Applying Technology to Collect Data in Physics (DP IB Physics): Revision Note

Applying technology to collect data in physics

• Modern physics relies heavily on technology to collect, process, and analyse data

• This allows scientists to spot patterns (trends) and make predictions using large amounts of data

• These large data sets can come from experiments or from tools like sensors, existing databases, or computer models and simulations

Collecting data using data loggers and sensors

Sensors

• Sensors detect changes in physical quantities (such as force, temperature, voltage, or light intensity) and convert them into electrical signals

• Examples of sensors in physics include:

  • Light gates

    • Measures time intervals very precisely

    • e.g. using two light gates to determine the speed of a trolley or a falling object

  • Motion sensors

    • Used to detect the position or velocity of moving objects

  • Force sensors

    • Measures the magnitude of forces acting over short time intervals

  • Temperature probes

    • Used to measure the temperature of a substance

    • e.g. monitoring the rate of heating or cooling in thermal experiments

  • Pressure sensors

    • Used to measure the pressure of gases or liquids

  • Digital ammeters, voltmeters and multimeters

    • Records electrical quantities in circuits, e.g. potential difference, current, and resistance

Use of a data logger and sensor

Data loggers

• The electrical signal from a sensor can be converted into a digital signal by a data logger or directly to a computer to be stored and analysed

• Data loggers quickly and accurately record measurements

• Results can often be shown in real time on a screen

• The data can then be

  • stored digitally on a computer

  • processed to work out averages and generate graphs

  • analysed to calculate gradients or uncertainties

• The advantages of using sensors and data loggers include:

  • Allows for more precise results than manual timing or measurement

  • Reduces human error (e.g. reaction times, subjectivity)

  • Data can be collected over very short or very long periods of time e.g. hourly readings of temperature over several days

  • A large amount of data can be collected

  • Data can be stored and analysed digitally

  • Increased safety in experiments with potential risks, such as measuring the temperature of boiling water

Data logging in physics

Identifying and extracting data from databases

• A database is a structured collection of data, so it can be searched, sorted, filtered and analysed quickly

• Data in a database can be any type of data, including text, images, videos, and audio

• Databases that you may come across during your studies include:

  • Material properties such as density, resistivity, or specific heat capacity

  • Astronomical databases containing information about stars, galaxies, and exoplanets

  • Particle physics data collected from large experiments such as CERN

Generating data from models and simulations

• A model is a simplified version of reality

• Models in physics are often used to represent and explain various phenomena, structures, and interactions at the atomic and molecular level 

  • The model can then be analysed or tested to learn more about how the system works and to predict how the system might respond to change

• Simulations are a valuable tool used by physicists to explore scenarios that may not be feasible or safe to investigate in a physical laboratory

• The accuracy and reliability of the simulation depend on the quality of the models and assumptions used to create them

• Simulations allow you to alter variables in a particular scenario and allow you to see the effect of these changes, for example:

  • Simulations of gas particles allow you to explore how gases behave

  • The simulation uses models of gas laws to predict how the system will respond to changes in temperature, pressure and volume, which are controlled by the user

  • Data can be collected from these predictions of behaviour

The PhET simulations website

Photo credit: PhET (opens in a new tab)

Carrying out image analysis and video analysis of motion

• Motion can be studied using a suitable video camera or a smartphone

  • Objects are filmed in front of a measurement grid or ruler

  • The video can be played frame-by-frame or analysed with software that tracks positions

  • From the recorded positions and time intervals, velocity and acceleration can be calculated

• This method is especially useful for studying fast-moving objects or complex motion where direct measurement is difficult

  • For example, freefall, projectile motion, collisions, oscillations

• The same can also be achieved by taking photos in quick succession of objects in motion

• For image or video analysis, the following must be known

  • The frames per second - used to determine the time taken

  • The scale of the frame - used to determine the distance, usually by placing a ruler in the shot with the object

Using video techniques to investigate motion