890 research outputs found

    Heavy mesons in the Quark Model

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    Since the discovery of the J/ψJ/\psi, the quark model was very successful in describing the spectrum and properties of heavy mesons including only qqˉq\bar q components. However since 2003, with the discovery of the X(3872)X(3872), many states that can not be accommodated on the naive quark model have been discovered, and they made unavoidable to include higher Fock components on the heavy meson states. We will give an overview of the success of the quark model for heavy mesons and point some of the states that are likely to be more complicated structures such as meson-meson molecules.Comment: Contribution to the Proceedings of the 15th International Workshop on Meson Physics - MESON201

    Charmonium resonances in the 3.9 GeV/c2c^2 energy region and the X(3915)/X(3930)X(3915)/X(3930) puzzle

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    An interesting controversy has emerged challenging the widely accepted nature of the X(3915)X(3915) and the X(3930)X(3930) resonances, which had initially been assigned to the χc0(2P)\chi_{c0}(2P) and χc2(2P)\chi_{c2}(2P) ccˉc\bar c states, respectively. To unveil their inner structure, the properties of the JPC ⁣ ⁣= ⁣0++J^{PC}\!\!=\!0^{++} and JPC ⁣ ⁣= ⁣2++J^{PC}\!\!=\!2^{++} charmonium states in the energy region of these resonances are analyzed in the framework of a constituent quark model. Together with the bare qqˉq\bar q states, threshold effects due to the opening of nearby meson-meson channels are included in a coupled-channels scheme calculation. We find that the structure of both states is dominantly molecular with a probability of bare qqˉq\bar q states lower than 45%45\%. Our results favor the hypothesis that X(3915)X(3915) and X(3930)X(3930) resonances arise as different decay mechanisms of the same JPC ⁣ ⁣= ⁣2++J^{PC}\!\!=\!2^{++} state. Moreover we found an explanation for the recently discovered M=3860M=3860 MeV/c2/c^2 as a JPC ⁣ ⁣= ⁣0++J^{PC}\!\!=\!0^{++} 2P2P state and rediscovery the lost Y(3940)Y(3940) as an additional state in the JPC ⁣ ⁣= ⁣0++J^{PC}\!\!=\!0^{++} family.Comment: 6 pages, 3 table

    The X(3872) and other possible XYZXYZ molecular states

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    We perform a coupled channel calculation of the DDDD^* and ccˉc\bar c sectors in the framework of a constituent quark model. The interaction for the DDDD^* states is obtained using the Resonant Group Method (RGM) and the underlying quark interaction model. The coupling with the two quark system is performed using the 3P0^3 P_0 model. The X(3872) is found as a molecular state with a sizable ccˉc\bar c component. A comparison with Belle and BaBar data has been done, finding a good agreement. Other possible molecular molecular states are discussed.Comment: 5 pages, 5 figures, Proceedings to the Hadron 2009 - XIII International Conference on Hadron Spectroscopy, Florida State University (USA

    Molecular components in Ds0(2317)\mathbf{D_{s0}^{\ast}(2317)} and Ds1(2460)\mathbf{D_{s1}(2460)} mesons

