User:Matthew Cordova/Notebook/Physics 307L/2010/11/10

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Safety There are no outstanding safety concerns for this lab. Equipment Combined Scintillator and PMT Computer running UCS 30 software Lead Bricks Spectech Universal Computer Spectrometer Power Supply Set Up A detailed set up can be found in Prof. Gold's lab manual. This lab was already set up when Sebastian and I chose to do this experiment, so I am unfamiliar with the details. Basically, a device which detects radiation is connected to a computer with software set up such that the number of detected 'events' are recorded over multiple intervals. These observations are what make up the data to be analyzed for this lab. Procedure The process of taking data for this lab is actually quite simple. Under the settings, Sebastian and I selected MCS mode. Under the settings menu, we set voltage to 1000V, number of bins to 256. These settings are held constant. The variable setting is the time interval for each bin. We chose 10ms, 20ms, 40ms, 80ms, 100ms, 200ms, 400ms, 1s and 2s intervals for our trials. With the correct settings selected, simply tell the computer to start collecting data. After this, wait and then proceed to the next trial. Save the runs as .cvs files, which can be opened in various applications for analysis. Calculations and Results The raw data and relevant equations can be found here, under the 'Data and Calculations' section. When you look at the standard deviation of this experiment tends toward the square root of the mean. It is because of this that we can say that the NaI detector was measuring a quantity which is distributed as a Poisson distribution. Note: In a true Poisson distribution, the standard deviation would be equal to the square root of mean. The reason this isn't quite the case is that we are dealing with random events. If one were to take more data points over longer intervals, the data would tend more and more towards a true Poisson distribution. Also, as we look at the graphs of Probability vs. Counts, it can be seen that as more information is recorded, the data tends to normalize. Note: As you can see, when there are small intervals, there are few counts, which results in obscure graphs. When more data is taken, however, you obtain a normal graph of Poisson distribution. References Brian Josey for general lab help. Dan for help setting up the software.