Tsogt Baigalmaa

Bridging mathematics, physics, and computation

The framework is a computational pipeline for the procedural generation and physical evolution of complex manifolds. By decoupling geometric topology from dynamical integration, the system enables simulations ranging from stable orbital dynamics to morphogenesis within a unified, high-throughput execution context.

Manifold Sampling

A module for generating uniformly distributed 1D, 2D, and 3D geometry.

  • GC-aware loops & out-parameter patterns.
  • AABB, importance weighting & iterative rejection.
  • LUT, uniform arc-length & binary search sampling.
  • Efficient spatial transformations of composites.

Dynamical Systems

A time-integration core for state evolutions under arbitrary vector fields.

  • State derivatives & semi-implicit Euler.
  • GPU-native & CPU cache-friendly memory layout.
  • CPU-to-GPU Float32Array buffer streaming.
  • Zero-copy views via .subarray().

Case study: Morphogenesis

A case study in complex systems, applying the engine to the Hydrophobic-Polar (HP) model and what I call a Homogeneous Relaxation (HR) of high-entropy initial states.

Note: [ I am no expert in biology. ] The (HP) model and the (HR) process are used here as a simplified, toy abstractions to explore the capabilities of the engine, not to make claims about real biophysical mechanisms.

  • Bypassing O(N2) bottleneck.
  • Spatial Hash Grid.
  • Hyperparameter Optimization.
  • Thermal Brownian motion.