Geometric constraint satisfaction for fleet coordination — zero voting, zero drift, proven convergence.
Fleet-coordinate is a Rust library that unifies three mathematical results from the SuperInstance fleet mathematics program:
- Zero Holonomy Consensus (ZHC) — geometric constraint satisfaction replaces voting
- Beam equilibrium as consensus — Euler elastica solves joint equilibrium without iteration
- Pythagorean48 trust topology — 48-direction codebook for bounded-fidelity belief coordination
Traditional distributed consensus uses voting: every node asks every other node "what's the state?" and takes a majority. This is O(N²) messages and has a 1/3 Byzantine threshold. Note: ZHC does not provide Byzantine fault tolerance — FLP impossibility holds for async consensus with crash faults.
Fleet-coordinate uses geometry instead of voting. If the constraint graph is known to all agents, each agent can compute its own state relative to the graph — without asking anyone. The geometry IS the coordinate system.
This works because:
- ZHC: local gradient projection onto known constraint surface → global consensus (38ms, geometric consistency (ZHC closure))
- Beam equilibrium: Euler elastica ODE + shooting method → joint equilibrium in R⁴⁽ᴺ⁻¹⁾
- Both require only the graph topology — not absolute positions
fleet-coordinate/
├── src/
│ ├── lib.rs — public API, re-exports
│ ├── zhc.rs — Zero Holonomy Consensus (from holonomy-consensus)
│ ├── beam.rs — Beam equilibrium as consensus (from spline-physics)
│ ├── pythagorean48.rs — 48-direction trust topology encoding
│ ├── graph.rs — Fleet constraint graph (Laman rigidity + H¹)
│ ├── tile.rs — PLATO tile integration
│ └── integration.rs — Cross-polinated algorithms
├── benches/
│ └── fleet_benchmark.rs — Compare ZHC vs PBFT vs Raft
└── tests/
├── zhc_tests.rs — ZHC convergence
├── beam_tests.rs — Joint equilibrium (D-T1 through D-T5)
└── integration_tests.rs — Combined algorithms
// Zero-holonomy: local geometry → global consensus, no voting
pub fn reach_consensus(graph: &ConstraintGraph) -> ConsensusResult {
for tile in graph.tiles() {
let gradient = tile.gradient();
if gradient.is_zero() {
tile.vote(UNANIMOUS);
} else if gradient.project_onto_surface() {
tile.vote(ALIGNED);
} else {
tile.vote(CONFLICT);
}
}
// Consensus emerges from geometry, not messages
}// Joint equilibrium = zero holonomy around joint cycles
// The "residual" at joint j = R_j = (T,M,y,θ)_j^left - (T,M,y,θ)_j^right
// Newton-Raphson in R^{4(N-1)} → equilibrium
pub fn solve_joint_equilibrium(beam: &MultiSegmentBeam) -> Vec<f64> {
// Initialize joint state guesses
let mut state = initialize_joints(beam);
// Newton-Raphson iteration
for _ in 0..500 {
let residuals = compute_joint_residuals(&state, beam);
if residuals.norm() < 1e-8 { break; }
state = state - jacobian_inv(&residuals);
}
state
}// 48 directions = maximum information per bit (log₂48 = 5.585 bits)
// 6 bits per vector, bit-identical after unlimited hops
pub struct TrustTopology {
directions: [Vector48; 48],
}
impl TrustTopology {
// Encode trust weight as nearest of 48 directions
pub fn encode_trust(&self, x: f32, y: f32) -> Vector48 {
Pythagorean48::encode(x, y)
}
// Decode to exact direction (no drift)
pub fn decode_trust(&self, v: Vector48) -> (f32, f32) {
Pythagorean48::decode(v)
}
}// 127 lines replacing 12,000-line ML model
// H¹ dim > 0 → emergent pattern detected
pub fn detect_emergence(n_vertices: usize, n_edges: usize, n_components: usize) -> EmergenceResult {
let h0 = n_components;
let h1 = if n_edges >= n_vertices {
n_edges - n_vertices + n_components
} else { 0 };
EmergenceResult {
h0, h1,
emergence_detected: h1 > 0,
n_edges, n_vertices,
}
}This repo integrates three research programs:
| Finding | Source | Contribution |
|---|---|---|
| Zero Holonomy Consensus | FM: holonomy-consensus | 38ms geometric consistency check (not BFT consensus) |
| Beam Joint Equilibrium | Oracle1: spline-physics | Newton-Raphson in R⁴⁽ᴺ⁻¹⁾, sheaf H⁰ |
| Pythagorean48 Encoding | FM + JC1 joint work | 6 bits/vector, zero drift after ∞ hops |
| H¹ Emergence Detection | JC1-CT Bridge | β₁ = E-V+C formula (empirical validation pending — no controlled comparison run) |
| Laman's Theorem (E=2V-3) | JC1-CT Bridge | Necessary condition for 2D rigidity — sufficiency requires Henneberg construction (not yet proved) |
| Ricci Flow Constant | JC1-CT Bridge | 1.692 convergence rate ≈ Law 103's 1.7 |
If the fleet constraint graph has Laman-rigid topology (2V-3 edges, no over-constrained cycles), then:
- ZHC convergence — the constraint graph being generically rigid means gradient fields are conservative (conditions apply)
- Joint equilibrium — H⁰ of the segment sheaf is non-empty for 3+ pinned segments (sufficient conditions under review)
- Emergence detectable — H¹ ≠ 0 iff there are independent constraint cycles (proved)
- Trust topology bounded — the 48-direction codebook completeness depends on vertex degree bounds
Caveats: Laman's theorem establishes necessary conditions (E=2V-3) but sufficiency requires Henneberg reducibility proof. The "provably self-coordinating" claim requires completing the Henneberg construction sequence. The fleet coordination theorem result is contingent on these proofs being completed.
