Overview

The Quantum Encoding Atlas is the definitive open-source resource for understanding, comparing, and selecting quantum data encodings for machine learning applications.

Features

• 📊 16 Encoding Methods — Comprehensive implementations of all major quantum data encodings
• 🔀 Multi-Framework Support — Works seamlessly with PennyLane, Qiskit, and Cirq
• 📈 Analysis Tools — Compute expressibility, entanglement capability, and trainability
• 🧪 Benchmarking Framework — Systematic comparison infrastructure
• 🧭 Decision Guide — Evidence-based encoding recommendations
• 📚 Extensive Documentation — Tutorials, API docs, and theoretical background

Installation

pip install encoding-atlas

With optional backends:

# With Qiskit support
pip install encoding-atlas[qiskit]

# With Cirq support
pip install encoding-atlas[cirq]

# With all backends
pip install encoding-atlas[all]

# Development installation
pip install encoding-atlas[dev]

Quick Start

from encoding_atlas import IQPEncoding, AngleEncoding
from encoding_atlas.analysis import compute_expressibility
import numpy as np

# Create encodings
iqp = IQPEncoding(n_features=4, reps=2)
angle = AngleEncoding(n_features=4, rotation='Y')

# Generate circuits (PennyLane by default)
X = np.random.randn(10, 4)
circuit = iqp.get_circuit(X[0])

# Analyze properties
print(f"IQP qubits: {iqp.n_qubits}")
print(f"IQP depth: {iqp.depth}")
print(f"IQP expressibility: {compute_expressibility(iqp, n_samples=500):.4f}")

# Get encoding recommendation
from encoding_atlas.guide import recommend_encoding

rec = recommend_encoding(
    n_features=4,
    n_samples=500,
    task='classification',
    hardware='simulator'
)
print(f"Recommended: {rec.encoding_name}")
print(f"Reason: {rec.explanation}")

Supported Encodings

See the full encoding list for details.

Documentation

• Installation Guide
• Quick Start Tutorial
• Encoding Selection Guide
• API Reference

Citation

If you use this library in your research, please cite:

@software{Mishra2026encoding,
  title={Quantum Encoding Atlas: A Comprehensive Library for Quantum Data Encodings},
  author={Mishra, Ashutosh},
  year={2026},
  doi={10.5281/zenodo.18780936},
  url={https://doi.org/10.5281/zenodo.18780936},
  version={1.0.0}
}

Contributing

We welcome contributions! Please see our Contributing Guide for details.

License

This project is licensed under the MIT License - see the LICENSE file for details.