Notebook Guide¶
Complete index of all 40 Jupyter notebooks in notebooks/.
Quickstart¶
| Notebook | Topic | Prerequisites |
|---|---|---|
| quickstart_colab | Single neuron, dense layer, spike raster | pip install sc-neurocore |
Core SC Pipeline (01–07)¶
| # | Notebook | What you learn | Tutorial cross-ref |
|---|---|---|---|
| 01 | 01_hdc_symbolic_query |
HDC/VSA symbolic memory with 10,000-bit vectors | Tutorial 04 |
| 02 | 02_fault_tolerant_logic |
Boolean logic with stochastic redundancy (survives 40% error) | Tutorial 27 |
| 03 | 03_end_to_end_pipeline |
Encode → synapse → popcount → LIF → VectorizedSCLayer | Tutorial 01 |
| 04 | 04_neuron_explorer |
Interactive exploration of 117+ neuron models | Tutorial 22 |
| 05 | 05_nir_bridge |
NIR graph import/export, cross-framework interop | Tutorial 30 |
| 06 | 06_network_engine |
Population-Projection-Network, E/I balance, STDP | Tutorial 31 |
| 07 | 07_identity_substrate |
Persistent spiking network, STDP consolidation | Tutorial 32 |
Feature Demos (08–13)¶
| # | Notebook | What you learn | Tutorial cross-ref |
|---|---|---|---|
| 08 | 08_equation_to_verilog |
ODE string → Python sim → Q8.8 Verilog RTL (LIF, FHN, Izhikevich) | Tutorial 33 |
| 09 | 09_topology_and_dynamics |
6 connectivity generators, degree distributions, dynamics comparison | Tutorial 83 |
| 10 | 10_spike_train_analysis |
ISI, CV, Fano, cross-correlation, van Rossum, PCA (127 functions) | Tutorial 23 |
| 11 | 11_biological_circuits |
Tripartite synapse (Ca²⁺), Rall dendrite (3/2 power law) | Tutorial 24 |
| 12 | 12_learning_rules |
STDP, e-prop eligibility, R-STDP, STP facilitation/depression | Tutorial 28 |
| 13 | 13_quantisation_pipeline |
Float → Q8.8 → SC probabilities → Verilog export, error budget | Tutorial 77 |
Advanced Topics (14–20)¶
| # | Notebook | What you learn | Tutorial cross-ref |
|---|---|---|---|
| 14 | 14_sc_arithmetic_theory |
AND=multiply, XNOR=bipolar, MUX=add, CORDIV=divide, Hoeffding bounds | Tutorial 19 |
| 15 | 15_fault_tolerance |
SC vs fixed-point under bit-flips/stuck-at, TMR majority vote | Tutorial 63 |
| 16 | 16_neuron_atlas |
12 models from 8 families (1907–2026), voltage traces | Tutorial 17 |
| 17 | 17_reservoir_computing |
Liquid state machine, temporal XOR, ridge readout | Tutorial 74 |
| 18 | 18_mixed_precision_sc |
Per-layer adaptive bitstream length, Hoeffding vs sensitivity | Tutorial 44 |
| 19 | 19_compression_and_pruning |
Magnitude/SC-aware pruning, quantisation sweep, Pareto | Tutorial 44 |
| 20 | 20_power_analysis |
Event-driven vs clock-driven toggle count, scaling with network size | Tutorial 41 |
Frontier Research (21–28)¶
These notebooks demonstrate capabilities unique to SC-NeuroCore — features not available in any other SNN framework.
| # | Notebook | What you learn | Uniqueness |
|---|---|---|---|
| 21 | 21_spike_alu |
Turing-complete spike-based ALU: logic gates, register, adder, sort | First spike ALU in an SNN framework |
| 22 | 22_ir_type_safety |
IR signal type checker: Bitstream/Rate/Spike/Fixed compatibility | First SNN→FPGA type system |
| 23 | 23_topological_observables |
Winding number, Ricci curvature, sheaf defect on coupling graphs | First topological observables on SNN |
| 24 | 24_identity_lazarus |
Lazarus checkpoint save/load/merge, TraceEncoder, DirectorController | First persistent AI identity substrate |
| 25 | 25_cortical_column_dynamics |
5-population canonical microcircuit, feedforward latency | Biophysically grounded column model |
| 26 | 26_spike_codec_benchmark |
5 codecs (ISI/AER/predictive/delta/streaming), density curves | Comprehensive codec comparison |
| 27 | 27_python_to_proven_silicon |
Complete ODE→sim→type check→Verilog→testbench→formal→resource | End-to-end verified hardware pipeline |
| 28 | 28_domain_bridge |
TensorStream prob↔bitstream↔quantum, Born rule, cos²(θ/2) | Cross-domain probability bridge |
Evidence Notebooks (29–39)¶
| # | Notebook | What you learn | Evidence boundary |
|---|---|---|---|
| 29 | 29_golden_path_evidence |
Deterministic training -> Q8.8 -> SC simulation -> typed IR -> generated Verilog -> manifest | Local generated evidence only; no physical FPGA, timing, power, QPU, or external-data claim |
| 30 | 30_shd_vertex_deployable_evidence |
Summarise downloaded SHD Vertex deployable-selector artifacts by seed | Available local artifacts only; no claim that all intended seeds are downloaded or externally accepted |
| 31 | 31_balanced_resonate_and_fire_evidence |
Verify BRF Algorithm 1 update, deterministic traces, guardrails, and committed benchmark artifact | Scalar model and benchmark evidence only; no full BRF-RSNN training reproduction or hardware timing claim |
| 32 | 32_posner_ibm_readiness_evidence |
Verify ORCA/IBM readiness gates, runtime JSON refusal paths, and minimum QPU shot budget | Readiness gates only; no ORCA-derived runtime parameter, IBM calibration, or QPU-result claim |
| 33 | 33_hil_digital_twin_evidence |
