The comprehensive library for quantum data encodings in machine learning
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The Quantum Encoding Atlas is the definitive open-source resource for understanding, comparing, and selecting quantum data encodings for machine learning applications.
- 📊 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
pip install encoding-atlasWith 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]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}")| Category | Encodings |
|---|---|
| Amplitude-based | AmplitudeEncoding |
| Angle-based | AngleEncoding (RX/RY/RZ), HigherOrderAngleEncoding |
| Basis | BasisEncoding |
| Entangling | IQPEncoding, ZZFeatureMap, PauliFeatureMap |
| Advanced | DataReuploading, HardwareEfficientEncoding, QAOAEncoding, HamiltonianEncoding |
| Symmetry & Equivariant | SymmetryInspiredFeatureMap, SO2EquivariantFeatureMap, CyclicEquivariantFeatureMap, SwapEquivariantFeatureMap |
| Trainable | TrainableEncoding |
See the full encoding list for details.
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}
}We welcome contributions! Please see our Contributing Guide for details.
This project is licensed under the MIT License - see the LICENSE file for details.