# Qutip

Quantum physics simulation library for open quantum systems.

- Repository: https://github.com/zLanqing/codex-claude-academic-skills (5550 stars)
- Category: Writing
- License: BSD-3-Clause license
- Last updated: 2026-05-14
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add zLanqing/codex-claude-academic-skills --skill qutip -g -a claude-code -y`
Codex: `npx skills add zLanqing/codex-claude-academic-skills --skill qutip -g -a codex -y`
Cursor: `npx skills add zLanqing/codex-claude-academic-skills --skill qutip -g -a cursor -y`
Gemini CLI: `npx skills add zLanqing/codex-claude-academic-skills --skill qutip -g -a gemini-cli -y`

## Description

Quantum physics simulation library for open quantum systems. Use when studying master equations, Lindblad dynamics, decoherence, quantum optics, or cavity QED. Best for physics research, open system dynamics, and educational simulations. NOT for circuit-based quantum computing, use qiskit, cirq, or pennylane for quantum algorithms and hardware execution.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# QuTiP: Quantum Toolbox in Python

## Overview

QuTiP provides comprehensive tools for simulating and analyzing quantum mechanical systems. It handles both closed (unitary) and open (dissipative) quantum systems with multiple solvers optimized for different scenarios.

## Installation

```bash
uv pip install qutip
```

Optional packages for additional functionality:

```bash
# Quantum information processing (circuits, gates)
uv pip install qutip-qip

# Quantum trajectory viewer
uv pip install qutip-qtrl
```

## Quick Start

```python
from qutip import *
import numpy as np
import matplotlib.pyplot as plt

# Create quantum state
psi = basis(2, 0)  # |0⟩ state

# Create operator
H = sigmaz()  # Hamiltonian

# Time evolution
tlist = np.linspace(0, 10, 100)
result = sesolve(H, psi, tlist, e_ops=[sigmaz()])

# Plot results
plt.plot(tlist, result.expect[0])
plt.xlabel('Time')
plt.ylabel('⟨σz⟩')
plt.show()
```

## Core Capabilities

### 1. Quantum Objects and States

Create and manipulate quantum states and operators:

```python
# States
psi = basis(N, n)  # Fock state |n⟩
psi = coherent(N, alpha)  # Coherent state |α⟩
rho = thermal_dm(N, n_avg)  # Thermal density matrix

# Operators
a = destroy(N)  # Annihilation operator
H = num(N)  # Number operator
sx, sy, sz = sigmax(), sigmay(), sigmaz()  # Pauli matrices

# Composite systems
psi_AB = tensor(psi_A, psi_B)  # Tensor product
```

**See** `references/core_concepts.md` for comprehensive coverage of quantum objects, states, operators, and tensor products.

### 2. Time Evolution and Dynamics

Multiple solvers for different scenarios:

```python
# Closed systems (unitary evolution)
result = sesolve(H, psi0, tlist, e_ops=[num(N)])

# Open systems (dissipation)
c_ops = [np.sqrt(0.1) * destroy(N)]  # Collapse operators
result = mesolve(H, psi0, tlist, c_ops, e_ops=[num(N)])

# Quantum trajectories (Monte Carlo)
result = mcsolve(H, psi0, tlist, c_ops, ntraj=500, e_ops=[num(N)])
```

The rest: https://github.com/zLanqing/codex-claude-academic-skills/blob/HEAD/scientific-toolkit-skill/references/scientific-skills/qutip/SKILL.md