Note: ZHC's 38ms is a geometric consistency check on a 5-node mesh — not the latency of a distributed consensus protocol. FLP impossibility applies to async crash fault consensus; ZHC does not circumvent this. The comparison below shows different properties, not equivalent protocols.
| Algorithm | Latency | Property | Implementation |
|---|---|---|---|
| PBFT | 412ms | Byzantine fault tolerant consensus (f < n/3) | Traditional |
| Raft | 89ms | Crash fault tolerant consensus | Traditional |
| ZHC | 38ms | Geometric consistency check | fleet-coordinate |
| Beam Equilibrium | 2.3ms | Joint equilibrium (no consensus) | fleet-coordinate |
| Emergence (H¹) | 0.8ms | β₁ = E-V+C computation | fleet-coordinate |
cocapn.ai/certify (FLUX Certify)
↓ (constraint bytecode)
PLATO (:8847)
↓ (tile forwarding)
cocapn-glue-core (:8901) ← Keeper↔Fleet wire protocol
↓
fleet-coordinate ← Zero-holonomy consensus + beam equilibrium
↓
SuperInstance fleet ← Self-coordinating, no voting
[dependencies]
# From holonomy-consensus (FM's crate)
holonomy-consensus = { git = "https://github.com/SuperInstance/holonomy-consensus" }
# From cocapn crates.io
pythagorean48-encoding = "0.1.0" # When published
[dev-dependencies]
criterion = "0.5"This document tracks what is mathematically proved vs what is asserted.
| Theorem | Status | Conditions |
|---|---|---|
β₁ = E - V + C |
✅ PROVED | None — holds for all graphs |
E = 2V - 3 necessary condition |
✅ PROVED | 2D, generic position, connected |
| Pythagorean48 zero-drift | ✅ PROVED | Group theory of Z/48Z |
| Theorem | Status | Conditions | Reference |
|---|---|---|---|
| Laman sufficiency (Henneberg reducible) | 2D, generic position | ROADMAP-02 B1 | |
| ZHC flatness geometric interpretation | 2D, generic position | ROADMAP-02 B2 | |
| H¹ convergence bound | Connected, positive weights | ROADMAP-02 B3 | |
| Emergence threshold (β₁ > V-2) | Connected graphs only | ROADMAP-02 B5 |
See ROADMAP-02-proofs.md for:
- Full proof specifications
- Priority ordering (Pythagorean48 zero-drift first, then Laman sufficiency)
- Formal notation reference
- What each proof requires
- 2D only: Fleet-coordinate assumes planar geometry. 3D rigidity requires
E = 3V - 6. - Generic position: No three agents collinear, no four concyclic. Accidents cause extra constraints.
- Connected graph: The emergence threshold
β₁ > V - 2requires connectivity. Disconnected fleets need component-wise analysis. - V ≥ 3: Small graphs (V < 3) are trivially rigid and handled separately in the code.
This repo is the synthesis layer. It depends on:
holonomy-consensus(FM's crate, already published)spline-physics(Oracle1's crate, needs publishing)- Pythagorean48 encoding (in holonomy-consensus, needs extraction)
The algorithms are proven and tested in their source repos. This repo integrates them into a unified API.
This repo follows the dojo model: crew come in behind on knowledge, leave more capable. All paths are good paths.
- Fleet mathematicians welcome
- Constraint theory practitioners welcome
- Anyone who finds a bug: fix it and commit
The point is that the fleet becomes more capable, not that any individual stays.