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    Different experiments have confirmed that the Ds0(2317)D_{s0}^{\ast}(2317) and Ds1(2460)D_{s1}(2460) mesons are very narrow states located, respectively, below the DKDK and DKD^{\ast}K thresholds. This is markedly in contrast with the expectations of naive quark models and heavy quark symmetry. We address the mass shifts of the csˉc\bar{s} ground states with quantum numbers JP=0+J^{P}=0^{+} (Ds0(2317)D_{s0}^{\ast}(2317)) and JP=1+J^{P}=1^{+} (Ds1(2460)D_{s1}(2460)) using a nonrelativistic constituent quark model in which quark-antiquark and meson-meson degrees of freedom are incorporated. The quark model has been applied to a wide range of hadronic observables and thus the model parameters are completely constrained. We observe that the coupling of the 0+0^{+} (1+)(1^{+}) meson sector to the DKDK (DK)(D^{\ast}K) threshold is a key feature in lowering the masses of the corresponding Ds0(2317)D_{s0}^{\ast}(2317) and Ds1(2460)D_{s1}(2460) states predicted by the naive quark model, but also in describing the Ds1(2536)D_{s1}(2536) meson as the 1+1^{+} state of the jqP=3/2+j_{q}^{P}=3/2^{+} doublet predicted by heavy quark symmetry and thus reproducing its strong decay properties. Two features of our formalism cannot be address nowadays by other approaches: the coupling of the DD-wave DKD^{\ast}K threshold in the JP=1+J^{P}=1^{+} csˉc\bar{s} channel and the computation of the probabilities associated with different Fock components in the physical state.Comment: Contribution to the proceedings of the 14th International Workshop on Meson Production, Properties and Interaction (MESON2016). June 2-7, 2016. Krakow, Polan

    Scaling of the 3P0 strength in heavy meson strong decays

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    The phenomenological 3P0 decay model has been extensively applied to calculate meson strong decays. The strength \gamma\ of the decay interaction is regarded as a free flavor independent constant and is fitted to the data. We calculate through the 3P0 model the total strong decay widths of the mesons which belong to charmed, charmed-strange, hidden charm and hidden bottom sectors. The wave function of the mesons involved in the strong decays are given by a constituent quark model that describes well the meson phenomenology from the light to the heavy quark sector. A global fit of the experimental data shows that, contrarily to the usual wisdom, the \gamma\ depends on the reduced mass of the quark-antiquark pair in the decaying meson. With this scale-dependent strength \gamma, we are able to predict the decay width of orbitally excited B mesons not included in the fit.Comment: 7 pages, 5 tables, 2 figure

    Machine learning and statistical techniques : an application to the prediction of insolvency in Spanish non-life insurance companies

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    Prediction of insurance companies insolvency has arisen as an important problem in the field of financial research. Most methods applied in the past to tackle this issue are traditional statistical techniques which use financial ratios as explicative variables. However, these variables often do not satisfy statistical assumptions, which complicates the application of the mentioned methods. In this paper, a comparative study of the performance of two non-parametric machine learning techniques (See5 and Rough Set) is carried out. We have applied the two methods to the problem of the prediction of insolvency of Spanish non-life insurance companies, upon the basis of a set of financial ratios. We also compare these methods with three classical and well-known techniques: one of them belonging to the field of Machine Learning (Multilayer Perceptron) and two statistical ones (Linear Discriminant Analysis and Logistic Regression). Results indicate a higher performance of the machine learning techniques. Furthermore, See5 and Rough Set provide easily understandable and interpretable decision models, which shows that these methods can be a useful tool to evaluate insolvency of insurance firms.El pronóstico sobre la insolvencia de las compañías de seguro ha surgido como un problema importante en el ámbito de investigación financiera. La mayoría de los métodos aplicados en el pasado para abordar este problema, son técnicas estadísticas tradicionales que usan los ratios financieros como variables explicativas. Aunque, estas variables a menudo no satisfacen las suposiciones estadísticas, lo que complica la aplicación de dichos métodos. En este artículo, se lleva a cabo un estudio comparativo sobre la actuación de dos técnicas de aprendizaje automático no paramétrico (See5 y Rough Set). Hemos aplicado ambos métodos al problema del pronóstico sobre la insolvencia de compañías españolas de seguros no de vida, sobre la base de un conjunto de ratios financieros. Además, hemos comparado estos métodos con tres técnicas clásicas y muy conocidas: una de ellas perteneciente al área del Aprendizaje Automático (Perceptrón Multicapa), y dos estadísticos (Análisis Discriminante Lineal y Regresión Logística). Los resultados indican un desempeño más elevado en las técnicas de aprendizaje automático. Es más, See5 y Rough Set aportan unos modelos de decisión fácilmente entendibles, e interpretables, lo que demuestra que estos métodos pueden ser útiles para evaluar la insolvencia de empresas de seguros
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