Date: March 23, 2026 | License: AGPL-3.0-or-later | MSRV: Rust 1.87 (2024 edition)
Status: V121 — 40 modules, 35 experiments, 691+ lib tests + 287 Python provenance tests, 395/395 validation checks (340 core + 55 NUCLEUS) + 140 metalForge checks, 110 active barraCuda delegations (67 CPU + 43 GPU) — synced against barraCuda v0.3.7, toadStool S158+, coralReef Iteration 55+. Three-tier parity proven: 29/29 validation binaries PASS at all three tiers. cargo deny check PASS, cargo clippy --all-features clean, cargo check --all-features compiles. ≥92% library line coverage (cargo llvm-cov --workspace --lib). V121: Deep debt + ecosystem absorption — biomeos/mod.rs refactored 631→232 lines (extracted storage, compute, registration, health, routing submodules), stats/agreement.rs refactored into directory (coefficient, error_metrics, efficiency, willmott, hit_rate), normalize_method() for legacy RPC prefixes, 5-tier socket discovery with socket-registry.json, NdjsonSink for machine-readable validation output, workspace lints deny unwrap_used/expect_used, IpcError::is_recoverable(), provenance trio run_lifecycle(), MCP capability_registry.toml, MSRV 1.87, hardcoding→capability-based patterns (temp_dir, env-driven server timeouts, generalized is_enabled()). V120: Deep audit execution — dispatch/ module, ValidationHarness expanded, #![forbid(unsafe_code)] on 50 binaries, DeviceCapabilities migration, release-mode CI. V119: Cross-ecosystem absorption — MSRV 1.85, provenance registry, cast module. V118: RPC expansion (16 capabilities), 110 delegations. V117–V115: All-features compilation, typed errors, ecoBin compliance.
The gap between what models predict and what instruments measure.
groundSpring is the reality layer in the ecoPrimals ecosystem. Where other springs validate clean science — hotSpring (nuclear math), airSpring (FAO-56 equations), wetSpring (taxonomy pipelines) — groundSpring lives in the space where those models meet the physical world.
Core question: "How do things actually look, and why is it different from what we expected?"
Clean models (other springs) → Noisy measurements (groundSpring) → Adapted models (neuralSpring)
-
Signal vs Noise — Distinguishing real phenomena from measurement artifacts. Sensor drift, calibration error, environmental interference. When airSpring's soil moisture sensor reads 0.32 instead of 0.30, is that real heterogeneity or instrument error?
-
Inverse Problems — From observations back to causes. Where did an earthquake start, from its emanations? What is a star's composition, from its light frequencies? What contaminant entered the watershed, from downstream sensor readings?
-
Sensing Systems — The physics of measurement itself. How do different instruments see the same phenomenon differently? A thermometer, a satellite, and a reanalysis model all "measure" temperature differently. Color and size have different meaning depending on the detector.
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Temporal Dynamics — How systems drift over time. Sensor degradation. Seasonal baselines. Long-term climate trends vs short-term weather noise. The geological clock vs the agricultural clock vs the astronomical clock.
-
Spatial Propagation — How signals travel through media. Seismic waves through rock. Light through atmosphere (extinction, redshift). Moisture through soil. Contaminants through aquifers. The medium distorts the message.
