2015
Welcome to Advanced Physics Lab 2015!
Instructors
Professor: Tobias Marriage (marriage@pha.jhu.edu)
Teaching Assistant: Devin Crichton (dcrichto@pha.jhu.edu)
Lab Guru: Steve Wonnell (wonnell@pha.jhu.edu)
The Advanced Lab Summary
In this class, you will conduct experiments, analyze data, and write up your results in reports.
Classes
The class times are Monday 10:00-12:50 and 1:30-4:20.
The class location is the Physics Undergraduate Computer lab (PUClab). A PUCLab login for the computers may also be useful. Access to the lab and computers is managed by Steve Wonnel.
Laptops should be brought to class.
The first half of class will be devoted to lecture and discussion of that week's topics. The first half of the 10am and 1:30am classes will be similar.
The second half of class will be devoted to work with hands on help from instructors.
Experiments
Brownian Motion (BM): The goal of this experiment is to estimate the Boltzmann constant using a measurement of the Brownian motion of microscopic spheres.
Speed of Light (SoL): In this experiment you use the classic "time of flight" measurement by Foucault to estimate the speed of light.
Galactic Rotation (GR): In this experiment you'll use a radio telescope to measure the rotational velocities in the Galactic disk and judge whether the data better fits a model with or without dark matter.
Raw Data Sets
Each student will collect their own data. For SoL, two students will need to collaborate, but each should obtain their own dataset.
Initial submission of data sets for evaluation occurs in the first week or two of the experiment.
Safety
Use your common sense in all situations. In these labs you'll encounter manageable hazards. Follow the instructions carefully. Food and drink are not allowed near the labs. Safety also follows from orderliness: please keep (and leave) the lab in an organized state. When in doubt ask an instructor.
Analysis
Analysis is the evaluation of data towards an interpretation that accounts for errors in the data. Roughly speaking there will be three analysis steps in this class:
- Process the raw data sets into a reduced dataset with errors,
- Interpret the reduced data in the context of a physical model and
- Assess the impact of systematic errors.
Tool for Analysis
The tool we will use for the analysis is the Python programming language and its numerical and scientific computing modules.
You will submit an IPython Notebook with your report.
Reports
For each experiment you will write a report.
The reports will be presented in a standard scientific format with use of figures and tables.
More information can be found in the report checklist.
Feedback
The professor will read and grade the reports. For the first two reports, students will meet one-on-one with the professor to discuss their work.
Tool for Reports
The document preparation system for reports is LaTeX.
You can also download LaTeX freeware for your personal computers (e.g., TeXworks on all platforms, TeXShop for Mac, TeXnicCenter for Windows).
Good online LaTeX editors also exist (e.g., ShareLaTeX, papeeria).
The computers in the PUC lab have various installations of LaTeX editors/compilers.
Readings
Lectures will be based on
Bevington & Robinson, Data Reduction and Error Analysis for the Physical Sciences, 3rd Edition, McGraw-Hill, ISBN 0-07-247227-8, 2003
I will have a couple class copies that you can read in the lab. Please keep these in the PUCLab.
Schedule
Date | 1st Half of Class | Reading | 2nd Half of Class and Homework |
---|---|---|---|
Jan 26 | Class Overview; Experiments, Measurement & Errors 1 | Bev. Ch1 | Install Ipython Notebook; Install LaTeX or use On-line LaTeX editor |
media:LaTeX_Example.txt, media:Python_Example.txt | |||
Feb 02 | Measurement and Errors 2; BM Introduction; LaTeX Tutorial | Bev. Ch 1&2 | Submit 1st BM Photoset by Sun Feb 08 11:59 pm (Email TA) |
media:AdvLabBrownianMotion2015.pdf | |||
Feb 09 | Probability Distributions; BM Analysis Discussion; Python Tutorial 1 | Bev. Ch 2 | Start analysis & writing initial sections of report |
media:Python_Tutorial_1_Data.txt | |||
Feb 16 | Propagation of Errors | Bev. Ch 3 | Working on Full Report |
Feb 23 | Method of Maximum Likelihood | Bev. Ch 4 | BM Report Due Friday Feb 27 5pm (Email Prof) |
Mar 2 | Student's t and Chi-sq Distributions; SoL Introduction | Bev. Ch 6 | Submit 1st SoL Data by Sun Mar 8 11:59 pm (GoogleForm); Schedule BM Report Reviews |
media:SpeedOfLightOverview2015 .pdf | |||
Mar 9 | Linear Least Squares 1; SoL Analysis Discussion; Python Tutorial 2 | Bev. Ch 6 | BM Report Reviews |
Mar 17-21 Spring Break | |||
Mar 23 | Review Line Fitting | Bev. Ch 7 | BM Report Reviews |
Mar 30 | General Linear Least Squares | SoL Report Due Friday April 3 5pm (Email Prof) | |
Apr 6 | Nonlinear Fitting 1; GR Introduction | Bev. Ch 8 | Schedule SoL Report Reviews |
media:GRIntroduction2015.pdf | |||
Apr 13 | Nonlinear Fitting 2; Python Tutorial 3 | Bev. Ch 8 | Submit 1st GR Data by Sun Apr 19 11:59 pm (GoogleForm); SoL Report Reviews |
media:Python_Tutorial_3_Data.txt | |||
Apr 20 | Experiment/Analysis Topic Review | - | SoL Report Reviews |
Apr 27 | Reserved for Overflow | - | GR lab due on Friday May 1 5pm (Email Prof) |
Other Useful Resources
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
Tutorials
In particular, see the previous year's tutorials.
And of course... Wikipedia!