QPC Highlights

Five tasks — hardware reach & JSON evidence

T01–T02: co-resident contexts on 156Q · T03–T04: cluster jobs with in-circuit bridges · T05: 24-context logistics (six jobs). See benchmarks page for honest scope.

Pilot on ibm_fez (16 cars, 48 vars, June 2026)

QPC decoder: 2 congested roads — ties greedy, QAOA, and 3-zone merge; beats random 7.46. Full suite: 5 IBM jobs on Fez (QPC job d8gq8q42upec739k6skg). Same score as 3-zone sequential — one coupled submission vs three.

Two documents (PDF + web)

Each pilot page links the author PDF (correct tables) and shows 3D diagrams derived from qpc_artifacts JSON (stage-wise scale-up and 156-qubit layout).

Author PDFs (correct table layout): Phase 1 (PDF) · Final report (PDF)

PQST-64 on a 64-Qubit Superconducting Quantum Processor

PQST-64 is a context-driven sampling benchmark (64 qubits, 30 cycles) run on IBM hardware. Unlike standard random circuit sampling (RCS), the circuit is deterministically generated from polycontextural logic. Executed on ibm_fez with 5000 shots; 100% uniqueness (5000/5000 distinct outcomes)—high-entropy output comparable in statistics to RCS at this scale; not by itself a claim of quantum advantage.

64Q PQST vs RCS: Identical Metrics on IBM Quantum

Direct comparison of PQST (context-driven) vs RCS (random gates) at 64 qubits, 30 layers, same brickwork connectivity. Both ran on IBM Quantum with 5000 shots. Matched statistics: heavy output probability 0.5002, entropy 12.29 bits, 5000 unique outcomes each—structural equivalence at this benchmark scale, not a standalone advantage claim.

QPC Detects Global Financial Crash Phase Transition

128 qubits on IBM Torino — QPC-SRD (Quantum Polycontextural Systemic Risk Detection) identifies cascade default probability, systemic collapse threshold θ, and most dangerous financial nodes. Unlike IBM/Vanguard portfolio optimization, QPC finds crash attractor states. Execution: 39.64s. 128 institutions (banks, asset managers, central banks), 4096 unique outcomes.

QPC HSBC Fraud Detection Pilot (PC-QRC-FD)

Executive outcome: QPC delivered a complete fraud-pilot workflow from data preparation to simulator benchmarking and IBM hardware execution. The pilot establishes technical feasibility, transparent benchmarking discipline, and a credible path toward bank-grade evaluation with sponsor data.

Hardware note: The archived Fez run uses full logical width (156 qubits), twelve contextures, scalable z+ctxpool readout, and the optional in-repo qpc_noise_reducer.py hook for shot-domain aggregation. IBM instance/token routing took iterative troubleshooting (documented on the sources page) — a normal artifact of cloud quantum accounts, not of the architecture alone.

PRCBS — RICT, CPRP, PCRT on IBM Torino & Fez

PRCBS (Polycontextural Relational Computation Benchmark Suite) runs three tests on real IBM hardware: RICT (relational encoding), CPRP (contextual phase reconstruction), PCRT (cascade reconstruction). Executed at 128Q and 156Q on IBM Torino and IBM Fez; 4096/4096 unique outcomes and 12.0 entropy on all three. Validates that QPC encodes relational, contextual, and cascade structure and produces maximum diversity on hardware.

Full-Pattern Reconstruction from Partial Measurement

This test demonstrates a distinct QPC architectural layer: distributed encoding and holographic-style reconstruction from partial observation. A pattern is encoded into a polycontextural interference field; only a subset of qubits is measured (e.g. 16 of 32). From that partial readout the full pattern is reconstructed—mirroring optical holography, associative memory, and distributed representation. Ideal vs hardware comparison shows the task is mastered in principle; results on Fez are restricted by device noise.

27Q → 64Q → 128Q on ibm_fez — ZZ correlators, ICC, FSP

PFQM V3 is the noise-first polycontextural frustrated-magnet family: three morphogrammatic contextures (FM, AFM, spin-liquid) plus minimal transjunction bridges on ibm_fez (Heron). Metrics are physical ZZ correlators from raw counts—ICC (even/odd bridge asymmetry) and FSP suppression (ctx2 vs. single-context baseline)—not high-dimensional bitstring entropy alone. Independent hardware campaigns at 27, 64, and 128 qubits (4096 shots, eight θ points each) give a scaling curve: mean ICC stays above the structured threshold on average; ctx2 stays the most frustrated block vs. ctx0 across scales. Full protocol, charts, and scorecard narrative live on the overview page; per-θ tables and IBM job IDs are on the data page.

QPC 3-Layer Architecture Verification

This test provides explicit, verifiable proof that QPC's 3-layer hierarchical architecture executes correctly on real IBM Quantum hardware. It verifies the architectural structure itself—proving that the three distinct layers (Kenogrammatic, Morphogrammatic, and Transjunctional) are properly constructed, transpiled, and executed on quantum hardware.

Multi-Contextual Global Supply Chain Optimization

This test demonstrates QPC's unique polycontextural capabilities by solving a real-world global supply chain optimization problem with 8 simultaneous optimization contexts. Unlike classical systems that optimize sequentially, QPC optimizes all contexts simultaneously, finding solutions that satisfy all constraints at once.

Multi-Contextual CO2 Emissions Optimization

This test demonstrates QPC's ability to solve real-world climate problems using real-world data. It optimizes CO2 emissions reduction across the world's top 20 emitting countries while simultaneously considering 8 different factors: emissions, economics, regulations, energy transition, geopolitical risks, technology availability, costs, and social impact. Uses actual CO2 data from the OWID dataset and GDP data from World Bank API.

2-Context True Parallel Quantum-Mechanical Multi-Contextual Computation

This test proves QPC architecture works with TRUE parallel quantum-mechanical multi-contextual computation. Unlike the 8-context test that runs contexts individually (due to hardware limits), this test executes both contexts simultaneously in a single quantum circuit with quantum-mechanical transjunctions connecting them.

⚠️ Hardware Limitation: We cannot run all 8 contexts simultaneously because NO quantum computer provider (IBM, Google, IonQ, Quantinuum, etc.) currently offers public access to systems with 520+ qubits. IBM confirmed Condor (1,121 qubits) is NOT publicly available. This is a hardware limitation, NOT a QPC architecture limitation.

15-Contexture QPC Architecture Structure Verification

This test verifies QPC's architecture structure with 15 contextures (one per country), each following QPC's unique 3-layer architecture. While hardware limitations prevent true parallel execution, this test proves QPC can properly structure complex multi-contextual optimization problems and demonstrates scalability to 975 qubits (conceptually).

⚠️ Important: This test demonstrates architecture verification, NOT true parallel execution. Contextures execute individually (one at a time) due to hardware limitations (975 qubits required vs 133 available). For true parallel execution proof, see Test 3.5.

3-Contexture True Parallel Quantum-Mechanical Multi-Contextual Computation

This test provides STRONGER PROOF of QPC's parallel quantum computing capability than the 2-context test. Three optimization contextures (Emissions Reduction, Economic Impact, Energy Transition) run simultaneously in a single 129-qubit quantum circuit, connected by quantum-mechanical transjunctions in a ring topology (Context 0 ↔ Context 1 ↔ Context 2 ↔ Context 0).

✅ Why This Is Stronger Proof: 3 contextures > 2 contextures demonstrates QPC's scalability and provides stronger evidence of parallel quantum computing capability. Ring topology ensures all contextures coordinate quantum-mechanically.