Physics
phys·ics · physis: nature · physika: natural things
Physics is a natural science that studies matter, its motion and behavior through space and time, and the related entities of energy and force.
- State the prediction you're testing before collecting data, not after.
- Report and propagate measurement uncertainty — a result without error bars isn't complete.
- Simple setups (pendulums, circuits, optics) can still produce genuine, checkable results.
- Simulation and modeling are legitimate substitutes when equipment isn't available.
Related areas & concentrations
Physics underpins the other natural sciences. Its neighbors give you applications, tools, and new problems to model.
Related research areas
- Chemistry: atoms, energy, and how matter interacts
- Biology: the physics of living systems, from senses to motion
- Engineering: turning physical principles into working devices
- Mathematics: the language physicists use to build and test models
- Astronomy: applying physics to stars, galaxies, and the universe
- Science & technology studies (STS): how physics shapes and is shaped by society
Sample concentrations
- Physics & biology — biological sensors: how, and how well, do they work?
- Physics & astronomy: relativity, cosmology, and the contents of the universe
- Optical diffraction patterns: what light does when it passes through small openings
- Fourier series and transforms: breaking signals into waves, with applications across physics
Four ways into a question
Most student physics research works in one of these areas. All are reachable with simple equipment, a smartphone, or a simulation.
Motion & Mechanics
Forces, energy, collisions, and oscillations — how and why things move.
How does a pendulum's period change as its swing gets wider?
Waves, Light & Sound
How waves travel, interfere, and diffract — and how we can analyze them.
How does the spacing of a laser's diffraction pattern change with slit width?
Electricity & Magnetism
Charges, currents, circuits, and the fields that connect them.
How does a magnet's field strength fall off with distance?
Astrophysics & Modern Physics
Relativity, cosmology, and the physics of very small and very large scales.
Can you estimate the Hubble constant from public galaxy data?
Turning an interest into a question
A topic isn't a research question. Narrow to one system, one variable you change and one you measure, and a prediction you can test.
Start from a phenomenon you can observe
A swinging object, a rainbow of light, a magnet pulling filings — something you can set up or find data for.
Pick your variables
Choose one thing to change, one thing to measure, and everything you'll hold constant.
State a prediction from theory
Use an equation or model to predict the result before you measure anything.
Check feasibility and precision
Can you measure accurately enough with your equipment to tell whether the prediction holds?
Methods & where to look
Pair a method you can carry out safely with the data, tools, and literature physicists actually use.
Common methods
- Tabletop experiments: pendulums, circuits, optics, and magnets.
- Smartphone sensors: accelerometers, light, and sound meters as lab tools.
- Simulation & modeling: coding a model and comparing it to data.
- Public data analysis: astronomical or particle-physics datasets.
- Signal analysis: using Fourier transforms to study waves and sound.
Lasers, high voltage, and strong magnets need adult supervision and proper safety gear.
Where to find data
- Simulations: PhET Interactive Simulations from the University of Colorado.
- Sensor apps: phyphox for turning a phone into a measurement device.
- Open data: NASA's data portals and CERN Open Data.
- Literature: the physics section of arXiv and The Physics Teacher.
Python with NumPy and Matplotlib is enough for most data analysis and modeling.
Measuring with uncertainty
Every measurement has error. Three habits make your results trustworthy — and comparable to theory.
Repeat
Take several measurements of each point. The spread tells you how precise your data really is.
Quantify
Estimate the uncertainty of every measurement and carry it through your calculations to error bars.
Compare
Ask whether theory and data agree within your uncertainty — and explain any gap honestly.
Cite every dataset, simulation, and source, and record your setup carefully so others could repeat it.