Based on Teaching Students How to Model, I am revising the lectures for the Advanced Lab class (PHY 451).

**Day 1: **

- Introduce ourselves & fill out background material (year, classes & labs taken)
- Syllabus (timeline, grading policy, expectations)
- Introduction to Learning Goals & Modeling Framework
- Logbook (which kind, what to write)
- Description of experiments
- Choose Lab partners
- List experiment preferences
- Python tutorial (installation, read data file, plot data file, fit data to parabola)

**Lectures 1 & 2: Modeling Framework**

- Learning Goals
- Designing & Troubleshooting Experiments
- Technical Lab Skills (Computer DAQ systems, Test & Measurement Equipment)
- Communication (Argumentation, PRL-style paper, APS-style talk)
- Modeling Framework

- Modeling Framework
- What is modeling? A abstract representation of a real physical system that is simplified, is predictive, and has specified limits to its applicability.
- Outline of framework
- Two models are needed (measurement system and physical system)
- Iterative, but needs a starting point (Prelab writeup)
- Making comparisons (Data reduction & Uncertainty analysis)

- Prelab writeup
- What is being measured?
- Why is it being measured?
- How is it being measured?
- What steps are required for the measurement?
- Initial model for physical system
- Initial model for measurement system
- perfectly linear
- infinite dynamic range
- infinite range
- zero intrinsic noise (infinite precision)
- infinite resolution
- instantaneous response
- zero offset (perfectly accurate)

- Example: Measuring voltages in a voltage divider
- Initial model for physical system: Ohm’s Law
- Initial model for measurement system: Galvanometer
- Make measurements with DMM and Oscilloscope
- Comparison
- Refine Model

**Lectures 3, 4, 5: Data Analysis Potpourri**

- Statistical vs. Systematic
- Precision vs. Accuracy
- Gaussian statistical
- Poisson statistical
- Uncertainty propagation
- Examples of estimating the statistical uncertainty
- Systematics – incomplete model
- Curve fitting – (least squares)
- Anscombe’s quartet

**Lecture 6: Estimating & Order of Magnitude Physics**

- Street-Fighting Mathematics

The Art of Educated Guessing and Opportunistic Problem Solving

By Sanjoy Mahajan - what big are things (typical length scales, powers of 10)
- how long does it take (typical time scales, time powers of 10)
- dimensional analysis

**Lecture 7,8,9: Communication (Argumentation, PRL-style paper, APS-style talk)**

- data visualization
- model visualization
- citations
- components of a paper
- components of a talk
- Calling Bullshit
- types of fallacies
- McGuire Quartet
- case studies

**Lecture 10: Two-level systems (optional)**

- energy levels of system
- energy of photon
- absorption
- spontaneous emission
- stimulated emission
- linewidth or energy resolution
- conservation of energy
- conservation of angular momentum

You must be logged in to post a comment.