Separability falsification · one IBM job, one quantum system

The primary architecture claim for QPC: when K objective contextures run coupled in one circuit, the measurement statistics show cross-context correlation that K independent IBM jobs miss. This page explains the task, the scoring, and the IBM Fez results from June 2026.

Plain English

What this test is: Separability falsification. One coupled IBM job (transjunctions ON) versus the same objectives as independent jobs (transjunctions OFF).
Why we did it: ICC is the falsification: joint structure the coupled arm can show, at matched readout.
What QPC computed: ICC (inter-context correlation) from raw shot counts at each context boundary. Same readout pipeline on both arms. Wiring is the independent variable.
Headline result: Toy instance 3/3 pass (gaps 0.052–0.106) · Cerrado real data gap 0.088 · part of JSC levels L1–L3 with public job IDs.
What we claim: Coupled runs show measurable joint structure on IBM Heron r2 (ibm_fez). Verification is via published job IDs and outcome tables.

The task

Build a quantum circuit with three objective blocks (e.g. carbon, biodiversity, social).
Coupled arm: connect blocks with transjunction gates → submit one job to IBM.
Control arm: run each block alone (transjunctions off) → submit three jobs, then pair samples as independent.
Ask: does the coupled run show extra correlation between adjacent objectives that the control misses?

When the gap is there, QPC is doing something quantum-joint: one circuit, one readout, joint structure the independent-job control misses.

Architecture metric: ICC. Portfolio / optimization scores sit on the Cerrado compare page.

How we score separability

We compare coupled (one IBM job, transjunctions on) vs separable control (independent jobs, samples paired as uncoupled). A proprietary inter-context correlation (ICC) witness is computed from shot statistics on aligned decision qubits at each context boundary. Both arms use identical readout and post-processing. Coupling is the difference.

Public pass criteria (outcomes only)

Coupled ICC materially exceeds separable control on the same backend
ICC gap meets pre-registered thresholds on toy and Cerrado instances
At full Heron width: per-boundary reporting when that is the registered readout

Exact ICC formula, readout schedule, and morphogram depth are proprietary. Independent verification uses published IBM job IDs below.

Toy soft-objective instance (15Q coupled, ibm_fez)

Synthetic three-contexture instance. Fixed seeds for reproducibility. 4096 shots each.

Seed	ICC gap	Coupled ICC	Pass	Coupled job ID
7	0.106	0.114	✓	`d8i3vdtv8cos73f549cg`
11	0.052	0.062	✓ (rerun)	`d8i429dv8cos73f54e60`
42	0.104	0.112	✓	`d8i3vu66983c73drmk10`

Strong pass: 3/3 seeds.

Cerrado real data (Goiás carbon portfolio)

Same open dataset as Ribeiro 2026 (arXiv:2602.09047). Three objective contextures. Shared-layout and full-width Heron r2 jobs.

Instance	Layout	Depth	Mean ICC gap	Verdict	Job ID
n=8, k=3	shared	~500	0.088	Pass	`d8i4065v8cos73f54a8g`
n=12, k=4	shared	474	0.088	Pass	`d8i42ic2upec739loi50`
n=28, k=7	full width	1329	0.031	Heron per-boundary	`d8i44rc2upec739loktg`

Full-width Heron r2, per-boundary readout (job d8i44rc2upec739loktg):

Transjunction boundary	Coupled ICC	Separable ICC	Gap	Per-boundary
carbon ↔ biodiversity	0.005	0.010	−0.005	·
biodiversity ↔ social	0.110	0.012	0.098	✓
social ↔ carbon	0.003	0.001	0.001	·

Architecture finding at full Heron width: the biodiversity↔social bridge shows a raw ICC gap of 0.098 on ibm_fez. That is the joint-structure signal at 156Q for this instance.

Separability falsification · one IBM job, one quantum system

The task

How we score separability

Public pass criteria (outcomes only)

Toy soft-objective instance (15Q coupled, ibm_fez)

Cerrado real data (Goiás carbon portfolio)

What this demonstrates