Incoprea validation round · 3 November 2026

Working research, not peer reviewed. AI-assisted. No new physical experiment was performed. Nine investigations are model, simulation or re-analysis; one (H203) uses a public NASA/JPL catalogue. Code, data, figures and the unmodified originals are in the release ZIP linked at the foot of this page. Negative results are kept in place.

Working research. Not externally peer reviewed. AI-assisted. No new physical experiment was performed. Nine investigations are model, simulation, or re-analysis; one (H203) uses a public NASA/JPL catalogue as measured data. Every number below is regenerated by the code in code/, with fixed seeds. The originals are preserved unmodified in orig/ with SHA-256 hashes.


0. What this is, and what it is not

The previous round produced five named investigations (I2, H0199, P1, P2, P3) and a large bank of new hypotheses. This round does three things:

  1. Reproduces the originals first, before extending them, and records where the original code and the original prose disagree.
  2. Runs an independent test of ten hypotheses that looked provable: the five named ones plus five from the Nov3 near-proof set (H123, H153, H203, H541, H346).
  3. Reports negative and inconvenient results with the same weight as supportive ones.

The status vocabulary is deliberately narrow:

Label Meaning
unsupported The argument does not establish the claim, or is circular; no independent evidence.
contradicted A direct derivation, numerical test, or dataset contradicts the claim (or a stated sub-claim).
internally verified The algebra and numerics are correct inside the stated model, and a second implementation reproduces them.
independently replicated A separate implementation, or a public dataset, reproduces the result.
experimentally supported Measured public data are consistent with the prediction. This is not a new experiment.

A result can carry two labels (for example, internally verified; sub-claim contradicted). That is the honest case for several of these.


1. Verdict at a glance

# ID Claim in one line Independent test Verdict Status
1 I2 A hidden substrate conductance biases every optical measurement of in-plane κ; the bias changes sign at λ=1 Finite-volume PDE solve + 400 synthetic experiments + held-out spot sizes Model confirmed; the sign change is at λ=0.4348, not 1; the beam-width label is off by 2; one spot cannot separate κ from G internally verified; two sub-claims contradicted
2 H0199 Interleaved witness patches beat edge blanks 6 fields × 7 layouts × 400 seeds, matched N and area, 3 estimators Distributed wins; edge bias is 23% and flat in N; the quoted 22.9% is patch-count dependent (16.7%–26.9%) internally verified; headline number refined
3 P1 T₂ ≤ 2T₁ is universal, and T₂/T₁ is a noise-spectrum meter Exact filter functions + density-matrix positivity + estimator sweep The model assumes W ≤ e^(−T/2T₁), so the “proof” is circular; the meter is not identifiable without an independent noise amplitude algebra internally verified; universality claim unsupported; meter unsupported
4 P2 J(d) = j_b + j_s/d separates bulk and surface photocurrent Dimensional audit + CRLB + two-layer forward model + antisymmetry protocol Law confirmed; quoted j_s is 100× too small; the clean test is illumination-side antisymmetry, not a thickness fit internally verified; unit sub-claim contradicted
5 P3 τ_φ ≤ ħQ/(k_BT) bounds oscillator coherence Exact identity + Lindblad + temperature sweep + squeezed bath For a thermal Markovian bath it is an equality, not a bound; the quantum form is exact; a squeezed bath exceeds it by e^(2r) internally verified; universal reading contradicted
6 H123 Repertoire coverage D ≥ σ²N^(−2/d) k-means in d=2,5,10 and a 2-D manifold in d=10 Exponent ≈ −2/d; the prefactor is 8–14, not 1; a 2-D manifold gives −0.83, not −0.2 internally verified; constant sub-claim refined
7 H153 Stemma reconstruction threshold b(1−2p)² > 1 80-tree Monte Carlo, b=2,3,4, depth 4–12 Threshold reproduced to 0.01–0.02 at finite depth; direction confirmed independently replicated numerically
8 H203 Impact-loss tail α = b/(3γ) 300k synthetic events + 1,074 NASA/JPL fireballs b ≈ 2.65–2.82 and α ≈ 1.33–1.41 for thresholds 0.2–2 kt; predicted 1.35 experimentally supported (catalogue), conditional
9 H541 Craze cells are Poisson–Voronoi: E[A]=1/λ, CV≈0.53 Periodic Voronoi Monte Carlo, 200–3,200 nuclei Mean identity exact; CV 0.519–0.543; exponential rejected; clustered/regular shift the CV internally verified; exponential guess contradicted
10 H346 Book-opening force scales as t³ 2-D plane-stress FEM, t/H = 0.005–0.08, plus joint compliance Slope 2.9997; absolute constant is 0.648× the beam formula; a fixed-compliance joint drives the slope to 0 internally verified; absolute constant refined

