Emittance Growth at LHC Injection from SPS and LHC Kicker Ripple

Fast pulsed kicker magnets are used to extract beams from the SPS and inject them into the LHC. The kickers exhibit time-varying structure in the pulse shape which translates into small offsets with respect to the closed orbit at LHC injection. The LHC damper systems will be used to damp out the resulting betatron oscillations, to keep the growth in the transverse emittance within specification. This paper describes the results of the measurements of the kicker ripple for the two systems, both in the laboratory and with beam, and presents the simulated performance of the transverse damper in terms of beam emittance growth. The implications for LHC operation are discussed

HIGH-FREQUENCY 3D GEOMORPHIC OBSERVATION USING HOURLY TERRESTRIAL LASER SCANNING DATA OF A SANDY BEACH

Geomorphic processes occur spatially variable and at varying magnitudes, frequencies and velocities, which poses a great challenge to current methods of topographic change analysis. For the quantification of surface change, permanent terrestrial laser scanning (TLS) can generate time series of 3D point clouds at high temporal and spatial resolution. We investigate how the temporal interval influences volume change observed on a sandy beach regarding the temporal detail of the change process and the total volume budget, on which accretion and erosion counteract. We use an hourly time series of TLS point clouds acquired over six weeks in Kijkduin, the Netherlands. A raster-based approach of elevation differencing provides the volume change over time per square meter. We compare the hourly analysis to results of a three- and six-week observation period. For the larger period, a volume increase of 0.3 m3/ m2 is missed on a forming sand bar before it disappears, which corresponds to half its volume. Generally, a strong relationship is shown between observation interval and observed volume change. An increase from weekly to daily observations leads to a five times larger volume change quantified in total. Another important finding is a temporally variable measurement uncertainty in the 3D time series, which follows the daily course of air temperature. Further experiments are required to fully understand the effect of atmospheric conditions on high-frequency TLS acquisition in beach environments. Continued research of 4D geospatial analysis methods will enable automatic identification of dynamic change and improve the understanding of geomorphic processes

Abort Gap Cleaning using the Transverse Feedback System: Simulation and Measurements in the SPS for the LHC Beam Dump System

The critical and delicate process of dumping the beams of the LHC requires very low particle densities within the $3 \mu$s of the dump kicker rising edge. High beam population in this so-called 'abort gap' might cause magnet quenches or even damage. Constant refilling due to diffusion processes is expected which will be counter-acted by an active abort gap cleaning system employing the transverse feedback kickers. In order to assess the feasibility and performance of such an abort gap cleaning system, simulations and measurements with beam in the SPS have been performed. Here we report on the results of these studies

FEATURE RELEVANCE ANALYSIS FOR 3D POINT CLOUD CLASSIFICATION USING DEEP LEARNING

3D point clouds acquired by laser scanning and other techniques are difficult to interpret because of their irregular structure. To make sense of this data and to allow for the derivation of useful information, a segmentation of the points in groups, units, or classes fit for the specific use case is required. In this paper, we present a non-end-to-end deep learning classifier for 3D point clouds using multiple sets of input features and compare it with an implementation of the state-of-the-art deep learning framework PointNet++. We first start by extracting features derived from the local normal vector (normal vectors, eigenvalues, and eigenvectors) from the point cloud, and study the result of classification for different local search radii. We extract additional features related to spatial point distribution and use them together with the normal vector-based features. We find that the classification accuracy improves by up to 33% as we include normal vector features with multiple search radii and features related to spatial point distribution. Our method achieves a mean Intersection over Union (mIoU) of 94% outperforming PointNet++’s Multi Scale Grouping by up to 12%. The study presents the importance of multiple search radii for different point cloud features for classification in an urban 3D point cloud scene acquired by terrestrial laser scanning

LHC Abort Gap Cleaning with the Transverse Damper

In the Large Hadron Collider, LHC, particles not captured by the RF system at injection or leaking out of the RF bucket may quench the superconducting magnets during beam abort. The problem, common to other superconducting machines, is particularly serious for the LHC due to the very large stored energy in the beam. For the LHC a way of removing the unbunched beam has been studied and it uses the existing damper kickers to excite resonantly the particles travelling along the abort gap. In this paper we describe the results of simulations performed with MAD X for various LHC optics configurations, including the estimated multipolar errors

Automated Classification of Airborne Laser Scanning Point Clouds

Making sense of the physical world has always been at the core of mapping. Up until recently, this has always dependent on using the human eye. Using airborne lasers, it has become possible to quickly "see" more of the world in many more dimensions. The resulting enormous point clouds serve as data sources for applications far beyond the original mapping purposes ranging from flooding protection and forestry to threat mitigation. In order to process these large quantities of data, novel methods are required. In this contribution, we develop models to automatically classify ground cover and soil types. Using the logic of machine learning, we critically review the advantages of supervised and unsupervised methods. Focusing on decision trees, we improve accuracy by including beam vector components and using a genetic algorithm. We find that our approach delivers consistently high quality classifications, surpassing classical methods

N-Methylimidazole Promotes The Reaction Of Homophthalic Anhydride With Imines

The addition of N-methylimidazole (NMI) to the reaction of homophthalic anhydride with imines such as pyridine-3-carboxaldehyde-N-trifluoroethylimine (9) reduces the amount of elimination byproduct and improves the yield of the formal cycloadduct, tetrahydroisoquinolonic carboxylate 10. Carboxanilides of such compounds are of interest as potential antimalarial agents. A mechanism that rationalizes the role of NMI is proposed, and a gram-scale procedure for the synthesis and resolution of 10 is also described

Progress with the Upgrade of the SPS for the HL-LHC Era

The demanding beam performance requirements of the High Luminosity (HL-) LHC project translate into a set of requirements and upgrade paths for the LHC injector complex. In this paper the performance requirements for the SPS and the known limitations are reviewed in the light of the 2012 operational experience. The various SPS upgrades in progress and still under consideration are described, in addition to the machine studies and simulations performed in 2012. The expected machine performance reach is estimated on the basis of the present knowledge, and the remaining decisions that still need to be made concerning upgrade options are detailed.Comment: 3 p. Presented at 4th International Particle Accelerator Conference (IPAC 2013