Meson distribution amplitudes: applications to weak radiative B decays and в transition form factors

This thesis examines the applications and determinations of meson light-cone distribution amplitudes, which enter the theoretical description of exclusive processes at large moment urn transfer. The investigation of such processes, in the context of в physics, provides one with a rich and extensive way of determining the Standard Model parameters of the CKM matrix, which are essential in describing CP violation, and searching for tell-tale signs of new physics beyond the Standard Model. We investigate the twist-2 and twist-3 distribution amplitudes of vector mesons and fully examine SU(3)(_F)-breaking effects and include leading G-parity violating terms. We use the conformal expansion allowing the distribution amplitudes to be described by a set of non-perturbative hadronic parameters which is reduced by invoking the QCD equation of motion to find various interrelations between the distribution amplitudes. Numerical values of the leading non-perturbative hadronie parameters are determined from QCD sum rules. The new distribution amplitude results find direct application in the radiative B decays to light vector mesons B → Vγ. We examine the phenomenologically most important observables in this decay mode using the formalism of QCD factorisation in which the distribution amplitudes play a vital role. We also include long-distance photon emission and soft quark loop effects, which formally lie outside the QCD factorisation formalism. The analysis encompasses all the relevant modes, that is B(_u),(_d)→(_p),(_w),K* and B(_s) → φ,K*.We also calculate the B → n(^1) transition form factor using QCD sum rules on the light- cone. The method relies on the collinear factorisation of the QCD dynamics into a pertur- batively calculable hard-scattering kernel and the non-perturbative universal distribution amplitudes. We include the singlet contribution originating from the U(1)a anomaly and bring the calculation consistently within the n-n(^1) mixing framework

Investigating cross-language speech retrieval for a spontaneous conversational speech collection

Cross-language retrieval of spontaneous speech combines the challenges of working with noisy automated transcription and language translation. The CLEF 2005 Cross-Language Speech Retrieval (CL-SR) task provides a standard test collection to investigate these challenges. We show that we can improve retrieval performance: by careful selection of the term weighting scheme; by decomposing automated transcripts into phonetic substrings to help ameliorate transcription errors; and by combining automatic transcriptions with manually-assigned metadata. We further show that topic translation with online machine translation resources yields effective CL-SR

Overview of the CLEF-2005 cross-language speech retrieval track

The task for the CLEF-2005 cross-language speech retrieval track was to identify topically coherent segments of English interviews in a known-boundary condition. Seven teams participated, performing both monolingual and cross-language searches of ASR transcripts, automatically generated metadata, and manually generated metadata. Results indicate that monolingual search technology is sufficiently accurate to be useful for some purposes (the best mean average precision was 0.18) and cross-language searching yielded results typical of those seen in other applications (with the best systems approximating monolingual mean average precision)

The role of topology and mechanics in uniaxially growing cell networks

In biological systems, the growth of cells, tissues, and organs is influenced by mechanical cues. Locally, cell growth leads to a mechanically heterogeneous environment as cells pull and push their neighbors in a cell network. Despite this local heterogeneity, at the tissue level, the cell network is remarkably robust, as it is not easily perturbed by changes in the mechanical environment or the network connectivity. Through a network model, we relate global tissue structure (i.e. the cell network topology) and local growth mechanisms (growth laws) to the overall tissue response. Within this framework, we investigate the two main mechanical growth laws that have been proposed: stress-driven or strain-driven growth. We show that in order to create a robust and stable tissue environment, networks with predominantly series connections are naturally driven by stress-driven growth, whereas networks with predominantly parallel connections are associated with strain-driven growth

Quantized transport, strain-induced perfectly conducting modes and valley filtering on shape-optimized graphene Corbino devices

The extreme mechanical resilience of graphene and the peculiar coupling it hosts between lattice and electronic degrees of freedom have spawned a strong impetus towards strain-engineered graphene where, on the one hand, strain augments the richness of its phenomenology and makes possible new concepts for electronic devices and, on the other hand, new and extreme physics might take place. Here, we demonstrate that the shape of substrates supporting graphene sheets can be optimized for approachable experiments where strain-induced pseudomagnetic fields (PMF) can be tailored by pressure for directionally selective electronic transmission and pinching-off of current flow down to the quantum channel limit. The Corbino-type layout explored here furthermore allows filtering of charge carriers according to valley and current direction, which can be used to inject or collect valley-polarized currents, thus realizing one of the basic elements required for valleytronics. Our results are based on a framework developed to realistically determine the combination of strain, external parameters, and geometry optimally compatible with the target spatial profile of a desired physical property --- the PMF in this case. Characteristic conductance profiles are analyzed through quantum transport calculations on large graphene devices having the optimal shape.Comment: 5+7 figures. Supporting information include