Generate HIL protocol, drift controller, digital twin, SEU schedule, and telemetry drift manifest | Local generated protocols and synthetic telemetry only; no physical hardware calibration or certification claim |
| 34 | 34_industrial_readiness_evidence |
Evaluate industrial application profiles, mandatory evidence categories, and fail-closed readiness arithmetic | Local readiness profile arithmetic only; no certification, target-hardware, or authority-accepted safety-case claim |
| 35 | 35_bci_closed_loop_evidence |
Process synthetic waveform windows through BCI compression, AER, rate decoding, emulator feedback, telemetry, and HIL manifests | Synthetic waveform and implant-emulator evidence only; no clinical, stimulation, physical implant, or HIL timing claim |
| 36 | 36_fault_resilience_evidence |
Run seeded fault-injection resilience mode, deterministic replay policy, radiation stress presets, and input guardrails | Local seeded fault-injection evidence only; no radiation qualification, mission acceptance, hardware SEU, or certified fault-tolerance claim |
| 37 | 37_neuro_symbolic_self_verification_evidence |
Verify neuro-symbolic inference traces, stable digests, tamper detection, symbol-score ordering, trace-only evidence, and vector guardrails | Internal consistency evidence only; no external semantic-truth, clinical, physical, or deployment-validity claim |
| 38 | 38_formal_snn_verification_standard_evidence |
Exercise the formal SNN verification profile, pass/fail/missing evidence accounting, wrong-kind rejection, optional safety-case evidence, and evidence guardrails | Local evidence-accounting behavior only; no external prover, model-checker, HDL proof, safety certification, or unbounded semantic-correctness claim |
| 39 | 39_self_hosted_hub_evidence |
Generate and validate offline-first hub manifests, model-zoo index, Compose hardening, opt-in benchmark plan, bundle files, and config guardrails | Local bundle generation only; no Docker start, image build, production exposure, network-isolation proof, or operational-security certification claim |
Running Notebooks¶
Local¶
Bash
pip install sc-neurocore[dev]
pip install matplotlib jupyter
jupyter notebook notebooks/
Google Colab¶
Use quickstart_colab.ipynb — installs sc-neurocore automatically.
Prerequisites by Notebook¶
| Notebooks | Extra dependencies |
|---|---|
| 01–16, 20, 25 | matplotlib (visualisation) |
| 17 | matplotlib, numpy.linalg (SVD) |
| 21–22 | None beyond sc-neurocore |
| 23 | matplotlib |
| 24 | tempfile (checkpoint I/O) |
| 26 | time (benchmarking) |
| 27 | None beyond sc-neurocore |
| 28 | matplotlib |
| 29 | None beyond sc-neurocore |
| 30 | None beyond sc-neurocore |
| 31 | None beyond sc-neurocore |
| 32 | None beyond sc-neurocore |
| 33 | None beyond sc-neurocore |
| 34 | None beyond sc-neurocore |
| 35 | None beyond sc-neurocore |
| 36 | None beyond sc-neurocore |
| 37 | None beyond sc-neurocore |
| 38 | None beyond sc-neurocore |
| 39 | pyyaml |
Test Coverage¶
Every notebook topic has a corresponding test suite in tests/:
| Notebook topic | Test file | Tests |
|---|---|---|
| Topology (09) | test_topology_generators.py |
26 |
| SC arithmetic (14) | test_sc_convergence.py |
13 |
| Fault tolerance (15) | test_fault_injection.py |
14 |
| Neuron atlas (16) | test_neuron_families.py |
57 |
| Learning rules (12) | test_learning_advanced.py |
11 |
| Quantisation (13) | test_quantisation_pipeline.py |
12 |
| Spike ALU (21) | test_spike_alu.py |
27 |
| IR types (22) | test_ir_type_checker.py |
existing |
| Topology obs (23) | test_topological_observables.py |
17 |
| Identity (24) | test_identity_lazarus.py |
20 |
| Cortical col (25) | test_cortical_column_dynamics.py |
13 |
| Domain bridge (28) | test_tensor_stream.py, test_quantum_hybrid.py |
24 |
| Golden path evidence (29) | test_notebooks/test_golden_path_notebook.py |
2 |
| SHD Vertex deployable evidence (30) | test_notebooks/test_shd_vertex_notebook.py |
2 |
| BRF evidence (31) | test_notebooks/test_brf_notebook.py |
2 |
| Posner/IBM readiness evidence (32) | test_notebooks/test_posner_ibm_readiness_notebook.py |
2 |
| HIL/digital twin evidence (33) | test_notebooks/test_hil_digital_twin_notebook.py |
2 |
| Industrial readiness evidence (34) | test_notebooks/test_industrial_readiness_notebook.py |
2 |
| BCI closed-loop evidence (35) | test_notebooks/test_bci_closed_loop_notebook.py |
2 |
| Fault resilience evidence (36) | test_notebooks/test_fault_resilience_notebook.py |
2 |
| Neuro-symbolic self-verification evidence (37) | test_notebooks/test_neuro_symbolic_self_verification_notebook.py |
2 |
| Formal SNN verification standard evidence (38) | test_notebooks/test_formal_snn_verification_standard_notebook.py |
2 |
| Self-hosted hub evidence (39) | test_notebooks/test_self_hosted_hub_notebook.py |
2 |
| SCPN (—) | test_scpn_integrated.py |
17 |
| CORDIV (14) | test_cordiv_division.py |
10 |
| Monitors (—) | test_network_monitors_stimulus.py |
19 |
Total new tests: 340 passing on Python 3.12.