| Experiment | Domain | Phase 0 (Python) | Phase 1 (Rust) | Key Question |
|---|---|---|---|---|
| 001: Sensor Noise | Agricultural | 32/32 PASS | 36/36 PASS | Bias vs variance in soil moisture sensors |
| 002: Observation Gap | Meteorological | PASS/SKIP | 13/13 PASS | Reanalysis model vs station readings |
| 003: Error Propagation | Agricultural | PASS | 15/15 PASS | How sensor noise becomes ET₀ uncertainty |
| 004: Sequencing Noise | Biological | PASS | 15/15 PASS | Taxonomic reliability vs sequencing depth |
| 005: Seismic Waves | Geological | PASS | 9/9 PASS | Source localization from noisy arrivals |
| 006: Signal Specificity | Biological | 12/12 PASS | 12/12 PASS | c-di-GMP signal vs noise in enzyme network |
| 007: RAWR Resampling | Statistics | 11/11 PASS | 11/11 PASS | Bayesian bootstrap vs naive bootstrap |
| 008: Anderson Localization | Mathematics | 8/8 PASS | 8/8 PASS | Lyapunov exponents in disordered media |
| 009: Almost-Mathieu Quasiperiodic | Mathematics | PASS | 8/8 PASS | Aubry-André metal-insulator transition |
| 010: Bistable Phenotypic Switching | Biological | PASS | 10/10 PASS | Fernandez 2020 PNAS bifurcation |
| 011: Multi-Signal QS Integration | Biological | PASS | 9/9 PASS | Srivastava 2011 dual-signal integration |
| 012: Spin Chain Transport | Mathematics | 18/18 PASS | 18/18 PASS | Kachkovskiy 2016 wavepacket MSD, transport exponent |
| 013: Resampling Convergence | Statistics | 8/8 PASS | 8/8 PASS | Lee & Liu 2024 bootstrap convergence |
| 014: Drift vs Selection | Biological | 7/7 PASS | 7/7 PASS | R. Anderson 2022 Wright-Fisher, Kimura fixation |
| 015: Uncertainty Bridge | Cross-domain | 8/8 PASS | 8/8 PASS | Sensor noise → Anderson ξ propagation |
| 016: Rare Biosphere | Biological | 11/11 PASS | 12/12 PASS | Sequencing depth determines rare taxa signal boundary |
| 017: Quasispecies Threshold | Evolutionary | 9/9 PASS | 6/6 PASS | Eigen's error threshold predicts mutation-driven information collapse |
| 018: Band Edge Structure | Mathematical | 8/8 PASS | 10/10 PASS | Transfer matrix reproduces tight-binding band-gap structure |
| 019: Jackknife Error Estimation | Inverse Problems & Spectral Reconstruction | 9/9 PASS | 9/9 PASS | Bazavov 2025 Phys Rev D 111, 094508 — jackknife variance, bias correction |
| 020: Freeze-Out Inverse Problem | Inverse Problems & Spectral Reconstruction | 8/8 PASS | 8/8 PASS | Bazavov 2016 Phys Rev D 93, 014512 — freeze-out temperature from hadron yields |
| 021: Spectral Function Reconstruction | Inverse Problems & Spectral Reconstruction | 8/8 PASS | 8/8 PASS | Bazavov 2025 arXiv 2501.12259 — spectral reconstruction from correlators |
| 022: ET₀ → Anderson Propagation | Cross-spring (FAO-56 + Anderson) | 7/7 PASS | 7/7 PASS | Humidity-dominated ET₀ error → localization length CV |
| 023: No-Till vs Tilled Sampling | Cross-spring (microbiome + soil) | 7/7 PASS | 7/7 PASS | Saturation depth by soil management regime |
| 024: Aggregate Stability Noise | Cross-spring (soil physics) | 8/8 PASS | 8/8 PASS | WSA measurement precision vs Anderson regime discrimination |
| 025: f32 vs f64 Precision Drift | WDM MD | 7/7 PASS | 7/7 PASS | Green-Kubo f32 accumulation bias |
| 026: System-size Convergence | WDM MD | 7/7 PASS | 7/7 PASS | Transport coefficient finite-size extrapolation |
| 027: GPU Vendor Parity | WDM MD | 7/7 PASS | 7/7 PASS | Cross-vendor transport coefficient agreement |
| 028: NPU Anderson Regime | Hardware (NPU) | 7/7 PASS | 9/9 PASS | Anderson regime classification on AKD1000 via int8 DMA |
| 029: Real GHCND ET₀ | Cross-spring (NOAA) | — | 6/6 PASS | Hargreaves vs Penman-Monteith on real/synthetic weather via NestGate |
| 030: Real NCBI 16S | Biological (NCBI) | — | 9/9 PASS | Rare biosphere detection on real/synthetic NCBI 16S metagenomes |
| 031: NUCLEUS Stack | Infrastructure | — | 28/28 PASS | Full NUCLEUS primal validation: Tower + Node + Squirrel + Nest |
| 032: IRIS Seismic | Geological (IRIS) | — | 12/12 PASS | IRIS FDSN station geometry + travel times via NestGate |
| 033: Tissue Anderson | Immunological (Paper 12) | — | 29/29 PASS | Cytokine Anderson lattice + geometry-aware drug scoring |
| 034: ET₀ Methods | Agricultural (FAO-56) | 15/15 PASS | 19/19 PASS | 5-method ET₀ cross-validation: PM, Hargreaves, Makkink, Turc, Hamon |
Phase 1 total: 395/395 PASS across 34 validation binaries (340 core + 55 NUCLEUS via --features biomeos). All public APIs return Result — zero panicking entry points.