The single most important result is negative: P1’s “proof” of T₂ ≤ 2T₁ assumes the inequality it reports. The bound may still be true — the density-matrix check is consistent with it — but the calculation does not establish it. The second most important is that I2’s sign change is at λ=0.4348, not λ=1, which changes which measurements are above or below the true κ.


2. Reproduce before extending

The originals were located, copied, hashed, and rerun before any new code was written.

Original Path Hash What was rerun Original number Reproduced
I2 blindspot-2026-11-01/investigations/I2_boundary_bias.py 27ec444a… python3 I2_boundary_bias.py R(1)=1.6769; spread 135.8 R(1)=1.676875; spread 135.76
H0199 further/04-H0199-reference-placement/code/h0199.py 6be22759… python3 code/h0199.py 22.9% edge bias 22.9898% noiseless; 23.12% with noise
P1/P2/P3 discovery07-2026-11-02/proofs/D07_proofs.py 6e9497dd… python3 proofs/D07_proofs.py 2.000; 200%; 381.9 µs 1.9999999999993; 200.0%; 381.9116 µs

The originals are in orig/ with orig/SHA256SUMS.txt. Nothing in the original folders was modified.

Where the original prose and the original code disagree. Three cases matter:

  1. I2 says the bias “crosses unity at λ = 1.” The code’s own R(1.0) returns 1.6769. The zero is at λ = 0.4348. This is not a rounding issue; it is a factor 1.68 in the inferred κ at the claimed crossover.
  2. P2 quotes j_s = 4×10⁻¹¹ A cm. The code evaluates j_s/d with d in metres. The same number in those units is 4×10⁻⁹ A/cm. The crossover stays at 200 nm because both terms were scaled together, which is why the error survived.
  3. P1 reports “exactly 2.000.” The value is 1.9999999999993 at N=32, i.e. 2.000 to three decimals. The model cannot exceed 2T₁ by construction (Section 4.3).

These are recorded, not silently corrected. The corrected statements are in each section.


3. I2 — the spot-size bias in in-plane thermal conductivity

3.1 Original claim and equations

A sheet of thickness d and conductivity κ on a substrate with interface conductance G is heated by a Gaussian spot. In steady state,

κ d ∇²T − G T = −q(r),     q(r) = (P / 2πs²) exp(−r²/2s²)

The Hankel transform gives, at the beam centre,

ΔT(0) = P/(4πκd) · e^λ E₁(λ),      λ = G s²/(2κd)
κ_app/κ = 1/[e^λ E₁(λ)] ≡ R(λ)

The original claims: R crosses 1 at λ=1; the crossover spot radius is s* = √(2κd/G); over plausible (s, G) the reported κ spans 136×; two spot sizes determine κ and G, while more laser powers do not.

3.2 Independent test

Three independent routes:

  1. Closed form vs an axisymmetric finite-volume solve of the PDE on r ∈ [0, L], with a symmetry condition at r=0 and T(L)=0. This does not use the Hankel transform at all.
  2. A 400-experiment synthetic recovery with κ ∈ [5, 500] W m⁻¹K⁻¹, G ∈ [10⁶, 10⁹] W m⁻²K⁻¹, s ∈ [0.2, 3] µm, d ∈ [20, 500] nm, 1% noise. The naive analysis reports κ_app and ignores G; the corrected analysis inverts with G known; the two-spot analysis fits both.
  3. Held-out spot sizes: fit at s = 0.4 and 1.2 µm, predict at 0.8 and 2.0 µm.

3.3 Results

The closed form is right. Finite-volume vs closed form agrees to 2.1×10⁻⁵ relative across λ = 0.05–10 (the residual is discretisation; the original Hankel check was 2×10⁻¹³). The equation is not in question.

