|
12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152535455565758596061626364 |
- # abp
-
- 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/).
-
- ![demo](examples/demo.gif)
-
- ## Installation
-
- It's easiest to install with `pip`:
-
- ```shell
- $ pip install --user abp
- ```
-
- Or clone and install in `develop` mode:
-
- ```shell
- $ git clone https://github.com/peteshadbolt/abp.git
- $ cd abp
- $ python setup.py develop --user
- $ python setup.py develop --user --prefix= # Might be required on OSX
- ```
-
- ## Visualization
-
- `abp` comes with a tool to visualize graph states in a web browser. It uses a client-server architecture.
-
- First, run `abpserver` in a terminal:
-
- ```shell
- $ abpserver
- Listening on port 5000 for clients..
- ```
- Then browse to `http://localhost:5001/`. Alternatively, `abpserver -v` will automatically pop a browser window.
-
- Now, in another terminal, use `abp.fancy.GraphState` to run a Clifford circuit:
-
- ```python
- >>> from abp.fancy import GraphState
- >>> g = GraphState(range(10))
- >>> for i in range(10):
- ... g.act_hadamard(i)
- ...
- >>> g.update()
- >>> for i in range(9):
- ... g.act_cz(i, i+1)
- ...
- >>> g.update()
- ```
-
- And you should see a visualization of the state:
-
- ![demo](examples/viz.png)
-
- ## Testing
-
- `abp` has a bunch of tests. You can run them all with `nose`:
-
- ```shell
- $ nosetests
- 53 tests run in 39.5 seconds (53 tests passed)
- ```
-
- 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.
|