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Python interface for the Quantum Exact Simulation Toolkit (QuEST)

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pyQuEST

A Python interface for the Quantum Exact Simulation Toolkit (QuEST) written mainly in Cython.

Getting started

After cloning the repository

$ git clone -b develop --recursive --shallow-submodules https://github.com/rrmeister/pyQuEST

it is recommended to create a virtual environment, e.g. with venv, we'll call it quantum-playground.

$ python3 -m venv quantum-playground
$ source quantum-playground/bin/activate

By default, pyQuEST will use double precision for its floating point variables, have multithreading enabled, but GPU acceleration and distributed computing disabled. These settings can be changed in the dictionary quest_config at the top of setup.py before compiling and installing the package.

After setting the compile options as required, the package can be compiled and installed using pip3.

$ pip3 install ./pyQuEST

For this last step — depending on your system — you might have to separately install the Python development headers, usually called python3-dev or python3-devel. Check your distribution for details if the installer cannot find Python.h.

Usage

After successful installation, we can start a Python interpreter — with e.g. ipython or python3 — and import pyQuEST to have a look at the environment it is running in.

Make sure to not launch your interpreter from within the pyQuEST folder, as the pyquest source directory would take precedence over the installed package and cause the import to fail.

In [1]: import pyquest

In [2]: pyquest.env
Out[2]: QuESTEnvironment(cuda=False, openmp=False, mpi=False, num_threads=1, num_ranks=1, precision=2)

The QuESTEnvironment class is automatically instantiated once upon module import and never needs to be called by the user. It contains internals and can return information about the execution environment, as above. If you changed the options in setup.py, make sure these are reflected in this output. If they are not, this indicates a problem during compiling.

Example

The most important classes are Register representing a quantum register, and the operators which can be applied to it. Let's create such a register with 3 qubits and look at its contents.

In [3]: from pyquest import Register

In [4]: from pyquest.unitaries import *

In [5]: reg = Register(3)

In [6]: reg[:]
Out[6]: array([1.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j])

Like in QuEST, the state is automatically initialised to the all-zero product state. To apply some gates to it, first import some unitaries and the Circuit class.

In [7]: from pyquest.unitaries import H, X, Ry

In [8]: from pyquest import Circuit

The operators are constructed from their classes with their target qubits, then any additional parameters (like a rotation angle), and then the control qubits as a keyword-only argument, e.g. Ry(0, .2, controls=[1]) creates a rotation operator about the y-axis of the Bloch sphere by 0.2 radians on qubit 0, controlled by qubit 1. A single operator can be applied to a register reg with reg.apply_operator(X(1)). To apply multiple operators at once, first collect them into a Circuit.

In [9]: circ = Circuit([H(0), X(2, controls=[0]), Ry(1, .23, controls=[2])])

In [10]: reg.apply_circuit(circ)

In [11]: reg[:]
Out[11]:
array([0.70710678+0.j, 0.        +0.j, 0.        +0.j, 0.        +0.j,
       0.        +0.j, 0.70243619+0.j, 0.        +0.j, 0.08113816+0.j])

Multiplying two registers together will return their inner product. For example, the expectation value of X(1) is

In [12]: temp = Register(copy_reg=reg)

In [13]: temp.apply_operator(X(1))

In [14]: reg * temp
Out[14]: (0.11398876176759418+0j)

A measurement can be performed with

In [15]: from pyquest.gates import M

In [16]: reg.apply_operator(M(1))
Out[16]: [0]

Remember that measurements are destructive.

In [17]: reg[:]
Out[17]:
array([0.70944592+0.j, 0.        +0.j, 0.        +0.j, 0.        +0.j,
       0.        +0.j, 0.70475988+0.j, 0.        +0.j, 0.        +0.j])

A register can also be directly modified, but may then end up in an invalid state if not properly normalised.

In [18]: reg[:] = 0

In [19]: reg[:]
Out[19]: array([0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j])

In [20]: reg[4] = 1j

In [21]: reg[:]
Out[21]: array([0.+0.j, 0.+0.j, 0.+0.j, 0.+0.j, 0.+1.j, 0.+0.j, 0.+0.j, 0.+0.j])

For further details on which operators are available and all methods of Register and Circuit, for now check out the documentation in the source files.

Development

If you want to contribute to the project or just play around with the source, you can use an editable install

$ pip3 install -e .

but this temporarily re-installs the build requirements every time the project is compiled and clutters the pyquest source directory with build artifacts. It is therefore a good idea to simply install the build requirements manually

$ pip3 install -r build_requirements.txt

and then call

$ python3 setup.py build

to build pyQuEST in the _skbuild/<os_id>/cmake-install/pyquest folder, or use

$ python3 setup.py install

to install the package without telling pip about it. This is really only recommended in a virtual environment.

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