C.26 - Quantum-Like Modeling Lens

Type: Architectural pattern Status: Stable Normativity: Normative unless explicitly marked informative

C.26:1 - Problem frame

FPF already has local patterns for decisions, boundaries, bridges, work, measurement, search, and quality bundles. Some real architecture cases still break when those patterns are applied as if every read, question, dashboard, workshop, bridge, or simplified representation were a passive view of a stable state.

Use this pattern only after the ordinary FPF subject assertion and exact predicate are in place and one exact contextual-model obstruction still changes what may be inferred or done. The obstruction may be a no-global-section result, incompatible probe algebra, order-sensitive instrument result, or another named failure of passive read, joint comparison, faithful-enough export, or use-preserving coarsening. A broad word such as context, a diagram, different labels, ordinary DDD locality, or mere model plurality does not open C.26.

What goes wrong if missed. A dashboard, workshop, metric, bridge, export, or coarsened model is treated as a passive faithful readout even when the probe, frame, publication, or representation shortcut changes what can be inferred.

What this buys. The user keeps the ordinary FPF pattern in charge and adds only the minimum quantum-like lens needed to prevent that concrete representational mistake.

Identity before the lens. When C.26 carries a quality ascription or model claim, first name the quality bearer or C.2.1 claim-bearing episteme, its effective U.ReferenceScheme, the probe or model frame, the comparison frame, and the applicable U.ClaimScope. State separately whether an EpistemeEmpiricalGroundingRelation obtains; a measurement, evidence reference, card, or label does not make it obtain.

If a viewpoint matters, record one U.ViewpointRef that resolves to the U.Viewpoint episteme P.

When evaluation Work is claimed, recover the actual performer System through A.13 and let A.15.1 independently admit the dated Work with its enacted Method. Cite the same obtaining A.13 assignment occurrence, its declared species, and F.6 only when the receiving use consumes precise assignment-bound attribution. Name a non-performing participant by its evaluation relation and position. Keep these neighboring values separate from the QL-use fields.

This pattern is not a physics claim. In FPF, quantum-like names a detached mathematical and representational lens, comparable in use to probability, calculus, optimization, or state-space modeling. A QL-lite note can supply a small recognition or conditional comparison. Choose additional mathematical or empirical support from what the receiving use needs the claim to establish, following :12b.

Unifying principle: use QL to make the first correct move cheaper.

What this lens buys in practice:

Plain glosses:

• quantum-like: a detached mathematical or representational lens, not a claim about what the target is made of.
• probe: an operation that both produces an output and may change the represented state or admissible use of the output.
• frame: the exact probe frame, measurement frame, comparison frame, or model frame selected by its subject pattern; the effective U.ReferenceScheme remains a separate part of the claim-use account.
• state: the represented condition relevant to the current decision.
• state update: a typed update claim. When load-bearing, say whether the update is a system change, work change, epistemic reading update, carrier update, emitted-output update, formal model update, or update-law change; do not let one phrase carry all of them.
• context: when locality may matter, recover the exact claim scope, reference scheme, local-sense endpoint, selected model-use structure, qualification window, viewpoint relation, or direct subject relation that the sentence actually needs.
• export: a carried representation whose use may lose timing, coordination, system-role or participation relations, use conditions, confidence, or relation structure.
• coarsening: an intentionally cheaper state representation with declared loss and reopen conditions.

Phrase hygiene:

Example style:

Informative bilingual translation note:

C.26:2 - Problem

Teams make five recurring representational mistakes that this lens addresses.

They treat a probe as a neutral read when the probe changes later answers or behavior. They combine two posterior-looking outputs as if both came from one shared sample space. They export a team state, dashboard value, or context-map result as if it were a faithful-enough export for the intended use. They compress a large state representation for speed and then reuse the shortcut outside its admissible-use scope. They let words such as quantum, entanglement, collapse, or field import ontology that the model never earned.

The team may approve a release from a dashboard whose publication and operational use changed the work it was supposed to report, average results produced in incompatible local algebras, reuse a local decision under a different effective reference scheme after the admitted bridge lost load-bearing meaning, or claim a speed gain because the representation was low-bit, linear, symbolic, or compressed without naming the loss.

