| name | cirq |
| description | Cirq is Google Quantum AI's open-source framework for designing, simulating, and running quantum circuits on quantum computers and simulators. |
| type | skill |
| created | 2026-02-27T00:00:00.000Z |
| domain | productivity |
| category | developer-experience |
| risk | unknown |
| source | community |
| tags | ["skill","productivity","developer-experience","cirq"] |
Cirq - Quantum Computing with Python
Cirq is Google Quantum AI's open-source framework for designing, simulating, and running quantum circuits on quantum computers and simulators.
When to Use
- You are designing, simulating, or executing quantum circuits with the Cirq ecosystem.
- You need Google Quantum AI-style primitives, parameterized circuits, or integrations like
cirq-google and cirq-ionq.
- You are prototyping or teaching quantum workflows in Python and want concrete circuit examples.
Installation
uv pip install cirq
For hardware integration:
uv pip install cirq-google
uv pip install cirq-ionq
uv pip install cirq-aqt
uv pip install cirq-pasqal
uv pip install azure-quantum cirq
Quick Start
Basic Circuit
import cirq
import numpy as np
q0, q1 = cirq.LineQubit.range(2)
circuit = cirq.Circuit(
cirq.H(q0),
cirq.CNOT(q0, q1),
cirq.measure(q0, q1, key='result')
)
print(circuit)
simulator = cirq.Simulator()
result = simulator.run(circuit, repetitions=1000)
print(result.histogram(key='result'))
Parameterized Circuit
import sympy
theta = sympy.Symbol('theta')
circuit = cirq.Circuit(
cirq.ry(theta)(q0),
cirq.measure(q0, key=)
)
sweep = cirq.Linspace(, start=, stop=*np.pi, length=)
results = simulator.run_sweep(circuit, params=sweep, repetitions=)
params, result (sweep, results):
theta_val = params[]
counts = result.histogram(key=)
()