IBM Eagle · ibm_torino · 133 qubits · 8 contexts · 10 February 2026

Eight climate contexts,
one coordinated readout

QPC maps CO₂ reduction for the world’s top 20 emitters onto eight labelled 65-qubit circuits and eight public IBM jobs. OWID and World Bank data sit in the encoding.

Contexts

Qubits / context

520

Logical width

8,192

Shots / solutions

13.0

Shannon entropy

Countries · 2024

Plain English

What this test is: Optimize CO₂ reduction across the top 20 emitting countries while scoring eight factors together: emissions, economics, regulations, energy transition, geopolitical risk, technology, cost, and social impact.
Why we did it: Many classical workflows treat those objectives sequentially or on separate models. QPC maps each factor as a context and runs one coordinated quantum workflow on IBM hardware.
What QPC computed: Eight 65-qubit jobs on ibm_torino. Logical width 520 qubits. Readouts combined into one eight-dimension result. OWID CO₂ (2024) and World Bank GDP in the encoding.
Headline result: 8 public IBM job IDs · entropy 13.0 · 8,192 solutions. Co-resident 156-qubit CO₂ on Heron r2 is on the open-instance ladder (T01, 4×39Q).

The eight contexts

Each context is its own 65-qubit circuit and its own IBM job. QPC then coordinates the eight readouts.

1. Emissions Reduction

Minimize CO₂ using the real OWID dataset

2. Economic Impact

Minimize GDP impact (World Bank data)

3. Regulatory Compliance

Meet Paris Agreement NDC targets

4. Energy Transition

Optimize renewable energy adoption

5. Geopolitical Risk

Minimize energy security risks

6. Technology Availability

Renewable capacity constraints

7. Cost Optimization

Minimize transition costs

8. Social Impact

Optimize employment and job creation

Countries in the panel: China, United States, India, Russia, Japan, Germany, Iran, South Korea, Saudi Arabia, Indonesia, Canada, Mexico, Brazil, South Africa, Turkey, Australia, United Kingdom, Italy, Poland, France.

How the architecture is used

Polycontextural structure: eight independent subsystems, coordinated after measurement.

8 independent contexts. Each is a 65-qubit quantum subsystem with its own optimization objective.
Per-context IBM jobs. Eight jobs on IBM Eagle (ibm_torino, 133 qubits). Logical width across the campaign is 520 qubits.
Coordinated readout. Results are combined after measurement into one eight-dimension solution.
Real-world data. OWID CO₂ and World Bank GDP encode the objectives.

What this campaign ran. Eight labelled 65-qubit contexts on IBM Eagle · ibm_torino · 133 qubits, one public job ID per context, OWID / World Bank inputs, Shannon entropy 13.0. Co-resident 156-qubit layouts on Heron r2 sit on the open-instance benchmark ladder (T01 CO₂, 4×39Q in one submission).

3-layer structure per context

1. Kenogrammatic

State preparation. Countries and parameters encoded into quantum states, with CO₂, GDP, and regulatory targets in the rotation angles.

2. Morphogrammatic

Entanglement. Proprietary encodings connect countries to optimization parameters and to the other dimensions.

3. Transjunctional

Measurement. Solutions are extracted; coordination across the eight contexts produces the global score.

What QPC ran

A genuine quantum computation on each 65-qubit circuit, then an eight-way coordinated readout.

Quantum characteristics

Superposition. Each context explores 2⁶⁵ possible quantum states.
Entanglement. Morphogrammatic layers connect countries and optimization parameters.
Quantum interference. Gates reshape amplitudes toward the scored solutions.
Measurement. Shots collapse to bitstrings that represent optimization solutions.

Architecture on this page

Eight labelled contexts, each with its own circuit and objective
Coordinated eight-way readout after the eight IBM jobs
Real CO₂ and economic indicators in the encoding
Solutions scored across all 8 dimensions together

Classical systems. Often treat contexts sequentially or on separate models.

Single-objective quantum (QAOA-class). One objective function, one circuit family.

QPC. Eight labelled contexts in one orchestrated workflow, with public IBM job IDs.

Results

IBM Eagle · ibm_torino · 10 February 2026. Eight 65-qubit jobs. Logical width 520 qubits.

Execution

Backend: IBM Eagle · ibm_torino · 133 qubits

Mode: Eight 65-qubit jobs, one per context. Logical width across the campaign: 520 qubits

Data: OWID CO₂ (2024), World Bank GDP API

Date: 10 February 2026

Eight-context execution

Logical width is 520 qubits (8 × 65). This campaign maps that width onto IBM Eagle as eight 65-qubit jobs. Results are combined after measurement.

This page (10 February 2026)

Eight labelled contexts, 65 qubits each, one IBM job per context
OWID CO₂ (2024) and World Bank GDP in the encoding
Readouts combined after measurement into one eight-dimension result
Eight public job IDs on ibm_torino

Later Heron r2 co-resident ladder

T01 CO₂: 4×39Q = 156Q in one submission on ibm_fez
Open-instance verified benchmarks

What this campaign delivered. QPC architectural structure at eight contexts, real-world data in the encoding, and quantum computation on each 65-qubit circuit, with public IBM job IDs.

How this campaign is structured

Each context is self-contained. Kenogrammatic, Morphogrammatic, and Transjunctional layers run as an independent quantum subsystem.
Coordination after measurement. The eight readouts become one eight-dimension score.
Structure preserved. Each context optimizes its dimension on real quantum hardware.
Results combined. Solutions from all 8 contexts are aggregated across all dimensions.

This test delivered: 8 independent optimization contexts; CO₂ and GDP in the encoding; multi-dimensional scoring on IBM hardware; logical width 520 qubits; 3-layer architecture on each context. Co-resident 156-qubit CO₂ on Heron r2 is on the open-instance ladder.

Context-specific scores

8,192 solutions per context. Score 1.3 on each published arm.

Emissions Reduction

Solutions 8,192 · Score 1.3 · OWID CO₂ (real)

Economic Impact

Solutions 8,192 · Score 1.3 · World Bank GDP (real)