4,104 research outputs found

    Multifloquet to single electronic channel transition in the transport properties of a resistive 1D driven disordered ring

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    We investigate the dc response of a 1D disordered ring coupled to a reservoir and driven by a magnetic flux with a linear dependence on time. We identify two regimes: (i) A localized or large length L regime, characterized by a dc conductance, g_{dc}, whose probability distribution P(g_{dc}) is identical to the one exhibited by a 1D wire of the same length L and disorder strength placed in a Landauer setup. (ii) A "multifloquet" regime for small L and weak coupling to the reservoir, which exhibits large currents and conductances that can be g_{dc} > 1, in spite of the fact that the ring contains a single electronic transmission channel. The crossover length between the multifloquet to the single channel transport regime, L_c, is controlled by the coupling to the reservoir.Comment: 5 pages, 4 figure

    Likelihood-free inference of experimental Neutrino Oscillations using Neural Spline Flows

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    In machine learning, likelihood-free inference refers to the task of performing an analysis driven by data instead of an analytical expression. We discuss the application of Neural Spline Flows, a neural density estimation algorithm, to the likelihood-free inference problem of the measurement of neutrino oscillation parameters in Long Baseline neutrino experiments. A method adapted to physics parameter inference is developed and applied to the case of the disappearance muon neutrino analysis at the T2K experiment.Comment: 10 pages, 3 figure

    DC four point resistance of a double barrier quantum pump

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    We investigate the behavior of the dc voltage drop in a periodically driven double barrier structure (DBS) sensed by voltages probes that are weakly coupled to the system. We find that the four terminal resistance R4tR_{4t} measured with the probes located outside the DBS results identical to the resistance measured in the same structure under a stationary bias voltage difference between left and right reservoirs. This result, valid beyond the adiabatic pumping regime, can be taken as an indication of the universal character of R4tR_{4t} as a measure of the resistive properties of a sample, irrespectively of the mechanism used to induce the transport.Comment: 4 pages, 3 figure

    L'experiment T2K detecta un fenomen nou en neutrins

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    L'experiment T2K, una col·laboració internacional on participen més de 500 físics de 12 països, ha detectat l'aparició de neutrins electrònics a partir d'un feix de neutrins muònics. És la primera vegada que s'observa aquest fenomen, conegut com a "oscil·lació", entre aquest tipus de neutrins, la qual cosa suposa un important pas per entendre millor aquesta partícula elemental. A més, aquesta detecció obre la porta a l'estudi experimental d'un dels principals misteris de l'Univers: el domini de la matèria enfront de l'antimatèria. En l'experiment participen investigadors de l'Institut de Física d'Altes Energies (IFAE, consorci Generalitat de Catalunya-Universitat Autònoma de Barcelona) i de l'Institut de Física Corpuscular (IFIC, CSIC-Universitat de València).El experimento T2K, una colaboración internacional donde participan más de 500 físicos de 12 países, ha detectado la aparición de neutrinos electrónicos a partir de un haz de neutrinos muónicos. Es la primera vez que se observa este fenómeno, conocido como "oscilación", entre este tipo de neutrinos, lo que supone un importante paso para entender mejor esta partícula elemental. Además, esta detección abre la puerta al estudio experimental de uno de los principales misterios del Universo: el dominio de la materia frente a la antimateria. En el experimento participan investigadores del Institut de Física d'Altes Energies (IFAE, consorcio Generalitat de Catalunya-Universitat Autònoma de Barcelona) y del Institut de Física Corpuscular (IFIC, CSIC-Universitat de València).The T2K experiment, an international collaboration with over 500 physicists from 12 different countries, has detected the appearance of electron neutrinos in a muon neutrino beam. It is the first time researchers observe this phenomenon - known as "oscillation" - in these types of neutrinos. The discovery could represent an important step towards a clearer understanding of this elementary particle. Having detected the presence of these types of neutrinos opens the door to an experimental study of one of the greatest mysteries of the Universe: the power of matter over antimatter. The experiment includes participation of researchers from the Institute of High Energy Physics (IFAE, consortium formed by the Government of Catalonia-Universitat Autònoma de Barcelona) and from the Institute of Corpuscular Physics (IFIC, CSIC- Universitat de València)

    Detecting and Monitoring Hate Speech in Twitter

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    Social Media are sensors in the real world that can be used to measure the pulse of societies. However, the massive and unfiltered feed of messages posted in social media is a phenomenon that nowadays raises social alarms, especially when these messages contain hate speech targeted to a specific individual or group. In this context, governments and non-governmental organizations (NGOs) are concerned about the possible negative impact that these messages can have on individuals or on the society. In this paper, we present HaterNet, an intelligent system currently being used by the Spanish National Office Against Hate Crimes of the Spanish State Secretariat for Security that identifies and monitors the evolution of hate speech in Twitter. The contributions of this research are many-fold: (1) It introduces the first intelligent system that monitors and visualizes, using social network analysis techniques, hate speech in Social Media. (2) It introduces a novel public dataset on hate speech in Spanish consisting of 6000 expert-labeled tweets. (3) It compares several classification approaches based on different document representation strategies and text classification models. (4) The best approach consists of a combination of a LTSM+MLP neural network that takes as input the tweet’s word, emoji, and expression tokens’ embeddings enriched by the tf-idf, and obtains an area under the curve (AUC) of 0.828 on our dataset, outperforming previous methods presented in the literatureThe work by Quijano-Sanchez was supported by the Spanish Ministry of Science and Innovation grant FJCI-2016-28855. The research of Liberatore was supported by the Government of Spain, grant MTM2015-65803-R, and by the European Union’s Horizon 2020 Research and Innovation Programme, under the Marie Sklodowska-Curie grant agreement No. 691161 (GEOSAFE). All the financial support is gratefully acknowledge
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