The Chaotic Vortex Score: A Deterministic Topological Invariant with Applications to DNA, Polymer, and Protein Classification

Description / Abstract:

This cientific approach intends to be a system that could save billions of dollars in the implementation of high-throughput drug discovery and advanced materials engineering.

Current R&D pipelines for pharmaceuticals suffer from a critical bottleneck: the computational cost of simulating molecular interactions is incredibly high, leading to slow time-to-market and expensive failures.

The Chaotic Vortex Score (CVS) is a high-efficiency classification engine designed to eliminate this bottleneck. By replacing slow, legacy analysis methods with a streamlined scoring system, we achieve processing rates of ~293,000 interactions per second on standard, low-cost hardware.

This extreme throughput allows organizations to:

1. Slash Compute Costs: Process massive datasets on commodity devices instead of expensive supercomputing clusters.
2. Accelerate Time-to-Market: Screen entire molecular libraries in seconds rather than weeks.
3. Reduce Failure Rates: Identify and discard non-viable drug candidates immediately, before investing in costly trials.

This paper presents the methodology and the engine capable of driving this efficiency at scale.