QPC Crisis Task. Final Report

Task process: database → QPC model → ibm_fez execution → reducer/graph → ranking.

1) Goal of the task

The goal was to run a complex real-world crisis structure (Middle East oil and gas conflict risk) as one QPC computation.

What the job delivered:

- A scenario model with many interdependent indicators.
- Execution on IBM Heron r2 · ibm_fez, 128 qubits.
- A consistent QPC ranking of four locked configurations.
- An end-to-end path: freeze → circuit → hardware → raw ranking → resilience diagnostics.

2) Database used

The run reads a frozen, data-driven scenario table:

- File: evidence bundle (NDA)
- Four scenarios, each with normalized indicators [0..1].
- Indicators:
  - transport, market, geopolitical, substitution, feasibility
  - war spread across region
  - Iran regime-change risk
  - regional infrastructure damage
  - pipeline and port damage
  - military attack intensity
  - Gulf involvement
  - international investigation pressure
  - risk bias, redundancy bias

The circuit is built from that table. The four units are S1 multi-theater spread, S2 Iran transition shock, S3 cross-border infrastructure destruction, and S4 Gulf direct intervention.

3) Computation process

1. Load scenarios from evidence bundle (NDA).
2. Map indicators to QPC contextures (phase and relational encoding).
3. Build the quantum circuit for all four scenarios in one register (partitioned qubit regions, 128 qubits).
4. Transpile and run on IBM Heron r2 · ibm_fez, 1024 shots.
5. Collect counts from the Sampler.
6. Score raw counts as the primary ranking.
7. Apply the QPC reducer (normalize, aggregate, readout path) as the diagnostic channel.
8. Apply graph refinement across scenario neighborhood relations.
9. Write ranking and report files.

Outputs:

- evidence bundle (NDA)
- qpc_crisis_summary.csv
- qpc_crisis_report.html
- Executive page: QPC_CRISIS_CUSTOMER_REPORT.html

The QPC reducer is the same resilience toolkit documented here: QPC Noise Reducer public report.

4) Result and meaning

Completed 128-qubit run on ibm_fez. Primary ranking on raw counts:

- Lead: S4_gulf_direct_intervention · raw relative score 100
- Full raw order:
1. S4 Gulf direct intervention · 100
2. S1 Multi-theater spread · 66.33
3. S3 Cross-border infrastructure destruction · 49.47
4. S2 Iran transition shock · 0

The reducer-plus-graph layer keeps the same order (100 · 64.10 · 47.24 · 0).

QPC held the scenario logics together and returned a coherence ranking a planner can use: readiness first on S4 and S1, deeper buffers on S3 and S2.

5) Was this task successful?

Yes.

What closed:

- Frozen four-scenario crisis table, integrated.
- IBM Heron r2 · ibm_fez execution at 128 qubits, 1024 shots.
- Raw ranking delivered: S4 → S1 → S3 → S2.
- Resilience channel on the same counts, same order after graph refinement.
- Executive and technical reports published with those numbers.

6) Why this matters for QPC architecture

This job shows QPC as a working architecture on a geopolitical-energy crisis space:

- Multi-context crisis systems held in one register.
- Interdependent indicators in one workflow.
- Execution on IBM Heron r2 with a usable ranking on raw counts.
- A reusable desk: new scenarios enter by updating the frozen table.

QPC computes complex crisis configurations as co-resident logics and returns a structured decision from the hardware job.