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The stability of a dark matter detector on the timescale of a few years is a key requirement due to the large exposure needed to achieve a competitive sensitivity. It is especially crucial to enable the detector to potentially detect any annual event rate modulation, an expected dark matter signature. In this work, we present the performance history of the DarkSide-50 dual-phase argon time projection chamber over its almost three-year low-radioactivity argon run. In particular, we focus on the electroluminescence signal that enables sensitivity to sub-keV energy depositions. The stability of the electroluminescence yield is found to be better than 0.5%. Finally, we show the temporal evolution of the observed event rate around the sub-keV region being consistent to the background prediction. Comment: 16 pages, 5 figures

A trainable neural equalizer based on the long short-term memory (LSTM) neural network architecture is proposed in this article to recover the channel output signal. The current widely used solution for the transmission line signal recovery is generally realized through a decision feedback equalizer (DFE) or : Feed forward equalizer (FFE) combination. The novel learning-based equalizer is suitable for highly nonlinear signal restoration, thanks to its recurrent design. The effectiveness of the LSTM equalizer (LSTME) is shown through an advance design system simulation channel signal equalization task, including a quantitative and qualitative comparison with an FFE–DFE combination. The LSTM neural network shows good equalization results compared with that of the FFE–DFE combination. The advantage of a trainable LSTME lies in its ability to learn its parameters in a flexible manner and to tackle complex scenarios without any hardware modification. This can reduce the equalizer implantation cost for variant transmission channels and bring additional portability in practical applications. International audience

DarkSide-20k is a rare-event search experiment aimed at finding signals of dark matter particles. It is a dual-phase detector that registers ionisation and scintillation signals originating from the particles interacting with the liquid argon detector medium. It is enclosed in a single-phase liquid argon neutron veto tank, equipped with Gd-loaded panels for capturing neutrons. Since vetoing and particle identification are carried out using the light signal, it is crucial to maximise the light yield. Light collection efficiency depends on optical properties of the detector and particularly for the veto detector, which has a photosensor coverage of the order of a per cent, the reflectivity of the walls has a big impact. To quantify the amount of collected light, a comprehensive Geant4 simulation is performed, which uses optical characterisation data. In this work, a detailed description of the optics model for the veto of the experiment will be discussed. Comment: Proceedings of 17th International Conference on Topics in Astroparticle and Underground Physics (TAUP 2021)

International audience; This paper presents an extension to a very low-resource parallel corpus collected in an endangered language, Griko, making it useful for computational research. The corpus consists of 330 utterances (about 20 minutes of speech) which have been transcribed and translated in Italian, with annotations for word-level speech-to-transcription and speech-to-translation alignments. The corpus also includes morphosyntactic tags and word-level glosses. Applying an automatic unit discovery method, pseudo-phones were also generated. We detail how the corpus was collected, cleaned and processed, and we illustrate its use on zero-resource tasks by presenting some baseline results for the task of speech-to-translation alignment and unsu-pervised word discovery. The dataset is available online, aiming to encourage replicability and diversity in computational language documentation experiments.

Exemple frappant de comportement collectif à grande échelle, les émeutes de 2005 en France ont commencé dans une banlieue pauvre de Paris, avant de s'étendre à tout le pays, sur une période d'environ trois semaines. De façon remarquable, malgré l'absence de déplacements des émeutiers, l'activité émeutière elle-même s'est bien déplacée. Les données journalières de police nationale auxquelles nous avons eu accès nous ont permis d'explorer la dynamique de propagation d'émeutes. Nous montrons ici qu'un modèle de type épidémiologique, comportant peu de paramètres libres et une variable sociologique caractérisant les quartiers défavorisés, rend compte de façon quantitative de la dynamique spatio-temporelle des émeutes. C'est la première fois qu'une telle modélisation, pilotée par les données, prend en compte la contagion intra mais aussi inter villes (par proximité géographique ou médias), et ceci sur une base journalière à l'échelle de tout un pays. Nous donnons une caractérisation mathématique précise de l'expression ``vague d'émeutes'', et fournissons une visualisation de la propagation autour de Paris qui révèle cette vague de manière inédite. L'accord remarquable entre modèle et faits empiriques met en évidence le rôle majeur de la proximité géographique dans la propagation des émeutes, malgré l'ubiquité de l'information transmise par les médias. Enfin, notre approche donne un cadre général à la modélisation des soulèvements collectifs spontanés. As a large-scale instance of dramatic collective behaviour, the 2005 French riots started in a poor suburb of Paris, then spread in all of France, lasting about three weeks. Remarkably, although there were no displacements of rioters, the riot activity did travel. Access to daily national police data has allowed us to explore the dynamics of riot propagation. Here we show that an epidemic-like model, with just a few parameters and a single sociological variable characterizing neighbourhood deprivation, accounts quantitatively for the full spatio-temporal dynamics of the riots. This is the first time that such data-driven modelling involving contagion both within and between cities (through geographic proximity or media) at the scale of a country, and on a daily basis, is performed. Moreover, we give a precise mathematical characterization to the expression “wave of riots”, and provide a visualization of the propagation around Paris, exhibiting the wave in a way not described before. The remarkable agreement between model and data demonstrates that geographic proximity played a major role in the propagation, even though information was readily available everywhere through media. Finally, we argue that our approach gives a general framework for the modelling of the dynamics of spontaneous collective uprisings. International audience

The embedding method for the calculation of the conductance through interacting systems connected to single channel leads is generalized to obtain the full complex transmission amplitude that completely characterizes the effective scattering matrix of the system at the Fermi energy. We calculate the transmission amplitude as a function of the gate potential for simple diamond-shaped lattice models of quantum dots with nearest neighbor interactions. In our simple models we do not generally observe an interaction dependent change in the number of zeroes or phase lapses that depend only on the symmetry properties of the underlying lattice. Strong correlations separate and reduce the widths of the resonant peaks while preserving the qualitative properites of the scattering phase. We acknowledge support from the Spanish MICINN through project FIS2009-07277, the NSF under grant No DMR-0706319, the ANR through grant ANR-08-BLAN-0030-02, and the Swiss NCCR MANEP. 10 pags., 3 figs. -- Advanced many-body and statistical methods in mesoscopic systems 27 June to 2 July 2011, Constanta, Romania