July 2026 · Fusion blanket · Full 156Q · IBM Heron r2

Fusion blankets need tritium answers.
QPC maps the whole model-risk landscape in one IBM job.

Nine published FLiBe liquid configurations × seventeen contextures on ibm_fez: full 156 qubits, one auditable Heron r2 job (d9a06m52su3c739l0eeg). The ORNL–IBM study shows fragmentation error (~110 kcal/mol) dwarfs the quantum solver residual (~0.7 kcal/mol). QPC couples methods, reliability signals, and engineering objectives in a single polycontextural layer on that published table.

Plain English

What this test is: A model-risk and decision-support circuit that encodes nine published conformations and seventeen contextures (method families, solver agreement, fragmentation conflict, extraction vs retention) on 156 qubits with three global junction qubits.
Why we did it: The paper’s own numbers show the quantum fragment solver matches its classical parent (~0.7 kcal/mol) while embedded vs full-molecule methods disagree by two orders of magnitude more. QPC’s question: can polycontextural coupling represent that whole uncertainty landscape in one auditable hardware run?
What QPC computed: ibm_fez · 8192 shots · 3 pre-registered variants in one job: coupled · intracontext-matched control · separable · job d9a06m52su3c739l0eeg.
Headline result: Joint-structure gap +0.0095. Coupled cross-contexture bridge correlations ≈2× the matched intracontext control on Fez. Top encoded recovery ranking: conformations 9 → 1 → 4 (aligns with weakest published ext-SQD binding cluster).
What we claim: QPC executes a fusion-relevant, full-width polycontextural model-risk layer with pre-registered controls and a public IBM job ID. Lane A is the raw joint-structure gap. Lane B ranks encoded published outputs.

What was computed, step by step

Public database intake. Nine conformations × eight tritium-binding methods from published Table S3 (flibe_binding_database.csv).
Seventeen contextures. Eight method bindings + full/embedded consensus + family agreement + quantum-solver agreement + fragmentation-conflict alert + extraction/retention favourability + data completeness.
Qubit map. 9 conformations × 17 contextures = 153 data qubits + 3 junction qubits (retention · extraction · reliability) = 156 total.
Circuit encoding. Each score normalized to a rotation angle; sparse cross-contexture bridges connect method families to consensus and junction objectives.
Three variants. Coupled (full polycontextural bridges) · intracontext-matched (same gate count, no cross-context coupling) · separable (no entangling structure).
IBM execution. Transpiled to Fez ISA, SamplerV2 with XY4 dynamical decoupling and measurement twirling, one submission with three circuits.
Decode. Bridge-pair correlations (Lane A) and conformation-level recovery scores (Lane B) from raw counts.

Published energies (CSV) → 17 contextures × 9 conformers → 156Q logical circuit → transpile(ibm_fez) → SamplerV2 [coupled | intracontext | separable] → counts.json → bridge ICC gap + conformation ranking

IBM Fez results · July 2026

Variant	ISA depth	2Q (CZ)	Mean \|bridge corr\|	Role
flibe_coupled	246	1573	0.0180	Polycontextural architecture arm
flibe_intracontext_matched	144	838	0.0085	Depth/gate-matched control
flibe_separable	5	0	0.0090	Separable baseline

Lane A pass signal: open joint-structure gap = +0.0095 (coupled − intracontext). Cross-contexture bridges retain measurably stronger correlations on IBM Heron r2.

Job ID: d9a06m52su3c739l0eeg · Backend: IBM Heron r2 ibm_fez · Shots: 8192 per circuit · Status: completed

Conformation ranking (Lane B · coupled decoder)

Provisional recovery score from coupled-circuit marginals. Ranks encoded published outputs from Table S3.

Rank	Conformation	Recovery score	Published ext-SQD binding (kcal/mol)	Note
1	9	0.691	−134.76	Weakest binding in table
2	1	0.579	−175.39	·
3	4	0.573	−138.13	3rd-weakest binding
4	7	0.555	−188.84	·
5	6	0.521	−157.88	6th-weakest binding

How to read Lane B: the ranking is the QPC decoder on the nine published conformations. The source paper’s engineering discussion uses ensemble averages over hundreds of liquid configurations. This pilot’s Lane B is that nine-row table, in one 156Q job.

