Two-dimensional super Yang-Mills theory investigated with improved resolution

In earlier work, N=(1,1) super Yang--Mills theory in two dimensions was found to have several interesting properties, though these properties could not be investigated in any detail. In this paper we analyze two of these properties. First, we investigate the spectrum of the theory. We calculate the masses of the low-lying states using the supersymmetric discrete light-cone (SDLCQ) approximation and obtain their continuum values. The spectrum exhibits an interesting distribution of masses, which we discuss along with a toy model for this pattern. We also discuss how the average number of partons grows in the bound states. Second, we determine the number of fermions and bosons in the N=(1,1) and N=(2,2) theories in each symmetry sector as a function of the resolution. Our finding that the numbers of fermions and bosons in each sector are the same is part of the answer to the question of why the SDLCQ approximation exactly preserves supersymmetry.Comment: 20 pages, 10 figures, LaTe

Forming norms: informing diagnosis and management in sports medicine

Clinicians aim to identify abnormalities, and distinguish harmful from harmless abnormalities. In sports medicine, measures of physical function such as strength, balance and joint flexibility are used as diagnostic tools to identify causes of pain and disability and monitor progression in response to an intervention. Comparing results from clinical measures against ‘normal’ values guides decision-making regarding health outcomes. Understanding ‘normal’ is therefore central to appropriate management of disease and disability. However, ‘normal’ is difficult to clarify and definitions are dependent on context. ‘Normal’ in the clinical setting is best understood as an appropriate state of physical function. Particularly as disease, pain and sickness are expected occurrences of being human, understanding ‘normal’ at each stage of the lifespan is essential to avoid the medicalisation of usual life processes. Clinicians use physical measures to assess physical function and identify disability. Accurate diagnosis hinges on access to ‘normal’ reference values for such measures. However our knowledge of ‘normal’ for many clinical measures in sports medicine is limited. Improved knowledge of normal physical function across the lifespan will assist greatly in the diagnosis and management of pain, disease and disability

ϕ\phi meson transparency in nuclei from ϕN\phi N resonant interactions

We investigate the $\phi$ meson nuclear transparency using some recent theoretical developments on the $\phi$ in medium self-energy. The inclusion of direct resonant $\phi N$-scattering and the kaon decay mechanisms leads to a $\phi$ width much larger than in most previous theoretical approaches. The model has been confronted with photoproduction data from CLAS and LEPS and the recent proton induced $\phi$ production from COSY finding an overall good agreement. The results support the need of a quite large direct $\phi N$-scattering contribution to the self-energy

Topological transversals to a family of convex sets

Let $\mathcal F$ be a family of compact convex sets in $\mathbb R^d$. We say that $\mathcal F$ has a \emph{topological $\rho$-transversal of index $(m,k)$} ($\rho<m$, $0<k\leq d-m$) if there are, homologically, as many transversal $m$-planes to $\mathcal F$ as $m$-planes containing a fixed $\rho$-plane in $\mathbb R^{m+k}$. Clearly, if $\mathcal F$ has a $\rho$-transversal plane, then $\mathcal F$ has a topological $\rho$-transversal of index $(m,k),$ for $\rho<m$ and $k\leq d-m$. The converse is not true in general. We prove that for a family $\mathcal F$ of $\rho+k+1$ compact convex sets in $\mathbb R^d$ a topological $\rho$-transversal of index $(m,k)$ implies an ordinary $\rho$-transversal. We use this result, together with the multiplication formulas for Schubert cocycles, the Lusternik-Schnirelmann category of the Grassmannian, and different versions of the colorful Helly theorem by B\'ar\'any and Lov\'asz, to obtain some geometric consequences

Relating CP-violating decays to the neutron EDM

We use the present upper bound on the neutron electric dipole moment to give an estimate for the upper limit of the CP-violating couplings of the $\eta(\eta')$ meson to the neutron. Using this result, we derive constraints on the CP-violating two-pion decays of the $\eta(\eta')$. Our results are relevant for the running and planned GlueX and LHCb measurements of rare meson decays.Comment: NSTAR 2017 conference proceeding

Structure of Pion Photoproduction Amplitudes

We derive and apply the finite energy sum rules to pion photoproduction. We evaluate the low energy part of the sum rules using several state-of-the-art models. We show how the differences in the low energy side of the sum rules might originate from different quantum number assignments of baryon resonances. We interpret the observed features in the low energy side of the sum rules with the expectation from Regge theory. Finally, we present a model, in terms of a Regge-pole expansion, that matches the sum rules and the high-energy observables.Comment: 19 pages, 15 figures and 4 table

The L3Pilot Common Data Format - Enabling Efficient Automated Driving Data Analysis

Analyzing road-test data is important for developing automated vehicles. L3Pilot is a European pilot project on level 3 automation, including 34 partners among manufacturers, suppliers and research institutions. Targeting around 100 cars and 1000 test subjects, the project will generate large amounts of data. We present a data format, allowing efficient data collection, handling and analysis by multiple organizations. A project of the scope of L3Pilot involves various challenges. Data come from a multitude of heterogeneous sources and are processed by a variety of tools. Recorded data span all data types generated in various vehicular sensors/systems and are enriched with external data sources. Videos supplement time-series data as external files. Derived measures and performance indicators \u2013 required to answer research questions about effectiveness of automated driving \u2013 are processed by analysis partners and included for each test session. As a file format, we chose HDF5, which offers a data model and software libraries for storing and managing data. HDF5 is designed for flexible and efficient I/O and for high volume and complex data. The usage of different computing environments for specific tasks is facilitated by the portability that comes with the format. Portability is also important for exploiting the rising potential within artificial intelligence (e.g. automatic scene detection and video annotation). Based on lessons learned from past field tests, we defined a general frame for the common data format that is aligned with the data processing steps of FESTA \u201cV\u201d evaluation methodology. The definitions include representation of the source signals and a hierarchical structure for including multiple datasets that are gradually supplemented (post-processed or annotated) during the various analysis steps. By using the HDF5 format, analysis partners have the freedom to exploit their familiar tools: MATLAB, Java, Python, R, etc. First comparisons between time-series data in previous projects (e.g. AdaptIVe) and the proposed data format show a reduction in storage size of around 80 %, without losses in performance. Much of that is due to efficient internal compression and structuring of data. Considering the amount of objective data involved in automated driving, this leads to a great benefit, in terms of usability. This paper presents a compact, portable, and extensible format aimed at handling extremely large amounts of field test data collected in automated driving pilots. As a harmonized format between tens of organizations performing tests in the L3Pilot project, the proposed format has the potential to promote data sharing as well as development of common tools and gain popularity for use in other projects. The format is designed to allow efficient storing of data and its iterative processing with analysis and evaluation tools. The format also considers the requirements of AI tools supporting neural network training and use