2014: Difference between revisions

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===Readings===
===Readings===


I will lecture weekly from the classic Bevington text, which is mainly on data analysis. In principle you can work from lecture notes, but you will get more out of the class if you read the text as well. I will have a couple class copies that you can read in the lab.
I will lecture weekly from the classic Bevington text, which is mainly on data analysis. In principle you can work from lecture notes, but you will get more out of the class if you read the text and take your own notes as well.


Bevington & Robinson, ''Data Reduction and Error Analysis for the Physical Sciences'', 3rd Edition, McGraw-Hill, ISBN 0-07-247227-8, 2003
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===
===Schedule===

Revision as of 00:34, 27 January 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

You will complete experiments over the course of the semester, each taking three weeks. The first experiment will start in the second week of the course. The planned experiments we will work through are the following.

  1. Brownian Motion: The goal of this experiment is to estimate the Boltzmann constant using a measurement of the brownian motion of microscopic spheres.
  2. Speed of Light: In this experiment you use the classic Foucault spinning mirror measurement to estimate the speed of light.
  3. Single Photon Interference: This experiment explores the interference of quantum wave functions.
  4. 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 beginning data analysis being taught in lectures and readings during the first half of the course. These should help you ramp up in terms of your familiarity with data and errors. They are also very cool measurements of two of the most important numbers in physics!

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. These are new experiments that we've developed over the last two years and think are particularly exciting.

Readings

I will lecture weekly from the classic Bevington text, which is mainly on data analysis. In principle you can work from lecture notes, but you will get more out of the class if you read the text and take your own notes as well.

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

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 Updates on Exp. 1
Feb 17 Estimates of Mean and Errors Bev. Ch 4 Updates on Exp. 1; Exp. 1 Report Draft Due
Feb 24 Monte Carlo Techniques Bev. Ch 5 Exp. 1 Report Due, Start Exp. 2
Mar 3 Linear Least Squares 1 Bev. Ch 6 Updates on Exp. 2
Mar 10 Linear Least Squares 2 Bev. Ch 7 Updates on Exp. 2
Mar 17-21 Spring Break
Mar 24 Nonlinear Fitting 1 Bev. Ch 8 Exp. 2 Due, Start Exp. 3
Mar 31 Nonlinear Fitting 2 Bev. Ch 9 Updates on Exp. 3
Apr 7 Maximum Likelihood Bev. Ch 10 Updates on Exp. 3
Apr 14 Testing the Fit Bev. Ch 11 Exp. 3 Due, Start Exp. 4
Apr 21 TBD - Updates on Exp. 4
Apr 28 TBD - Updates on Exp. 4

Other Useful Texts

Data Analysis

  • Press, Teukolsky, Vetterling, Flannery, Numerical Recipes in C (Available online)
  • Lupton, "Statistics in Theory and Practice"

LaTeX

You might also find useful websites from previous years.