Vacuum Intelligence Architecture Specification: Event-Driven Analog Memristor Optimal Power/Flow Solver Integration

We present a unified hardware-software architecture for resilient, antifragile decision-making in contested logistics environments. The system is built on a stochastic reservoir computer governed by a double-well Langevin equation, a hyperbolic echo state network (HypER) for hierarchical representation, a synchronicity order parameter for early disruption detection, and a meta-optimizer that performs simulated annealing over reservoir parameters to improve recovery after shocks. The core innovation is a dual-mode memristor crossbar that functions both as the physical reservoir and as an event-driven analog optimal power/flow (OPF) solver. This reconfigurable fabric eliminates the need for a digital convex optimization engine, reduces SWaP, and transforms the hypothesis generator into a physically grounded planner. Full mathematical mappings, hardware specifications, and a TRL 2 to TRL 6 roadmap are provided.Version 1.2

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-12
DOI
https://doi.org/10.5281/zenodo.20669318
Primary Topic
Neural Networks and Reservoir Computing
Type
article
Field-Weighted Citation Impact
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article

Vacuum Intelligence Architecture Specification: Event-Driven Analog Memristor Optimal Power/Flow Solver Integration

Damon John
Zenodo (CERN European Organization for Nuclear Research)
Neural Networks and Reservoir Computing
article

Vacuum Intelligence Architecture Specification: Event-Driven Analog Memristor Optimal Power/Flow Solver Integration

Damon John
article en

Abstract

We present a unified hardware-software architecture for resilient, antifragile decision-making in contested logistics environments. The system is built on a stochastic reservoir computer governed by a double-well Langevin equation, a hyperbolic echo state network (HypER) for hierarchical representation, a synchronicity order parameter for early disruption detection, and a meta-optimizer that performs simulated annealing over reservoir parameters to improve recovery after shocks. The core innovation is a dual-mode memristor crossbar that functions both as the physical reservoir and as an event-driven analog optimal power/flow (OPF) solver. This reconfigurable fabric eliminates the need for a digital convex optimization engine, reduces SWaP, and transforms the hypothesis generator into a physically grounded planner. Full mathematical mappings, hardware specifications, and a TRL 2 to TRL 6 roadmap are provided.Version 1.2

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 4%
Neural Networks and Reservoir Computing
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Vacuum Intelligence Architecture Specification: Event-Driven Analog Memristor Optimal Power/Flow Solver Integration — Damon John · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS