Teaching

10.005: Electricity and Magnetism

An introduction to Electromagnetism. Electrostatics: electric charge, Coulomb’s law, electrostatic field, Gauss’ Law, electric potential difference, electrostatic energy; Electric structure of matter: conductors, capacitors, and dielectrics. Electric Current: current, resistance, Ohm’s Law, and DC circuit theory with capacitors; Magnetostatics: magnetic field, Lorentz Force Law, Biot-Savart Law, and Ampere’s law; Magnetic properties of materials; Time-varying fields: electromotive force, Faraday’s law of induction, inductors, energy stored in magnetic field; Maxwell’s equations: displacement current, Poynting vector, and conservation of energy; Electromagnetic Waves: plane, standing and travelling conditions.

At the end of the term, students will be able to: apply Coulomb’s and Gauss’ law in simple geometries; apply, in simple circuits, Kirchoff’s and Ohm’s law; explain the generation of magnetic fields from currents using Ampere’s law and the Biot-Savart law; explain the concept of inductance; be familiar with Maxwell’s equations; calculate the Poynting vector and be able to explain how it relates to the flow of electromagnetic energy; Snell’s law, polarisation, interference and diffraction of light.

 

30.502: Research Methods

For the most part 30.502 is dedicated to the provision of essential tools for the analysis of empirical data. The first time an experiment is conducted, the results often show little correspondence to the refined value or outcome. Errors and uncertainties need to be minimised through refined  experiments and the remaining errors need to be estimated to add validity to the measurements.

In this course you will learn to analyse errors and uncertainties, use probability distributions to describe uncertainties in data, and evaluate the statistical significance of experimental results.  The course will also teach methods to smooth, fit, and filter data. In the final part of the course we will discuss honesty and ethics in research.

Often survival as a researcher depends on your ability to get the most from your valuable data. In 30.502 will learn how to survive!