Abstract: Aims. Traditional star-galaxy classification techniques often rely on feature estimation from catalogs, a process susceptible to introducing inaccuracies, thereby potentially jeopardizing the classification's reliability. Certain galaxies, especially those not manifesting as extended sources, can be misclassified when their shape parameters and flux solely drive the inference. We aim to create a robust and accurate classification network for identifying stars and galaxies directly from astronomical images.Methods. The AutoSourceID-Classifier (ASID-C) algorithm developed for this work uses 32x32 pixel single filter band source cutouts generated by the previously developed AutoSourceID-Light (ASID-L) code. By leveraging convolutional neural networks (CNN) and additional information about the source position within the full-field image, ASID-C aims to accurately classify all stars and galaxies within a survey. Subsequently, we employed a modified Platt scaling calibration for the output of the CNN, ensuring that the derived probabilities were effectively calibrated, delivering precise and reliable results.Results. We show that ASID-C, trained on MeerLICHT telescope images and using the Dark Energy Camera Legacy Survey (DECaLS) morphological classification, is a robust classifier and outperforms similar codes such as SourceExtractor. To facilitate a rigorous comparison, we also trained an eXtreme Gradient Boosting (XGBoost) model on tabular features extracted by SourceExtractor. While this XGBoost model approaches ASID-C in performance metrics, it does not offer the computational efficiency and reduced error propagation inherent in ASID-C's direct image-based classification approach. ASID-C excels in low signal-to-noise ratio and crowded scenarios, potentially aiding in transient host identification and advancing deep-sky astronomy.

Abstract: In this paper, we explore a scenario where the dark matter is a mixture of interacting and non interacting species. Assuming dark matter-photon interactions for the interacting species, we find that the suppression of the matter power spectrum in this scenario can mimic that expected in the case of massive neutrinos. Our numerical studies include present limits from Planck Cosmic Microwave Background data, which render the strength of the dark matter photon interaction unconstrained when the fraction of interacting dark matter is small. Despite the large entangling between mixed dark matter and neutrino masses, we show that future measurements from the Dark Energy Instrument (DESI) could help in establishing the dark matter and the neutrino properties simultaneously, provided that the interaction rate is very close to its current limits and the fraction of interacting dark matter is at least of O (10%). However, for that region of parameter space where a small fraction of interacting DM coincides with a comparatively large interaction rate, our analysis highlights a considerable degeneracy between the mixed dark matter parameters and the neutrino mass scale.

Abstract: We perform a theoretical study of the D-s(+) ->pi(+)pi(+)pi(-)eta decay. We look first at the basic D-s(+) decay at the quark level from external and internal emission. Then we hadronize a pair or two pairs of q (q) over bar states to have mesons at the end. Posteriorly the pairs of mesons are allowed to undergo final state interaction, by means of which the a(0)(980), f(0)(980), a(1)(1260), and b(1)(1235) resonances are dynamically generated. The G parity is used as a filter of the possible channels, and from those with negative G parity only the ones that can lead to pi(+)pi(+)pi(-)eta at the final state are kept. Using transition amplitudes from the chiral unitary approach that generates these resonances and a few free parameters, we obtain a fair reproduction of the six mass distributions reported in the BESIII experiment.