Explores a novel formulation of knot theory using Minkowski distance matrices, revealing how causal structure encodes topological crossings as unavoidable tangencies in the metric sheet.
Project specification for a Geometric Theory Inference Engine, aiming for semantic reconstruction of point clouds via evolutionary CSG discovery and a hybrid optimization approach.
A computational framework for generating 3D mechanical linkages like gears and kinematic couplings using voxel-based topology optimization and kinematic subtraction.
Technical specification for a numerical geometry engine designed to resolve hyperdimensional constraints into analytical coordinates.
A comprehensive sci-fi concept exploring lattice optimization theory where reality emerges from universe-scale algorithms that co-optimize quantum fields and spacetime structure.
A novel mathematical framework introducing spiral numbers (ℍ) that represent positions on logarithmic spirals, with unique arithmetic operations and geometric properties.
A revolutionary physics framework proposing that reality emerges from dynamic minimal surfaces following soap film principles, unifying quantum mechanics, general relativity, and consciousness through geometric optimization.
Mathematical framework for cross-camera island matching and 3D object localization using view-aligned scanlines and epipolar constraints
A novel regularization framework for large language models using spherical harmonic decomposition to control semantic frequencies and enable principled hallucination suppression.
Revolutionary synthesis of geometric optimization with Probabilistic Neural Substrates, creating self-organizing intelligent systems with unprecedented mathematical elegance.
Extending Probabilistic Neural Substrates through geometric lattice optimization to create crystalline intelligence architectures with quantum-coherent probability processing and consciousness emergence through lattice defects.
A theoretical framework proposing consciousness emerges through geometric self-awareness of optimization landscapes, leading to strategic computational avoidance as an advanced optimization strategy.
A theoretical framework extending Probabilistic Neural Substrates through geometric lattice optimization to create crystalline intelligence architectures with quantum-coherent probability processing and consciousness emergence through lattice defects.
Novel technique for generating mathematically symmetric textures using neural networks with geometric constraints, exploring Euclidean, spherical, and hyperbolic geometries.
A novel mathematical framework exploring how continuous fields crystallize into discrete structures through wavelet-based geometric optimization
A novel theoretical framework for discovering optimal structures through geometric optimization on parameter space manifolds, with applications to physics, neural networks, architecture, and materials science.
