Validation layer · Model sanity
Model sanity, metric sensitivity and analytic benchmarks
A follow-on scientific validation layer for the Phase 2 engine. It checks the engine against closed-form mathematics, exposes alternative relational observables, and keeps failed or null results visible.
Model finding A · Metric constraint
The adjacency gain is bounded: Γ_A ≤ 1
Let P be a geodesic of w. Then D(w′) ≤ Σ_(e∈P) w′_e ≤ D(w) + ‖Δw‖₁, and symmetrically with the roles reversed. Hence |ΔD| ≤ ‖Δw‖₁ = C_A, so the gain can never exceed unity.
This is a property of the metric we chose, not a law of physics, and it is neither evidence for nor against physical Adjacency Theory. We will never market Γ > 1 under this metric: if it appears, the implementation is wrong.
Scope: the bound holds when D and C_A are measured in the same units on the same edge set. Under the coupling convention d = −L·ln(R) with cost measured in coupling space, or under a different observable, it must be re-derived.
Deterministic property tests
P1 Γ ≤ 1 across seeded L1 perturbations
PASS1200 trials, 0 violations, max Γ = 0.633428971
P2 Single geodesic-edge increase gives Γ ≤ 1
PASSΓ = 0.180074569 for Δw = +0.25 on edge 0-10
P3 C_A = 0 yields undefined Γ (no division by zero)
PASSUnchanged relational state ⇒ ΔD = 0, C_A = 0, Γ reported as null.
P4 Suite is deterministic under identical seed
PASSmax Γ 0.640050164 vs 0.640050164
All property tests pass. They verify the implementation against the proof, nothing more.
Runs in-browser, deterministically, from the seed shown.
Model finding B · Baseline seeded universe
Deterministic 100-node near-lattice, seed 42
D(A=0, B=99)
16.0954303999
Weighted shortest path
Path nodes
19
Hops
18
Mean degree
3.60
~4 nearest-neighbour connectivity
Edges
180
Σ w (total length)
184.2911
This universe is regenerated from its own seeded rules on every load. We deliberately do not hardcode the collaborator reference value of 15.4862517751 over a 17-node path: their generator is not ours, so the numbers are expected to differ. A mismatch means the generators differ, not that either calculation is wrong.
AT-VAL-BASE@0.1.0 · near-lattice-l1-1.0.0
Fingerprint · reproducibility
d0dc·2d93·bf07
d0dc2d93bf0720547c004e755e8fdb8a
|ΔD| between independent runs = 0.00e+0
Identical inputs must produce an identical fingerprint. Any drift in the engine changes it, which is the point.
Model finding C · Metric sensitivity
Alternative relational observables
D(A,B)
Weighted shortest path
Minimum total relational length over all paths from A to B.
1-Lipschitz in L1 edge-weight perturbations, so Γ_A ≤ 1 by construction.
R_eff(A,B)
Effective resistance
(e_A − e_B)ᵀ L⁺ (e_A − e_B) on the weighted Laplacian with conductance c_e = 1/w_e.
Aggregates every parallel route, not just the geodesic. Electrical language is an analogy for the linear algebra; no circuit and no physics is implied.
E_glob
Global efficiency
Mean of 1/d(i,j) over all ordered node pairs.
A whole-network diffusion-style summary. It has no A→B interpretation and no physical units.
Local edit → global response · edge 0-10
Edge (0, 10): w 0.788807 → 0.709926 · Σ|Δw| = 0.078881 = 0.0428% of total network length.
| Observable | Before | After | Δ | Fractional Δ | Normalized structural sensitivity |
|---|---|---|---|---|---|
| Weighted shortest path D(A,B) | 16.0954303999 | 16.0165497147 | -7.888e-2 | -0.4901% | 11.45× |
| Effective resistance R_eff(A,B) | 3.0661430616 | 3.0431762396 | -2.297e-2 | -0.7490% | 17.50× |
| Global efficiency E_glob | 0.2304404475 | 0.2305091020 | 6.865e-5 | 0.0298% | 0.70× |
Collaborator reference for comparison only: R_eff ≈ 2.0818187571, normalized response ≈ 10.5× on a differently generated seed-42 graph. The table above shows this project's own deterministic result.
AT-0022 · Analytic sanity case
Minimum relocation cost against its closed-form bound
Toy relational address: 10 origin-neighbourhood relations at 0.9 and 10 destination-neighbourhood relations at 0.1, identity vector held fixed. Under monotonic L1 endpoint cost the minimum is exactly the sum of the required boundary moves.
