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SC-NeuroCore Component Inventory

Version: 3.13.3 Date: 2026-03-11

This document lists all components in the sc-neurocore framework, organized by domain. Sections 1--3 and 6--7 are implemented and tested. Sections 4--5 contain modules from the broader Anulum Research / SCPN theoretical framework that are planned but not yet implemented in this repository.

1. Core Neuromorphic

  • neurons/
    • StochasticLIFNeuron: Leaky Integrate-and-Fire with noise and refractory period.
    • FixedPointLIFNeuron: Bit-true integer model for RTL verification.
    • HomeostaticLIFNeuron: Self-regulating firing threshold.
    • StochasticDendriticNeuron: Multi-compartment neuron for non-linear logic (XOR).
  • synapses/
    • BitstreamSynapse: Basic stochastic weight multiplication.
    • StochasticSTDPSynapse: Spike-Timing-Dependent Plasticity.
    • RewardModulatedSTDPSynapse: R-STDP for reinforcement learning.
  • layers/
    • SCLearningLayer: Dense layer with local plasticity.
    • SCConv2DLayer: Stochastic 2D Convolution.
    • SCRecurrentLayer: Reservoir Computing / RNN.
    • VectorizedSCLayer: High-performance 64-bit packed simulation.

2. Advanced Computing & AGI

  • transformers/
    • StochasticTransformerBlock: "S-Former" with spike-based attention.
  • world_model/
    • PredictiveWorldModel: Stochastic state transition forecasting.
    • SCPlanner: Action selection via predictive modeling.
  • spatial/
    • VoxelGrid, PointCloud: 3D spatial representations.
    • SpatialTransformer3D: Attention-based 3D data processing.
  • generative/
    • SCTextGenerator: Token-level probabilistic text synthesis.
    • SCAudioSynthesizer: Waveform generation from bitstreams.
    • SC3DGenerator: 3D point cloud and mesh export.
  • graphs/
    • StochasticGraphLayer: Event-based Graph Neural Network (GNN).
  • hdc/
    • HDCEncoder, AssociativeMemory: Hyperdimensional Computing logic.
  • chaos/
    • ChaoticRNG: Logistic Map bitstream generator (True Randomness).

3. Physical & Biological Integration

  • bio/
    • GeneticRegulatoryLayer: Gene Regulatory Network (GRN) dynamics.
    • DNAEncoder: Bitstream-to-Nucleotide storage interface.
    • ConnectomeEmulator: Whole-brain emulation framework.
    • NeuromodulatorSystem: Dopamine/Serotonin emotional state dynamics.
  • physics/
    • StochasticHeatSolver: Random walk PDE solver.
    • WolframHypergraph: Universe evolution via hypergraph rewriting.
  • robotics/
    • StochasticCPG: Central Pattern Generator for locomotion.
    • SwarmCoupling: Brain-to-Brain synchronization protocol.
  • optics/
    • PhotonicBitstreamLayer: Laser phase noise interference simulation.

4. Quantum & Meta-Computing

  • quantum/
    • QuantumStochasticLayer: Variational Quantum Circuit (VQC) bridge.
    • AnyonBraidLayer: Topological quantum computing.
  • meta/
    • TimeCrystalLayer: Discrete Time Crystal (Period Doubling).
    • VacuumNoiseSource: Zero-point energy harvesting.
    • OracleLayer: Hyper-Turing predictive lookahead.
    • EventHorizonLayer: Black Hole information scrambling.
    • CTCLayer: Closed Timelike Curve (Time Travel) consistency solver.
    • RecursiveSelfImprover: Singularity self-rewriting architecture.
    • OmegaIntegrator: Omega Point universal integration.
    • AgentDAO: Decentralized governance and consensus.
    • DarkForestAgent: Fermi Paradox game-theoretic logic.

5. Post-Silicon & Speculative

  • post_silicon/
    • ReversibleLayer: Adiabatic logic (Toffoli gates).
    • FemtoSwitch: Quark Color Charge computing ($SU(3)$).
    • CellularComputer: Synthetic cell molecular collision logic.
    • CatomLattice: Programmable Matter (Claytronics) reconfiguration.
  • exotic/
    • MyceliumLayer: Fungal network transport dynamics.
    • ReactionDiffusionSolver: Chemical Turing pattern computing.
    • MechanicalLatticeLayer: Stiffness-adaptive material logic.
    • RadHardLayer: Space-hardened TMR (Triple Modular Redundancy).
    • DysonSwarmNet: Matrioshka Brain hierarchical energy harvesting.
    • ConstructorCell: Von Neumann Universal Constructor.
    • DysonPowerGrid: Stellar-scale energy distribution.

