Results from a prototype beam monitor in the Tevatron using synchrotron light
A prototype synchrotron light monitor has been installed in the Tevatron at the downstream edge of a superconducting dipole magnet. Synchrotron light produced at the upstream edge of the magnet is sufficiently separated from the proton beam to be picked off by the monitor's mirror and diverted to its detector. It is shown that the way to enrich the low-wavelength region is to rely either upon short magnets (or an undulator which is a series of short magnets) or the sharp transition between the zero field region and the full-field region of a dipole magnet. The measured light intensity at different beam energies was compared to the predicted values. The parameters of a beam profile monitor are discussed.<<ETX>>
A POSSIBLE SYNCHROTRON LIGHT BEAM PROFILE MONITOR IN RHIC.
This report examines the possibility of observing transverse beam profiles by using synchrotron light emission from the 100 GeV/nucleon heavy-ion gold beam in the Relativistic Heavy Ion Collider (RHIC). Synchrotron radiation experiences a shift towards higher photon energy when the magnetic field at the end of a dipole varies rapidly over a short distance. Synchrotron light signals from high energy (larger than 400 GeV) proton beams have already been routinely used to observe the transverse beam profiles at the SPS in CERN and at the TEVATRON at Fermilab. Because of the modest relativistic factor of the fully stripped stored gold ions in RHIC this ''push'' towards higher critical energy is not large enough to place the synchrotron light within the visible region of the spectrum. The critical wavelength remains within the infrared region. A 77K cooled infrared array detector with 160 elements, made of PbSe (Lead salt) could be used for beam profile detection. It would cover the wavelength range between 1 and 6 microns, with maximum sensitivity at a wavelength of 4.5 microns.
RDF Keyword Search based on Keywords-To-SPARQL Translation
In this paper, we present a summary of our work on RDF keyword search. Given a set of keywords, our method automatically generates a set of candidate SPARQL queries, and their natural language description, to be evaluated on the RDF data graph. We discuss our approach, highlighting current and future directions.