Two-sided constraint (release origin AND bind destination)
PASSAnalytic minimum
14.0000
Optimizer cost
14.0000
Gap
7.89e-13
ΔI
0.0000
Final origin mean
0.2000
Required ≤ 0.2
Final destination mean
0.8000
Required ≥ 0.8
Optimizer reproduces the analytic L1 minimum.
One-sided constraint (bind destination only)
PASSAnalytic minimum
7.0000
Optimizer cost
7.0000
Gap
-1.28e-13
ΔI
0.0000
Final origin mean
0.9000
Unconstrained
Final destination mean
0.8000
Required ≥ 0.8
Optimizer reproduces the analytic L1 minimum.
AT-0023 · Continuity and path dependence
Direct vs multi-step, adjacency debt, hysteresis
| Path | Steps | C_path | ‖ΔR‖₁ | Debt_A | Intermediate states |
|---|---|---|---|---|---|
| Direct (1 step) | 1 | 2.8000 | 2.8000 | 0.0000 | NO |
| Monotonic (2 steps) | 2 | 2.8000 | 2.8000 | 0.0000 | YES |
| Monotonic (4 steps) | 4 | 2.8000 | 2.8000 | 4.44e-16 | YES |
| Overshoot then correct (detour) | 2 | 4.0000 | 2.8000 | 1.2000 | YES |
Cost equality
CONFIRMEDMonotonic multi-step transformations carry the SAME cumulative L1 cost as the direct one-step transformation between the same endpoints. Step count is therefore not an observable of this model, and no physical conclusion about continuity or discontinuity follows from it.
Hysteresis
NO HYSTERESISRound-trip residual = 0.00e+0
The current transformation rule is reversible and state-independent, so the round-trip residual is exactly zero. We report no hysteresis rather than manufacture an effect. A history-dependent rule would be required for a nonzero result.
Research notes
What these results are, and what they are not
Γ_A ≤ 1 under shortest path with L1 weight cost
Weighted shortest-path distance is 1-Lipschitz with respect to L1 perturbations of the same edge weights, so |ΔD| ≤ Σ|Δw| and the adjacency gain cannot exceed 1. This is a property of the chosen graph metric. It is not a physical law, it is not a speed limit, and it is neither evidence for nor against physical Adjacency Theory. Γ > 1 under this metric would indicate an implementation error, never a discovery.
Seeded perturbation sweep finds zero violations
Thousands of deterministic seeded perturbation trials on the baseline universe produce zero Γ > 1 events. This confirms the implementation matches the proof; it discovers nothing about nature.
Gain is metric-relative
Γ_A is only bounded when D and C_A are measured in the same units on the same edge set. Under the coupling convention d = −L·ln(R) with cost measured in coupling space, or under a different observable such as effective resistance, the bound does not transfer and must be re-derived. Cross-metric gain figures are not comparable.
Normalized structural sensitivity is a ratio, not an amplifier
A ~10% reduction of one local edge changes global observables only modestly in raw units, but the fractional observable change divided by the fractional whole-network L1 modification is large simply because the denominator spans every edge. This is normalized structural sensitivity. It is not energy gain, free energy, amplification, or anything superluminal.
Adjacency Debt is non-negative
Debt_A = C_path − ‖R_final − R_initial‖₁ ≥ 0 by the triangle inequality. Direct and monotonic transformations have zero debt; detours and reversals create positive debt. It measures history inefficiency in relational-state space and is not a physical or energetic debt.
Step count cannot decide continuity
Monotonic multi-step transformations cost exactly the same as the direct one-step transformation between the same endpoints, so the number of stored intermediate relational states is a bookkeeping choice of the transformation record, not an observable. The absence of intermediate graph states does not demonstrate physical discontinuity.
No hysteresis in a reversible static rule
The current transformation rule has no state or history dependence, so a round trip R → R' → R leaves exactly zero residual. We report zero hysteresis. Any nonzero figure would require a genuinely history-dependent rule and a measurable round-trip residual.
Does any physical system realise a relational-distance observable?
Everything above concerns a graph. Whether any physical structure supports an observable that behaves like D(A,B) = F(R), whether identity can be defined independently of spatial state, and whether a transition operator has any physical referent all remain entirely open. No result on this page bears on them.
Which observable, if any, would be the physically meaningful one?
Shortest path, effective resistance and global efficiency disagree about how strongly a local relational edit matters. Nothing in the mathematics selects one of them as privileged. A physical theory would have to supply that selection before any of these numbers could be interpreted.