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Optimization of Data Analysis through One-Cut and Two-Cut Techniques in Experimental Physics

This presentation by Daniel J. Cruz from Texas A&M University explores the utilization of single and dual cut analyses within physics data, aiming to enhance data interpretation and optimization of expected cross-sections in experiments. It emphasizes the importance of careful cut selection and presents findings from an experiment using data from Eunsin Lee's Ph.D. thesis. The results demonstrate that while two cuts can generally improve outcomes, caution is required to avoid diminishing returns. The analysis employs experimental data fitting techniques and presents graphical findings on cut performance.

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Optimization of Data Analysis through One-Cut and Two-Cut Techniques in Experimental Physics

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Presentation Transcript

  1. Daniel J. Cruz Dept. of Physics and Astronomy Texas A&M University Two Cut Analysis Optimization

  2. Presentation • Overview • Utilizing Cuts • Actual Experiment • Results • Summary 2

  3. Overview • Utilize cuts in physics to better analyze data • Show that care needs to be taken when making cuts (cannot make them blindly) • Sometimes two cuts AREN’T better than one cut 3

  4. Utilizing Cuts 4

  5. One Cut Analysis • Cut away part of data • Stick with most useful • Free to move cut selection (in this case, 200 GeV) 5

  6. Two Cut Analysis • Cut away part of data, then separate rest in two cuts • Cut A is original cut, cut B is new cut within original • Makes data more manageable • Can move both cuts, or keep one cut (A) static while moving other cut (B) 6

  7. Actual Experiment 7

  8. Expected Cross Sections • We look for 95% confidence limit on expected cross section, σproduction • Utilize cuts technique to optimize σ95 • Used modified Fortran Limiting Calculator program, coded by Dr. Joel Walker of Sam Houston State University 8

  9. Experiment • Data taken from Eunsin Lee’s Ph.D. thesis at Texas A&M, Phys. Rev. Lett. 104, 011801 (2010) • Binned values were used, as well as fitted values • Graph provided by Chris Davis (modified graph in slides 5 and 6) 9

  10. Background • Fitted background • Used an exponential curve • Red dots are fit, black dots are actual data 10

  11. Acceptance • Fitted acceptance • Used a Gaussian curve • Red dots are fit, black dots are actual data 11

  12. One Cut Experiment • Red dots are actual data • Black dots are fitted data • Optimum is 22 fb at 240 GeV (22.5 fb at 250 GeV for fitted curve) • What about two cuts? 12

  13. Two Cut Experiment • Minimum of 21 fb at (240,36) • However, places where σ95 > 22 fb • Better than one cut in places, worse in other places! • Graph provided by Chris Davis 13

  14. Results 14

  15. How much better can you get? • Plot of cut A(250 GeV) as a function of cut B; black dotted line indicates limit at 250 GeV (22.45 fb) • By manipulating our cut B, we can optimize to 21.3 fb (achieved with cut Bat 350 GeV) 15

  16. One Cut -> Two Cut • You always (ok, most of the time) get an improvement • Have to be careful in order to maximize improvement • Shown is 2-D Minimum Limit vs. Cut A (notice that lowest limit achieved is better than 1-D) 16

  17. Summary • In MOST cases, two cuts > one cut (have to be careful, though) • Delicate in how to choose cut B (otherwise, you get result which is roughly equal to one cut) 17

  18. The Endquestions?

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