The sign change is at λ = 0.4348, not 1. Solving R(λ)=1 gives λ* = 0.434818. At λ=1, R = 1.6769: the reported κ is 68% high, not at the crossover. The crossover spot radius should be s* = √(2λ*κd/G) = 0.932√(κd/G), not √(2κd/G). This is a real correction to the paper’s central figure.

The beam width is off by 2. In the formula, q ∝ exp(−r²/2s²). If w is the 1/e² intensity radius, q ∝ exp(−2r²/w²), so s = w/2. The original calls s the 1/e² radius and uses s = w. Using w instead of s multiplies λ by 4. For three representative cases the inferred κ_app changes by factors 2.08, 2.75 and 3.45. The fix is one line: s = w/2, or write λ = G w²/(8κd).

Ignoring G is catastrophic; one spot with G known is not. Across 400 draws, the naive κ_app has median absolute error 144% and 90th percentile 8,300%. With G known, one spot gives median 2.8%, 90th percentile 37% (the inversion is ill-conditioned near the substrate-dominated limit). Two spots with G fitted give median 3.3%, but 4.5% of draws fail by more than 50% when both spots are substrate-dominated. Conditional on max λ < 10, the two-spot fit gives median 2.2%, 90th percentile 4.8%, maximum 7.5%.

Held-out prediction is good when the design spans the crossover. Median relative error 0.68%, 90th percentile 1.97%, maximum 4.4% at the two unseen spot sizes.

The spread is parameter-range dependent. The original 136× is reproduced for its range; a wider plausible grid (w = 0.5–2 µm, G = 10⁶–10⁸) gives R from 0.143 to 51.0, a 356× spread. The asymptotic statement is the robust one: for λ ≫ 1, κ_app → Gs²/(2d), independent of the material.

3.4 Strongest prior research

The 2-D heat-spreading solution with a substrate conductance is standard in optothermal Raman and TDTR metrology; the same e^λE₁(λ) structure appears in thin-film thermal models. Relevant anchors: the refined optothermal Raman measurement of lateral and interfacial conductivity in MoS₂/MoSe₂ (ACS Appl. Mater. Interfaces), and the variable-spot-size laser-flash Raman method for 2-D heterostructures (ScienceDirect). The metrological point — that the substrate term makes the reported κ depend on the beam size — is what this investigation adds.

3.5 Known vs potentially novel

3.6 Falsification criteria

3.7 Corrected hypothesis

For a Gaussian spot, define s as the 1/e² amplitude radius (= w/2 for a beam of 1/e² intensity radius w). Then

κ_app/κ = R(λ),   λ = G s²/(2κd),   R(λ*) = 1 at λ* = 0.4348

A single spot gives one number and cannot separate κ from G. A two-spot design with at least one spot in 0.1 < λ < 3 gives ~2% κ at 1% noise; a design with both spots at λ > 10 is unidentifiable regardless of how many powers are measured.

Status: internally verified; the λ=1 crossing and the beam-width label are contradicted. No experimental data.


I2 bias curve and error distribution
I2. The bias crosses unity at λ=0.435, not at the claimed λ=1; and ignoring the substrate conductance produces errors up to five orders of magnitude.

4. H0199 — where the witness blanks go

4.1 Original claim and estimator

A substrate carries M=25 reactive patches. Their uptake is R_i = ε f(x_i) + noise; N inert witnesses measure W_j = f(x_j) + noise. The estimator is

ε̂ = Σ_i R_i / Σ_i f̂(x_i)

with f̂ interpolated from the witnesses by quadratic least squares. The claim: interleaving witnesses among the reactive patches beats putting all blanks at the edge. The dossier reports 0.8–1.0% RMSE for distributed vs 22.9% for edge on a boundary-null field.

4.2 Independent test

4.3 Results

The 22.9% is reproduced exactly, but it is not a universal number. For the original 25-patch inset grid, the noiseless edge bias is 22.9898% — precisely the mean of f over those 25 patch locations minus 1. The continuum mean over the full substrate is 20.24%, and over the inset region it tends to 30.3%. Sweeping M at fixed inset:

M 9 16 25 36 49 100
edge bias 16.7% 20.8% 23.0% 24.4% 25.3% 26.9%

So the headline number is a property of the patch layout and count. The qualitative conclusion — edge-only fails for a boundary-constant field — is unaffected and is the stronger statement.

