qmsolve
QuTiP
qmsolve | QuTiP | |
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32 | 6 | |
748 | 1,591 | |
0.0% | 1.6% | |
0.0 | 9.8 | |
over 1 year ago | 1 day ago | |
Python | Python | |
BSD 3-clause "New" or "Revised" License | BSD 3-clause "New" or "Revised" License |
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qmsolve
- QMsolve: A Python module for solving and visualizing the Schrödinger equation
- Anyone has a relatively "simple" program for solving 2D time-dependent Schrödinger equations?
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I recently started playing around with Schrödinger's equation. And after a lot of tinkering I got a simulation to work! My first experiment: an electron versus a wall.
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 Schrodinger’s eqn
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Quantum resonant tunneling simulation. Despite having less energy than the lower, the upper electron has a higher chance of passing through the barriers by exciting the resonant eigenstate of the nanostructure!
In the visualization, the color hue shows the phase of the wave function of the electron ψ(x,y, t), while the opacity shows the amplitude. The transmittance spectrum, computed by taking the Fourier transform of the incident and transmitted wavefunction, can be found in this plot.
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Visualization of the quantum energy eigenstates of an electron confined in a pumpkin-shaped potential immersed in a uniform, strong magnetic field
The simulation was done with qmsolve, a python open-source page we made for visualizing and solving the Schrödinger equation.
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Quantum mechanical simulation of the cyclotron motion of an electron confined under a strong, uniform magnetic field, made by solving the Schrödinger equation. As time passes, the wavepacket spatial distribution disperses until it finally reaches a stationary state with a fixed radial length!
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 equations. You may find the stability conditions to be too limiting when it comes to performance, at least when compared to the other methods.
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Simulation of a particle scattering in a Sierpinski carpets potential fractals (Schrödinger equation version). When the Sierpinski order is enough large (level 3) to make the separation of the blocks smaller than the particle wavelength, it is unable to penetrate it.
The simulator used can be found here.
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Quantum particles scattering in Sierpinski carpets potential fractals, made solving the Schrödinger equation [OC]
The Schrödinger 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.
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Quantum Physics with Python: A Package for Solving and Visualizing the Schrödinger Equation
Also, the script that returns this visualization can be found here.
QuTiP
- Single Photon Source Simulation in Qiskit?
- Qutip: Simulate Quantum Systems in Python
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Which programming language is best to simulate a quantum computer?
I think Python would be a more mainstream choice and so you'll find modules like qiskit or [qutip(https://qutip.org/) already exist and will make life easier.
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How much would I benefit if I started working on my coding skills before uni?
If you want to be a bit more physics-focused in your coding, it might help to dig up a course or textbook on numerical methods in physics. Being able to numerically solve differential equations is probably the most generally applicable skill in physics. Machine learning methods are pretty ''hot right now'' and might be fun to have a look into. And for quantum technology in particular, you might enjoy having a look at some python packages like Kwant for quantum transport, QuTiP for quantum dynamics and Qiskit for quantum computing. You won't understand the physics for this for quite some time, they might help serve as a bit of inspiration and an indication as to what physicists can use programming for.
- QuTiP (Quantum Toolbox in Python) open-source internship (deadline: 17th Apr 2022) with Google Summer of Code
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Would it be bad to simulate a time-dependent Hamiltonian by evaluating it at discrete t_i and implementing H(t_i) for however many t_i I want?
If you're talking about simulating a hamiltonian on a regular computer then you may want to check out Qutip. It's a python module where a lot of this stuff has already been worked out, including simulating time dependent hamiltonians. I did an undergrad project on QC and this helped me get past a lot of the roadblocks like this and freed up more time to learn about the field, it also becomes a useful toy to play around with and get an intuition for a lot of stuff.
What are some alternatives?
SchrodingerWellPython - 2D 3D Time independent FDM Schrodinger equation solver for arbitrary shape of well
qiskit - Qiskit is an open-source SDK for working with quantum computers at the level of extended quantum circuits, operators, and primitives.
PythonCompphys - Some python workbooks with various topics from Computational Physics
SimPy
catsim - Computerized Adaptive Testing Simulator
salabim - salabim - discrete event simulation in Python
chaos-theory - Playing around with chaos theory simulations. Creating equilibrium graphs and visualizing the logistic maps.
octadist - A tool for calculating distortion parameters in coordination complexes.
ElectronVisualized - Public Archive: Beautiful and Elegant Quantum Mechanics Visualization.
Colour - Colour Science for Python
ObsPy - ObsPy: A Python Toolbox for seismology/seismological observatories.
Cirq - A python framework for creating, editing, and invoking Noisy Intermediate Scale Quantum (NISQ) circuits.