| Module | Purpose | GPU Tier |
|---|---|---|
stats::agreement |
RMSE, MAE, MBE, NSE, R², IA, hit rate (R²/NSE deduplicated via shared coefficient_of_efficiency) |
GPU dispatched (rmse, mbe via FusedMapReduceF64/SumReduceF64) + CPU delegated |
stats::metrics |
mean, std_dev, sample_std_dev, percentile | GPU dispatched (mean via SumReduceF64, std_dev via VarianceReduceF64) + CPU delegated |
stats::correlation |
Pearson/Spearman correlation, covariance | GPU dispatched (pearson_r via CorrelationF64, covariance via CovarianceF64) + CPU delegated |
stats::distributions |
norm_cdf, norm_ppf, χ² | 3 CPU delegated |
stats::regression |
Linear, quadratic, exponential, logarithmic fits | 4 CPU delegated |
decompose |
Bias-variance decomposition, noise floor | CPU-only (scalar) |
fao56 |
FAO-56 Penman-Monteith equation chain | Absorbed (barracuda Op::Fao56Et0) + GPU batch (BatchedElementwiseF64) |
prng |
Xorshift64 PRNG, Box-Muller normal | B (DefaultRng aligned) |
rarefaction |
Multinomial sampling, Shannon/Simpson diversity, Bray-Curtis, evenness, analytical rarefaction | C (WGSL production ready) |
seismic |
Haversine, travel time, grid-search inversion | GPU-ready (V31 dispatch) |
gillespie |
Gillespie SSA for stochastic chemical kinetics | GPU dispatched (batch via GillespieGpu) |
bootstrap |
Bootstrap (mean/median/std) + RAWR confidence intervals | A Lean (barracuda::stats) |
anderson |
Anderson localization, Lyapunov exponents, analytical ξ(W,E), 2D/3D eigenvalues, disorder sweep, spectral diagnostics, empirical spectral density, Marchenko-Pastur bounds, transition detection | A Lean (barracuda::spectral + special + stats::spectral_density + ops::peak_detect_f64) |
almost_mathieu |
Almost-Mathieu quasiperiodic localization, level spacing | A Lean (barracuda::spectral) |
linalg |
Tridiag eigensolver (implicit QL with Wilkinson shifts) — shared by transport + band_structure | B (adapt) |
transport |
Wavepacket MSD, transport exponent (re-exports linalg::tridiag_eigh for compat) |
B (adapt) |
error |
Typed input validation errors (InputError: LengthMismatch, InsufficientData, OutOfRange) |
N/A |
drift |
Wright-Fisher fixation, Kimura fixation probability, neutral diversity trajectory | CPU delegated (kimura_fixation_prob S70+) + GPU batch (WrightFisherGpu) |
cast |
Centralized numeric casts with documented safety | N/A |
kinetics |
Hill + Monod kinetics (shared bistable + multi-signal) | A Lean (barracuda::stats::hill, monod) |
validate |
Generic Write harness (hotSpring pattern) | N/A |
rare_biosphere |
Chao1, detection power/threshold, abundance-occupancy, singleton fraction | GPU-ready (V31 dispatch) |
quasispecies |
Eigen error threshold, master frequency, Wright-Fisher mutation simulation | GPU-ready (V31 dispatch) |
band_structure |
Transfer matrix, band edge detection, count bands, periodic Hamiltonian | GPU-ready (V31 dispatch) |
jackknife |
Jackknife variance, bias correction, leave-one-out resampling | CPU delegated (jackknife_mean_variance S70+) |
freeze_out |
Freeze-out temperature inversion, hadron yield fitting | GPU-ready (V31 dispatch) |
