ISTINYE UNIVERSITY BİLGİ PAKETİ / DERS KATALOĞU
| Physics (DR) (English) | |||||
| PhD | TR-NQF-HE: Level 8 | QF-EHEA: Third Cycle | EQF-LLL: Level 8 | ||
Course Introduction and Application Information
| Course Code: | PHYS6003 | ||||
| Course Name: | Analysis Methods in Particle Physics | ||||
| Semester: |
Spring |
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| Course Credits: |
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| Language of instruction: | English | ||||
| Course Condition: | |||||
| Does the Course Require Work Experience?: | No | ||||
| Type of course: | Departmental Elective | ||||
| Course Level: |
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| Mode of Delivery: | Face to face | ||||
| Course Coordinator: | Doç. Dr. ANDREW JOHN BEDDALL | ||||
| Course Lecturer(s): | Assoc. Prof. Dr. Andrew Beddall | ||||
| Course Assistants: |
Course Objective and Content
| Course Objectives: | The student will be introduced the underlying principles of analysis methods and their applications to selected areas. Theoretical derivations will be given and demonstrated with practical applications. |
| Course Content: | Analysis objects, photon conversion tomography, invariant mass spectra, counting particles, signal significance, background rejection techniques, likelihood, ROC curves, modeling mass spectra, Monte Carlo, measuring resolution, calibration, signal hunting and upper limits, multivariate discrimination, methods in particle identification. |
Learning Outcomes
|
The students who have succeeded in this course;
1) Will have applied knowledge of probability and statistics to building analysis tools for particle physics. 2) Will have learned some analysis methods that are commonly used in particle physics. 3) Gained experience in analysis through practical assignments and projects. |
Course Flow Plan
| Week | Subject | Related Preparation |
| 1) | Introduction to the course | - |
| 2) | Analysis objects, photon conversion tomography | - |
| 3) | Invariant mass spectra | - |
| 4) | Counting particles, signal significance | - |
| 5) | Background rejection techniques, likelihood, ROC curves | - |
| 6) | Modeling mass spectra | - |
| 7) | Mid-term project | - |
| 8) | Monte Carlo, measuring resolution, calibration | - |
| 9) | Signal hunting and upper limits | - |
| 10) | Methods in particle identification | - |
| 11) | Multivariate discrimination | - |
| 12) | Final project | - |
Sources
| Course Notes / Textbooks: | "Introduction to Statistics and Data Analysis for Physicists", Gerhard Bohm, Günter Zech. https://bib-pubdb1.desy.de/record/389738 Luca Lista "Statistical Methods for Data Analysis in Particle Physics" Second Edition; Spinger . |
| References: | -- |
Course - Program Learning Outcome Relationship
| Course Learning Outcomes | 1 |
2 |
3 |
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|---|---|---|---|---|---|---|---|---|---|
| Program Outcomes | |||||||||
| 1) Possession of fundamental and recents theories and experimental techniques in the field of high energy and particle physics. | 1 | 2 | |||||||
| 2) Effective use of the theoretical knowledge on applications. | 2 | ||||||||
| 3) Competence in using analysis tools and equipment in experimental studies. | 2 | 3 | |||||||
| 4) Advanced design competence about particle detectors and/or particle accelerators. | |||||||||
| 5) Possession of data acquisition, data analysis and data processing skills. | 3 | 3 | |||||||
| 6) Competence to do independent research in the field of High Energy and Particle Physics. | 1 | 2 | |||||||
| 7) Having R&D and/or P&D experience on Particle Detectors and Particle Accelerators. | |||||||||
| 8) Collaborative work competence required by experimental and phenomenological research activities in the field of High Energy and Particle Physics. | |||||||||
| 9) Competence in understanding, using and developing the software and hardware required by particle physics research and applications, from data analysis to detector and accelerator design. | 2 | 2 | |||||||
Course - Learning Outcome Relationship
| No Effect | 1 Lowest | 2 Average | 3 Highest |
| Program Outcomes | Level of Contribution | |
| 1) | Possession of fundamental and recents theories and experimental techniques in the field of high energy and particle physics. | 1 |
| 2) | Effective use of the theoretical knowledge on applications. | |
| 3) | Competence in using analysis tools and equipment in experimental studies. | 3 |
| 4) | Advanced design competence about particle detectors and/or particle accelerators. | |
| 5) | Possession of data acquisition, data analysis and data processing skills. | 2 |
| 6) | Competence to do independent research in the field of High Energy and Particle Physics. | |
| 7) | Having R&D and/or P&D experience on Particle Detectors and Particle Accelerators. | |
| 8) | Collaborative work competence required by experimental and phenomenological research activities in the field of High Energy and Particle Physics. | |
| 9) | Competence in understanding, using and developing the software and hardware required by particle physics research and applications, from data analysis to detector and accelerator design. |
Assessment & Grading
| Semester Requirements | Number of Activities | Level of Contribution |
| Homework Assignments | 14 | % 60 |
| Project | 3 | % 40 |
| total | % 100 | |
| PERCENTAGE OF SEMESTER WORK | % 100 | |
| PERCENTAGE OF FINAL WORK | % | |
| total | % 100 | |
Workload and ECTS Credit Calculation
| Activities | Number of Activities | Preparation for the Activity | Spent for the Activity Itself | Completing the Activity Requirements | Workload | ||
| Course Hours | 14 | 0 | 3 | 42 | |||
| Study Hours Out of Class | 14 | 0 | 6 | 84 | |||
| Project | 3 | 2 | 10 | 36 | |||
| Homework Assignments | 14 | 0 | 3 | 3 | 84 | ||
| Total Workload | 246 | ||||||