Cirq was developed by the Google AI Quantum Team, and the public alpha was announced at the International Workshop on Quantum Software and Quantum Machine Learning on July 18, 2018.^[2] A demo by QC Ware showed an implementation of QAOA solving an example of the maximum cut problem being solved on a Cirq simulator.^[3]

Quantum programs in Cirq are represented by "Circuit" which is made up of a series of "Moments" representing slices of quantum gates that should be applied at the same time.^[4] The programs can be executed on local simulators^[5] or against hardware supplied by IonQ, Pasqal,^[6] Rigetti, and Alpine Quantum Technologies^[7]

The following example shows how to create and measure a Bell state in Cirq.

import cirq

# Pick qubits
qubit0 = cirq.GridQubit(0, 0)
qubit1 = cirq.GridQubit(0, 1)

# Create a circuit
circuit = cirq.Circuit(
    cirq.H(qubit0),
    cirq.CNOT(qubit0, qubit1),
    cirq.measure(qubit0, key="m0"),
    cirq.measure(qubit1, key="m1")
)

Printing the circuit displays its diagram

print(circuit)
# prints
# (0, 0): ───H───@───M('m0')───
#                │
# (0, 1): ───────X───M('m1')───

Simulating the circuit repeatedly shows that the measurements of the qubits are correlated.

simulator = cirq.Simulator()
result = simulator.run(circuit, repetitions=5)
print(result)
# prints
# m0=11010
# m1=11010

OpenFermion is a library that compiles quantum simulation algorithms to Cirq.^[2]

TensorFlow Quantum is an extension of TensorFlow that allows TensorFlow to be used to explore hybrid classical-quantum machine learning algorithms.^[8]

ReCirq is a repository of research projects done using Cirq.^[9]

Qsim is a high performance wave function simulator that leverages gate fusing, AVS/FMA instructions, and OpenMP to achieve fast simulation rates. Qsimcirq allows one to use qsim from within Cirq.^[10]