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Scripps College    
 
    
 
  Jul 26, 2017
 
2013-2014 Academic Catalog THIS IS AN ARCHIVED CATALOG. LINKS MAY NO LONGER BE ACTIVE AND CONTENT MAY BE OUT OF DATE!

Physics


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Please refer to the Science  section of this catalog.

The physics major places a strong emphasis on computational and numerical techniques while still retaining the core material common to all physics majors. Many problems which are not readily solvable using traditional methods will be incorporated into the program, and solutions will involve numerical integration, computer modeling, and other numerical techniques introduced in the classroom and laboratory.

Learning Outcomes of the Program in Physics

When confronted with an unfamiliar physical or dynamical system or situation, students should be able to:

  1. Develop a conceptual framework for understanding the system by identifying the key physical principles, relationships, and constraints underlying the system.
  2. Translate that conceptual framework into an appropriate mathematical format/model.
  3. (a) If the mathematical model/equations are analytically tractable, carry out the analysis of the problem to completion (by demonstrating knowledge of a proficiency with the standard mathematical tools of physics and engineering).
    (b) If the model/equations are not tractable, develop a computer code and/or use standard software/programming languages (e.g., Matlab, Maple, Python) to numerically simulate the model system.
  4. Intelligently analyze, interpret, and assess the reasonableness of the answers obtained and/or the model’s predictions.
  5. Effectively communicate their findings (either verbally and/or via written expression) to diverse audiences.

In a laboratory setting, students should be able to:

  1. Design an appropriate experiment to test out a hypothesis of interest.
  2. Make basic order-of-magnitude estimates.
  3. Demonstrate a working familiarity with standard laboratory equipment (e.g., oscilloscopes, DMMs, signal generators, etc.).
  4. Identify and appropriately address the sources of systematic error and statistical error in their experiment.
  5. Have proficiency with standard methods of data analysis (e.g., graphing, curve-fitting, statistical analysis, Fourier analysis, etc.).
  6. Intelligently analyze, interpret, and assess the reasonableness of their experimental results.
  7. Effectively communicate their findings (either verbally and/or via written expression) to diverse audiences.

Programs

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