arXiv subjects

J. Tuggle

Publications and source records attributed to J. Tuggle.

3 recordsLinked to original sources

arXiv2018

Secondary ion mass spectrometry for SRF cavity materials

Historically, many advances in superconducting radio frequency (SRF) cavities destined for use in advanced particle accelerators have come empirically, through the iterative procedure of modifying processing and then performance testing. However, material structure is directly responsible for performance. Understanding, the link between processing, structure, and performance will streamline and accelerate the research process. In order to connect processing, structure, and performance, accurate and robust materials characterization methods are needed. Here one such method, SIMS, is discussed with focus on analysis of SRF materials. In addition, several examples are presented, showing how SIMS is being used to further understanding of materials based SRF technologies.

physics.acc-ph↗

arXiv2009

The Evolution of FTK, a Real-Time Tracker for Hadron Collider Experiments

We describe the architecture evolution of the highly-parallel dedicated processor FTK, which is driven by the simulation of LHC events at high luminosity (1034 cm-2 s-1). FTK is able to provide precise on-line track reconstruction for future hadronic collider experiments. The processor, organized in a two-tiered pipelined architecture, execute very fast algorithms based on the use of a large bank of pre-stored patterns of trajectory points (first tier) in combination with full resolution track fitting to refine pattern recognition and to determine off-line quality track parameters. We describe here how the high luminosity simulation results have produced a new organization of the hardware inside the FTK processor core.

physics.ins-det↗

arXiv2009

Development of FTK architecture: a fast hardware track trigger for the ATLAS detector

The Fast Tracker (FTK) is a proposed upgrade to the ATLAS trigger system that will operate at full Level-1 output rates and provide high quality tracks reconstructed over the entire detector by the start of processing in Level-2. FTK solves the combinatorial challenge inherent to tracking by exploiting the massive parallelism of Associative Memories (AM) that can compare inner detector hits to millions of pre-calculated patterns simultaneously. The tracking problem within matched patterns is further simplified by using pre-computed linearized fitting constants and leveraging fast DSP's in modern commercial FPGA's. Overall, FTK is able to compute the helix parameters for all tracks in an event and apply quality cuts in approximately one millisecond. By employing a pipelined architecture, FTK is able to continuously operate at Level-1 rates without deadtime. The system design is defined and studied using ATLAS full simulation. Reconstruction quality is evaluated for single muon events with zero pileup, as well as WH events at the LHC design luminosity. FTK results are compared with the tracking capability of an offline algorithm.

physics.ins-det↗