Measurements of the masses, lifetimes and mixings of B hadrons at the Tevatron

The Tevatron, with p p-bar collisions at sqrt(s)=1.96TeV can produce all flavors of B hadrons and allows for unprecedented studies in the B physics sector. The CDF and D0 collaborations have more than 5 fb-1 of data recorded. I present here a selection of results on the masses, lifetimes and mixings of B hadrons using between 1.0 and 2.8fb-1 of data.Comment: 5 pages, 3 figures. Proceedings for Recontres de Moriond QCD 2009, references adde

Risk management: understanding why is as important as understanding how

The management of risk is a key area within a number of ACCA papers, and exam questions related to this area are common. It is vital that students are able to apply risk management techniques, such as using derivative instruments to hedge against risk, and offer advice and recommendations as required by the scenario in the question. It is also equally important that students understand why corporations manage risk in theory and in practice, because risk management costs money but does it actually add more value to a corporation? This article explores the circumstances where the management of risk may lead to an increase in the value of a corporation

Moral imagination or heuristic toolbox? Events and the risk assessment of structured financial products in the financial bubble

The paper uses the example of the failure of bankers and financial managers to understand the risks of dealing in structured financial products, prior to the financial collapse, to investigate how people respond to crises. It focuses on whether crises cause people to challenge their habitual frames by the application of moral imagination. It is proposed that the structure of financial products and their markets triggered the use of heuristics that contributed to the underestimation of risks. It is further proposed that such framing heuristics are highly specialised to specific contexts, and are part of a wider set of heuristics that people carry in their cognitive ‘adaptive tool boxes’. Consequently, it is argued, when a crisis occurs the heuristics are not challenged, but are simply put away, and other more appropriate heuristics put to use until a sense of normality returns, and the use of the old heuristics is resumed

Organisational slack, corporate reputation and financial performance

This discussion paper aims to fill the gap left by the latest research on organisational slack that has been focused on emerging economies or on a single company or on a single industry. Senior executives’ perceptions that contribute to a measure of corporate reputation are tested as a proxy measure of unabsorbed slack. Disaggregating the components that make up reputation enables the perceptions of a company’s ‘ability to innovate’ and how efficiently they ‘use their corporate assets’ to also be tested as measures of unabsorbed, perceptual or discretionary slack. The impact of these variables is considered in terms of company performance

Gaussian Process Emulators in coastal wave modelling

A majority of the coastal wave modelling analysis require using historical data from physical observations or from computer simulations. Such simulators are often computationally expensive (takes long for a single evaluation run) and therefore it is normally a bottleneck in the analysis. Meta models are increasingly used as surrogates of the complex simulators to improve the efficiency of the bottleneck step. The performance of the meta model is vital when selecting the model as this would greatly influence the conclusions that are drawn from the analysis. In this thesis we apply the Gaussian Process Emulator as a meta model of a wave transformation simulator, SWAN. The GPE is advantageous compared to other meta models as the predictions from the GPE are in the form of a distribution (mean and variance) and predicting at an event used to train the GPE returns perfect predictions with no uncertainty. Univariate and multivariate approaches of the GPE are presented and compared in case studies. In addition simple diagnostics to validate the GPE are discussed. Look–up table (LUT) approach is a commonly used traditional meta model in coastal modelling. This is based on multidimensional linear interpolation of points on a regular grid. A case study shows the performance improvement that can be gained by using GPE over this traditional LUT approach. The GPE needs less than 2% of the simulator runs required for the LUT to obtain a similar accuracy. When introducing the multivariate GPE we identify two types of multiple outputs. We present a principal component GPE (PC-GPE) and a separable GPE for highly correlated and high dimensional output. These methods are compared to fitting multiple univariate GPE’s. In terms of accuracy the multiple univariate GPE outperformed the other methods however the PC-GPE tends to be moreefficient with only a small compromise on accuracy. For low dimensional output that is weekly correlated we present the linear model of coregionalisation (LMC) GPE which is a more flexible technique than the separable GPE. We compared this with the separable GPE and to fitting multiple univariate GPEs. The LMC GPE gave similar results as the multiple univariate GPE, but it is unstable and took a significant amount of time to fit. Finally, we describe three approaches of selecting a design (simulator runs used to train the GPE). We aim to select a design that will maximise the information we can get from the simulator in order to inform the GPE given the limited simulator runs. The aim of this thesis is to present the GPE methodology in a concise manner with running examples throughout. The novelty here is to show the application of GPEs to coastal wave modelling in order to help alleviate the computational burden and improve accuracy when using meta-models to avoid the bottleneck in the analysis

