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

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%.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-14
DOI
https://doi.org/10.5281/zenodo.22753170
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
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article

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

Rowan Brad Quni-Gudzinas, QNFO Research Collective
Zenodo (CERN European Organization for Nuclear Research)
Quantum Computing Algorithms and Architecture
article

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

Rowan Brad Quni-Gudzinas, QNFO Research Collective
article en

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%.

Zenodo (CERN European Organization for Nuclear Research)
Q-Flex (United States) (US), Camber Collective (United States) (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 8%
Quantum Computing Algorithms and Architecture
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