Modeling the Electric Field Due to Parallel Plates Using Python
Model electric fields between parallel plates using Python and 20,000 points, avoiding calculus for a clear visualization.
Phasor Addition of Waves with Python
Animate wave interference using phasors and Python, exploring amplitude addition through rotating vectors.
Solution for the 1D Infinite Square Well in Quantum Mechanics
Solve the Schrödinger equation for a one-dimensional infinite square well, exploring quantum mechanics fundamentals and wave function behavior.
Quantum Mechanics: Using the Shooting Method and Python to Solve the 1D Square Well
Solve the 1D infinite square well numerically using Python and the shooting method, exploring an alternative approach to quantum mechanics problem-solving.
Solving Schrödinger's Equation as an Eigenvalue Problem with Numpy
Explore numerical solutions to the 1D infinite square well using Python's NumPy library and the finite difference method for Schrödinger's equation.
1D Square Well with Step Potential - Shooting Method
Solve 1D square well with step potential numerically using Python's shooting method. Explore infinite potential walls and half-step potential.
1D Square Well with Step Potential - Finite Difference Solution
Explore numerical solutions for 1D square well with step potential using finite difference method in Python. Learn eigenvalue problem solving and result normalization.
A Better Spring-Ball Model for Bouncing - Now with More Springs
Explore an improved spring-ball model for bouncing, featuring multiple interconnected balls and springs for enhanced simulation accuracy.
Quantum Mechanics: Wave Function for a Particle on a Ring
Explore wave functions for particles confined to rings, including normalized solutions and Python plotting code.
How to Solve Relative Velocity Problems in Physics
Master relative velocity concepts in physics through practical problem-solving. Tackle train, boat, and airplane scenarios to understand vector-based calculations and real-world applications.
Using a Bunch of Balls to Model the Ideal Gas Law in Python
Model the ideal gas law with bouncing balls in Python and calculate pressure and temperature.
Modeling the Cavendish Experiment with Python
Model the Cavendish experiment using Python to explore gravitational forces between masses. Learn to simulate and analyze this classic physics experiment through coding.
Building a Better Ball Collision Model for Solar System Simulation in Python
Improve ball collision modeling for a flat solar system simulation, focusing on conservation of momentum and angular momentum.
Electric Field due to a Dipole - Far Field Approximation
Derive the far field approximation for an electric dipole, exploring its mathematical foundations and practical applications in electromagnetic theory.
Numerical Line Integrals with Python
Explore numerical line integrals using Python to calculate work done in force fields. Gain practical coding skills for solving complex physics problems.
Electric Field due to a Charged Ring - Python Calculation and Derivation
Derive the electric field of a uniform charged ring using Python and analytical methods. Compare numerical and theoretical approaches.
Which String Breaks First? Modeling a Physics Demo with Python
Model a physics demo of two strings supporting a mass using Python to determine which string breaks first when pulled.
Matter and Interactions: Magnetic Field - Chapter 17 Summary
Explore magnetic fields, currents, and dipoles through interactive demos and key concepts in electromagnetism.
Two Ways to Calculate the Change in Potential Near a Dipole
Explore two methods for calculating potential change near a dipole: using electric field expression and numerical computation with Python.
Magnetic Field due to a Loop of Current - Python Calculation Included
Derive the magnetic field from a current loop and perform numerical calculations using Python, enhancing understanding of electromagnetic principles.
Finding the Value of Pi from a Random Walk Using Python
Explore Python coding to calculate pi using random walks, from 1D to 3D simulations. Enhance mathematical understanding through practical programming.