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- .. abp documentation master file, created by
- sphinx-quickstart on Sun Jul 24 18:12:02 2016.
- You can adapt this file completely to your liking, but it should at least
- contain the root `toctree` directive.
-
-
- ``abp``
- ===============================
-
- This is the documentation for ``abp``. It's a work in progress.
-
- .. toctree::
- :hidden:
- :maxdepth: 2
-
- modules
-
-
- ``abp`` is a Python port of Anders and Briegel' s `method <https://arxiv.org/abs/quant-ph/0504117>`_ for fast simulation of Clifford circuits.
- That means that you can make quantum states of thousands of qubits, perform any sequence of Clifford operations, and measure in any of :math:`\{\sigma_x, \sigma_y, \sigma_z\}`.
-
- Installing
- ----------------------------
-
- You can install from ``pip``:
-
- .. code-block:: bash
-
- $ pip install --user abp==0.5.0
-
- Alternatively, clone from the `github repo <https://github.com/peteshadbolt/abp>`_ and run ``setup.py``:
-
- .. code-block:: bash
-
- $ git clone https://github.com/peteshadbolt/abp
- $ cd abp
- $ python setup.py install --user
-
- If you want to modify and test ``abp`` without having to re-install, switch into ``develop`` mode:
-
- .. code-block:: bash
-
- $ python setup.py develop --user
-
- Quickstart
- ----------------------------
-
- Let's make a new ``GraphState`` object with a register of three qubits:
-
- >>> from abp import GraphState
- >>> g = GraphState(3)
-
- All the qubits are initialized by default in the :math:`|+\rangle` state::
-
- >>> print g.to_state_vector()
- |000❭: √1/8 + i √0
- |100❭: √1/8 + i √0
- |010❭: √1/8 + i √0
- |110❭: √1/8 + i √0
- |001❭: √1/8 + i √0
- |101❭: √1/8 + i √0
- |011❭: √1/8 + i √0
- |111❭: √1/8 + i √0
-
- We can also check the stabilizer tableau::
-
- >>> print g.to_stabilizer()
- 0 1 2
- ---------
- X
- X
- X
-
- Or look directly at the vertex operators and neighbour lists::
-
- >>> print g
- 0: IA -
- 1: IA -
- 2: IA -
-
- This representation might be unfamiliar. Each row shows the index of the qubit, then the **vertex operator**, then a list of neighbouring qubits. To understand vertex operators, read the original paper by Anders and Briegel.
-
- Let's act a Hadamard gate on the zeroth qubit -- this will evolve qubit ``0`` to the :math:`H|+\rangle = |1\rangle` state::
-
- >>> g.act_hadamard(0)
- >>> print g.to_state_vector()
- |000❭: √1/4 + i √0
- |010❭: √1/4 + i √0
- |001❭: √1/4 + i √0
- |011❭: √1/4 + i √0
- >>> print g
- 0: YC -
- 1: IA -
- 2: IA -
-
- And now run some CZ gates::
-
- >>> g.act_cz(0,1)
- >>> g.act_cz(1,2)
- >>> print g
- 0: YC -
- 1: IA (2,)
- 2: IA (1,)
- >>> print g.to_state_vector()
- |000❭: √1/4 + i √0
- |010❭: √1/4 + i √0
- |001❭: √1/4 + i √0
- |011❭: -√1/4 + i √0
-
- Tidy up a bit::
-
- >>> g.del_node(0)
- >>> g.act_hadamard(0)
- >>> print g.to_state_vector()
- |00❭: √1/2 + i √0
- |11❭: √1/2 + i √0
-
- Cool, we made a Bell state. Incidentally, those those state vectors and stabilizers are genuine Python objects, not just stringy representations of the state::
-
- >>> g = abp.GraphState(2)
- >>> g.act_cz(0, 1)
- >>> g.act_hadamard(0)
- >>> psi = g.to_state_vector()
- >>> print psi
- |00❭: √1/2 + i √0
- |11❭: √1/2 + i √0
-
- ``psi`` is a state vector -- i.e. it is an exponentially large vector of complex numbers. We can still run gates on it::
-
- >>> psi.act_cnot(0, 1)
- >>> psi.act_hadamard(0)
- >>> print psi
- |00❭: √1 + i √0
-
- But these operations will be very slow. Let's have a look at the stabilizer tableau::
-
- >>> tab = g.to_stabilizer()
- >>> print tab
- 0 1
- ------
- Z Z
- X X
- >>> print tab.tableau
- {0: {0: 3, 1: 3}, 1: {0: 1, 1: 1}}
- >>> print tab[0, 0]
- 3
-
- Quantum mechanics is nondeterminstic. However, it's often useful to get determinstic behaviour for testing purposes. You can force ``abp`` to behave determinstically by setting::
-
- >>> abp.DETERMINSTIC = True
-
-
- Visualization
- ----------------------
-
- You can visualize states in 3D using the tool at `https://abv.peteshadbolt.co.uk/`. At some point I will merge the code for that server into this repo.
-
- In order to visualize states you must give each node a position attribute::
-
- >>> g.add_qubit(0, position={"x": 0, "y":0, "z":0}, vop="identity")
- >>> g.add_qubit(0, position={"x": 1, "y":0, "z":0}, vop="identity")
-
- There's a utility function in ``abp.util`` to construct those dictionaries::
-
- >>> from abp.util import xyz
- >>> g.add_qubit(0, position=xyz(0, 0, 0), vop="identity")
- >>> g.add_qubit(1, position=xyz(1, 0, 0), vop="identity")
-
- Then it's really easy to get a 3D picture of the state::
-
- >>> g.push()
- Shared state to https://abv.peteshadbolt.co.uk/lamp-moon-india-leopard
-
- That's a secret URL that you can use to collaboratively edit and view graph states in the browser. There are only a few billion such URLs so it should not be considered extremely secure. If you want, you can also load an existing state::
-
- >>> g = GraphState()
- >>> g.pull("https://abv.peteshadbolt.co.uk/lamp-moon-india-leopard")
- >>> g.show()
-
- GraphState API
- -------------------------
-
- The ``abp.GraphState`` class is the main interface to ``abp``.
-
- .. autoclass:: abp.GraphState
- :special-members: __init__
- :members:
-
- .. _clifford:
-
- The Clifford group
- ----------------------
-
- .. automodule:: abp.clifford
-
- |
-
- The ``clifford`` module provides a few useful functions:
-
- .. autofunction:: abp.clifford.use_old_cz
- :noindex:
-
- Testing
- ----------------------
-
- ``abp`` has a bunch of tests. It tests against all sorts of things, including the circuit model, Anders & Briegels' original code, Scott Aaronson's ``chp``, and common sense. You can run all the tests using ``nose``::
-
- $ 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.
-
- Reference
- ----------------------------
-
- More detailed docs are available here:
-
- * :ref:`genindex`
- * :ref:`modindex`
- * :ref:`search`
-
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