Quantum Encoding Atlas
The comprehensive library for quantum data encodings in machine learning
Documentation | Website | Tutorials | API Reference | PyPI
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
| 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.
Documentation
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.
1 maintainer
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file encoding_atlas-1.0.0.tar.gz.
File metadata
- Download URL: encoding_atlas-1.0.0.tar.gz
- Upload date:
- Size: 1.5 MB
- Tags: Source
- Uploaded using Trusted Publishing? Yes
- Uploaded via:
twine/6.1.0 CPython/3.13.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
18a7ec704db5f03c1f9885d0956585a684d76e73fd4f9ab8e4bb213d390e4f2d
|
|
| MD5 |
fd2f8d522b7af382ac5e5a5b379b0d20
|
|
| BLAKE2b-256 |
3482fc5596b010d29138b312329a7644c4c07f237fe0cbce75e32dbd2dd2171c
|
Provenance
The following attestation bundles were made for encoding_atlas-1.0.0.tar.gz:
Publisher:
publish-pypi.yml on encoding-atlas/quantum-encoding-atlas
-
Statement:
-
Statement type:
https://in-toto.io/Statement/v1 -
Predicate type:
https://docs.pypi.org/attestations/publish/v1 -
Subject name:
encoding_atlas-1.0.0.tar.gz -
Subject digest:
18a7ec704db5f03c1f9885d0956585a684d76e73fd4f9ab8e4bb213d390e4f2d - Sigstore transparency entry: 1078001012
- Sigstore integration time:
-
Permalink:
encoding-atlas/quantum-encoding-atlas@f76037fb7e706b9ab0569edf116bf48842ff138d -
Branch / Tag:
refs/tags/v1.0.0 - Owner: https://github.com/encoding-atlas
-
Access:
public
-
Token Issuer:
https://token.actions.githubusercontent.com -
Runner Environment:
github-hosted -
Publication workflow:
publish-pypi.yml@f76037fb7e706b9ab0569edf116bf48842ff138d -
Trigger Event:
push
-
Statement type:
File details
Details for the file encoding_atlas-1.0.0-py3-none-any.whl.
File metadata
- Download URL: encoding_atlas-1.0.0-py3-none-any.whl
- Upload date:
- Size: 399.1 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? Yes
- Uploaded via:
twine/6.1.0 CPython/3.13.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
edbd00c932793abbd261d612f52f4390ffc747f2f684227b38b0f51e4764a09b
|
|
| MD5 |
ac9c0a531b12876a981d7f66a197c012
|
|
| BLAKE2b-256 |
8d003698238cf9976e3bd741fde2db85ab8d886edf01d91339edb34de2cadb96
|
Provenance
The following attestation bundles were made for encoding_atlas-1.0.0-py3-none-any.whl:
Publisher:
publish-pypi.yml on encoding-atlas/quantum-encoding-atlas
-
Statement:
-
Statement type:
https://in-toto.io/Statement/v1 -
Predicate type:
https://docs.pypi.org/attestations/publish/v1 -
Subject name:
encoding_atlas-1.0.0-py3-none-any.whl -
Subject digest:
edbd00c932793abbd261d612f52f4390ffc747f2f684227b38b0f51e4764a09b - Sigstore transparency entry: 1078001022
- Sigstore integration time:
-
Permalink:
encoding-atlas/quantum-encoding-atlas@f76037fb7e706b9ab0569edf116bf48842ff138d -
Branch / Tag:
refs/tags/v1.0.0 - Owner: https://github.com/encoding-atlas
-
Access:
public
-
Token Issuer:
https://token.actions.githubusercontent.com -
Runner Environment:
github-hosted -
Publication workflow:
publish-pypi.yml@f76037fb7e706b9ab0569edf116bf48842ff138d -
Trigger Event:
push
-
Statement type:
