2014
Welcome to Advanced Physics Lab 2014!
Instructors
Professor: Tobias Marriage (marriage@pha.jhu.edu), Office: Bloomberg 215
TAs: Ian Anderson (ianderso@pha.jhu.edu), Office: Bloomberg 429
Lab Guru: Steve Wonnell (wonnell@pha.jhu.edu), Office: Bloomberg 478
Wiki
This page (https://wiki.pha.jhu.edu/advlab_wiki/index.php/2014) is your source of much course-related knowledge. Useful materials will be distributed here.
Also check out general descriptions of labs and pages for previous years at
https://wiki.pha.jhu.edu/advlab_wiki/index.php
General Description
In this class, you you'll learn
- how to conduct an experiment, collecting data with special attention to estimating systematic and statistical measurement errors,
- how to model the data,
- and how to present your work through scientific writing.
These three aspects essentially define the course. Each lab will be evaluated based on how well the three aspects are realized.
Classes
Times: Monday 10:00-12:50 and 1:30-4:30
Classes will run in a seminar format. They will begin with a lecture followed by discussion and short updates on experimental work from students. A shared online directory (Google drive) will be used to upload update material.
At the beginning of a new experiment, an introduction to the new experiment will also be given in the class.
Experiments
Four experiments will be completed over the course of the semester, each taking three weeks. These experiments will start in the second week of the course. The nominal experiments we will work through are the following.
- Brownian Motion: The goal of this experiment is to estimate the Boltzmann constant using a measurement of the brownian motion of microscopic spheres.
- Speed of Light: In this experiment you use the classic Foucault spinning mirror measurement to estimate the speed of light.
- Single Photon Interference: This experiment explores the interference of quantum wave functions.
- Radio Astronomy: In this experiment you'll use a 1.4 GHz (21 cm) radio telescope to look out into the galaxy and (possibly) beyond.
The first two experiments are intended to be a good match to the data analysis being taught in lectures and readings during the first half of the course. The second two experiments, to be completed in the second half of the semester, are intended to be matched to the more advanced material presented in lectures and readings during the second half of the course.
Readings
Weekly readings will be assigned from this text:
Bevington & Robinson, Data Reduction and Error Analysis for the Physical Sciences, 3rd Edition, McGraw-Hill, ISBN 0-07-247227-8, 2003
Schedule
Below is the nominal schedule for the course.
| Date | Lecture | Weekly Reading | Other Notes |
|---|---|---|---|
| Jan 27 | Class Overview, Measurement & Errors | Bev. Ch1 | Work on basic LaTeX and Python examples |
| Class material to go here. | |||
| Feb 03 | Probability Distributions, Exp. 1 Introduction | Bev. Ch 2 | Start Exp. 1 |
| Feb 10 | Propagation of Errors | Bev. Ch 3 | Give updates on Experiment 1 |
| Feb 17 | Propagation of Errors | Bev. Ch 3 | Give updates on Experiment 1 |
| Feb 24 | Propagation of Errors | Bev. Ch 3 | Give updates on Experiment 1 |
| Mar 3 | Propagation of Errors | Bev. Ch 3 | |
| Mar 10 | Propagation of Errors | Bev. Ch 3 | Mar 17-21 Spring Break |
| Mar 24 | Propagation of Errors | Bev. Ch 3 | Give updates on Experiment 1 |
| Mar 31 | Propagation of Errors | Bev. Ch 3 | Give updates on Experiment 1 |
| Apr 7 | Propagation of Errors | Bev. Ch 3 | Give updates on Experiment 1 |
| Apr 14 | Propagation of Errors | Bev. Ch 3 | Give updates on Experiment 1 |
| Apr 21 | Propagation of Errors | Bev. Ch 3 | Give updates on Experiment 1 |
| Apr 28 | Propagation of Errors | Bev. Ch 3 | Give updates on Experiment 1 |
Jan 27: Welcome Lecture,
Feb 03: First Lab Begins
Feb 11: LaTeX Tutorial
Feb 18: Second Lab Begins
Mar 04: Third Lab Begins (Mar 18-24 is Spring Break; Lab 3 due before Mar 25)
Mar 25: Fourth Lab Begins
Apr 08: Fifth Lab Begins
Apr 22: Sixth Lab Begins (Due the day after reading period)
Other Useful Texts
Data Analysis
- Press, Teukolsky, Vetterling, Flannery, Numerical Recipes in C (Available online)
- Lupton, "Statistics in Theory and Practice"
LaTeX
- Lamport, LaTeX: A Document Preparation System
- A Not Too Short Introduction to LaTeX: media:not_too_short.pdf
You might also find useful websites from previous years.