Two architectures on the same published FLiBe table

Dimension	ORNL–IBM ext-SQD campaign	QPC FLiBe pilot (this job)
Primary goal	Sample LUCJ circuits per embedded fragment; recover energies via ext-SQD + selected CI	Couple already computed binding energies across methods and reliability contextures in one polycontextural inference layer
Hybrid structure	Many fragment jobs (classical FCI <13 orbitals; QPU ≥13) + HPC EWF assembly + classical recovery per fragment	One 156Q IBM job with three pre-registered architecture variants
What quantum solves	Individual fragment correlation (66 logical qubits max per fragment)	Simultaneous representation of method disagreement, solver reliability, fragmentation conflict, and extraction/retention objectives
Dominant error source (paper)	Fragmentation/bath (~110 kcal/mol family gap)	QPC’s model-risk layer: that family gap, encoded as co-resident contextures
Public reproducibility	Literature campaign as published	Full QPC pipeline public: CSV database, scripts, IBM job ID, counts JSON

QPC vs Heron industry pilots (manufacturing / logistics)

Pilot	Domain	156Q use	Lane A (ICC)	Lane B (decoder KPI)
Manufacturing	Assembly-line scheduling	3 line contextures + padding	Implicit in coupled layout	0 late jobs, schedule cost 39.79
Logistics	Route assignment HUBO	3 route contextures	·	Decoder beats greedy (−49.80 vs −49.52)
FLiBe / Tritium (this)	Fusion blanket model risk	17 contextures × 9 conformers + 3 junctions	Gap +0.0095 vs intracontext	Conformation ranking 9·1·4 top
MCGS	Gauge-sector ICC	3 sector contextures	3/3 raw pass, gaps 0.349 · 0.243 · 0.131	Physics-motivated instance

QPC path across these pilots: multiple objectives live in one coupled quantum submission with pre-registered controls. FLiBe extends this to scientific model risk (method families, fragmentation conflict, data completeness) at full Heron r2 width.

Data verification

1. Published chemistry database

Source file: vendor_benchmarks/flibe_tritium/flibe_binding_database.csv (nine conformations, eight methods from Table S3).
Reproduced statistics: ext-SQD vs TCI mean absolute difference = 0.668 kcal/mol; full vs embedded family gap mean = 108.03 kcal/mol.
Verify locally: .venv/bin/python3 vendor_benchmarks/flibe_tritium/qpc_flibe_tritium.py analyze

2. IBM hardware execution

Job ID: d9a06m52su3c739l0eeg on IBM Heron r2 ibm_fez. Retrievable via IBM Quantum Platform.
Archived artifacts: results/flibe_tritium_ibm_fez.json, results/flibe_tritium_run/submission.json, counts.json, decoded.json.
Logical → ISA metrics recorded in submission manifest (coupled depth 246, 1573 CZ).

3. Reproducibility chain

Build: qpc_flibe_tritium.py build → logical QPY + manifest.
Run: qpc_flibe_compare.py --mode ibm --backend ibm_fez --shots 8192 --wait.
Decode: bridge correlations and conformation scores are deterministic functions of archived counts.
Aer cross-check: --mode aer (MPS after transpile; ~72 s at 512 shots locally).

4. What is public

CSV database, scripts, IBM job ID, counts JSON, and the three-variant architecture readout.
Open reference compiler; proprietary QPC compiler injectable via --compiler-plugin.
Joint-structure metric on this page is the open diagnostic used for this FLiBe job.

Published database insight (why this matters)

The ORNL study’s own numbers establish a hierarchy of errors:

Quantum fragment solver (ext-SQD) vs embedded classical parent: ~0.7 kcal/mol.
Full-molecule vs embedded method families: ~108 kcal/mol. Fragmentation dominates.

QPC’s polycontextural treatment targets the simultaneous representation of local correlation, long-range polarization, method disagreement, and engineering objectives: the layer where a single auditable quantum object carries the whole model-risk map.

← Home announcement Heron industry pilots Joint Structure Challenge

Fusion blankets need tritium answers.QPC maps the whole model-risk landscape in one IBM job.

What was computed, step by step

IBM Fez results · July 2026

Conformation ranking (Lane B · coupled decoder)

Two architectures on the same published FLiBe table

QPC vs Heron industry pilots (manufacturing / logistics)

Data verification

1. Published chemistry database

2. IBM hardware execution

3. Reproducibility chain

4. What is public

Published database insight (why this matters)

Fusion blankets need tritium answers.
QPC maps the whole model-risk landscape in one IBM job.