Module quantum_neural_odes 

Quantum Neural Ordinary Differential Equations (QNODEs)

This module implements quantum neural ODEs, extending classical neural ODEs to the quantum domain. Quantum Neural ODEs use quantum circuits to parameterize the derivative function in continuous-depth neural networks.

Structs

BenchmarkResults

Benchmark results comparing quantum and classical approaches

NoiseModel

Noise model for quantum devices

QNODEConfig

Configuration for Quantum Neural ODEs

QuantumCircuit

Quantum circuit for the neural ODE

QuantumGate

Individual quantum gates

QuantumNeuralODE

Quantum Neural ODE Model

SolverState

Solver state for continuous integration

TrainingMetrics

Training metrics for QNODEs

Enums

AnsatzType

Quantum circuit ansatz types

GateType

Types of quantum gates

IntegrationMethod

Integration methods for ODEs

OptimizationStrategy

Optimization strategies for QNODE training

Functions

benchmark_qnode_vs_classical

Benchmark Quantum Neural ODE against classical Neural ODE

create_hardware_efficient_ansatz

Helper functions for quantum operations Create hardware-efficient ansatz

create_real_amplitudes_ansatz

Create real amplitudes ansatz