Abstract's Details

Diagnostics for LUSI Instruments
Abstract ID	I&D-02
Presenter	Yiping Feng
Presentation Type	Poster
Full Author List	Y. Feng (1)
Affiliations	(1) LUSI/LCLS, SLAC, 2575 Sand Hill Rd., Menlo Park, CA 94025, USA
Category	Instrumentation/Development
Abstract	Linac-based X-ray FELs such as the LCLS are fundamentally different from storage-ring based synchrotron sources. The X-ray amplification process, self amplified spontaneous emission, (SASE) starts from a random electron density distribution, and each X-ray pulse will consist of a random sequence of a large number of uncorrelated coherent radiation spikes of varying degrees of saturation. As such, the LCLS is expected to exhibit inherent intensity, spatial, temporal, and spectral fluctuations on a pulse-by-pulse basis. A suite of X-ray photon diagnostic devices will be designed and implemented to fully characterize these fluctuations and provide accurate intensity, timing, and positional calibration to the experimental measurements to be carried out on the instruments at LCLS.
Footnotes
Funding Acknowledgement

Controls and Data Systems for LUSI Instruments
Abstract ID	I&D-03
Presenter	Yiping Feng
Presentation Type	Poster
Full Author List	Y. Feng (1)
Affiliations	(1) LUSI/LCLS, SLAC, 2575 Sand Hill Rd., Menlo Park, CA 94025, USA
Category	Instrumentation/Development
Abstract	The 120 Hz per-pulse data collection/reduction, multi-Gigabit/sec data rate, multi-Terabyte daily data volume, and sub-picosecond timing control requirements of LCLS experiments go far beyond those at existing synchrotron sources, requiring considerable complexity and sophistication in controls and data systems’ design, implementation, and integration. As such, the LUSI controls and data systems will include a data acquisition subsystem capable of not only capturing large data sets on a per pulse basis, but also processing experimental data on the fly. A data management subsystem including fast on-line data storage and an interface to a Petabyte data farm for long term archiving and retrieval, and a data analysis subsystem consisting of large CPU nodes for computational-intensive off-line analysis will also be required.
Footnotes
Funding Acknowledgement