C.26:3 - Forces

C.26:4 - Solution

Start with the ordinary FPF pattern. Recover the exact claim, bearer or EntityOfConcern, effective reference scheme, scope, probe or model frame, and comparison frame before asking whether a quantum-like lens remains useful. Add C.26 only when a named contextual-model obstruction survives ordinary measurement, comparison, bridge, causal, work, evidence, and representation treatment and changes an admissible engineering inference. Preserve incompatible-probe results in their own local algebras. The main entry question for the whole cluster is: “Which exact obstruction remains, and what should the user now do differently because it remains?”

Application sequence:

1. Name the ordinary FPF pattern that already carries the baseline question.
2. Recover the exact claim-bearing subject: quality bearer or C.2.1 model-claim episteme, effective U.ReferenceScheme, probe or model frame, comparison frame, and U.ClaimScope; record grounding and viewpoint only through their separately obtaining relations.
3. Name the concrete representational mistake: passive read, shared comparison frame, false faithful-enough export claim for the intended use, exact-state shortcut, or unsupported coarsened representation.
4. Apply the ordinary subject patterns and retain C.26 only if one named contextual-model obstruction survives and changes the admissible inference or action.
5. Fill the QL-lite card if that cue survives; otherwise return to the ordinary subject pattern without QL wording.
6. Emit one practical result: use the ordinary pattern only, add a QL-lite note, select one C.26 child pattern as the applicable pattern body, add evidence and assurance, or drop the QL wording.
7. Identify what the result will be used to establish. Add the applicable account when prediction, model adoption, comparative performance, assurance or another relied-on conclusion needs it. A reusable conditional explanation within the same assumptions can remain small; apply :12b and reuse adequate existing support.

C.26 ordinary output: produce one of these, then stop or select the neighboring applicable pattern body:

• no C.26 pattern selection because the ordinary FPF pattern carries the case;
• QL-lite note with the minimum sufficient field set;
• selection of one C.26 child pattern as the applicable pattern body;
• escalation to evidence, assurance, or formal-model work when the claim’s evidence or authority demand requires it.

Keep the entry cost proportional to the use. A QL situation does not begin with a full record.

Do not make the decision-bearing or assurance record the ordinary entry cost. The everyday pattern move is a small recognition note plus a bounded action.

Choose detail by the receiving question:

Apply the same selection when writing, checking or reusing a pattern. The role of the reader does not determine the form or amount of support. Use C.11.DUA when deciding whether additional work can improve the receiving decision enough to justify its cost.

Checking discipline:

Cluster maxim: retain the support adequate for the receiving question. Add assurance work when a consequential unresolved premise requires it; reuse, publication or a formal notation alone does not change what has to be established.

Pattern-local-note dependency rule: when an existing FPF pattern cites C.26 or a C.26.* child, the pattern’s ordinary action guidance and conformance text remain primary. The citation means only: if a residual QL cue remains after the ordinary FPF pattern has carried its part, use this lens for that residue. It does not make every citing-pattern case depend on the full C.26 record or on every child-pattern semantic.

Model-use structure and crossing boundary. Select a BoundedModelUseStructure only when the organization of one exact model episteme, admitted model-use holons, obtaining applicability/use/coherence relations, applied constraints, invariants, and one named receiving use changes the decision. Compare two such structures only after each is independently selected on that basis. Assert a subject crossing only when an exact direct governor makes one direction-sensitive crossing occurrence obtain among those exact structures. When the direct governor is absent, return the exact missing-governor blocker.

QL boundary selection:

The default output is a QL-lite card. Keep it short: the three conditional identity rows below may be written as one line, and they are required only when the note carries a quality ascription or model claim.

Decision diff examples:

Minimum ordinary-pattern return from the QL activation test:

Ordinary patterns: C.16 + A.15.
Disposition: no QL wording. The stated facts establish a performative metric effect; no contextual-model obstruction surviving those ordinary patterns is established.
Claim line: exact readiness-ascription claim ReadinessAscription-4 about bearer DeliverySystem-12 under OperationsReferenceScheme; probe/model frame ReadinessPublicationFrame; comparison frame PrePostReadinessFrame; claim scope ReleaseWindow-W.
Grounding and viewpoint: no EpistemeEmpiricalGroundingRelation is yet established; OperationsViewpointRef resolves to OperationsViewpoint-P. Admitted ReleaseEvaluationSystem-7 performs dated ReleaseAssessmentWork-7, enacts ReleaseAssessmentMethod-3, and is holder of obtaining ReleaseEvaluatorAssignment-7, a directly declared ReleaseEvaluatorSystemRoleAssignment occurrence; after A.13 performer-basis recovery and independent A.15.1 Work admission, F.6 states that the System performed the Work under that assignment.
Mistake prevented: dashboard result would be read as passive release-readiness evidence.
Probe effect: publication changed team behavior during W.
Decision diff: do not use dashboard alone for release; add independent work traces.
Stop: this note locates how dashboard publication changed the work being assessed. Resolve the resulting readiness question with the applicable work and measurement Methods.

