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About
Use cases: design, ml
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What's inside
- Skill name
cirq- Description
- Google quantum computing framework. Use when targeting Google Quantum AI hardware, designing noise-aware circuits, or running quantum characterization experiments. Best for Google hardware, noise modeling, and low-level circuit design. For IBM hardware use qiskit; for quantum ML with autodiff use pennylane; for physics simulations use qutip.
- License
- Apache-2.0
- Metadata
- skill-author: K-Dense Inc.
- Instructions
- 339 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
Files (9)
- SKILL.md
- building.md · references/
- experiments.md · references/
- hardware.md · references/
- noise.md · references/
- simulation.md · references/
- transformation.md · references/
- demo.cpython-313.pyc · scripts/__pycache__/
- demo.py · scripts/
SKILL.md (first lines)
# 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.histogram(key='m')
print(f"θ={theta_val:.2f}: {counts}")
```
## Core Capabilities
### Circuit Building
For comprehensive information about building quantum circuits, including qubits, gates, operations, custom gates, and circuit patterns, see:
- **[references/building.md](references/building.md)** - Complete guide to circuit construction
Common topics:
- Qubit types (GridQubit, LineQubit, NamedQubit)
- Single and two-qubit gates
- Parameterized gates and operations
- Custom gate decomposition
- Circuit organization with moments
- Standard circuit patterns (Bell states, GHZ, QFT)
- Import/export (OpenQASM, JSON)
- Working with qudits and observables
### Simulation
For detailed information about simulating quantum circuits, including exact simulation, noisy simulation, parameter sweeps, and the Quantum Virtual Machine, see:
- **[references/simulation.md](references/simulation.md)** - Complete guide to quantum simulation
Common topics:
- Exact simulation (state vector, density matrix)
- Sampling and measurements
- Parameter sweeps (single and multiple parameters)
- Noisy simulation
- State histograms and visualization
- Quantum Virtual Machine (QVM)
- Expectation values and observables
- Performance optimization
### Circuit Transformation
For information about optimizing, compiling, and manipulating quantum circuits, see:
- **[references/transformation.md](references/transformation.md)** - Complete guide to circuit transformations
Common topics:
- Transformer framework
- Gate decomposition
- Circuit optimization (merge gates, eject Z gates, drop negligible operations)From lamm-mit/scienceclaw, Apache-2.0.
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Signals
- Stars
- 250
- Forks
- 47
- Open issues
- 1
- Last commit (this folder)
- Mar 14, 2026 (7 months ago)
- Last release
- Jun 23, 2026 (4 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- Apache-2.0
- Repository
- github.com/lamm-mit/scienceclaw
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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cirq skill. Agent Mart. https://agentmart.dev/skills/lamm-mit-cirq (last updated 2026-10-24)