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Quantum Encoding Atlas

A unified Python library for quantum data encodings. 16 encoding methods, 3 backends, and built-in analysis tools for expressibility, entanglement, and trainability.

Get Started → Explore Encodings GitHub ↗ PyPI ↗
$ pip install encoding-atlas
16
Encodings

Why Quantum Encoding Atlas?

Everything you need to encode classical data into quantum states — from research prototyping to production benchmarking.

16 Encoding Methods

From simple angle rotations to equivariant feature maps, with a consistent API across every encoding.

Browse encodings →
Multi-Backend

Generate circuits for PennyLane, Qiskit, and Cirq from the same encoding object. Switch backends with one parameter.

Quick start →
📊
Analysis Tools

Compute expressibility, entanglement capability, trainability gradients, and resource costs automatically.

Learn more →
🧭
Decision Guide

Not sure which encoding to use? The built-in recommendation engine suggests the best encoding for your problem.

Get recommendations →
📜
Rich Documentation

Every encoding has detailed theory, circuit diagrams, mathematical formulations, and code examples.

Read the concepts →
Benchmarking Suite

Compare encodings head-to-head on real datasets with statistical rigor. Visualize tradeoffs between cost and performance.

Start benchmarking →

How It Works

1
Choose
Pick an encoding from our catalog or let the decision guide recommend one
2
Encode
Create the encoding with a unified API and generate quantum circuits
3
Analyze
Inspect expressibility, entanglement, trainability, and resource costs
4
Compare
Benchmark against alternatives and visualize the tradeoff landscape

Encoding Catalog

16 production-ready encodings covering simple rotations, kernel methods, variational circuits, and symmetry-preserving maps.

Angle Encoding
AngleEncoding
Single-qubit rotations for baselines and shallow circuits
Simulable
Amplitude Encoding
AmplitudeEncoding
Encode data into state amplitudes for qubit-limited regimes
Entangling
IQP Encoding
IQPEncoding
Instantaneous Quantum Polynomial circuits with provable hardness
Entangling
Data Re-uploading
DataReuploading
Universal approximation through repeated data injection
Entangling Variational
ZZ Feature Map
ZZFeatureMap
Pairwise ZZ interactions for quantum kernel methods
Entangling
Hardware Efficient
HardwareEfficientEncoding
Optimized for NISQ hardware connectivity constraints
Entangling Variational
Trainable Encoding
TrainableEncoding
Learnable parameters for task-adapted feature maps
Entangling Variational
SO(2) Equivariant
SO2EquivariantFeatureMap
Preserves continuous rotational symmetry in encoded data
Entangling Equivariant

View all 16 encodings →

Works with your favorite quantum framework
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