This completes the ordinary-pattern return: the dashboard must not be treated as a passive readiness read, and the stated facts do not yet activate QL. Reopen C.26 only if one named contextual-model obstruction survives the ordinary account and changes an admissible inference or action. Reuse adequate existing support under :12b; publication of this note alone requires no new assurance account.

Use the C.11 mini-output discipline across the cluster: finish with one choice result or governed follow-up.

Retire QL when the residual cue disappears. If A.6, F.9, C.16, A.10, B.3, A.15, C.25, A.6.3.CSC, A.6.3.RT, or another ordinary FPF pattern now carries the claim without a false passive read, false shared frame, false faithful export, unsupported distributed-state reading, or QL-specific coarsening residue, remove QL wording from the active working note or pattern prose.

Use the lens only after the activation test survives both sides. C.26 remains active only when one named contextual-model obstruction survives the ordinary subject patterns and changes an admissible engineering inference or action: for example, a no-global-section result, an incompatible-probe algebra, or an order-sensitive instrument effect. Bridge loss, feedback, coupling, openness, compression, coarsening, vocabulary, graph shape, and DDD locality are not QL cues by themselves. Preserve each local result in its own algebra unless an independently admitted joint-comparison route exists; do not manufacture a global frame or infer a structure crossing from comparison.

Canonical cue grammar:

Apply both sides of the activation test:

Keep incompatible-probe outputs in their own exact algebras. A common label, common diagram, or desire to average does not supply a joint probability space, comparison relation, grounding relation, or cross-structure occurrence.

Practical payoff in ordinary prose:

• “the metric reported readiness” becomes “the metric publication or measurement regime functioned as a probe interaction that changed readiness behavior”;
• “two risk scores disagree” becomes “the two scores may come from non-shared comparison frames with no declared admissible joint comparison route”;
• “the workshop discovered the split” becomes “the workshop was a probe whose order and framing changed alignment and local meaning”;
• “the team knows” becomes “coordinated work evidences a low-recoverability distributed-state reading with carriers, window, and export loss”;
• “this smaller model is enough” becomes “this coarsened state representation carries only its declared admissible-use scope and reopen condition”.

C.26:4.1 - Inherited QL boundary

Invariant QL-NQ: within FPF, quantum-like is a detached mathematical and representational modeling lens. It may use quantum-theory-derived structures such as contextual probability, Hilbert-like state spaces, non-Boolean logic, instruments, operator-like update, order effects, open-system descriptions, or incompatible probes.

Quantum-like does not assert physical quantum substrate, microscopic quantum process, qubits, quantum computation, physical entanglement, nonlocal causality, literal collapse, mystical observer effects, social substance, or collective mind. A physical-quantum claim is a different claim and needs separate physical or empirical support outside this pattern cluster.

Child patterns inherit QL-NQ. They should not restate the global boundary as local guidance unless they are repairing a specific confused phrase.

C.26:4.2 - Pattern selector

C.26:4.2.1 - Causal-use exit before QL retention

Before retaining QL-lite, QL-NQ, or a quantum-like framing for a claim being made, check whether the actual question is intervention, counterfactual comparison, causal effect, causal fairness, causal policy, off-policy causal evaluation, or realizability of counterfactual-rung data. If so, redirect the claim or question to C.28 before any quantum-like retention.

CC-C26-CAUSAL-EXIT:
If the question under repair is intervention, counterfactual comparison,
causal effect, causal fairness, causal policy, off-policy causal evaluation, or realizability of counterfactual-rung data,
redirect the claim or question to C.28 before retaining QL-lite or QL-NQ.

