ProjectQ - An open source software framework for quantum computing

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, AQT devices, AWS Braket, Azure Quantum, or IonQ service provided devices
• 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

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(f"Measured {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:

The same statement in ProjectQ's syntax is:

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:

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:

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:

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,
)

Running a quantum program on a AWS Braket provided device

To run a program on some of the devices provided by the AWS Braket service, choose the AWSBraketBackend. The currend devices supported are Aspen-8 from Rigetti, IonQ from IonQ and the state vector simulator SV1:

from projectq.backends import AWSBraketBackend

creds = {
    'AWS_ACCESS_KEY_ID': 'your_aws_access_key_id',
    'AWS_SECRET_KEY': 'your_aws_secret_key',
}

s3_folder = ['S3Bucket', 'S3Directory']
device = 'IonQ'
eng = MainEngine(
    AWSBraketBackend(
        use_hardware=True,
        credentials=creds,
        s3_folder=s3_folder,
        num_runs=1024,
        verbose=False,
        device=device,
    ),
    engine_list=[],
)

python3 -m pip install projectq[braket]

cd /path/to/projectq/source/code
python3 -m pip install -ve .[braket]

Running a quantum program on a Azure Quantum provided device

To run a program on devices provided by the Azure Quantum.

Use AzureQuantumBackend to run ProjectQ circuits on hardware devices and simulator devices from providers IonQ and Quantinuum.

from projectq.backends import AzureQuantumBackend

azure_quantum_backend = AzureQuantumBackend(
    use_hardware=False, target_name='ionq.simulator', resource_id='<resource-id>', location='<location>', verbose=True
)

python3 -m pip install projectq[azure-quantum]

cd /path/to/projectq/source/code
python3 -m pip install -ve .[azure-quantum]

Running a quantum program on IonQ devices

To run a program on the IonQ trapped ion hardware, use the IonQBackend and its corresponding setup.

Currently available devices are:

• ionq_simulator: A 29-qubit simulator.
• ionq_qpu: A 11-qubit trapped ion system.

import projectq.setups.ionq
from projectq import MainEngine
from projectq.backends import IonQBackend

token = 'MY_TOKEN'
device = 'ionq_qpu'
backend = IonQBackend(
    token=token,
    use_hardware=True,
    num_runs=1024,
    verbose=False,
    device=device,
)
compiler_engines = projectq.setups.ionq.get_engine_list(
    token=token,
    device=device,
)
eng = MainEngine(backend, 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 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.

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:

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 expectation 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. There, you will also find OS-specific hints, a small introduction to the ProjectQ syntax, and a few code examples. More example codes and tutorials can be found in the examples folder here on GitHub.

Also, make sure to check out the ProjectQ website and the detailed code documentation.

How to contribute

For information on how to contribute, please visit the ProjectQ website or send an e-mail to [email protected].

Please cite

When using ProjectQ for research projects, please cite

• Damian S. Steiger, Thomas Haener, and Matthias Troyer "ProjectQ: An Open Source Software Framework for Quantum Computing" Quantum 2, 49 (2018) (published on arXiv on 23 Dec 2016)
• Thomas Haener, Damian S. Steiger, Krysta M. Svore, and Matthias Troyer "A Software Methodology for Compiling Quantum Programs" Quantum Sci. Technol. 3 (2018) 020501 (published on arXiv on 5 Apr 2016)

Authors

The first release of ProjectQ (v0.1) was developed by Thomas Haener and Damian S. Steiger in the group of Prof. Dr. Matthias Troyer at ETH Zurich.

ProjectQ is constantly growing and many other people have already contributed to it in the meantime.

License

ProjectQ is released under the Apache 2 license.