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# abp 0.4.22 |
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Python port of Anders and Briegel' s [method](https://arxiv.org/abs/quant-ph/0504117) for fast simulation of Clifford circuits. |
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Python port of Anders and Briegel' s [method](https://arxiv.org/abs/quant-ph/0504117) for fast simulation of Clifford circuits. You can read the full documentation [here](https://peteshadbolt.co.uk/abp/). |
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## Documentation |
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You can read the full documentation [here](https://peteshadbolt.co.uk/abp/). You can also build it locally using Sphinx with `make doc`. |
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## Installation |
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It's easiest to install with `pip`: |
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```shell |
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@@ -19,42 +20,3 @@ $ python setup.py develop --user |
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$ python setup.py develop --user --prefix= # Might be required on OSX |
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``` |
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## Visualization |
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`abp` comes with a tool to visualize graph states in a web browser. It uses a client-server architecture. |
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First, run `abpserver` in a terminal: |
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```shell |
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$ abpserver |
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Listening on port 5000 for clients.. |
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``` |
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Then browse to `http://localhost:5001/`. Alternatively, `abpserver -v` will automatically pop a browser window. |
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Now, in another terminal, use `abp.fancy.GraphState` to run a Clifford circuit: |
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```python |
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>>> from abp.fancy import GraphState |
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>>> g = GraphState(10) |
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>>> for i in range(10): |
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... g.act_hadamard(i) |
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... |
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>>> g.update() |
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>>> for i in range(9): |
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... g.act_cz(i, i+1) |
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... |
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>>> g.update() |
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``` |
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And you should see a visualization of the state. |
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## Testing |
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`abp` has a bunch of tests. You can run them all with `nose`: |
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```shell |
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$ nosetests |
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53 tests run in 39.5 seconds (53 tests passed) |
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``` |
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Currently I use some reference implementations of `chp` and `graphsim` which you won't have installed, so some tests will be skipped. That's expected. |