Matched layouts, boundary-null field, N=12, noise 2%:

layout RMSE bias 95% CI
edge 23.12% +22.86% 22.75–23.44
grid 0.93% −0.07% 0.86–1.00
jitter 1.34% −0.10% 1.24–1.45
random 1.91% +0.39% 1.70–2.15
interleaved 1.26% +1.04% 1.19–1.32
D-optimal 2.78% +2.64% 2.70–2.85
maximin 1.11% +0.92% 1.06–1.16

More edge blanks do not help. Edge RMSE from N=4 to N=100: 22.7, 22.1, 23.3, 23.1, 22.9, 22.9, 23.1, 23.1%. The error is a bias set by extrapolation, not a variance set by sample size.

The rim-enhanced field is worse for edge. Edge 37.85%, grid 1.03%, interleaved 5.91%, maximin 9.81%, D-optimal 18.14%. Random placement misses the rim (3.60%); a grid samples it.

Optimising for the wrong model is a failure mode. The D-optimal layout for a quadratic basis puts points at the boundary and is worse than a space-filling design on both adversarial fields (18.1% vs 9.8% on the rim; 2.8% vs 1.1% on boundary-null). Design optimality is model-relative.

The GP estimator is not a rescue. On boundary-null: edge 16.9%, grid 2.9%, interleaved 1.6%. The bias shrinks because the GP prior pulls the interior toward the boundary value, but it does not vanish.

4.4 Strongest prior research

Spatial sampling, kriging, and D-optimal design are mature. The relevant prior is the standard result that a polynomial fitted only on a boundary cannot identify interior structure; the deposition literature’s centre-to-edge non-uniformity is the physical instantiation. The original dossier’s own stop rule already anticipated the caveat.

4.5 Known vs potentially novel

4.6 Falsification criteria

4.7 Corrected hypothesis

Use interior/distributed witnesses whenever the process can produce centre-to-edge or rim structure. Edge-only blanks are not merely suboptimal; they are unidentifiable for a field that is constant on the boundary. The 22.9% figure should be quoted as “23% for a 25-patch inset grid; 17–27% across M=9–100”, not as a universal constant. Interleaving is one way to sample the interior; a space-filling design is at least as good and more robust.

Status: internally verified; the headline number is refined, not contradicted. No experimental data.


H0199 layout RMSE
H0199. At matched N=12 the edge layout is wrong by 23–38% on adversarial fields; more edge blanks do not help.

5. P1 — T₂ ≤ 2T₁: theorem, assumption, or estimator artefact?

5.1 Original claim and model

The original claims T₂ ≤ 2T₁ is universal, that a violation would signal non-Markovian noise, and that T₂*/T₁ is a monotone meter of the noise exponent β. The calculation uses the exact CPMG filter function

F(ω,T) = |∫₀ᵀ s(t) e^{iωt} dt|²,     χ(T) = (1/π)∫ S(ω)F(ω,T)/ω² dω
W(T) = exp(−χ(T)) exp(−T/2T₁)

and defines T₂ as the time at which W falls to 1/e.

5.2 Independent test

  1. Reimplemented the filter function and checked it against direct time-domain integration (7 cases where the filter is not cancellation-limited; max relative difference 3.4×10⁻⁴, at N=8 and ω=10⁵ where the exact value is ~10⁻¹³).
  2. Proved the inequality algebraically and evaluated W(2T₁) for β ∈ {0.5,1,2}, N ∈ {0,1,4,32}.
  3. Checked density-matrix positivity for 40 random initial states × 120 times under amplitude damping plus pure dephasing; checked the Choi matrix of the dephasing channel.
  4. Compared five T₂ estimators on four coherence curves.
  5. Swept the noise amplitude A at fixed β to test whether T₂*/T₁ measures β.

