There are a lot of tools for making advanced quantum mechanical computations, but very few tools for visualizing them. This is the reason why we created QMsolve: To provide a tool for students for experimenting and making the subject more accessible. In a nutshell, what it's represented in the presentation video is the probability cloud of an electron confined in a potential representing a diatomic molecule. This is the solution of the following equation (Schrödinger equation): H ψ = E ψ where H is the Hamiltonian, ψ is the wave function, and E is its energy. The wavefunctions ψ that satisfy the condition from above, are called eigenstates. They represent the possible states of a particle confined in a potential whose observable energy is constant. The eigenstates represented were computed with QMsolve with high accuracy (less than 1% of relative error) by diagonalizing 10^6 x 10^6 Hamiltonian matrix discretized using finite differences. All of this procedure is nicely encapsulated and can be easily reproduced with QMsolve minimalist object-oriented interface.

QMsolve

Visualizing quantum physics with Python

Visualizing quantum physics with Python