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Due Date |
Assignment |
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1) Friday, February 2 |
Reproduce the results of the examples given on pages 18 and 21 of Lecture 02. These examples require data files for the graph and histogram. |
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2) Friday, February 9 |
Estimate the identification probabilities for electrons and photons in a hypothetical experiment. Compare the expectation values of a function for a uniform distribution. |
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3) Friday, March 2 |
Determine the best fit mean and width for a sample of Gaussian distributed data using the maximum likelihood method. Start from the example code and modify for a Gaussian distribution. |
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4) Friday, March 2 |
Construct a simulation of a B meson decay experiment. You will need the gRandom->Exp(tau), and gRandom->Gaus(mean,sigma) methods in root. |
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5) Friday, March 30 |
Start a data analysis using the eventData.txt found in the examples directory. Write a function to read the data based on the example code. Reproduce the energy distribution presented in lecture 17 starting from the example script. Make event distributions for the decay signal time, event direction (split MC in to electron and muon neutrino types). Finally for MC events, plot the neutrino energies for each type of neutrino, and the neutrino directions. |
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6) Friday, May 3 |
Derive an estimate for the number of events resulting from neutrons decaying to a π° and a neutrino. Follow the techniques outlined in lectures 21 and 22 to select π° events and then fit the resulting distribution to find the total contribution from nucleon decay. You should reproduce the figure on page 5 of lecture 25 which shows the difference between the observed number of events vs π° momentum and the expectation. |
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