Post #3: Correcting for Beam Effects in the Qweak Experiment

I continue here where I left off before in my last post. This is my final post, and it details the results and conclusions of my research:

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Post #2: Correcting for Beam Effects in the Qweak Experiment

In this post, I will describe in greater detail the underpinnings of both the Qweak Experiment and my work. The material is extracted from a paper that I wrote for the REU (Research Experience for Undergraduates) program in physics. I’ll spare anyone reading this from the math in the actual paper, which I will describe qualitatively here:

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Kalman Filter Update 3

I recently finished up the final stages of applying the Kalman filter, and obtained estimates of the test-beam particles’ momentum errors, which was the main purpose of this project. I have discussed in previous posts how I propagated the Kalman filter through the beamline, and hinted in my last post that I had finally taken momentum errors into account. The method to do this was iterative in nature; I first applied the Kalman filter through the beamline and obtained values for the directional errors at wirechambers 2 and 3. These could be used to obtain the error in the measured bend angle, and this could be used to find a momentum error. We then ran the filter again, but used this new bend error to obtain improved errors in the wirechamber 3 directional error. We then found an improved bend and momentum error, etc. This process was repeated 3 or 4 times, by which point the further iterations made almost no improvement on the values obtained.

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Post #1: Correcting for Beam Effects in the Qweak Experiment

First of all, I want to start off with a summary and explanation of my abstract and purpose: I am working to correct data measured by the Qweak experiment at Jefferson Lab for natural beam imperfections which create ‘false asymmetries’ in the data. This is done by calculating correlations between different beam properties and the data (asymmetries measured by the main detectors) and removing these correlations from the data. Correlations are not calculated in the same way that one might in a stats class. They are calculated for each successive event (there are some 90,000 events in each data file that I use) so that precision is not lost as one calculates over such a large set of data. These values are then used to correct the main detector data, removing the ‘false asymmetries’ due to the beam motion. Greater explanation of this process and results will follow in subsequent blog posts.

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