5.3 Results

The “proof” is circular. The model is a product:

W(T) = exp(−χ(T)) · exp(−T/2T₁)  ≤  exp(−T/2T₁)

because exp(−χ) ≤ 1. Therefore W(T₂)=e⁻¹ implies exp(−T₂/2T₁) ≥ e⁻¹, i.e. T₂ ≤ 2T₁. The inequality is assumed by the functional form, not derived from the physics. Numerically, W(2T₁) = e⁻¹exp(−χ(2T₁)) is strictly below e⁻¹ for every χ>0; the slack ranges from 1.3×10⁻¹³ (β=2, N=32) to 0.368 (β=0.5, FID). The bisection can never return a value above 2T₁.

The “exactly 2.000” is rounding. The maximum ratio in the table is 1.9999999999993; at N=32, β=1 it is 1.99999987. The bound is an asymptote approached from below, not a saturated equality.

Positivity is consistent with the bound. The worst violation of |ρ₀₁|² ≤ ρ₀₀ρ₁₁ over the random-state sweep is 2.6×10⁻¹⁶ (machine zero). The Choi matrix of the pure-dephasing channel is PSD for γ ∈ [0,1]. The bound is what positivity plus amplitude damping gives; the filter-function calculation is a complicated way of evaluating a special case.

The estimator changes the answer by a factor of 7. On curves with T₁=100 µs:

curve first 1/e (µs) area (µs)
exponential, T₂=150 µs 150.0 147.3
Gaussian, τ=120 µs 120.0 106.3
stretched, τ=120 µs 120.0 157.0
revival 21.9 74.2

The “first crossing” is meaningless for a curve that revives; the area definition is the stable one. This is the original’s own caveat, now quantified.

**T₂*/T₁ is not a β meter.** At fixed β=1, varying the noise amplitude A by 10⁻³ to 10² changes the ratio from 1.94 to 0.036. Conversely, 37 different (β, A) pairs give the same ratio 1.2. The ratio is a function of (β, A, band, T₁), not of β alone. The calibration table is conditional on the arbitrary A_cal and the 10²–10⁸ rad/s band.

5.4 Strongest prior research

The bound T₂ ≤ 2T₁ is standard for a qubit with amplitude damping plus pure dephasing; it follows from the positivity of the density matrix, not from a noise-spectrum integral. Reports of T₂ > 2T₁ on hardware exist (for example the IBM Washington discussion on Quantum Computing Stack Exchange) and are usually attributed to different T₁/T₂ measurement conditions, non-exponential decays, or leakage — not to a failure of positivity. The 2026 Spectral Bottleneck Constraint (Zenodo, May 2026) is a related no-go result: no universal asymptotic rate law can depend only on an aggregate.

5.5 Known vs potentially novel

5.6 Falsification criteria

5.7 Corrected hypothesis

For a qubit with amplitude damping and pure dephasing, T₂ ≤ 2T₁ holds, and the filter-function model reproduces it only because it assumes it. T₂/T₁ is a consistency check and a lower bound on the dephasing rate, not a spectrum meter. A credible β inference needs an independently measured noise amplitude and band (or a direct noise spectrum); the ratio alone is degenerate.

Status: the algebra is internally verified; the universality claim is unsupported (circular); the meter is unsupported. Positivity is consistent with the bound.


P1 meter and estimator dependence
P1. T₂*/T₁ moves by a factor of 50 at fixed spectrum when the noise amplitude changes; the ratio is not a β meter.

6. P2 — bulk plus surface photocurrent

6.1 Original claim and equations

In a centrosymmetric film the bulk photovoltaic current vanishes by symmetry, so the measured current density is

J(d) = j_b + j_s/d

with j_b in A cm⁻² and j_s in A cm (a sheet current per unit width). The original quotes j_b=2×10⁻⁴ A cm⁻², j_s=4×10⁻¹¹ A cm, crossover 200 nm, a 100 nm film reading +200% above bulk, and a 50 nm/1 µm ratio of 4.17.

6.2 Independent test

  1. Dimensional audit of the equation and the code.
  2. Cramér–Rao lower bound on (j_b, j_s) as a function of thickness range and noise.
  3. A two-layer forward model: a surface layer of thickness t_s with conductivity σ_s on a bulk σ_b, J = σ_b E + (σ_s−σ_b)t_s E/d. Fit the two-parameter law and compare the recovered j_s to the true (σ_s−σ_b)t_s E.
  4. A distinctive protocol: illumination-side antisymmetry. If J(+)=j_b+j_s/d and J(−)=j_b−j_s/d, then the half-sum is j_b and the half-difference is j_s/d. The half-difference versus 1/d has slope j_s and zero intercept.
  5. A symmetric-interface null: two identical surfaces cancel j_s, so J(d) is thickness-independent.

