsar exhibit deviations from simple power-law behaviour. These findings suggest that pulsars with well-determined spectra are more likely to show spectral flattening or turnover than average. Our work demonstrates how SKA-Low stations can be meaningfully used for scientifically useful measurements and analysis of pulsar radio spectra, which are important inputs for informing pulsar surveys and science planned with the SKA-Low.