Continuous-Variable Kinematic Computing: A Hydrodynamic Architecture
Ivaylo Anastasov
The rapid development of modern computing has historically focused on the manipulation of discrete logic states—first through classical binary transistors (0 and 1), and more recently through the probabilistic superposition of qubits. While discrete-state quantum computing offers profound theoretical advantages, the practical engineering of these systems faces significant challenges, most notably environmental decoherence and extreme cryogenic cooling requirements. This paper proposes a complementary analog computing architecture inspired by the Rapid Alignment Kinematic Theory of Spin (RAKTS). Rather than attempting to isolate discrete probability states from a noisy environment, this architecture embraces the environment as a continuous computational medium. By modeling information not as probabilistic amplitudes, but as continuous geometric "Vector Nodes" subject to physical hydrodynamic drag (Landau-Lifshitz damping), we outline the theoretical foundation for an Analog Topological Processor. We demonstrate that non-linear environmental interactions, typically modeled as destructive decoherence in quantum systems, can function as a stabilizing geometric funnel to drive the system into robust logical attractors at room temperature. Finally, we establish the Turing completeness of the framework by simulating a universal Kinematic NAND Gate driven by background field bias and fluid-dynamic resistance, presenting a noise-resilient alternative for next-generation analog hardware accelerators. Keywords Analog Computing, Kinematic Logic Gate, Hydrodynamic Drag Computation, Continuous-Variable Processor, Turing-complete Analog Hardware, Decoherence-free Logic, Field Medium, RAKTS Additional Info Repository: https://github.com/rt20bg/Anastasov_Theory
•Jun 7, 2026•0 citations