6.3 Results

The numbers reproduce. J(100 nm)/j_b = 3.0 (+200%); J(50 nm)/J(1 µm) = 4.167; crossover 200 nm. The algebra is right.

The quoted j_s is 100× too small. The code evaluates j_s/d with d in metres. The same numerical value 4×10⁻¹¹ then has units A m cm⁻¹, i.e. 4×10⁻⁹ A/cm. Written with d in cm, the correct j_s is 4.0×10⁻⁹ A/cm. The crossover is unchanged because j_b and j_s were scaled together. This is a unit-label error, not a physics error, but it would mislead anyone converting the number.

The fit needs a wide thickness range. CRLB at 3% relative noise, 60 points:

thickness range ratio σ(j_b)/j_b σ(j_s)/j_s
20 nm–2 µm 100:1 0.64% 1.69%
100 nm–1 µm 10:1 0.99% 2.07%
20–200 nm 10:1 2.23% 1.17%
500 nm–2 µm 4:1 1.19% 6.21%
1–2 µm 2:1 2.20% 15.65%

A two-parameter separation from a 2:1 series is not credible at 3% noise; the original’s 100:1 series is well conditioned. The correlation between the two parameters is −0.64 to −0.98, so the fit is a classic collinearity problem.

The 1/d law is exact for a uniform surface layer. In the two-layer model the fit recovers j_s to 0.4–4.5% (noise-limited), and the true j_s is (σ_s−σ_b)t_s E. The law is not a microscopic derivation; it is dimensional bookkeeping for a sheet current. A surface layer whose thickness or conductivity changes with d breaks it.

The clean test is antisymmetry, not a thickness series. The half-difference recovers j_s = 4.0×10⁻⁹ A/cm exactly and the half-sum recovers j_b = 2.0×10⁻⁴ A cm⁻². A symmetric device has j_s = 0 and no 1/d term. This is a distinctive, cheap prediction: reverse the illumination side (or the contact polarity) and the surface term changes sign while the bulk term does not.

6.4 Strongest prior research

The 1/d dilution of a sheet current is standard. The relevant recent literature is the interface-BPVE programme: “Giant bulk photovoltaic effect driven by interfacial symmetry breaking in MoS₂/Ta₂NiSe₅ heterostructures” (Nature Communications, 2026) and “High performance bulk photovoltaics in narrow-bandgap centrosymmetric ultrathin films” (Materials Horizons, 2020), plus thickness-dependent BPVE in 3R-MoS₂ (Advanced Physics Research, 2025). These support the physical premise — a centrosymmetric film can show an interface-dominated photocurrent — and make the 1/d term plausible. The novel part here is the separation protocol, not the law.

6.5 Known vs potentially novel

6.6 Falsification criteria

6.7 Corrected hypothesis

J(d) = j_b + j_s/d with j_s in A/cm and d in cm. The quoted j_s should be 4.0×10⁻⁹ A/cm, not 4×10⁻¹¹. The law is exact for a uniform surface layer; its microscopic interpretation requires t_s and σ_s. The decisive test is the illumination-side antisymmetry: J(+)−J(−) = 2j_s/d, with a null in a symmetric device.

Status: internally verified; the unit sub-claim is contradicted; the law is conditional on geometry. No experimental data.


7. P3 — the fluctuation–dissipation coherence bound

7.1 Original claim and equations

A harmonic oscillator of frequency ω₀, quality factor Q and bath temperature T has

τ_φ ≤ ħQ/(k_BT)          (classical)
τ_φ ≤ 1/[γ(n_th+1/2)]    (quantum),  γ=ω₀/Q,  n_th=1/(e^{ħω₀/k_BT}−1)

At Q=10⁶, T=20 mK, f₀=100 kHz the classical bound is 382 µs.

