← ClaudeAtlas

cirqlisted

Quantum computing framework for building, simulating, optimizing, and executing quantum circuits. Use this skill when working with quantum algorithms, quantum circuit design, quantum simulation (noiseless or noisy), running on quantum hardware (Google, IonQ, AQT, Pasqal), circuit optimization and compilation, noise modeling and characterization, or quantum experiments and benchmarking (VQE, QAOA, QPE, randomized benchmarking).
aiskillstore/marketplace · ★ 334 · Web & Frontend · score 80
Install: claude install-skill aiskillstore/marketplace
# 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. ## Installation ```bash uv pip install cirq ``` For hardware integration: ```bash # Google Quantum Engine uv pip install cirq-google # IonQ uv pip install cirq-ionq # AQT (Alpine Quantum Technologies) uv pip install cirq-aqt # Pasqal uv pip install cirq-pasqal # Azure Quantum uv pip install azure-quantum cirq ``` ## Quick Start ### Basic Circuit ```python import cirq import numpy as np # Create qubits q0, q1 = cirq.LineQubit.range(2) # Build circuit circuit = cirq.Circuit( cirq.H(q0), # Hadamard on q0 cirq.CNOT(q0, q1), # CNOT with q0 control, q1 target cirq.measure(q0, q1, key='result') ) print(circuit) # Simulate simulator = cirq.Simulator() result = simulator.run(circuit, repetitions=1000) # Display results print(result.histogram(key='result')) ``` ### Parameterized Circuit ```python import sympy # Define symbolic parameter theta = sympy.Symbol('theta') # Create parameterized circuit circuit = cirq.Circuit( cirq.ry(theta)(q0), cirq.measure(q0, key='m') ) # Sweep over parameter values sweep = cirq.Linspace('theta', start=0, stop=2*np.pi, length=20) results = simulator.run_sweep(circuit, params=sweep, repetitions=1000) # Process results for params, result in zip(sweep, results): theta_val = params['theta'] counts = result.histog