{
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  "slug": "paper-problem-substrate-mapping",
  "title": "The Problem-Substrate Mapping: A Framework for Honest Computational Investment",
  "authors": [
    "Rowan Brad Quni-Gudzinas"
  ],
  "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%.",
  "abstract_markdown": "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%.",
  "date": "2026-07-08",
  "first_published": "2026-07-08",
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  "modified": "2026-09-14T14:50:50Z",
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    "titles": [
      {
        "title": "The Problem-Substrate Mapping: A Framework for Honest Computational Investment"
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    "publicationYear": "2026",
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        "subject": "problem-substrate mapping"
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      {
        "subject": "thermodynamic computing"
      },
      {
        "subject": "neuromorphic computing"
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      {
        "subject": "optical computing"
      },
      {
        "subject": "quantum computing"
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        "description": "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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