5b. Implemented Modules (Not Listed Above)

  • nir_bridge/
    • from_nir(), to_nir(): NIR graph import/export (18/18 primitives)
    • SCNetwork: Topological execution engine for imported NIR graphs
    • SCSubgraphNode, SCMultiPortSubgraphNode: Nested graph support
    • Verified interop: Norse, snnTorch, SpikingJelly, Sinabs, Rockpool
  • compiler/
    • IR graph builder, parser, verifier
    • SystemVerilog + MLIR/CIRCT emitters
    • Weight quantizer, type checker
  • identity/
    • IdentitySubstrate: 3-population persistent SNN (HH + WB + HR)
    • TraceEncoder: LSH text-to-spike encoding
    • StateDecoder: PCA + attractor extraction
    • Checkpoint: Lazarus protocol (save/restore/merge)
    • DirectorController: L16 cybernetic self-regulation
  • network/
    • Population-Projection-Network engine (3 backends: Python, Rust, MPI)
    • Per-synapse delays, spike-gating, weight sparsity exploitation
    • 6 topology generators, 12 visualization plots
  • model_zoo/
    • 10 pre-built network configs, 3 pre-trained weight sets (MNIST, SHD, DVS)
  • conversion/
    • convert(): ANN-to-SNN conversion (PyTorch → rate-coded SNN)
    • QCFSActivation: conversion-aware training activation
  • training/
    • Surrogate gradient training cells (LIF, ALIF, RecurrentLIF, EPropALIF)
    • DelayLinear: trainable per-synapse delays with differentiable interpolation
    • ConvSpikingNet (99.49% MNIST)
  • learning/
    • 13 plasticity rules: pair/triplet/voltage STDP, BCM, BPTT, TBPTT, EWC, e-prop, R-STDP, MAML, homeostatic, STP, structural
  • adapters/
    • Holonomic L1-L16 adapters with JAX acceleration
  • scpn/
    • SCPN 16-layer stack implementations
  • solvers/
    • ODE solvers (RK4, Euler)
  • datasets/
    • Dataset loaders (MNIST, SHD, DVS)
  • cli/
    • sc-neurocore command-line interface
  • spike_codec/ — Spike Codec Library (6 codecs, unified API)
    • codec.py: SpikeCodec — ISI + LEB128 varint baseline (50-200x).
    • predictive_codec.py: PredictiveSpikeCodec — EMA predictor + XOR error coding for BCI implants.
    • delta_codec.py: DeltaSpikeCodec — inter-channel XOR residuals for correlated probe arrays.
    • streaming_codec.py: StreamingSpikeCodec — fixed-latency, independently decodable frames.
    • aer_codec.py: AERSpikeCodec — address-event representation for neuromorphic routing.
    • waveform_codec.py: WaveformCodec — end-to-end raw 10-bit waveform compression (spike detect + template match + LFP compress, 24x on 1024ch).
    • registry.py: get_codec(), list_codecs(), recommend_codec() — unified lookup and auto-selection.

6. Systems, Pipeline & Tools

  • core/
    • TensorStream: Unified high-performance data pipeline.
    • CognitiveOrchestrator: Central executive with attention/goals.
    • DigitalSoul: Agent state persistence and immortality.
    • VonNeumannProbe: Code-level self-replication.
    • MindDescriptionLanguage: Substrate-independent soul format.
    • MetaCognitionLoop: Computational self-awareness.
  • pipeline/
    • DataIngestor: Multimodal dataset preparation.
    • SCTrainingLoop: Standard and RL training orchestration.
  • ensembles/
    • EnsembleOrchestrator: Multi-agent mission coordination.
  • accel/
    • jit_kernels.py: Numba JIT acceleration for bit-packing and MAC operations.
    • MPIDriver: Distributed cluster-scale simulation.
  • export/
    • SCOnnxExporter: ONNX-compatible JSON schema export.
  • hdl_gen/
    • VerilogGenerator: Automated Verilog RTL generation.
    • SpiceGenerator: Analog SPICE netlist export.
  • profiling/
    • EnergyProfiler: 45nm Energy (J) and CO2e estimation.
  • security/
    • WatermarkInjector: Backdoor weight injection.
    • ZKPVerifier: Zero-Knowledge Proof commitments.
    • DigitalImmuneSystem: Anomaly detection and threat response.
    • AsimovGovernor: Ethical constraint implementation.
  • verification/
    • FormalVerifier: Interval arithmetic proofs for safety properties.
    • CodeSafetyVerifier: AST-based analysis for self-modifying code.
  • math/
    • CategoryTheoryBridge: Functors between Stochastic, Quantum, and Bio domains.
  • interfaces/
    • BCIDecoder: Neural signal (EEG) interface.
    • DVSInputLayer: Event Camera (AER) interface.
    • PlanetarySensorGrid: Global telemetry aggregation.
    • SymbiosisProtocol: Human-AI thought exchange protocol.
    • InterstellarDTN: Long-range delay-tolerant networking.
    • RealWorldInterfaces: LSL and ROS2 mock bridges.
  • viz/
    • WebVisualizer: HTML5/Canvas network topology renderer.
    • NeuroArtGenerator: Generative AI for internal state expression.
  • analysis/
    • PhiEvaluator: IT Consciousness ($\Phi$) measurement.
    • Explainability: Spike-to-concept semantic mapping.
    • KardashevEstimator: Civilization progress metrics.
    • QualiaTuringTest: Subjectivity verification framework.

7. Deployment

  • deploy/: Dockerfile and Compose configuration for containerization.