spectral_recon |
Spectral function reconstruction from Euclidean correlators | GPU delegated (tikhonov_solve) |
biomeos |
biomeOS Neural API client: JSON-RPC 2.0, capability routing, UDS server, NestGate storage (behind biomeos feature) |
N/A |
dispatch |
JSON-RPC method dispatch: measurement.* semantic routing to library functions (behind biomeos feature) |
N/A |
provenance |
Provenance Trio lifecycle: session create, dehydrate, attribute via capability calls (behind biomeos feature) |
N/A |
nestgate |
NestGate data pipeline: NCBI/NOAA providers, provenance key schemas, cache-through (behind biomeos feature) |
N/A |
esn |
Echo State Network regime classification: EsnClassifier (barracuda-gpu), rule-based classify_by_spacing_ratio, spectral_features |
GPU dispatched (barracuda-gpu ESN) + CPU rule-based |
lanczos |
Sparse eigensolver for 2D/3D Anderson: sparse_eigenvalues, eigenvalues_from_csr (barracuda-gpu only) |
GPU dispatched (barracuda spectral Lanczos) |
npu |
NPU integration for Akida neuromorphic inference (behind npu feature) |
NPU (AKD1000) |
niche |
Self-knowledge module: capabilities, dependencies, cost estimates, feature gates, consumed capabilities (airSpring pattern) | N/A |
primal_names |
Centralized primal name constants for socket paths, discovery, env checks (wetSpring V119 pattern); zero hardcoded strings in production | N/A |
groundspring-forge |
Hardware discovery, cross-substrate dispatch, PCIe topology, multi-stage pipeline, NUCLEUS atomics, remote NUCLEUS discovery (26 workloads, 5+ substrates, 120 tests) |
metalForge crate |
cargo test --workspace # 990+ tests, all PASS
cargo test --workspace --all-features # all feature paths tested
cargo test --workspace --features biomeos # NUCLEUS client active
cargo test --workspace --features barracuda-gpu # GPU dispatch active
cargo clippy --workspace --all-targets -- -D warnings -W clippy::pedantic -W clippy::nursery
cargo fmt --check # clean
# Barracuda-delegated mode (validates cross-spring math)
cargo test --workspace --features barracuda
cargo test --workspace --features barracuda-gpu
# NPU mode (BrainChip AKD1000)
cargo test --workspace --features npu # npu module + Exp 028
# metalForge live hardware binaries
cargo run --bin validate_metalforge_inventory
cargo run --bin validate_metalforge_gpu
cargo run --bin validate_metalforge_cross_substrate
cargo run --bin validate_metalforge_titan_v
# Run all validation binaries at once (meta-binary)
cargo run --bin validate_all
# Individual validation binaries (hotSpring pattern: exit 0 = pass, exit 1 = fail)
cargo run --bin validate_decompose
cargo run --bin validate_rarefaction
cargo run --bin validate_seismic
cargo run --bin validate_weather
cargo run --bin validate_fao56
cargo run --bin validate_signal_specificity
cargo run --bin validate_rawr
cargo run --bin validate_anderson
cargo run --bin validate_quasiperiodic
cargo run --bin validate_bistable
cargo run --bin validate_multisignal
cargo run --bin validate_transport
cargo run --bin validate_resampling_conv
