28,259 research outputs found

    On Uniqueness And Existence of Conformally Compact Einstein Metrics with Homogeneous Conformal Infinity

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    In this paper we show that for a generalized Berger metric g^\hat{g} on S3S^3 close to the round metric, the conformally compact Einstein (CCE) manifold (M,g)(M, g) with (S3,[g^])(S^3, [\hat{g}]) as its conformal infinity is unique up to isometries. For the high-dimensional case, we show that if g^\hat{g} is an SU(k+1)\text{SU}(k+1)-invariant metric on S2k+1S^{2k+1} for kβ‰₯1k\geq1, the non-positively curved CCE metric on the (2k+1)(2k+1)-ball B1(0)B_1(0) with (S2k+1,[g^])(S^{2k+1}, [\hat{g}]) as its conformal infinity is unique up to isometries. In particular, since in \cite{LiQingShi}, we proved that if the Yamabe constant of the conformal infinity Y(S2k+1,[g^])Y(S^{2k+1}, [\hat{g}]) is close to that of the round sphere then any CCE manifold filled in must be negatively curved and simply connected, therefore if g^\hat{g} is an SU(k+1)\text{SU}(k+1)-invariant metric on S2k+1S^{2k+1} which is close to the round metric, the CCE metric filled in is unique up to isometries. Using the continuity method, we prove an existence result of the non-positively curved CCE metric with prescribed conformal infinity (S2k+1,[g^])(S^{2k+1}, [\hat{g}]) when the metric g^\hat{g} is SU(k+1)\text{SU}(k+1)-invariant.Comment: Comments are welcome

    QBDT, a new boosting decision tree method with systematic uncertainties into training for High Energy Physics

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    A new boosting decision tree (BDT) method, QBDT, is proposed for the classification problem in the field of high energy physics (HEP). In many HEP researches, great efforts are made to increase the signal significance with the presence of huge background and various systematical uncertainties. Why not develop a BDT method targeting the significance directly? Indeed, the significance plays a central role in this new method. It is used to split a node in building a tree and to be also the weight contributing to the BDT score. As the systematical uncertainties can be easily included in the significance calculation, this method is able to learn about reducing the effect of the systematical uncertainties via training. Taking the search of the rare radiative Higgs decay in proton-proton collisions ppβ†’h+Xβ†’Ξ³Ο„+Ο„βˆ’+Xpp \to h + X \to \gamma\tau^+\tau^-+X as example, QBDT and the popular Gradient BDT (GradBDT) method are compared. QBDT is found to reduce the correlation between the signal strength and systematical uncertainty sources and thus to give a better significance. The contribution to the signal strength uncertainty from the systematical uncertainty sources using the new method is 50-85~\% of that using the GradBDT method.Comment: 29 pages, accepted for publication in NIMA, algorithm available at https://github.com/xialigang/QBD
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