Objective: To establish a comprehensive and up-to-date baseline of hardware performance and costs for each candidate architecture and the classical baseline. Actions: • Collect the latest, peer-reviewed metrics on coherence times, gate fidelities, energy requirements, and access pricing for all five quantum architectures (trapped-ion, superconducting, photonic, topological, neutral-atom) as well as 8 × A100 classical GPU clusters. • Source data from public spec sheets, technical white papers, and direct communication with quantum cloud providers (IonQ, IBM Q, AWS Braket, etc.). • Integrate these metrics into a starter throughput-per-dollar table (χ), normalizing across paradigms for direct comparison. • Document all sources and assumptions, ensuring transparency and reproducibility.

A baseline χ table with supporting documentation, forming the foundation for subsequent experimental phases.

$4,190 USD

Milestone 1 will be considered successful if a transparent, normalized χ baseline is created for all six compute architectures, using at least four validated performance and cost metrics per platform, backed by reproducible documentation, and ready to support cross-paradigm benchmarking in later phases.

Objective: To empirically measure the execution performance and error behavior of OpenCog Hyperon’s core cognitive kernels across classical (GPU) and available quantum backends, producing its throughput-per-dollar (χ) of each architecture on key AGI micro-tasks under controlled scenarios. Actions: 1. Kernel Selection & Formalization 2. Hardware-Specific Compilation 3. Simulated & Native Execution 4. Throughput and Fidelity Analysis 5. Cross-Platform Benchmark Table

Deliverable: A kernel-specific χ benchmark report, containing: • Executable representations of each kernel. • Compilation traces and circuit schematics. • Benchmark tables of real and simulated performance across platforms. • Annotated heatmaps comparing throughput, cost, and fidelity. • Diagnostic notes on failure modes or compile-time bottlenecks.

$12,165 USD

Phase 2 will be successful when OpenCog Hyperon’s core AGI kernels are implemented and executed across both classical and multiple quantum hardware backends, yielding real, fidelity-adjusted χ values with full traceability. This outcome establishes the first comparative performance baseline for AGI-relevant computation across emerging quantum paradigms.

Objective: To project how each quantum architecture must evolve—across gate fidelity, decoherence time, qubit count, compilation efficiency, or cost—to outperform classical hardware on AGI kernel tasks. This phase quantifies how far each paradigm is from crossing the "quantum advantage frontier" in AGI workloads and identifies the most leverageable parameters. Actions: 1. Construct Frontier Models 2. Sensitivity Analysis 3. Construct Quantum Advantage Frontier 4. Forecast Platform Readiness 5. Prescribe Development Priorities

• A set of χ parametric models (analytical or empirical) • Sensitivity heatmaps and elasticity plots per platform • Quantum Advantage Surface plots (2D/3D) • Distance-to-frontier scores with annotated platform gaps • Timeline and feasibility scorecard (including alignment with vendor roadmaps)

$14,475 USD

Phase 3 will be considered successful when the project produces calibrated, platform-specific models of χ (fidelity-adjusted throughput-per-dollar), quantifies how each key hardware parameter affects performance, and defines the exact technical conditions under which each quantum architecture can surpass the classical GPU baseline in AGI workloads.

Objective: To convert benchmarking results and frontier models into a realistic, staged deployment strategy. This phase determines which quantum architecture is most viable for short- to medium-term AGI integration, which AGI kernels it should run, and how development teams should proceed, technically and operationally, toward hybrid and native quantum AGI execution. Actions 1. Platform Suitability Ranking 2. Kernel–Platform Affinity Mapping 3. Deployment Model Design 4. Timeline + Risk Model 5. Output Strategy Toolkit

• Platform ranking index and scoring methodology. • AGI kernel-to-platform affinity matrix. • Deployment architecture diagrams (hybrid, kernel-attached, full native). • Timelines with capability checkpoints. • Strategic risk memo for investors, CTOs, and research leads. • Open-source toolkit for reproducing χ-based benchmarking.

$9,170 USD

Phase 4 will be successful when benchmarking insights and quantum frontier projections are translated into a realistic, technically sound deployment strategy. This includes selecting the most viable quantum architecture, mapping AGI kernels to hardware capabilities, defining integration models, and delivering an actionable roadmap supported by risk and timeline analysis.