First determination of the CPCP content of D→π+π−π+π−D \to \pi^+\pi^-\pi^+\pi^- and updated determination of the CPCP contents of D→π+π−π0D \to \pi^+\pi^-\pi^0 and D→K+K−π0D \to K^+K^-\pi^0

Quantum-correlated $\psi(3770) \to D\bar{D}$ decays collected by the CLEO-c experiment are used to perform a first measurement of $F_+^{4\pi}$, the fractional $CP$-even content of the self-conjugate decay $D \to \pi^+\pi^-\pi^+\pi^-$, obtaining a value of $0.737 \pm 0.028$. An important input to the measurement comes from the use of $D \to K^0_{\rm S}\pi^+\pi^-$ and $D \to K^0_{\rm L}\pi^+\pi^-$ decays to tag the signal mode. This same technique is applied to the channels $D \to\pi^+\pi^-\pi^0$ and $D \to K^+K^-\pi^0$, yielding $F_+^{\pi\pi\pi^0} = 1.014 \pm 0.045 \pm 0.022$ and $F_+^{KK\pi^0} = 0.734 \pm 0.106 \pm 0.054$, where the first uncertainty is statistical and the second systematic. These measurements are consistent with those of an earlier analysis, based on $CP$-eigenstate tags, and can be combined to give values of $F_+^{\pi\pi\pi^0} = 0.973 \pm 0.017$ and $F_+^{KK\pi^0} = 0.732 \pm 0.055$. The results will enable the three modes to be included in a model-independent manner in measurements of the unitarity triangle angle $\gamma$ using $B^\mp \to DK^\mp$ decays, and in time-dependent studies of $CP$ violation and mixing in the $D\bar{D}$ system.Comment: Minor revisions following journal acceptanc

Application of machine learning techniques to support decision making under uncertainty in water resource management

Water companies in the UK are required to produce long-term plans of water resources for their supply area every five years, detailing how they will maintain secure, sustainable supplies , taking account of social and environmental impacts as well as economic costs. Extensive ensemble modelling of water resource systems underpins the production of these reports and the resulting investments chosen to maintain supplies into the future. Adoption of new guidance on the use of advanced Decision Making Methods (DMMs) and Risk Based Planning has demanded a more comprehensive modelling approach. Modelling and analytical efficiencies are increasingly required for their use and to realise their full benefits. Existing water resources, hydrological, groundwater, and demand models traditionally used by water companies are often not ideally suited for use in these DMMs. Consequently a toolset of approaches is evolving to enable UK water companies to undertake this more complex decision making. Key elements of this toolset include emulation modelling to complement computationally more expensive process models, machine learning techniques for groundwater assessment and to optimise reservoir control curves considering multiple objectives, and agent based models to explore the spatial and temporal pattern of demand over ensembles of plausible futures. These methods support the rapid simulation times required for applying the DMMs to provide a holistic view of system behaviour under large supply-side, demand-side and policy uncertainties. User-friendly tools and dashboards are being used to explore and communicate the outputs and facilitate effective decision-making, involving all stakeholders. This toolset of approaches is being increasingly adopted in the UK, demonstrating the potential for innovative methods to interpret and present complex modelling results. Due to the flexible structure of the tools, and the generic approaches used, these techniques can readily be applied to a wide range of settings. However, the absence of physical process representation in some of these methods, and associated implications, must be considered in their application and by planners when interpreting results. Methods in themselves are not a replacement for diligent water planning, but a tool to support it