cargo run --bin validate_drift
cargo run --bin validate_uncertainty_bridge
cargo run --bin validate_rare_biosphere
cargo run --bin validate_quasispecies
cargo run --bin validate_band_edge
cargo run --bin validate_jackknife
cargo run --bin validate_freeze_out
cargo run --bin validate_spectral_recon
cargo run --bin validate_npu_anderson
cargo run --bin validate_et0_anderson
cargo run --bin validate_notill_sampling
cargo run --bin validate_aggregate_stability
cargo run --bin validate_precision_drift
cargo run --bin validate_size_convergence
cargo run --bin validate_vendor_parity
cargo run --bin validate_tissue_anderson
cargo run --bin validate_et0_methods
# NUCLEUS / biomeOS validation (requires biomeos feature, NUCLEUS optional)
cargo run --features biomeos --bin validate_real_ghcnd_et0
cargo run --features biomeos --bin validate_real_ncbi_16s
cargo run --features biomeos --bin validate_nucleus_stack
cargo run --features biomeos --bin validate_iris_seismicpip install -e ".[dev]"
python3 -m pytest tests/ -v # 29 experiments (287 tests)
ruff check control/ tests/ # zero errors
mypy control/ tests/ # zero errorscargo llvm-cov --workspace --lib # ≥92% library line coverage (target 90%)Median of 3 trials across all 28 experiments (Feb 27, 2026). See data/bench_rust_vs_python.json for full data.
| Experiment | Python (s) | Rust (s) | Speedup |
|---|---|---|---|
| Exp 001: Sensor Noise | 0.38 | 0.07 | 5.3× |
| Exp 002: Observation Gap | 0.27 | 0.08 | 3.6× |
| Exp 003: Error Propagation | 0.34 | 0.08 | 4.4× |
| Exp 004: Sequencing Noise | 0.14 | 0.09 | 1.5× |
| Exp 005: Seismic Inversion | 7.42 | 0.14 | 53.5× |
| Exp 006: Signal Specificity | 26.51 | 0.86 | 31.0× |
| Exp 007: RAWR Resampling | 4.54 | 0.64 | 7.1× |
| Exp 008: Anderson Localization | 21.96 | 0.77 | 28.6× |
| Exp 009: Quasiperiodic | 0.65 | 11.32 * | 0.1× |
| Exp 010: Bistable Switching | 3.26 | 0.18 | 18.1× |
| Exp 011: Multi-Signal QS | 4.25 | 0.10 | 44.7× |
| Exp 012: Spin Chain Transport | 0.92 | 0.31 | 3.0× |
| Exp 013: Resampling Convergence | 1.36 | 0.13 | 10.4× |
| Exp 014: Drift vs Selection | 0.42 | 1.14 | 0.4× |
| Exp 015: Uncertainty Bridge | 1.32 | 0.12 | 11.1× |
| Exp 016: Rare Biosphere | 0.38 | 0.20 | 1.9× |
| Exp 017: Quasispecies Threshold | 0.12 | 0.09 | 1.3× |
| Exp 018: Band Edge Structure | 0.23 | 0.11 | 2.1× |
| Exp 019: Jackknife Estimation | 0.12 | 0.07 | 1.7× |
| Exp 020: Freeze-Out Inverse | 0.36 | 0.07 | 5.1× |
| Exp 021: Spectral Recon | 0.12 | 0.07 | 1.7× |
| Exp 022: ET₀ Anderson | 0.87 | 0.10 | 8.6× |
| Exp 023: No-Till Sampling | 0.11 | 0.09 | 1.3× |
| Exp 024: Aggregate Stability | 0.14 | 0.09 | 1.6× |
| Exp 025: Precision Drift | 27.93 | 3.18 | 8.8× |
| Exp 026: Size Convergence | 0.12 | 0.07 | 1.6× |
| Exp 027: Vendor Parity | 0.14 | 0.12 | 1.1× |
| Exp 028: NPU Anderson | 0.12 | 0.08 | 1.5× |
| Total | 104.49 | 20.35 | 5.1× |
| Total (excl. LAPACK-bound) | 103.84 | 9.04 | 11.5× |
* Exp 009/014: Rust custom QR/Wright-Fisher vs NumPy LAPACK/SciPy. Barracuda-gpu (Sturm tridiag from hotSpring S26) closes the gap: 47.7× speedup for Exp 009.
