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SLAC Technical Note: SLAC-TN-11-007
SLAC Release Date: June 22, 2011
Data Acquisition in a High Harmonic Generation Lab and at LCLS
Hirokawa, Takako .
In this paper, we examine data acquisition in a high harmonic generation (HHG) lab and preliminary data analysis with the Cyclohexadiene Collaboration at the Linac Coherent Light Source (LCLS) at SLAC National Accelerator Laboratory. HHG experiments have a large number of parameters that need to be monitored constantly. In particular, the pressure of the target is critical to HHG yield. However, this pressure can fluctuate wildly and without a tool to monitor it, it is difficult to analyze the c... Show Full Abstract
In this paper, we examine data acquisition in a high harmonic generation (HHG) lab and preliminary data analysis with the Cyclohexadiene Collaboration at the Linac Coherent Light Source (LCLS) at SLAC National Accelerator Laboratory. HHG experiments have a large number of parameters that need to be monitored constantly. In particular, the pressure of the target is critical to HHG yield. However, this pressure can fluctuate wildly and without a tool to monitor it, it is difficult to analyze the correlation between HHG yield and the pressure. I used the Arduino microcontroller board and created a complementary MATLAB graphical user interface (GUI), thereby enhancing the ease with which users can acquire time-stamped parameter data. Using the Arduino, it is much easier to match the pressure to the corresponding HHG yield. Collecting data by using the Arduino and the GUI is flexible, user-friendly, and cost-effective. In the future, we hope to be able to control and monitor parts of the lab with the Arduino alone. While more parameter information is needed in the HHG lab, we needed to reduce the amount of data during the cyclohexadiene collaboration. This was achieved by sorting the data into bins and filtering out unnecessary details. This method was highly effective in that it minimized the amount of data without losing any valuable information. This effective preliminary data analysis technique will continue to be used to decrease the size of the collected data. Show Partial Abstract
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