Abstract: We provide three Fortran programs which evaluate the QCD analytic (holomorphic) couplings A(v)(Q(2)) for complex or real squared momenta Q(2). These couplings are holomorphic analogs of the powers a(Q(2))(v) of the underlying perturbative QCD (pQCD) coupling a(Q(2)) equivalent to alpha(s)(Q(2))/pi, in three analytic QCD models (anQCD): Fractional Analytic Perturbation Theory (FAPT), Two-delta analytic QCD (2 delta anQCD), and Massive Perturbation Theory (MPT). The index v can be noninteger. The provided programs do basically the same job as the Mathematica package anQCD.m published by us previously (Ayala and Cvetic, 2015), but are now written in Fortran. Program summary Program title: AanQCDext Catalogue identifier: AEYKv10 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEYICv1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 12105 No. of bytes in distributed program, including test data, etc.: 98822 Distribution format: tar.gz Programming language: Fortran. Computer: Any work-station or PC where Fortran 95/200312008 (gfortran) is running. Operating system: Operating system Linux (Ubuntu and Scientific Linux), Windows (in all cases using gfortran). Classification: 11.1, 11.5. Nature of problem: Calculation of values of the running analytic couplings A(v)(Q(2); N-f) for general complex squared momenta Q(2) equivalent to -q(2), in three analytic QCD models, where A(v)(Q(2); N-f) is the analytic (holomorphic) analog of the power (alpha(s)(Q(2); N-f)/pi)(v). Here, A(v)(Q(2); N-f) is a holomorphic function in the Q(2) complex plane, with the exception of the negative semiaxis (-infinity, -M-thr(2)], reflecting the analyticity properties of the spacelike renormalization invariant quantities D(Q(2)) in QCD. In contrast, the perturbative QCD power (alpha(s)(Q(2); N-f)/pi)(v) has singularities even outside the negative semiaxis (Landau ghosts). The three considered models are: Analytic Perturbation theory (APT); Two-delta analytic QCD (2 delta anQCD); Massive Perturbation Theory (MPT). We refer to Ref. [1] for more details and literature. Solution method: The Fortran programs for FAPT and 2 delta anQCD models contain routines and functions needed to perform two-dimensional numerical integrations involving the spectral function, in order to evaluate A(v)(Q(2)) couplings. In MPT model, one-dimensional numerical integration involving A(1)(Q(2)) is sufficient to evaluate any A(v)(Q(2)) coupling. Restrictions: For unphysical choices of the input parameters the results are meaningless. When Q(2) is close to the cut region of the couplings (Q(2) real negative), the calculations can take more time and can have less precision. Running time: For evaluation of a set of about 10 related couplings, the times vary in the range t similar to 10(1)-10(2) s. MPT requires less time, t similar to 1-10(1) s. References: [1] C. Ayala and G. Cvetic, anQCD: a Mathematica package for calculations in general analytic QCD models, Comput. Phys. Commun. 190 (2015) 182.

Abstract: The goal of the NEXT experiment is the observation of neutrinoless double beta decay in Xe-136 using a gaseous xenon TPC with electroluminescent amplification and specialized photodetector arrays for calorimetry and tracking. The NEXT Collaboration is exploring a number of reconstruction algorithms to exploit the full potential of the detector. This paper describes one of them: the Maximum Likelihood Expectation Maximization (ML-EM) method, a generic iterative algorithm to find maximum-likelihood estimates of parameters that has been applied to solve many different types of complex inverse problems. In particular, we discuss a bi-dimensional version of the method in which the photosensor signals integrated over time are used to reconstruct a transverse projection of the event. First results show that, when applied to detector simulation data, the algorithm achieves nearly optimal energy resolution (better than 0.5% FWHM at the Q value of 136Xe) for events distributed over the full active volume of the TPC.

Abstract: Asymmetric Dark Matter (ADM) models invoke a particle-antiparticle asymmetry, similar to the one observed in the Baryon sector, to account for the Dark Matter (DM) abundance. Both asymmetries are usually generated by the same mechanism and generally related, thus predicting DM masses around 5 GeV in order to obtain the correct density. The main challenge for successful models is to ensure efficient annihilation of the thermally produced symmetric component of such a light DM candidate without violating constraints from collider or direct searches. A common way to overcome this involves a light mediator, into which DM can efficiently annihilate and which subsequently decays into Standard Model particles. Here we explore the scenario where the light mediator decays instead into lighter degrees of freedom in the dark sector that act as radiation in the early Universe. While this assumption makes indirect DM searches challenging, it leads to signals of extra radiation at BBN and CMB. Under certain conditions, precise measurements of the number of relativistic species, such as those expected from the Planck satellite, can provide information on the structure of the dark sector. We also discuss the constraints of the interactions between DM and Dark Radiation from their imprint in the matter power spectrum.

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: Aims. With the ever-increasing survey speed of optical wide-field telescopes and the importance of discovering transients when they are still young, rapid and reliable source localization is paramount. We present AutoSourceID-Light (ASID-L), an innovative framework that uses computer vision techniques that can naturally deal with large amounts of data and rapidly localize sources in optical images. Methods. We show that the ASID-L algorithm based on U-shaped networks and enhanced with a Laplacian of Gaussian filter provides outstanding performance in the localization of sources. A U-Net network discerns the sources in the images from many different artifacts and passes the result to a Laplacian of Gaussian filter that then estimates the exact location. Results. Using ASID-L on the optical images of the MeerLICHT telescope demonstrates the great speed and localization power of the method. We compare the results with SExtractor and show that our method outperforms this more widely used method. ASID-L rapidly detects more sources not only in low- and mid-density fields, but particularly in areas with more than 150 sources per square arcminute. The training set and code used in this paper are publicly available.