1,393 research outputs found

    Muography applied to nuclear waste storage sites

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    Legacy storage sites for nuclear waste can pose a serious environmental problem. In fact, since certain sites date from the middle of the last century when safety protocols had not been properly established and strict bookkeeping was not enforced, a situation has evolved where the content of storage silos is basically known only with a large uncertainty both on quantity and quality. At the same time maintenance work on old storage structures is becoming ever more urgent and yet this work requires exactly that information which is now lacking on the type of waste that was stored inside. Because of the difficulty in accessing the storage silos and the near impossibility of making visual inspections inside, techniques have to be developed which can determine the presence or absence of heavy elements (i.e. uranium) within the structures. Muography is a very promising technique which could allow the survey of previously inaccessible structures. We have begun an evaluation performing feasibility studies using simulations based on real case scenarios. This paper will outline the storage site scenarios and then present some of the results obtained from the Monte Carlo simulations

    Model independent measurements of Standard Model cross sections with Domain Adaptation

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    With the ever growing amount of data collected by the ATLAS and CMS experiments at the CERN LHC, fiducial and differential measurements of the Higgs boson production cross section have become important tools to test the standard model predictions with an unprecedented level of precision, as well as seeking deviations that can manifest the presence of physics beyond the standard model. These measurements are in general designed for being easily comparable to any present or future theoretical prediction, and to achieve this goal it is important to keep the model dependence to a minimum. Nevertheless, the reduction of the model dependence usually comes at the expense of the measurement precision, preventing to exploit the full potential of the signal extraction procedure. In this paper a novel methodology based on the machine learning concept of domain adaptation is proposed, which allows using a complex deep neural network in the signal extraction procedure while ensuring a minimal dependence of the measurements on the theoretical modelling of the signal.Comment: 16 pages, 10 figure

    a geant4 framework for generic simulations of atmospheric muon detection experiments

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    A flexible and adaptive simulation framework based on Geant4 is presented. The framework has been developed in order to speed up the deployment of full-featured Monte Carlo simulation codes for small/medium sized particle detection experiments with generic geometries. Specific components related to atmospheric muon experiments have been developed and are presented as well

    a possible point of contact between cosmic ray physics and archaeology muon absorption radiography at the tharros phoenician roman site

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    Several on-going activities exploiting the potential of the muon-absorption radiography technique are focusing on the study of large volcanic structures located in different geographical regions. Nonetheless, the possible application of this non-destructive surveying method to other fields is also under consideration by different groups. Looking backward to the history of muon radiography, we can learn how the first important success of this technique was achieved in the archaeological field by the physicist Luis W. Alvarez in the 1960s. Further examples of possible applications can be found concerning geological and mining applications. In this paper a possible application of muon absorption radiography in the context of the archaeological research is proposed. Results of a simulation of a simplified case study are presented

    Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

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    Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

    Search for heavy resonances decaying to two Higgs bosons in final states containing four b quarks