Beam-beam-induced orbit effects at LHC

For high bunch intensities the long-range beam-beam interactions are strong enough to provoke effects on the orbit. As a consequence the closed orbit changes. The closed orbit of an unperturbed machine with respect to a machine where the beam-beam force becomes more and more important has been studied and the results are presented in this paper.Comment: 5 pages, contribution to the ICFA Mini-Workshop on Beam-Beam Effects in Hadron Colliders, CERN, Geneva, Switzerland, 18-22 Mar 201

Temperature-dependent ion mixing and diffusion during sputtering of thin films of CrSi_2 on silicon

Measurements of sputtering yields and composition profiles have been carried out using backscattering spectrometry for samples of CrSi_2 on Si irradiated with 200‐keV Xe ions. When the CrSi_2 layer is thinner than the ion range, the sputtering yield ratio of Si to Cr increases from 3.5 for room‐temperature irradiation to 65 at 290 °C. For a thick sample, the corresponding increase is from 2.4 to 4.0. only. These changes are explained in terms of a rise in the Si surface concentration at 290 °C. The driving force for this process seems to be the establishment of stoichiometric CrSi_2 compound. Transport of Si to the surface is by ion mixing in the thin sample and thermal diffusion through the thick layer

Impact of Power Allocation and Antenna Directivity in the Capacity of a Multiuser Cognitive Ad Hoc Network

This paper studies the benefits that power control and antenna directivity can bring to the capacity of a multiuser cognitive radio network. The main objective is to optimize the secondary network sum rate under the capacity constraint of the primary network. Exploiting location awareness, antenna directivity, and the power control capability, the cognitive radio ad hoc network can broaden its coverage and improve capacity. Computer simulations show that by employing the proposed method the system performance is significantly enhanced compared to conventional fixed power allocation

Saber: window-based hybrid stream processing for heterogeneous architectures

Modern servers have become heterogeneous, often combining multicore CPUs with many-core GPGPUs. Such heterogeneous architectures have the potential to improve the performance of data-intensive stream processing applications, but they are not supported by current relational stream processing engines. For an engine to exploit a heterogeneous architecture, it must execute streaming SQL queries with sufficient data-parallelism to fully utilise all available heterogeneous processors, and decide how to use each in the most effective way. It must do this while respecting the semantics of streaming SQL queries, in particular with regard to window handling. We describe SABER, a hybrid high-performance relational stream processing engine for CPUs and GPGPUs. SABER executes windowbased streaming SQL queries in a data-parallel fashion using all available CPU and GPGPU cores. Instead of statically assigning query operators to heterogeneous processors, SABER employs a new adaptive heterogeneous lookahead scheduling strategy, which increases the share of queries executing on the processor that yields the highest performance. To hide data movement costs, SABER pipelines the transfer of stream data between different memory types and the CPU/GPGPU. Our experimental comparison against state-ofthe-art engines shows that SABER increases processing throughput while maintaining low latency for a wide range of streaming SQL queries with small and large windows sizes