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Contents
Overview
Installation
Quickstart / Tutorials
Minimal Core Demo
Benchmark Performance Demo
Hypercausal Chain Demo
Training with Callbacks Demo
Advanced Training with Callbacks
Quantum Hypercore Case Study
Full Hypercausal System Demo (PennyLane + SPSA + KL)
Architecture
Theory / Concepts
Integration
Benchmarks / Performance
Changelog / Versioning
Contributing
API Overview
Backends
C++ Backend (pybind11)
PennyLane Backend
Qiskit Backend
Callbacks
Callback Base Classes
Depth Control Callback
Telemetry Callback
Core Engine
Backend Interface
Quantum Model Abstractions
Backend Registry
Core Types
Examples
Minimal Core Demo
Hypercausal Graph
Hypercausal Graph
Hypercausal Node
Hypercausal Policy
Loss Functions
Coherence Loss
Consistency Loss
Task Loss
Metrics
Anomaly Metrics
Control Metrics
Forecasting Metrics
Optimization
Optimizer API
Registry: NumPy Optimizers
NumPy Optimizers
Adaptive Adam Optimizer (Adam)
Dual Ascent Controller (DA)
Finite Difference Evaluator (FD)
K-FAC Natural Curvature Optimizer (K-FAC)
Model Predictive Controller (MPC)
Natural Gradient Descent (NGD)
SPSA Stochastic Optimizer (SPSA)
Trust-Region Stability Optimizer (TR)
Core Utility Functions (Utils)
Predictors
Anticipator — module
Projector — module
GitHub Repository
.rst
.pdf
Loss Functions
Contents
Submodules
Loss Functions
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Submodules
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Coherence Loss
Consistency Loss
Task Loss
Contents
Submodules
