Module quantum_ml 

Quantum Machine Learning Accelerators

This module provides quantum machine learning acceleration capabilities, integrating variational quantum algorithms, quantum neural networks, and hybrid quantum-classical optimization routines.

Re-exports

pub use classical_integration::*;

pub use gradients::*;

pub use hardware_acceleration::*;

pub use inference::*;

pub use optimization::*;

pub use quantum_neural_networks::*;

pub use training::*;

pub use variational_algorithms::*;

Modules

classical_integration

Classical-Quantum Integration for ML

gradients

Quantum Gradient Computation

hardware_acceleration

Hardware Acceleration for Quantum ML

inference

Quantum Machine Learning Inference Engine

optimization

Quantum Machine Learning Optimization

quantum_neural_networks

Quantum Neural Networks

training

Quantum Machine Learning Training

variational_algorithms

Variational Quantum Algorithms for Machine Learning

Structs

CircuitStructure

Circuit structure representation

InferenceData

Inference data structure

InferenceResult

Inference result

ModelRegistry

Model registry for managing trained models

QMLAccelerator

Quantum Machine Learning Accelerator

QMLConfig

Configuration for QML accelerator

QMLDiagnostics

QML diagnostics

QMLModel

QML model representation

TrainingEpoch

Training epoch information

TrainingStatistics

Training statistics

Enums

GradientMethod

Gradient computation methods

ModelExportFormat

Model export formats

NoiseResilienceLevel

Noise resilience levels

OptimizerType

Types of optimizers for QML

QMLModelType

QML model types

Functions

create_qaoa_accelerator

Create a QAOA accelerator

create_vqc_accelerator

Create a VQC (Variational Quantum Classifier) accelerator