Reconstructing sparticle mass spectra using hadronic decays

Most sparticle decay cascades envisaged at the Large Hadron Collider (LHC) involve hadronic decays of intermediate particles. We use state-of-the art techniques based on the K⊥ jet algorithm to reconstruct the resulting hadronic final states for simulated LHC events in a number of benchmark supersymmetric scenarios. In particular, we show that a general method of selecting preferentially boosted massive particles such as W±, Z0 or Higgs bosons decaying to jets, using sub-jets found by the K⊥ algorithm, suppresses QCD backgrounds and thereby enhances the observability of signals that would otherwise be indistinct. Consequently, measurements of the supersymmetric mass spectrum at the per-cent level can be obtained from cascades including the hadronic decays of such massive intermediate bosons

Simple formulas for rotation averages of spectroscopic intensities

We give a self-contained exposition of the “ensemble method”, a rule for calculating rotation averages of spectroscopic absorption intensities. The rule is mathematically exact and conceptually simple and applies to rotation averages for several axes of rotation occurring in helical and superhelical symmetry. A measure of dichroism, DI, is introduced which has a simple multiplicative property relative to axes of rotation. There are several applications to linear dichroism spectroscopy

Text-pose estimation in 3D using edge-direction distributions

This paper presents a method for estimating the orientation of planar text surfaces using the edge-direction distribution (EDD) extracted from the image as input to a neural network. We consider canonical rotations and we developed a mathematical model to analyze how the EDD changes with the rotation angle under orthographic projection. In order to improve performance and solve quadrant ambiguities, we adopt an active-vision approach by considering a pair of images (instead of only one) with a slight rotation difference between them. We then use the difference between the two EDDs as input to the network. Starting with camera-captured front-parallel images with text, we apply single-axis synthetic rotations to verify the validity of the EDD transform model and to train and test the network. The presented text-pose estimation method is intended to provide navigation guidance to a mobile robot capable of reading the textual content encountered in its environment.</p