The Front-End electronics for the liquid Argon instrumentation of the LEGEND-200 experiment

In this paper we provide a detailed technical description of the Front-End electronics for the liquid Argon instrumentation of the LEGEND-200 experiment, searching for the very rare, hypothetical neutrinoless double $\beta$ decay process at the Italian Laboratori Nazionali del Gran Sasso. The design stems from the need to read out the silicon photo-multiplier response to the scintillation light in the liquid Argon with excellent single-photon resolution. The Front End is required to be placed far from the detectors to meet the experiment's radio-purity constraints, which represented a challenge for a high signal-to-noise ratio. We address how this could be achieved in a stable way. The system was installed in July 2021 and has been commissioned with the rest of LEGEND-200, proving we could attain a very low overall level of electrical noise, of 200 $\mu$V on average

Data mining of large astronomical databases with neural tools

The International Virtual Observatory will pose unprecedented problems to data mining. We shortly discuss the effectiveness of neural networks as aids to the decisional process of the astronomer, and present the AstroMining Package. This package was written in Matlab and C++ and provides an user friendly interactive platform for various data mining tasks. Two applications are also shortly outlined: the derivation of photometric redshifts for a subsample of objects extracted from the Sloan Digital Sky Survey Early Data Release, and the evaluation of systematic patterns in the telemetry data for the Telescopio Nazionale GalilEo (TNG)

Structure-function discrepancy: inhomogeneity and/ndelays in synchronized neural networks

The discrepancy between structural and functional connectivity in neural systems forms the challenge in understanding/ngeneral brain functioning. To pinpoint a mapping between structure and function, we investigated the effects of/n(in)homogeneity in coupling structure and delays on synchronization behavior in networks of oscillatory neural masses by/nderiving the phase dynamics of these generic networks. For homogeneous delays, the structural coupling matrix is largely/npreserved in the coupling between phases, resulting in clustered stationary phase distributions. Accordingly, we found only/na small number of synchronized groups in the network. Distributed delays, by contrast, introduce inhomogeneity in the/nphase coupling so that clustered stationary phase distributions no longer exist. The effect of distributed delays mimicked/nthat of structural inhomogeneity. Hence, we argue that phase (de-)synchronization patterns caused by inhomogeneous/ncoupling cannot be distinguished from those caused by distributed delays, at least not by the naked eye. The here-derived/nanalytical expression for the effective coupling between phases as a function of structural coupling constitutes a direct/nrelationship between structural and functional connectivity. Structural connectivity constrains synchronizability that may be/nmodified by the delay distribution. This explains why structural and functional connectivity bear much resemblance albeit/nnot a one-to-one correspondence. We illustrate this in the context of resting-state activity, using the anatomical/nconnectivity structure reported by Hagmann and others.This work was funded by ERC Advanced Grant: DYSTRUCTURE (n. 295129), by the Spanish Research Project SAF2010-16085 and by the CONSOLIDER-/nINGENIO 2010 Program CSD2007-00012, and the FP7-ICT BrainScal