What changes in practice: “the model is quantum-like” cannot be used to skip causality-ladder rung declaration, causal identification, causal evidence support basis, or counterfactual sampling realizability.

C.26 keeps quantum-like modeling discipline; C.28 governs causal-use support, including counterfactual material.

Use this as a diagnostic sequence before retaining QL wording. DDD, microservice domain analysis, and direct boundary, model-use, local-sense, and Bridge subject patterns stay first for service cuts, integration points, and exported meaning. Retain QL only when one named contextual-model obstruction survives those subject patterns and changes what can admissibly be inferred.

1. Measurement, metric, scale, method, evidence, or assurance load goes first to measurement and evidence patterns: C.16, A.10, or B.3.
2. Bridge, translation, publication availability, rendering, or exported-loss question goes first to its applicable subject pattern: F.9 for an exact SenseCell Bridge; E.24.PUB for publication occurrence, form, and carrier; E.17 only for a current multi-view publication form or face; and E.17.EFP only for a current explanation-faithfulness claim.
3. A causal intervention, command, or routine question goes first to its pattern. For precise Work enactment, recover each exact actual performer System through A.13 and let A.15.1 independently admit the dated Work with its enacted Method. Cite the same obtaining A.13 assignment occurrence, its declared species, and F.6 only when the account or its receiving use expressly consumes precise assignment-bound attribution; F.6 identifies neither assignment nor performer, and missing or failed F.6 leaves the Work intact. A non-performing relation participant stays with its relation and position.
4. Boundary or interface wording, service-interface typing, bridge endpoint, relation precision, or lexeme-collision question goes first to the subject pattern: A.1 for holon delimitation or boundary crossing, A.6.P for relation precision or service/access recovery, A.6.0 or A.6.5 for signature or slot claims, A.6.M for module-interface claims, A.6.F for functional ports or elements, A.6.C only when recovered contract, SLA, protocol, or agreement-like wording bundles promise, utterance or publication, governance, Work or consequence, or evidence claims, A.6.B only for L, A, D, or E statement classification inside a boundary package, and A.7, E.10, or F.18 for wording-use repair.
5. Quality, viability, feedback, or control-tuning question goes first to quality, dynamics, and measurement patterns: C.25, U.Dynamics, and C.16.
6. Suspect option menu, unknown alternative, local plateau, basin movement, or candidate-generation question goes first to search and regime patterns: B.5.2, C.18, C.19, or A.19.
7. Retain QL only for the remaining declared state, probe, export, frame, open-information-system, or coarsening cue.

C.26 does not choose among options, generate missing alternatives, or settle C.11 decision quality. It can mark that the available readings sit in non-shared comparison frames or lack a declared admissible joint comparison relation; the choice or search output still belongs to C.11, B.5.2, C.18, C.19, or A.19.

C.26:4.3 - Escalation by evidence or authority demand

Math reveal sequence:

Most C.26 use should stay at M0 or M1.

Select the evidence-use class from the question the result must answer. QLP-0 and QLP-1 cover recognition and working support. QLP-2 and QLP-3 supply the additional comparison or assurance needed by a receiving decision. The classes identify useful contributions; they do not require collecting them again when an adequate account is available. Mathematical formality and evidence use are separate choices.

Evidence-use class scales by use:

C.26:4.4 - Recognition case matrix

C.26:4.5 - State-representation coarsening card

This card discipline is active when a fuller state representation is too detailed, unstable, unavailable, or expensive for the current bounded decision and a reduced-detail state representation is useful only under a declared QL cue.

A.6.3.CSC carries controlled coarsened rendering; A.6.3.RT carries same-selected-entity representation-scheme transition; A.19, U.Dynamics, modeling patterns, and ordinary abstraction patterns carry ordinary state abstraction. C.26 carries only the residual QL cue plus the loss/use boundary for this shortcut.

Question-to-pattern map:

Start with this coarsening mini-card:

For the representation shortcut itself, fill this coarsening card:

If the text claims that the shortcut is faster, cheaper, more compressed, more linear, more stable, or more tractable, add this claim declaration. The claim is separate from the coarsening card: the card controls the reduced-detail state representation; the declaration controls the performance or tractability assertion.

No speed, compression, linearity, or tractability claim follows merely from the words linear, operator, quantum-like, quantized, tokenized, low-bit, finite-dimensional, compressed, or symbolic.

