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PHYS 7363, Prof. Saptaparna Bhattacharya

Discusses particle detection and detectors. Designed for experimental particle physicists or for those who want to understand the basic physics and techniques in particle detection. Prerequisite: PHYS 6380. Corequisites: Mastery of one modern computing language such as C++, Python, or Java; the ability to work in a Linux OS environment. If the primary language is not C++, students should be able to learn enough C++ after a brief introduction at the beginning of the course.

Access this course on canvas and submit assignments exclusively via canvas

PHYS7363-001-1257

Resources

  • Particle Detectors: Fundamentals and Applications Hermann Kolanoski, Norbert Wermes

Class schedule

  • Monday, Wednesday, Friday, 12-12:50 pm US Central

Final exam and grades

The final grade in this course comes from three parts:

  • 50% of the final grade: The final project will account for 50% of the grade.
  • 40% of the final grade: Midterm (closed-book) exam.
  • 10% of the final grade from exercises and classroom participation

Grading in this course is standards based and not rank/percentile based. That is, each deliverable towards the final grade (final exam, midterm, and exercises) has a pre-defined amount of points that can be achieved. The grades are assigned not based on how well you do compared to peer students, but in your mastery of the material against the lectures' material (following the course requirements). Grades are measuring results and not efforts, since we have no way to measure how much effort has been put into each worksheet.

The relative fractional number of points that are given in total and individually for each the exams and the exercises follow the interpretations in the table below: To get an A-level grade you will have to do as well as could reasonably expected. For a B-level grade your submissions have noticeable flaws, but you are well above the minimum standard. A C-level grade signifies minimum requirements. A D-level grade signifies that some aspects have been learned, but the minimum requirements have not been met.

To summarize, the grade numerical score is as follows and translates to the letter grade as in the table below:

\begin{align} \text{final grade numerical score} & = \min\Bigg(1.0,\Bigg[ 0.5 \frac{\text{achieved points in final project}}{\text{maximum attainable points in final project}} \\ & + 0.4 \frac{\text{achieved points in midterm exam}}{\text{maximum attainable points in midterm exam}}\\ & + 0.1 \frac{\text{achieved points in exercises}}{\text{maximum attainable points in exercises}} + 0.01 \Bigg]\Bigg) \,. \end{align}

We further add one percent so that students just at the margin of a better grade will receive that. Under no circumstances is (additional) grade bumping performed at the end of the semester, and we consider this an unfair preferential treatment.

Grade scale

Numerical Score

Interpretation

A

[93,100]%

The student did as well as could reasonably be expected.

A-

[90,93)%

B+

[87,90)%

The student’s mastery of the material has noticeable flaws but is well above the minimum standard.

B

[83,87)%

B-

[80,83)%

C+

[77,80)%

The student met the minimum requirements for the course.

C

[73,77)%

C-

[70,73)%

D+

[67,70)%

The student learned some of the material but did not meet minimum requirements.

D

[63,67)%

D-

[60,63)%

F

[0,60)%

The student learned little or none of the material.