Individual skill
pennylane
Cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Enables building and training quantum circuits with automatic differentiation, seamless integration with PyTorch/JAX/TensorFlow, and device-independent execution across simulators and quantum hardware (IBM, Amazon Braket, Google, Rigetti, IonQ, etc.). Use when working with quantum circuits, variational quantum algorithms (VQE, QAOA), quantum neural networks, hybrid quantum-classical models, molecular simulations, quantum chemistry calculations, or any quantum computing tasks requiring gradient-based optimization, hardware-agnostic programming, or quantum machine learning workflows.
cli-tool/components/skills/scientific/pennylane/SKILL.md
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SKILL.mdcore · 7,571 bytesSKILL.mdcore · 7,571 bytesSKILL.mdcore · 7,571 bytesSKILL.mdcore · 7,571 bytesSKILL.mdcore · 7,571 bytesSKILL.mdcore · 7,571 bytesSKILL.mdcore · 7,571 bytesreferences/advanced_features.mddoc · 14,984 bytesreferences/devices_backends.mddoc · 13,079 bytesreferences/getting_started.mddoc · 5,097 bytesreferences/optimization.mddoc · 16,696 bytesreferences/quantum_chemistry.mddoc · 14,438 bytesreferences/quantum_circuits.mddoc · 9,395 bytesreferences/quantum_ml.mddoc · 14,532 bytes
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# PennyLane
## Overview
PennyLane is a quantum computing library that enables training quantum computers like neural networks. It provides automatic differentiation of quantum circuits, device-independent programming, and seamless integration with classical machine learning frameworks.
## Installation
Install using uv:
```bash
uv pip install pennylane
```