If the shortcut carries a transition-speed, stabilization, or control claim, add the optional dynamics card:

C.26:5 - Archetypal Grounding

Tell: A reliability dashboard says “Ready” after a new readiness metric is published. Before publication, teams treated incidents as local triage. After publication, they change priorities to satisfy the metric, while unmeasured recovery work gets delayed.

Show, System side: the delivery system, teams, dashboard, incident-handling cycle, and release decision form one operational situation. The dashboard is not only a window; it is part of the work ecology because it changes attention, escalation, and behavior.

Show, Episteme side: the ordinary account uses C.16 and A.15 for the metric and changed work, A.10 for evidence use, and B.3 only if the release-assurance question is current. Its useful result is to treat the dashboard as evidence affected by publication and behavior, not as a passive readiness read. No surviving contextual-model obstruction is supplied, so this case returns without QL wording.

Second ordinary-pattern return: a large state-space model is too expensive for triage, so the team uses four typed operational states. Use the direct modeling and state-abstraction method to establish the retained distinctions, loss, bounded use, and reopen trigger. Mere reduction to four states does not activate C.26; a named residual contextual-model obstruction would be a separate premise.

C.26:5.1 - Matching local distributions can still block a joint model

In this constructed mathematical example, a modeler wants to export three specified pair-measurement distributions as one probability distribution over binary variables A, B and C. Only the pair measurements AB, BC and AC are available in the stipulated model. The proposed export requires each repeated variable to have one shared meaning and value across its two pair accounts; this is an explicit assumption of the comparison, not an inference from a repeated label.

The following probabilities are stipulated model inputs, not observed frequencies:

Each row sums to one. Each variable has probability 1/2 of either value in both accounts where it appears. Every local outcome is possible, so checking only allowed assignments leaves all eight binary triples available. These local checks do not establish a joint probability law.

Use C.29 for the declared mathematical correspondence and C.29.1 for the proposed transfer: projecting the joint distribution onto each pair must recover that row. The missing comparison is whether any such joint distribution exists. This is the probabilistic global-section question in Abramsky and Brandenburger, §§2.4–3 and 4.3. A measurement or cross-context meaning claim would separately need its C.16 or F.9 basis.

Derive the obstruction. For one binary triple, let D count unequal pairs. If all three values agree, D = 0; otherwise one differs from the other two and D = 2. Every probability distribution on triples therefore has E[D] ≤ 2. The supplied pair accounts instead require

E[D] = P(A != B) + P(B != C) + P(A != C)
     = 3/4 + 3/4 + 3/4 = 9/4.

Thus no nonnegative joint probability distribution reproduces all three rows under the stated identification. This is a probabilistic no-global-section result; it does not say that no individual triple is locally possible.

Use the result. Keep the pair accounts separate and reject the proposed joint export. A statistic needing that joint law remains unsupported. Changing the pair laws, the shared-variable assumption or the requested statistic reopens the comparison; adding a joint table without that change cannot repair it. The construction establishes no observed probe effect, physical quantum realization or empirical adequacy.

Compare an unobstructed case. Give each of the six nonconstant triples probability 1/6 and give 000 and 111 probability zero. Every pair then has probabilities (1/6, 1/3, 1/3, 1/6). These revised local laws have the displayed joint model. Pairwise availability alone therefore does not activate C.26.

The first useful result here is the exact obstruction to the live joint-export proposal. Ordinary probability theory or C.29.1 can supply the same argument; use an already adequate argument directly without an extra QL note. The C.26 contribution is this named contextual-model comparison, not a claim that QL is the only or faster way to compute it.

C.26:6 - Bias-Annotation

This pattern intentionally biases authors toward ordinary FPF patterns before QL vocabulary. That bias prevents prestige use of the word quantum-like and keeps the mathematical lens focused on its declared representational payoff.

It also biases authors toward minimal admissible outputs. In ordinary use, the right result is often “apply the neighboring FPF pattern”, “do not merge these comparison frames”, “mark this dashboard as an instrument”, or “return to the source representation if the shortcut fails”.

The pattern may under-admit some mathematically valid QL models when the author cannot explain the practical payoff. That is acceptable for FPF pattern prose: a model that cannot say what it buys the working reader is not ready for Core-facing law.

C.26:7 - Conformance Checklist