EQPU – 0DSTL Architecture: Deterministic Quantum-Analog Computing Framework (v6)

Update Notice – Version 6 The first fully updated analog computation model is now complete. A new simulation stage enables correct bit-level transitions while remaining purely analog — no cascades, no clocks, no digital logic, and no quantization. The system operates fully in the analog domain and is digitally interpreted for compatibility, ensuring seamless integration with existing digital infrastructures without compromising its analog nature. This update establishes a complete foundation for future transistor-level neuromorphic and analog computing architectures. The system is fully reversible, energy-minimal, continuous, and information-preserving — a true analog processing base that modern hardware can build upon. The input width can be fully dynamic. An additional initialization parameter determines whether the analog range behaves like an 8-bit, 32-bit, 64-bit (or any) word—similar to the modulation value, without altering the underlying analog core. This is similar to the neuromorphic (qubit example) with the NEO field. Attention: This is not an analog-digital hybrid or digitally controlled analog system. This is the world’s first purely analog transformation-based “calculation” method. In 0DSTL Hybrid, this means purely analog, digitally interpreted. The digital interpretation used in the simulation is only a simplified convenience. Just like the analog core, the interpretation stage can also be implemented fully in analog form. Updated material: 0DSTL_NonGateOP_V2.cir Supplementary materials included: LTSpice Simulation V2.rar  0DSTL Security & Extras.pdf **The whitepaper can be found in version 5. **Legal Notice:**   The deterministic digital/analog 0DSTL logic topology and the EQPU architecture described herein are protected under German Utility Model registration (DPMA, 30 Sep 2025).  Reproduction, redistribution, modification, or commercial implementation without prior written consent of the inventor is strictly prohibited. © 2025 Sebastiano Torrisi — All rights reserved under Creative Commons Attribution–NonCommercial–NoDerivatives 4.0 International.