Expand description
Circuit integration for quantum machine learning
This module provides seamless integration between quantum ML algorithms and the QuantRS2 circuit module, enabling efficient execution of quantum circuits on various backends.
Structs§
- Backend
Manager - Backend integration for multiple simulators
- Device
Topology - Device topology representation
- Expressionvity
Metrics - Circuit expressivity metrics
- Hardware
Aware Compiler - Hardware-aware circuit compiler
- MLCircuit
Analyzer - Circuit analysis for ML applications
- MLCircuit
Optimizer - Circuit optimization for ML workloads
- MLGate
Fusion Pass - Gate fusion pass for ML circuits
- Parameter
Consolidation Pass - Parameter consolidation pass
- Parameterized
Layer - Parameterized quantum circuit layer
- QuantumML
Executor - Quantum circuit executor for ML applications
- Qubit
Properties - Qubit properties for device characterization
- Trainability
Metrics - Circuit trainability metrics
Enums§
- Optimization
Pass Type - Enum of optimization passes
- Rotation
Axis - Rotation axis for parameterized gates
Traits§
- Optimization
Pass - Trait for circuit optimization passes
- Quantum
Layer - Trait for quantum layers in ML circuits