Crate constraint_theory_core 

Constraint Theory Core - High-Performance Geometric Engine

This crate provides the core mathematical operations for the SuperInstance Constraint Theory system, including:

• Pythagorean snapping (Phi-Folding Operator)
• Ricci flow evolution
• Holonomy transport
• Sheaf cohomology
• Rigidity percolation

Performance

• Target: <100ns per tile operation
• SIMD: AVX2/AVX-512 for x86_64, NEON for ARM
• Memory: Zero-allocation hot paths

Example

use constraint_theory_core::{PythagoreanManifold, snap};

let manifold = PythagoreanManifold::new(200);
let vec = [0.6f32, 0.8];
let (snapped, noise) = snap(&manifold, vec);
assert!(noise < 0.01);

SIMD Batch Processing

For high-throughput applications, use SIMD batch processing:

use constraint_theory_core::PythagoreanManifold;

let manifold = PythagoreanManifold::new(200);
let vectors = vec![[0.6, 0.8], [0.8, 0.6], [0.1, 0.99]];
let results = manifold.snap_batch_simd(&vectors);

for (snapped, noise) in results {
    println!("Snapped: {:?}, Noise: {}", snapped, noise);
}

Re-exports

pub use curvature::ricci_flow_step;

pub use curvature::RicciFlow;

pub use manifold::snap;

pub use manifold::PythagoreanManifold;

pub use manifold::PythagoreanTriple;

pub use percolation::FastPercolation;

pub use percolation::RigidityResult;

pub use tile::ConstraintBlock;

pub use tile::Origin;

pub use tile::Tile;

Modules

cohomology

Sheaf Cohomology Computation

curvature

Ricci Flow and Curvature Computation

gauge

Gauge Connection and Parallel Transport

kdtree

KD-tree spatial index for fast constraint state lookup

manifold

Pythagorean Manifold - The Rigidity Matroid

percolation

Rigidity Percolation using Laman’s Theorem

simd

SIMD-optimized operations for constraint theory

tile

Core data structures for the Constraint Theory engine

Enums

CTErr

Core error type

Constants

VERSION

Version information

Type Aliases

CTResult

Result type for constraint theory operations