Open Source Quantum ML
QuantumEncoding Atlas

The definitive open-source resource for quantum data encodings in machine learning

16 Encodings3 FrameworksDecision GuideMIT Licensed
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Everything you need for quantum encoding

A complete toolkit for exploring, implementing, and comparing quantum data encoding strategies.

16 Encodings

From angle rotations to symmetry-equivariant feature maps. Unified API, comprehensive coverage.

3 Frameworks

PennyLane, Qiskit, Cirq. Write once, switch backends with a single parameter.

Deep Analysis

Expressibility, entanglement capability, trainability, and resource costs — all quantified.

Decision Guide

Evidence-based recommendations tailored to your data, hardware, and constraints.

Get Started in Three Steps

From installation to analysis in under a minute.

1

Install

bash
$ pip install encoding-atlas
2

Choose Your Encoding

python
from encoding_atlas import IQPEncoding

encoding = IQPEncoding(n_features=4, reps=2)
print(f"Qubits: {encoding.n_qubits}")
3

Analyze & Compare

python
from encoding_atlas.analysis import compute_expressibility

score = compute_expressibility(
    encoding, n_samples=1000
)
print(f"Expressibility: {score:​.4f}")
0Encoding Methods
0Quantum Frameworks
0Analysis Dimensions
0Encoding Categories
MITOpen Source License

Ready to find the right encoding?

Explore all 16 quantum data encodings, compare their properties, or let our decision guide recommend one for your specific use case.

MIT LicensedPython 3.9+Framework Agnostic