2015
Welcome to Advanced Physics Lab 2014!
Under Construction (Oct 2014)
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 times are Monday 10:00-12:50 and 1:30-4:20.
The 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 safety instructions at all times. 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
After taking the . For this class there will be three steps:
- Process the raw data sets into a reduced dataset with errors
- Interpret the reduced data in the context of a physical model
- 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.
Report
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) |
Grading
Grades breakdown as
- 80% Labs
- 20% Preparation (weekly updates and submission of drafts)
Each lab grade will be divided into three equal sections: experiment execution (20 pts), data analysis (20 pts), and presentation (20 pts).
Collaboration Policy
Execution of the experiment may be done in collaboration with others. Furthermore, students are encouraged to discuss experiments, analysis, and other course related issues with their peers (and, of course, with the instructors). However, each person should carry out their own data analysis (e.g., no code sharing), produce their own plots, and write their own report.
Ethics
The strength of the university depends on academic and personal integrity. In this course, you must be honest and truthful. Ethical violations include cheating on exams, plagiarism, reuse of assignments, improper use of the Internet and electronic devices, unauthorized collaboration, alteration of graded assignments, forgery and falsification, lying, facilitating academic dishonesty, and unfair competition. For more info: http://e-catalog.jhu.edu/undergrad-students/student-life-policies/.
Work Submission and Late Reports
Final Reports
Work should be submitted by email in PDF format to the professor (marriage@pha.jhu.edu) and TA (ianderso@pha.jhu.edu). To help us organize, the subject of the email should be "Advanced Lab: [last name]" where [last name] is your last name.
The reports are due by midnight on the day before the next lab begins. The grade of late reports will be multiplied by exp(-(days late)/7), where days late can be fractional (starting from midnight).
In this class it's crucial not to procrastinate.
All reports will be returned within 2 weeks from the submission date.
Participation
Update material (plots etc) for discussion should be uploaded to the shared drive before class.
As required, you should submit drafts of your report with introduction and procedure after the first week and through data analysis by the end of the second week of the lab. Drafts should be submitted in the same way described above for the final report, though the filename should indicate that it's a draft to avoid confusion.
Anatomy of an Experiment
Experiment Execution. The first step in executing an experiment is to have a good idea of the phenomenon being measured -- the reason why you're doing the experiment. Then you need to have a thorough knowledge of the experimental apparatus. With this preparation you will be able to take data. But obtaining measured values is not enough. You need both values and errors. You need to conduct the experiment in a way that estimates systematic errors and statistical errors. Systematic errors can be checked for by conducting the experiment in more than one way that should, e.g., give the same result and checking for discrepancies. Statistical errors may be obtained by repeating the experiment and evaluating the sample variance of the data or there might be an analytic expectation for the statistical error, as in the case of counting experiments.
Data Analysis and Interpretation. The input to data analysis consists of measured values and their errors. You then fit this data with some physical model. If the fit is "good", then you can believe the best-fit model parameters and associated model parameter errors. These model parameters tell you something about the physical world.
Presentation Lab reports constitute the language of the course. The sections of a report are
- Abstract -- Summarily say the aim of the experiment and what you used to measure the phenomenon. Then quote your result which is usually some physical parameter with errors.
- Introduction -- Describe qualitatively the phenomenon being measured and the history of the measurements and theory behind the current experiment (seminal works cited etc). This should not contain much information about what you did in the experiment-- just roundly what you aim to do. The intro is mainly useful background and can be relatively brief.
- Theory -- Introduce quantitatively the physical effect that you're trying to probe. Introduce equations.
- Experiment Description and Data -- Describe the experiment setup and procedure. Also describe the data and errors. In particular you'll likely be giving the averages of your many samples collected and errors on those average. These should appear in a plot and, when possible, a table.
- Data Analysis -- Derive a theoretical interpretation from the data propagating errors to theoretical model parameters etc. If appropriate, discuss the "goodness" of the model fit.
- Discussion -- Interpret your results and discuss what may have gone wrong if, e.g., the fit in the Data Analysis section was not good.
- Conclusion -- A short section where you summarize the paper. This section could possibly include future directions to take the work.
Lab Report Specifications
The reports are to be created on a computer with computer generated graphics, plots, etc. The document preparation system for the reports is LaTeX. The computers in the PUC lab have various installations of LaTeX editors/compilers. You can also download freeware for your personal computers. I think the online editor "ShareLaTeX" is pretty good.
The lab reports should have an abstract, an introduction, a theory section, description of the experiment (apparatus and procedure) and reduced data and errors, description of the analysis of the data, discussion of results, a conclusion, and a bibliography.
The format should have 1" margins with no smaller than 11 point font. The maximum number of pages is 6, including figures and tables. Be concise.
A standard strategy is to create your figures first in order to guide the body of the text.
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
You might also find useful websites from previous years.
Tutorials: In particular, see the previous year's tutorials.
And of course... Wikipedia!