2024MNRAS.528.2952G

Hot dust in the proximity of active galactic nuclei (AGNs) strongly emits in the near-infrared producing a red excess that, in type 2 sources, can be modelled to measure its temperature. In the era of high spatial resolution multiwavelength data, mapping the hot dust around supermassive black holes is important for the efforts to achieve a complete picture of the dust's role and distribution around these compact objects. In this work, we propose a methodology to detect the hot dust emission in the proximity of type 2 AGNs and measure its temperature using K-band spectra (λ_c = 2.2 µm). To achieve this, we have developed NIRDUST, a PYTHON package for modelling K-band spectra, estimating the dust temperature, and characterizing the involved uncertainties. We tested synthetic and real spectra in order to check the performance and suitability of the physical model over different types of data. Our tests on synthetic spectra demonstrated that the obtained results are influenced by the signal-to-noise ratio (S/N) of the input spectra. However, we accurately characterized the uncertainties, which remained below ∼150 K for an average S/N per pixel exceeding 20. Applying NIRDUST to NGC 5128 (Centaurus A), observed with the Gemini South Telescope, we estimated a dust temperature of 662 and 667 K from Flamingos-2 spectra and 697 and 607 K from Gemini Near-Infrared Spectrograph (GNIRS) spectra using two different approaches.