ProjectQ - An open source software framework for quantum computing

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ProjectQ is an open source effort for quantum computing.

It features a compilation framework capable of targeting various types of hardware, a high-performance quantum computer simulator with emulation capabilities, and various compiler plug-ins. This allows users to

• run quantum programs on the IBM Quantum Experience chip
• simulate quantum programs on classical computers
• emulate quantum programs at a higher level of abstraction (e.g., mimicking the action of large oracles instead of compiling them to low-level gates)
• export quantum programs as circuits (using TikZ)
• get resource estimates

Examples

First quantum program

.. code-block:: python

from projectq import MainEngine  # import the main compiler engine
from projectq.ops import H, Measure  # import the operations we want to perform (Hadamard and measurement)

eng = MainEngine()  # create a default compiler (the back-end is a simulator)
qubit = eng.allocate_qubit()  # allocate a quantum register with 1 qubit

H | qubit  # apply a Hadamard gate
Measure | qubit  # measure the qubit

eng.flush()  # flush all gates (and execute measurements)
print("Measured {}".format(int(qubit)))  # converting a qubit to int or bool gives access to the measurement result

ProjectQ features a lean syntax which is close to the mathematical notation used in quantum physics. For example, a rotation of a qubit around the x-axis is usually specified as:

.. image:: docs/images/braket_notation.svg :alt: Rx(theta)|qubit> :width: 100px

The same statement in ProjectQ's syntax is:

.. code-block:: python

Rx(theta) | qubit

The |-operator separates the specification of the gate operation (left-hand side) from the quantum bits to which the operation is applied (right-hand side).

Changing the compiler and using a resource counter as a back-end

Instead of simulating a quantum program, one can use our resource counter (as a back-end) to determine how many operations it would take on a future quantum computer with a given architecture. Suppose the qubits are arranged on a linear chain and the architecture supports any single-qubit gate as well as the two-qubit CNOT and Swap operations:

.. code-block:: python

from projectq import MainEngine
from projectq.backends import ResourceCounter
from projectq.ops import QFT
from projectq.setups import linear

compiler_engines = linear.get_engine_list(num_qubits=16,
                                          one_qubit_gates='any',
                                          two_qubit_gates=(CNOT, Swap))
resource_counter = ResourceCounter()
eng = MainEngine(backend=resource_counter, engine_list=compiler_engines)
qureg = eng.allocate_qureg(16)
QFT | qureg
eng.flush()

print(resource_counter)

# This will output, among other information,
# how many operations are needed to perform
# this quantum fourier transform (QFT), i.e.,
#   Gate class counts:
#       AllocateQubitGate : 16
#       CXGate : 240
#       HGate : 16
#       R : 120
#       Rz : 240
#       SwapGate : 262

Running a quantum program on IBM's QE chips

To run a program on the IBM Quantum Experience chips, all one has to do is choose the IBMBackend and the corresponding setup:

.. code-block:: python

import projectq.setups.ibm
from projectq.backends import IBMBackend

token='MY_TOKEN'
device='ibmq_16_melbourne'
compiler_engines = projectq.setups.ibm.get_engine_list(token=token,device=device)
eng = MainEngine(IBMBackend(token=token, use_hardware=True, num_runs=1024,
                            verbose=False, device=device),
                 engine_list=compiler_engines)

Running a quantum program on AQT devices

To run a program on the AQT trapped ion quantum computer, choose the AQTBackend and the corresponding setup:

.. code-block:: python

import projectq.setups.aqt
from projectq.backends import AQTBackend

token='MY_TOKEN'
device='aqt_device'
compiler_engines = projectq.setups.aqt.get_engine_list(token=token,device=device)
eng = MainEngine(AQTBackend(token=token,use_hardware=True, num_runs=1024,
                            verbose=False, device=device),
                 engine_list=compiler_engines)

Classically simulate a quantum program

ProjectQ has a high-performance simulator which allows simulating up to about 30 qubits on a regular laptop. See the simulator tutorial <https://github.com/ProjectQ-Framework/ProjectQ/blob/feature/update-readme/examples/simulator_tutorial.ipynb>__ for more information. Using the emulation features of our simulator (fast classical shortcuts), one can easily emulate Shor's algorithm for problem sizes for which a quantum computer would require above 50 qubits, see our example codes <http://projectq.readthedocs.io/en/latest/examples.html#shor-s-algorithm-for-factoring>__.

The advanced features of the simulator are also particularly useful to investigate algorithms for the simulation of quantum systems. For example, the simulator can evolve a quantum system in time (without Trotter errors) and it gives direct access to expectation values of Hamiltonians leading to extremely fast simulations of VQE type algorithms:

.. code-block:: python

from projectq import MainEngine
from projectq.ops import All, Measure, QubitOperator, TimeEvolution

eng = MainEngine()
wavefunction = eng.allocate_qureg(2)
# Specify a Hamiltonian in terms of Pauli operators:
hamiltonian = QubitOperator("X0 X1") + 0.5 * QubitOperator("Y0 Y1")
# Apply exp(-i * Hamiltonian * time) (without Trotter error)
TimeEvolution(time=1, hamiltonian=hamiltonian) | wavefunction
# Measure the expection value using the simulator shortcut:
eng.flush()
value = eng.backend.get_expectation_value(hamiltonian, wavefunction)

# Last operation in any program should be measuring all qubits
All(Measure) | qureg
eng.flush()

Getting started

To start using ProjectQ, simply follow the installation instructions in the tutorials <http://projectq.readthedocs.io/en/latest/tutorials.html>. There, you will also find OS-specific hints, a small introduction to the ProjectQ syntax, and a few code examples <http://projectq.readthedocs.io/en/latest/examples.html>. More example codes and tutorials can be found in the examples folder here <https://github.com/ProjectQ-Framework/ProjectQ/tree/develop/examples>__ on GitHub.

Also, make sure to check out the ProjectQ website <http://www.projectq.ch>__ and the detailed code documentation <http://projectq.readthedocs.io/en/latest/>__.

How to contribute

For information on how to contribute, please visit the ProjectQ website <http://www.projectq.ch>__ or send an e-mail to [email protected].

Please cite

When using ProjectQ for research projects, please cite

• Damian S. Steiger, Thomas Häner, and Matthias Troyer "ProjectQ: An Open Source Software Framework for Quantum Computing" Quantum 2, 49 (2018) <https://doi.org/10.22331/q-2018-01-31-49>__ (published on arXiv <https://arxiv.org/abs/1612.08091>__ on 23 Dec 2016)
• Thomas Häner, Damian S. Steiger, Krysta M. Svore, and Matthias Troyer "A Software Methodology for Compiling Quantum Programs" Quantum Sci. Technol. 3 (2018) 020501 <https://doi.org/10.1088/2058-9565/aaa5cc>__ (published on arXiv <http://arxiv.org/abs/1604.01401>__ on 5 Apr 2016)

Authors

The first release of ProjectQ (v0.1) was developed by Thomas Häner <http://www.comp.phys.ethz.ch/people/person-detail.html?persid=179208>__ and Damian S. Steiger <http://www.comp.phys.ethz.ch/people/person-detail.html?persid=165677>__ in the group of Prof. Dr. Matthias Troyer <http://www.comp.phys.ethz.ch/people/troyer.html>__ at ETH Zurich.

ProjectQ is constantly growing and many other people <https://github.com/ProjectQ-Framework/ProjectQ/graphs/contributors>__ have already contributed to it in the meantime.

License

ProjectQ is released under the Apache 2 license.