Skip to content
Agentmart
Submit a tool
This entry duplicates cirq, which is the one we list in search.

cirq

Google quantum computing framework.

Skill by lamm-mit

IndexedApache-2.0★ 250
Write a review

Chalk Labs

Need help deploying cirq?

Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.

Book a call

Install

Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/lamm-mit-cirq

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

Get the weekly diff

The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.

We use your email only for this newsletter. Privacy

About

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.

Use cases: design, ml

No reviews yet. Installed it? Reviews come from verified installers only. How reviews work

Permissions: not checked yet.

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.

More from lamm-mit/scienceclaw

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
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

Same skill elsewhere

Copies of this SKILL.md published by others; search shows only one of them.

More from lamm-mit

Done for you

Rather not set it up yourself?

Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.

See how we build AI agents →Read the case studies

Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.

launches shipped
50+
launches shipped
media placements
500+
media placements
founders on every account
2
founders on every account

Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block

Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.

Get cirq running in your business

Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.

Goes to the Chalk Labs founders, not the newsletter. Privacy

Need help deploying cirq?

CallGet help
Cite this page

cirq skill. Agent Mart. https://agentmart.dev/skills/lamm-mit-cirq (last updated 2026-10-24)