The Problem-Substrate Mapping: A Framework for Honest Computational Investment

DOI: 10.5281/zenodo.21255346 July 8, 2026
Phase IV of the Qubit Delusion series. Translates the critique into a concrete investment portfolio: matching computational problem classes (optimization, linear algebra, probabilistic inference, quantum simulation, cryptography, general-purpose) to optimal physical substrates (Ising machines, optical processors, neuromorphic, analog quantum simulators, reversible classical, fault-tolerant QC). Proposes a standardized five-question evaluation framework with red flags and green flags. The resulting portfolio allocates ~45% to thermodynamic/analog, 25% to optical, 20% to neuromorphic, and ~10% to quantum — a near-inversion of current R&D allocation where gate-model QC absorbs ~60%.

The Problem-Substrate Mapping: A Framework for Honest Computational Investment

Authors: ["QNFO Research Collective"]

Published: 2026-07-08

DOI: [10.5281/zenodo.21255346](https://doi.org/10.5281%2Fzenodo.21255346)

Abstract

Phase IV of the Qubit Delusion series. Translates the critique into a concrete investment portfolio: matching computational problem classes (optimization, linear algebra, probabilistic inference, quantum simulation, cryptography, general-purpose) to optimal physical substrates (Ising machines, optical processors, neuromorphic, analog quantum simulators, reversible classical, fault-tolerant QC). Proposes a standardized five-question evaluation framework with red flags and green flags. The resulting portfolio allocates ~45% to thermodynamic/analog, 25% to optical, 20% to neuromorphic, and ~10% to quantum — a near-inversion of current R&D allocation where gate-model QC absorbs ~60%.

---

This paper is part of the QNFO research corpus.

Ask QWAV about this paper

Related Papers