Mathematical parity: 29/29 PROVEN — both languages validate against the
same shared benchmark JSONs. See data/parity_report.json.
Run benchmarks: python3 scripts/bench_rust_vs_python.py
Run parity report: python3 scripts/parity_report.py
| Mode | Wall time (s) | Δ vs local |
|---|---|---|
| Local (no features) | 12.5 | baseline |
| BarraCUDA CPU | 18.4 | +47% (dispatch overhead on small workloads) |
| BarraCUDA GPU | 9.9 | −21% (1.27× faster) |
| Mode | Wall time (s) | Δ vs local |
|---|---|---|
| Local (no features) | 50.3 | baseline |
| BarraCUDA CPU | 29.0 | −42% (1.73× faster) |
110 active delegations (67 CPU + 43 GPU). Cross-spring evolution powers
this: hotSpring precision shaders (DF64 core, Sturm tridiag — 47.7× for Exp 009),
wetSpring bio shaders (Gillespie SSA, diversity fusion, Bray-Curtis),
neuralSpring stats (chi-squared, KL divergence, matrix correlation),
airSpring hydrology (seasonal pipeline, Hargreaves ET₀), and groundSpring
spectral shaders (Anderson Lyapunov, uncertainty propagation).
PrecisionRoutingAdvice + runtime f64 smoke test (V97) guards all 21 GPU dispatch paths
via get_device_f64_safe() — hardware-aware routing with empirical f64 reduction verification.
Every spring contributes shaders that benefit the entire ecosystem through barraCuda:
hotSpring (precision) ─────┐
df64_core, Sturm tridiag, │ All absorbed into barraCuda v0.3.5
stress_virial, CG kernels ├──► 784 WGSL shaders, f64-canonical
│ with f16/f32/f64/Df64 per hardware
wetSpring (bio) ────────────┤
smith_waterman, gillespie, │ toadStool S158+ routes hardware
fused_map_reduce, HMM │ coralReef compiles to native GPU binary
│
neuralSpring (ML) ──────────┤ groundSpring consumes 110 ops:
chi_squared, KL_divergence,│ 67 CPU delegated, 43 GPU dispatched
matrix_correlation, ESN │
│
airSpring (hydrology) ──────┤
hargreaves, seasonal_pipe, │
moving_window, Brent root │
│
groundSpring (spectral) ────┘
anderson_lyapunov, welford,
chi_squared → ALL springs
f64 bug → PrecisionRoutingAdvice
Phase 0 (Python) → Phase 1 (Rust) → Phase 2 (GPU) → Phase 3 (Hardware) → Phase 4 (NUCLEUS)
NumPy/SciPy Pure safe Rust BarraCUDA/ToadStool metalForge dispatch biomeOS Neural API
✓ Complete ✓ 395/395 PASS ◐ 110 active 30 workloads Tower+Node+Squirrel
11.5× slower 35/35 experiments (67+43) 24 GPU + 2 NPU + 2 CPU-only NestGate data pipes
990+ workspace tests PCIe topology NUCLEUS atomics
Pipeline dispatch Sovereign degradation
Write locally → Hand off → Lean on upstream → Cross-substrate → Primal orchestration
(metalForge) (wateringHole/) (barracuda ops) (metalForge forge) (biomeOS graphs)
Lean progress: 110 functions delegate to barracuda with graceful sovereign fallback.
67 CPU delegated via #[cfg(feature = "barracuda")], 43 GPU dispatched via
#[cfg(feature = "barracuda-gpu")]. V97: runtime f64 reduction smoke test
ensures GPU correctness — detects naga/SPIR-V zeros bug, graceful CPU fallback.
All local shaders absorbed upstream; only 2 unique anderson_lyapunov*.wgsl
reference shaders remain in metalForge. 13-tier tolerance architecture, all gates green.
NUCLEUS progress: biomeOS Neural API integration via #[cfg(feature = "biomeos")].
Tower (BearDog) health + beacon, Node (ToadStool) compute capabilities, Squirrel AI
health — all validated live. NestGate data pipelines (NCBI, NOAA GHCND, IRIS FDSN)
wired with sovereign fallback to synthetic data.
See specs/BARRACUDA_EVOLUTION.md for GPU promotion mapping.
See specs/PRIMAL_INTERACTION_EVOLUTION.md for NUCLEUS evolution.
See metalForge/ for absorption-ready shaders and the manifest.
| Spring | What It Validates | What groundSpring Adds |
|---|---|---|
| hotSpring | Clean nuclear math (f64, GPU) | How AME2020 mass uncertainties propagate to model predictions |
| airSpring | FAO-56 ET₀, soil calibration | The REAL sensor noise — quantifying factory vs field calibration |
| wetSpring | Microbiome taxonomy, PFAS detection | Sequencing error rates, mass spec noise floors |
| neuralSpring (future) | ML surrogates, transfer learning | groundSpring provides labeled dirty data; NPU dispatch via metalForge |
| biomeOS / NUCLEUS | Primal orchestration, data acquisition | groundSpring validates Tower+Node+Squirrel+Nest through Neural API |
groundSpring/
├── control/ # Phase 0 Python experiments
│ ├── common.py # Shared statistical primitives
│ ├── sensor_noise/ # Exp 001: bias-variance decomposition
│ ├── observation_gap/ # Exp 002: model vs station
│ ├── error_propagation/ # Exp 003: Monte Carlo through FAO-56
│ ├── sequencing_noise/ # Exp 004: taxonomic noise floor
│ ├── seismic/ # Exp 005: wave propagation + source inversion
│ ├── signal_specificity/ # Exp 006: c-di-GMP Gillespie SSA
│ ├── rawr_resampling/ # Exp 007: RAWR vs bootstrap
│ ├── anderson_localization/ # Exp 008: Anderson localization Lyapunov
│ ├── quasiperiodic/ # Exp 009: Almost-Mathieu Quasiperiodic
│ ├── bistable_switching/ # Exp 010: Bistable phenotypic switching
│ ├── multisignal_qs/ # Exp 011: Multi-signal QS integration
│ ├── spin_transport/ # Exp 012: Spin chain transport (Kachkovskiy 2016)
│ ├── resampling_convergence/ # Exp 013: Resampling convergence (Lee & Liu 2024)
│ ├── drift_selection/ # Exp 014: Drift vs selection (R. Anderson 2022)
│ ├── uncertainty_bridge/ # Exp 015: Sensor noise → Anderson ξ uncertainty
│ ├── rare_biosphere/ # Exp 016: Rare biosphere signal detection
│ ├── quasispecies_threshold/ # Exp 017: Eco-evolutionary noise threshold
│ ├── band_edge/ # Exp 018: Band edge structure
│ ├── jackknife_estimation/ # Exp 019: Jackknife error estimation (Bazavov 2025)
│ ├── freeze_out_inverse/ # Exp 020: Freeze-out inverse problem (Bazavov 2016)
│ ├── spectral_recon/ # Exp 021: Spectral function reconstruction (Bazavov 2025)
│ ├── et0_anderson_propagation/ # Exp 022: ET₀ → Anderson uncertainty
│ ├── notill_sampling/ # Exp 023: No-till vs tilled 16S sampling
│ ├── aggregate_stability/ # Exp 024: Aggregate stability noise
│ ├── precision_drift/ # Exp 025: f32 vs f64 precision drift
│ ├── size_convergence/ # Exp 026: System-size convergence
│ ├── vendor_parity/ # Exp 027: GPU vendor parity
│ ├── npu_anderson/ # Exp 028: NPU Anderson regime classification
