CirQ is an open-source quantum computing library developed in Python by Google, which allows building, optimizing, simulating, and executing quantum circuits. More specifically, CirQ allows simulating circuits on specific qubit configurations, which can optimize a circuit for a certain qubit architecture. Information on the library's features is available in the documentation and on CirQ's GitHub. Like Snowflurry, CirQ can be used to execute quantum circuits on the MonarQ quantum computer.

Installation¶

The CirQ quantum computer simulator is available on all our clusters. The Python programming language must be loaded before accessing it. It is preferable to work in a Python virtual environment.

module load python/3.11
virtualenv --no-download --clear ~/ENV && source ~/ENV/bin/activate
pip install --no-index --upgrade pip
pip install --no-index cirq==1.4.1
python -c "import cirq"
pip freeze > cirq-1.4.1-reqs.txt

The last command creates a file named cirq-1.4.1-reqs.txt, which you can reuse in a job script, as described below.

Running on a Cluster¶

::: sh title="script.sh"

!/bin/bash¶

SBATCH --account=def-someuser # specify your account name¶

SBATCH --time=00:15:00 # modify if needed¶

SBATCH --cpus-per-task=1 # modify if needed¶

SBATCH --mem-per-cpu=1G # modify if needed¶

Load module dependencies.¶

module load StdEnv/2023 gcc python/3.11

Generate the virtual environment in $SLURM_TMPDIR.¶

virtualenv --no-download ${SLURM_TMPDIR}/env source ${SLURM_TMPDIR}/env/bin/activate

Install CirQ and its dependencies.¶

pip install --no-index --upgrade pip pip install --no-index --requirement ~/cirq-1.4.1-reqs.txt

Modify the CirQ program.¶

python cirq_example.py

You can then [submit your job to the scheduler](../../running-jobs/running_jobs.md).

## Example Usage: Bell States
Bell states are the simplest states that allow explaining both superposition and entanglement on qubits.
The [CirQ](https://github.com/quantumlib/Cirq) library allows building a Bell state as follows:
```python
import cirq
from cirq.contrib.svg import SVGCircuit
from cirq import H, CNOT

qubits = cirq.LineQubit.range(2)
circuit = cirq.Circuit(H.on(qubits[0]), CNOT.on(qubits[0], qubits[1]))
circuit.append(cirq.measure(qubits, key='m'))
SVGCircuit(circuit)

This code constructs and displays a circuit that prepares a Bell state. The H gate (Hadamard gate) creates an equal superposition of |0⟩ and |1⟩ on the first qubit, while the CNOT gate (controlled-X gate) creates entanglement between the two qubits. This Bell state is thus an equal superposition of the |00⟩ and |11⟩ states. Simulating this circuit using CirQ allows visualizing the results. In this diagram, the integer 3 represents the |11⟩ state, since 3 is written as 11 in binary. ```python import matplotlib.pyplot as plt s = cirq.Simulator().run(circuit, repetitions=1000) counts = s.histogram(key='m') cirq.plot_state_histogram(counts, plt.subplot())