Contact Interactions Probe Effective Dark Matter Models at the LHC

Effective field theories provide a simple framework for probing possible dark matter (DM) models by reparametrising full interactions into a reduced number of operators with smaller dimensionality in parameter space. In many cases these models have four particle vertices, e.g. qqXX, leading to the pair production of dark matter particles, X, at a hadron collider from initial state quarks, q. In this analysis we show that for many fundamental DM models with s-channel DM couplings to qq-pairs, these effective vertices must also produce quark contact interactions (CI) of the form qqqq. The respective effective couplings are related by the common underlying theory which allows one to translate the upper limits from one coupling to the other. We show that at the LHC, the experimental limits on quark contact interactions give stronger translated limits on the DM coupling than the experimental searches for dark matter pair production.Comment: 6 pages, 3 figure

Illuminating Dark Matter at the ILC

The WIMP (weakly interacting massive particle) paradigm for dark matter is currently being probed via many different experiments. Direct detection, indirect detection and collider searches are all hoping to catch a glimpse of these elusive particles. Here, we examine the potential of the ILC (International Linear Collider) to shed light on the origin of dark matter. By using an effective field theory approach we are also able to compare the reach of the ILC with that of the other searches. We find that for low mass dark matter (< 10 GeV), the ILC offers a unique opportunity to search for WIMPS beyond any other experiment. In addition, if dark matter happens to only couple to leptons or via a spin dependent interaction, the ILC can give an unrivalled window to these models. We improve on previous ILC studies by constructing a comprehensive list of effective theories that allows us to move beyond the non-relativistic approximation.Comment: 26 page

Modelling a case study in Astronomy with IMS Learning Design

Burgos, D., & Tattersall, C. (2008). Modelling a case study in Astronomy with IMS Learning Design [Electronic Version]. Journal of Interactive Media in Education, 2008 from http://jime.open.ac.uk/2008/19/.IMS Learning Design provides a counter to the trend towards designing for lone-learners reading from screens. It guides staff and educational developers to start not with content, but with learning activities and the achievement of learning objectives. It recognises that learning can happen without learning objects, learning is different from content consumption and that learning comes from being active. It recognises, too, that learning happens when learners cooperate to solve problems in social and work situations. In all this, it stresses that focus should fall on the learning in eLearning. This paper examines how IMS Learning Design (IMS-LD) and the current generation of IMS-LD based tooling can be used to model an eLearning case study in Astronomy, hosted by a workshop at ICALT 2006

CheckMATE 2: From the model to the limit

We present the latest developments to the CheckMATE program that allows models of new physics to be easily tested against the recent LHC data. To achieve this goal, the core of CheckMATE now contains over 60 LHC analyses of which 12 are from the 13 TeV run. The main new feature is that CheckMATE 2 now integrates the Monte Carlo event generation via Madgraph and Pythia 8. This allows users to go directly from a SLHA file or UFO model to the result of whether a model is allowed or not. In addition, the integration of the event generation leads to a significant increase in the speed of the program. Many other improvements have also been made, including the possibility to now combine signal regions to give a total likelihood for a model.Comment: 53 pages, 6 figures; references updated, instructions slightly change

Representing adaptive and adaptable Units of Learning:How to model personalized eLearning in IMS Learning Design

Burgos, D., Tattersall, C., & Koper, E. J. R. (2007). Representing adaptive and adaptable Units of Learning. How to model personalized eLearning in IMS Learning Design. In B. Fernández Manjon, J. M. Sanchez Perez, J. A. Gómez Pulido, M. A. Vega Rodriguez & J. Bravo (Eds.), Computers and Education: E-learning - from theory to practice. Germany: Kluwer.In this chapter we examine how to represent adaptive and adaptable Units of Learning with IMS Learning Design in order to promote automation and interoperability. Based on a literature study, a distinction is drawn between eight types of adaptation that can be classified in three groups: a) the main group, with interfaced-base, learning-flow and content-base; b) interactive problem solving support, adaptive information filtering, adaptive user grouping; and c) adaptive evaluation and changes on-the-fly. Several sources of information are used in adaptation: user, teacher and set of rules. In this paper, we focus on the core group a). Taking the various possible inputs to an eLearning process, we analyze how to model personalized learning scenarios related to these inputs explaining how these can be represented in IMS Learning Design

Exponential random graph models for multilevel networks

Advisors: Alan Polansky.Committee members: Sanjib Basu; Nader Ebrahimi.This master's thesis investigates the use of exponential random graph models for multilevel networks. It begins by describing some basic ideas in network analysis and then moves into the use of models to describe observed networks. After establishing modeling concepts for single-level networks, the discussion expands to modeling multilevel networks, which is a less common practice, and provides a brief multilevel modeling application. Focus is given to ERGM theory basics and highlights potential problems that researchers may encounter when employing these methods. Ultimately, the reader leaves with a sense of how and why network complexity can be modeled and some of the challenges that face network research.M.S. (Master of Science

Participating in LN4LD

This short document is a guide to LN4LD, the Learning Network for Learning Design, designed to provide the infrastructure for the Learning Designers Community of Practice (CoP) in EU UNFOLD project.UNFOL