Experimental Physics
How physicists design experiments, build and understand their apparatus, analyse data and report results with honest uncertainties: why measurement is the test of theory, precision versus accuracy, random versus systematic error and a pendulum whose small-angle formula hides a bias; experimental design with variables, controls, dimensional analysis, scaling, log-log plots, lever arm, error budgets and blind analysis; Type A and Type B uncertainties, analytic and Monte Carlo propagation and the weighted mean; weighted least squares from maximum likelihood, parameter covariance, chi-squared and p-values, residual plots and model comparison with the Akaike information criterion; circuits, Thévenin equivalents, complex impedance, instrument loading, Wheatstone bridges, calibration and traceability, and grounding; RC filters, Bode plots, op-amps with negative feedback, the gain-bandwidth product and Johnson, shot and flicker noise; analogue-to-digital conversion, the sampling theorem, aliasing and lock-in detection of signals buried in noise; the classic experiments of Thomson's e/m and Millikan's oil drops, the photoelectric effect and Planck's constant, Franck and Hertz, Michelson interferometry, the speed of light and grating spectroscopy of hydrogen; laboratory safety with high voltage, lasers, radiation and cryogens, research integrity and reproducibility; and a capstone on writing the lab report and paper and on peer review, all supported by runnable Python examples.
PHYS-397 Year 3 3 credits 12 lessons · 4 h 23 min ▶ Video lessons coming soon
Offered by HSM University · Physics
This is the Canadian version of this course. See the American version.
What you'll learn
- Explain how measurement tests theory, distinguish precision from accuracy and random from systematic error, and recognize how a systematic effect can dominate a precise result.
- Design an experiment by identifying variables and controls, using dimensional analysis and scaling, choosing the range of data and estimating the number of repeats needed.
- Estimate Type A and Type B uncertainties, propagate them analytically and by Monte Carlo simulation, and combine measurements with a weighted mean.
- Fit models to data by weighted least squares, obtain parameter uncertainties, test the fit with chi-squared, residuals and p-values, and compare models with the Akaike information criterion.
- Analyse DC and AC circuits with Thévenin equivalents and complex impedance, predict and correct instrument loading, and use bridges and bench instruments correctly.
- Design RC filters and op-amp amplifiers, interpret Bode plots and the gain-bandwidth product, and calculate Johnson and shot noise and signal-to-noise ratios.
- Digitize signals without aliasing, choose sampling rates and anti-aliasing filters, and explain and simulate lock-in detection of signals buried in noise.
- Analyse the Thomson e/m and Millikan oil-drop experiments, extract e/m and the elementary charge from data, and evaluate questions of data selection.
- Determine Planck's constant and a work function from photoelectric data and an excitation energy from Franck–Hertz data, with honest uncertainties.
- Use interferometers and grating spectrometers to measure wavelengths and distances, explain historical measurements of the speed of light, and calibrate optical instruments.
- Apply the hierarchy of controls to electrical, laser, radiation, cryogenic and pressure hazards, and practise research integrity, including corrections for multiple comparisons and reproducible methods.
- Write a laboratory report or paper with correct structure, rounding and uncertainty statements, clear figures and quantitative comparisons, and describe how peer review works.
Course content
12 lessons · 4 h 23 min total · final exam
- 1 Why experimental physics: measurement as the test of theory 23 min · quiz
- 2 Designing an experiment: variables, controls and scaling 22 min · quiz
- 3 Uncertainty I: random and systematic errors, propagation 21 min · quiz
- 4 Uncertainty II: fitting, chi-squared and model comparison 22 min · quiz
- 5 Electronics for physicists I: circuits, impedance and measurement instruments 22 min · quiz
- 6 Electronics for physicists II: amplifiers, filters, op-amps and signal-to-noise 22 min · quiz
- 7 Data acquisition, sampling and lock-in detection 22 min · quiz
- 8 Classic experiments I: Millikan oil drop and e/m 22 min · quiz
- 9 Classic experiments II: photoelectric effect, Franck–Hertz and Planck's constant 21 min · quiz
- 10 Classic experiments III: interferometry, speed of light and spectroscopy 21 min · quiz
- 11 Lab safety, ethics and reproducibility 23 min · quiz
- 12 Capstone: writing up results — the lab report, the paper and peer review 22 min · quiz
- E Final exam 20 questions
Requirements
Recommended background. You can start any course at any time.
Description
How physicists design experiments, build and understand their apparatus, analyse data and report results with honest uncertainties: why measurement is the test of theory, precision versus accuracy, random versus systematic error and a pendulum whose small-angle formula hides a bias; experimental design with variables, controls, dimensional analysis, scaling, log-log plots, lever arm, error budgets and blind analysis; Type A and Type B uncertainties, analytic and Monte Carlo propagation and the weighted mean; weighted least squares from maximum likelihood, parameter covariance, chi-squared and p-values, residual plots and model comparison with the Akaike information criterion; circuits, Thévenin equivalents, complex impedance, instrument loading, Wheatstone bridges, calibration and traceability, and grounding; RC filters, Bode plots, op-amps with negative feedback, the gain-bandwidth product and Johnson, shot and flicker noise; analogue-to-digital conversion, the sampling theorem, aliasing and lock-in detection of signals buried in noise; the classic experiments of Thomson's e/m and Millikan's oil drops, the photoelectric effect and Planck's constant, Franck and Hertz, Michelson interferometry, the speed of light and grating spectroscopy of hydrogen; laboratory safety with high voltage, lasers, radiation and cryogens, research integrity and reproducibility; and a capstone on writing the lab report and paper and on peer review, all supported by runnable Python examples.
Part of the Science stream, typically taken in year 3.