QPC Oil & Gas Crisis Evaluation

Task presentation — Content and goal

Before interpreting the results, here is what the task was and what we set out to achieve.

Task content

Evaluate five Middle East oil and gas supply-chain crisis scenarios that differ in severity and structure. Each scenario combines six interrelated factors:

Transport — Can tankers and LNG carriers move? At what cost?
Market — How do prices and demand respond?
Geopolitical — Regional tensions, sanctions, political risk
Substitution — Alternative routes, suppliers, energy sources
Feasibility — Can response measures be implemented in practice?
Risk & redundancy — How much buffer and backup exists?

The five scenarios range from relatively mild (limited war, shipping open) to severe (full Hormuz closure, infrastructure damage). The question is: which scenario is most coherent when all factors are evaluated together—and which is hardest to absorb?

Task goal

Optimize and compare the five scenarios to support strategic decision-making. The goal is to produce a ranking that indicates:

• Which scenario is relatively most manageable for allocation and contingency planning
• Which scenario presents the greatest structural stress (contradictions between factors)
• Where to prioritize resources, redundancy, and response capacity

We do not predict probabilities or timelines. We evaluate the internal coherence of each scenario—how well transport, market, geopolitical, substitution, and feasibility align—and rank them accordingly.

What was achieved

We ran a single quantum computation on real IBM hardware to evaluate and rank five crisis scenarios in parallel. Each scenario combined multiple factors: transport risk, market conditions, geopolitical stress, substitution options, and feasibility—the kind of multi-dimensional problem where classical methods struggle to capture interdependencies.

128
Qubits used

5
Scenarios in parallel

IBM Fez
Quantum hardware

2048
Shots per run

Best-ranked scenario

Scenario 1 — Limited war, shipping open
Tankers and LNG carriers continue moving, but war-risk premium, insurance, and freight costs rise sharply.

Customer takeaway: Operationally stable short-term, but still vulnerable to escalation and sentiment shock.

Full scenario ranking

Relative robustness score (0–100). Higher scores indicate scenarios where transport, market, geopolitical, substitution, and feasibility factors align more coherently.

Rank	Scenario	QPC score	Takeaway
1	Limited war, shipping open	100	Operationally stable short-term; vulnerable to escalation
2	Full Hormuz closure	95	Worst structural case; QPC optimizes under collapse
3	Partial Hormuz disruption	62	Manageable with active multi-layer control
4	Red Sea danger, Hormuz open	38	Gulf eastward, Atlantic compensation westward
5	Infrastructure damage + irregular transport	0	Hard to absorb; route + physical export impairment

How to interpret the results (according to the task goal)

The task was to optimize and compare. Here is what the ranking means for your decisions.

Higher QPC score (e.g. 100, 95) — The factors in this scenario align more coherently. Transport, market, geopolitical, substitution, and feasibility are less contradictory. Implication: This scenario is relatively more manageable for allocation and contingency planning. You can prioritize it for operational readiness—it is the “least worst” structurally.

Lower QPC score (e.g. 38, 0) — The factors contradict each other more. The scenario presents greater structural stress. Implication: Harder to plan, absorb, or allocate. These scenarios need more redundancy, more aggressive mitigation, and may require emergency protocols.

Ranking vs. severity — Note: the highest-scoring scenario is not necessarily the “safest” in the traditional sense. A scenario with open shipping (S1) scores highest because its factors cohere—it is operationally stable short-term, even if vulnerable to escalation. A full Hormuz closure (S4) scores second because, although severe, its structure is clearer: collapse mode. S5 (infrastructure damage) scores lowest because it combines route risk and physical impairment—maximum contradiction, hardest to absorb.

What to do with this — Use the ranking to guide where to invest redundancy, where to build contingency plans first, and which scenarios require the most urgent response capacity. The task goal was comparison and optimization; the results deliver that comparison.

How QPC works (simple explanation)

Quantum Polycontextural Computing treats each scenario as a set of contexts (transport, market, geopolitical, substitution, feasibility) that must be evaluated together, not in isolation.

1. Context encoding — Each factor is encoded as a quantum phase. The more factors a scenario has, the more “quantum dimensions” we use.

2. Relational coupling — QPC links these contexts through entangling gates. How transport relates to market, how geopolitical stress affects substitution, etc., is represented in the quantum state.

3. Redundancy & coherence — We add redundant views (redA, redB, redC) and measure coherence: when contexts agree, the signal strengthens; when they contradict, we penalize.

4. Graph refinement — Similar scenarios (e.g. partial vs full Hormuz disruption) influence each other’s scores, so neighboring scenarios are smoothed.

Noise and disturbance — what to know

Today’s quantum computers are noisy. QPC is designed to work despite that.

What is noise? Real quantum hardware suffers from decoherence (quantum states decay), readout errors (wrong bit when measuring), and gate inaccuracies. This “disturbs” the ideal computation.

How does QPC handle it?

Redundancy — Multiple qubits encode the same logical factor. If some are corrupted, others can still carry the signal.
Noise reducer — We use a software module that normalizes counts, aggregates over repeated runs, and (when possible) corrects readout errors. Raw hardware output is “cleaned” before scoring. Buyer-oriented documentation: QPC Noise Reducer — public report.
Relative comparison — We rank scenarios relative to each other, not against an absolute ideal. Noise tends to affect all scenarios similarly, so the ranking remains meaningful.

Bottom line: The scores you see are produced on real, noisy hardware. They are not perfect, but they reflect a coherent quantum evaluation that classical methods cannot replicate. As hardware improves, results will sharpen further.

Oil & Gas Crisis Scenario Evaluation