118159758
Study of $B^{0}_{s} \rightarrow D_s^{(*)+}D_s^{(*)-}$ and $B^{0}_{s} \rightarrow \phi\phi$ Decays at CDF
Under certain theoretical assumptions, the branching fraction of B{sub s}{sup 0} {yields} D{sub s}{sup (*)+}D{sub s}{sup (*)-} is directly sensitive to the relative decay width difference {Delta}{Lambda}{sub s}{sup CP}/{Lambda}{sub s} in the B{sub s}{sup 0} system, which is predicted to be sizable in the standard model. Using approximately 4 fb{sup -1} of data collected by the CDF II detector at the Tevatron p{bar p} collider, the CDF collaboration is currently performing an exclusive selection of B{sub s}{sup 0} {yields} D{sub s}{sup (*)+}D{sub s}{sup (*)-} signal candidates in several hadronic modes in order to provide a new branching fraction measurement. In contrast to former analyses, we start to have sensitivity in disentangling D{sub s}{sup (*)+}D{sub s}{sup (*)-}, enabling us to measure the branching fractions of B{sub s}{sup 0} {yields} D{sub s}{sup +}D{sub s}{sup -}, B{sub s}{sup 0} {yields} D{sub s}{sup (*)+}D{sub s}{sup -} and B{sub s}{sup 0} {yields} D{sub s}{sup (*)+}D{sub s}{sup (*)-} separately. Yet another interesting mode is the decay of the B{sub s}{sup 0} into a {phi} pair. This is a vector-vector decay dominated by the b {yields} s{ovr ss} penguin transition, which is a sensitive probe for possible new physics effects. Here we present a new measurement ofmore » the branching fraction based on a clean sample of about 300 B{sub s}{sup 0} {yields} {phi}{phi} signal events in a dataset with an integrated luminosity of 2.9 fb{sup -1}.« less
125542777
Measurement of the Exclusive and Inclusive Branching Fractions of $B^{0}_{s} \to D^{(*)+}_{s}D^{(*)-}_{s}$ Decays at CDF and its Implications on the Decay Width Difference in the $B^{0}_{s}-B^{-0}_{s}$ Meson System
126387358
BISTATE t-EXPANSION OF THE SU(2) LATTICE GAUGE THEORY
10550999
Dynamic quantum clustering: a method for visual exploration of structures in data
A given set of data points in some feature space may be associated with a Schrödinger equation whose potential is determined by the data. This is known to lead to good clustering solutions. Here we extend this approach into a full-fledged dynamical scheme using a time-dependent Schrödinger equation. Moreover, we approximate this Hamiltonian formalism by a truncated calculation within a set of Gaussian wave functions (coherent states) centered around the original points. This allows for analytic evaluation of the time evolution of all such states opening up the possibility of exploration of relationships among data points through observation of varying dynamical distances among points and convergence of points into clusters. This formalism may be further supplemented by preprocessing such as dimensional reduction through singular-value decomposition or feature filtering.