Quantum Polycontextural Systemic Risk Detection (QPC-SRD) — Real-world run on IBM Quantum hardware. Cascade probability, collapse threshold, and most dangerous financial nodes identified in <40 seconds.
The goal of this experiment was to test whether the Quantum Polycontextural Computer (QPC) can execute a large-scale systemic financial risk analysis representing the global financial network.
The system models 128 financial institutions (banks, asset managers, insurers) connected through credit exposure, derivatives relationships, and asset correlations. The computational task is to explore the extremely large configuration space of this network and identify states in which financial stress propagates across institutions and produces a systemic collapse scenario.
The model is formulated as a quantum optimization problem, where high-energy configurations correspond to unstable financial states. From the quantum sampling results, the system computes:
This experiment demonstrates the capability of QPC to execute complex real-world systemic risk computations on quantum hardware.
Institutions ranked by stress frequency in high systemic-risk quantum samples. Higher stress frequency = higher contribution to cascade risk.
| Rank | Institution | Stress Frequency |
|---|---|---|
| 1 | Sumitomo Mitsui | 87.32% |
| 2 | UniCredit | 85.37% |
| 3 | Vanguard | 85.12% |
| 4 | ING | 83.90% |
| 5 | Santander | 77.56% |
| 6 | Crédit Agricole | 75.37% |
| 7 | Prudential UK | 73.41% |
| 8 | Mizuho | 72.93% |
| 9 | Mitsubishi UFJ | 69.27% |
| 10 | Allianz | 67.07% |
Hardware: IBM ibm_torino, 133 qubits. Job ID: d6ph6inr88ds73db5a7g. Circuit: 128 qubits, depth 1149 (transpiled 30648). Shots: 4096. Execution: 39.64 seconds.
Institutions under stress in the highest-risk quantum configuration (H = 81.57):
Goldman Sachs, Citigroup, Bank of America, Barclays, Deutsche Bank, Société Générale, Santander, UniCredit, ING, Crédit Agricole, Mitsubishi UFJ, Sumitomo Mitsui, Mizuho, Vanguard, Capital Group