9,661 research outputs found

    Simulation of instability at transition energy with a new impedance model for CERN PS

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    Instabilities driven by the transverse impedance are proven to be one of the limitations for the high intensity reach of the CERN PS. Since several years, fast single bunch vertical instability at transition energy has been observed with the high intensity bunch serving the neutron Time-of-Flight facility (n-ToF). In order to better understand the instability mechanism, a dedicated measurement campaign took place. The results were compared with macro-particle simulations with PyHEADTAIL based on the new impedance model developed for the PS. Instability threshold and growth rate for different longitudinal emittances and beam intensities were studied

    Interpretation of AMS-02 electrons and positrons data

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    We perform a combined analysis of the recent AMS-02 data on electrons, positrons, electrons plus positrons and positron fraction, in a self-consistent framework where we realize a theoretical modeling of all the astrophysical components that can contribute to the observed fluxes in the whole energy range. The primary electron contribution is modeled through the sum of an average flux from distant sources and the fluxes from the local supernova remnants in the Green catalog. The secondary electron and positron fluxes originate from interactions on the interstellar medium of primary cosmic rays, for which we derive a novel determination by using AMS-02 proton and helium data. Primary positrons and electrons from pulsar wind nebulae in the ATNF catalog are included and studied in terms of their most significant (while loosely known) properties and under different assumptions (average contribution from the whole catalog, single dominant pulsar, a few dominant pulsars). We obtain a remarkable agreement between our various modeling and the AMS-02 data for all types of analysis, demonstrating that the whole AMS-02 leptonic data admit a self-consistent interpretation in terms of astrophysical contributions.Comment: 33 pages, 26 figures and 4 tables, v2: accepted for publication in JCAP, minor changes relative to v

    Time and Geometric Quantization

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    In this paper we briefly review the functional version of the Koopman-von Neumann operatorial approach to classical mechanics. We then show that its quantization can be achieved by freezing to zero two Grassmannian partners of time. This method of quantization presents many similarities with the one known as Geometric Quantization.Comment: Talk given by EG at "Spacetime and Fundamental Interactions: Quantum Aspects. A conference to honour A.P.Balachandran's 65th birthday

    Flavored tetraquark spectroscopy

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    The recent confirmation of the charged charmonium like resonance Z(4430) by the LHCb experiment strongly suggests the existence of QCD multi quark bound states. Some preliminary results about hypothetical flavored tetraquark mesons are reported. Such states are particularly amenable to Lattice QCD studies as their interpolating operators do not overlap with those of ordinary hidden-charm mesons

    Backbone of credit relationships in the Japanese credit market

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    We detect the backbone of the weighted bipartite network of the Japanese credit market relationships. The backbone is detected by adapting a general method used in the investigation of weighted networks. With this approach we detect a backbone that is statistically validated against a null hypothesis of uniform diversification of loans for banks and firms. Our investigation is done year by year and it covers more than thirty years during the period from 1980 to 2011. We relate some of our findings with economic events that have characterized the Japanese credit market during the last years. The study of the time evolution of the backbone allows us to detect changes occurred in network size, fraction of credit explained, and attributes characterizing the banks and the firms present in the backbone.Comment: 14 pages, 8 figure

    Bank-firm credit network in Japan. An analysis of a bipartite network

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    We present an analysis of the credit market of Japan. The analysis is performed by investigating the bipartite network of banks and firms which is obtained by setting a link between a bank and a firm when a credit relationship is present in a given time window. In our investigation we focus on a community detection algorithm which is identifying communities composed by both banks and firms. We show that the clusters obtained by directly working on the bipartite network carry information about the networked nature of the Japanese credit market. Our analysis is performed for each calendar year during the time period from 1980 to 2011. Specifically, we obtain communities of banks and networks for each of the 32 investigated years, and we introduce a method to track the time evolution of these communities on a statistical basis. We then characterize communities by detecting the simultaneous over-expression of attributes of firms and banks. Specifically, we consider as attributes the economic sector and the geographical location of firms and the type of banks. In our 32 year long analysis we detect a persistence of the over-expression of attributes of clusters of banks and firms together with a slow dynamics of changes from some specific attributes to new ones. Our empirical observations show that the credit market in Japan is a networked market where the type of banks, geographical location of firms and banks and economic sector of the firm play a role in shaping the credit relationships between banks and firms.Comment: 9 pages, 4 figures, 2 Table

    Detection of hidden structures on all scales in amorphous materials and complex physical systems: basic notions and applications to networks, lattice systems, and glasses

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    Recent decades have seen the discovery of numerous complex materials. At the root of the complexity underlying many of these materials lies a large number of possible contending atomic- and larger-scale configurations and the intricate correlations between their constituents. For a detailed understanding, there is a need for tools that enable the detection of pertinent structures on all spatial and temporal scales. Towards this end, we suggest a new method by invoking ideas from network analysis and information theory. Our method efficiently identifies basic unit cells and topological defects in systems with low disorder and may analyze general amorphous structures to identify candidate natural structures where a clear definition of order is lacking. This general unbiased detection of physical structure does not require a guess as to which of the system properties should be deemed as important and may constitute a natural point of departure for further analysis. The method applies to both static and dynamic systems.Comment: (23 pages, 9 figures
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