│ └── et0_methods/ # Exp 034: Multi-method ET₀ cross-validation
├── crates/
│ ├── groundspring/ # Phase 1 Rust library (40 modules incl. rawr, esn, lanczos, tissue_anderson, biomeos, nestgate, npu, primal_names)
│ └── groundspring-validate/ # 34 validation binaries (hotSpring pattern)
├── metalForge/ # Write → Absorb → Lean artifacts
│ ├── forge/ # groundspring-forge crate: hardware discovery, dispatch, topology, pipeline, atomics, remote
│ ├── npu/akida/ # AKD1000 NPU integration, HARDWARE.md
│ ├── ABSORPTION_MANIFEST.md # Module-by-module absorption inventory
│ └── shaders/ # Production WGSL shaders for ToadStool absorption
├── graphs/ # biomeOS pipeline graphs (deploy, Tower, Node, cross-substrate, validation)
├── niches/ # BYOB niche YAML definitions (groundspring-measurement)
├── .github/workflows/ci.yml # GitHub Actions CI
├── wateringHole/ # Handoff directory (V119 current)
├── specs/
│ ├── BARRACUDA_EVOLUTION.md # Module → GPU promotion mapping + PRNG roadmap
│ ├── BARRACUDA_REQUIREMENTS.md # GPU kernel gap analysis
│ ├── CROSS_SPRING_EVOLUTION.md # Cross-spring shader provenance
│ ├── PRIMAL_INTERACTION_EVOLUTION.md # NUCLEUS Neural API evolution (V0–V6)
│ ├── LAN_DEPLOYMENT_READINESS.md # LAN HPC readiness assessment
│ └── PAPER_REVIEW_QUEUE.md # 30 papers, three-tier control matrix, open data audit
├── whitePaper/ # Study, methodology, baseCamp, experiments
│ ├── baseCamp/ # Per-faculty research briefings (7 faculty)
│ ├── experiments/ # Per-experiment summaries (001-035)
├── tests/ # Python test suite (29 experiments + parity)
├── Cargo.toml # Rust workspace (barracuda feature gate)
├── CONTRIBUTING.md
├── CHANGELOG.md
└── LICENSE # AGPL-3.0-or-later
Same as all ecoPrimals springs:
| Component | Specification |
|---|---|
| CPU | Intel i9-12900K (16C/24T, 5.2 GHz) |
| RAM | 64 GB DDR5-4800 |
| GPU | NVIDIA GeForce RTX 4070 (12 GB VRAM) |
| GPU | NVIDIA Titan V (12 GB HBM2) |
| NPU | BrainChip AKD1000 (80 NPs, 10 MB SRAM, PCIe 2.0 x1) |
| Storage | 1 TB NVMe SSD |
| OS | Pop!_OS 22.04 (Ubuntu-based) |
AGPL-3.0-or-later — See LICENSE
| Version | Date | Milestone |
|---|---|---|
| Init | Feb 16 | Repository initialized |
| Phase 1 | Feb 25 | 29 experiments PASS in Rust |
| V21 | Feb 26 | Complete barraCuda rewiring |
| V26 | Feb 27 | metalForge live hardware (RTX 4070, Titan V, AKD1000) |
| V39 | Feb 27 | NUCLEUS integration + NestGate data pipelines |
| V53 | Feb 28 | 57 active delegations + GPU grid adapters |
| V68 | Mar 2 | L-BFGS refinement, 4D Anderson |
| V76 | Mar 5 | Structural evolution, deep debt zero |
| V85 | Mar 6 | coralReef sovereign compilation (SM70/SM89) |
| V97 | Mar 7 | Three-tier parity proven (29/29 binaries × 3 tiers) |
| V110 | Mar 16 | Cross-ecosystem absorption, #[expect(reason)] migration |
| V115 | Mar 18 | Zero panicking APIs, ecoBin compliance, 930+ tests |
| V118 | Mar 19 | RPC expansion (16 caps), 110 delegations, 960+ tests |
| V119 | Mar 22 | Deep audit + cross-ecosystem absorption, 990+ tests, ≥92% coverage |
Part of ecoPrimals · wateringHole · AGPL-3.0-or-later