Visual quantum mechanics simulations
QMsolve provides intuitive and visually appealing 1D, 2D, and 3D visualizations of quantum mechanical systems, making it an excellent tool for education and gaining physical intuition about quantum phenomena.
Easy to use Python API
The library offers a straightforward, high-level Python interface that allows users to define potentials, set up Hamiltonians, and run simulations with relatively few lines of code, lowering the barrier to entry for quantum mechanics simulations.
Support for time-dependent simulations
QMsolve can compute and animate time-dependent quantum states, allowing users to visualize wavepacket evolution and dynamics, which is particularly valuable for teaching and research demonstrations.
Open source and free
The project is fully open source under a permissive license, making it freely available for students, educators, and researchers without any cost or licensing restrictions.
Multiple dimensionality support
The library supports solving quantum mechanical problems in 1D, 2D, and 3D, giving users flexibility to explore a range of systems from simple particle-in-a-box to more complex three-dimensional potentials.
QMsolve is a solid, open-source Python framework for solving and visualizing quantum mechanical systems numerically, making it a good choice for education and exploratory computational physics rather than production-grade research computing.
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The latest comments about QMsolve on Reddit. This can help you find out how popualr the product is and what people think about it.
Very nice. I just stumbled upon this repo in my free time that I was going to take a look at https://github.com/quantum-visualizations/qmsolve. Also does visualization of Schrodingerโs eqn. Source: over 3 years ago
The simulation was done with qmsolve, a python open-source page we made for visualizing and solving the Schrรถdinger equation. Source: almost 5 years ago
As mentioned in another comment, here's the link to the source code. For the split-step method I found this resource very helpful. For the Crank-Nicholson method I don't have any free resources to share, except for the wikipedia article. There is another method from this article which is easier to implement than split-step or Crank-Nicholson since it doesn't require taking Fourier transforms or solving a system of... Source: almost 5 years ago
These examples are made qmsolve, an open-source python open-source package we are developing for visualizing and solving the Schrรถdinger equation, with which we recently added an efficient time-dependent solver! Source: almost 5 years ago
The Schrรถdinger equation was solved using a Split Fourier method, which is one of the most efficient and accurate methods to solve the time-dependent version. The simulator used is also OC and is posted here. Source: about 5 years ago
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