7.2 Independent test

  1. Reproduced the numbers.
  2. Derived the exact identity and compared it with the classical limit across T = 1 µK–300 K.
  3. Solved the two-level Lindblad equation with amplitude damping and heating; fitted the ρ₀₁ decay and compared with γ(n_th+1/2).
  4. Computed the squeezed-thermal-bath dephasing rate Γ_φ = γ e^{−2r}(n_th+1/2), which exceeds the thermal bound by e^{2r}.
  5. Searched the 2025–2026 literature for a counterexample to a universal spectral bound.

7.3 Results

The numbers reproduce. Classical 381.9116 µs; quantum 381.911627 µs; ratio 0.999999995; ħω₀/k_BT = 2.4×10⁻⁴.

The quantum expression is exact, and it is an identity. For a thermal Markovian bath,

Γ_φ = γ(n_th+1/2) = (γ/2)coth(ħω₀/2k_BT)
τ_φ = (2Q/ω₀)tanh(ħω₀/2k_BT)

The two-level Lindblad fit gives Γ_φ/γ = 0.5, 1.0, 5.5 for n_th = 0, 0.5, 5 — matching n_th+1/2 to 10⁻¹¹. The “bound” is an equality for the model it describes.

The classical form is the high-T limit, and it is very good at ordinary temperatures. The 10% deviation from the exact form occurs at T = 4.34 µK for f₀=100 kHz. At 20 mK the correction is 4.8×10⁻⁹. The “quantum correction” is therefore irrelevant for essentially all optomechanics at 100 kHz; it matters only in the microkelvin regime. The classical formula diverges as T→0 and is not a bound there; the quantum form is.

The bound is not universal: a squeezed bath beats it. With squeezing parameter r, Γ_φ = γ e^{−2r}(n_th+1/2), so τ_φ exceeds the thermal bound by e^{2r}: 2.72× at r=0.5, 7.39× at r=1, 54.6× at r=2. This is outside the claim’s stated scope (a squeezed bath is non-thermal), but it shows that the inequality is a thermal-equilibrium statement, not a law of nature. A driven/parametric system can do the same.

The 2026 literature search did not find the specific September counterexample. The closest 2026 items are the Spectral Bottleneck Constraint (Zenodo, 24 May 2026), a no-go theorem for aggregate asymptotic rate laws, and the September 2026 induced-coherence paper (arXiv:2609.35523), which is about interferometric triality, not this bound. A systematic search of web indexes and arXiv listings on 3 November 2026 found no paper that directly contradicts τ_φ ≤ ħQ/(k_BT) for a thermal bath. If a specific September 2026 counterexample exists outside the indexed sources, it should be supplied; the honest statement is that this search did not locate it.

7.4 Strongest prior research

The FDT relation S_F = 4mγk_BT and the thermal dephasing rate γk_BT/(ħω₀) are standard in optomechanics and in the theory of damped oscillators. The quantum form (2Q/ω₀)tanh(ħω₀/2k_BT) is the same identity written with n_th. The 2026 no-go result is a warning against three-number consistency claims in general, not a direct test of this one.

7.5 Known vs potentially novel

7.6 Falsification criteria

7.7 Corrected hypothesis

For a single harmonic oscillator linearly coupled to a Markovian thermal bath, τ_φ = 1/[γ(n_th+1/2)] exactly. The classical ħQ/(k_BT) is the high-temperature limit and is accurate to 10% above ~4.3 µK at 100 kHz. The inequality τ_φ ≤ ħQ/(k_BT) is a thermal-equilibrium consistency check, not a universal bound; squeezed or driven baths exceed it by e^{2r} or more.

Status: internally verified; the universal reading is contradicted by the squeezed bath; the thermal-bath identity is exact. No experimental data.


8. H123 — the repertoire as a quantizer

8.1 Claim

For X ~ N(0, σ²I_d) and a codebook of N points, the Gaussian rate–distortion converse gives D ≥ σ²N^{−2/d}, so the RMS coverage error decays as N^{−1/d}. The claim is a theorem transplant from rate–distortion theory.

8.2 Test

Lloyd/k-means quantizers with KD-tree assignment, N = 8…4096, d = 2, 5, 10, and a 2-D manifold embedded in d=10. Fit the log–log slope over N ≥ 64.

8.3 Results

source fitted slope predicted −2/d prefactor D·N^{2/d}
Gaussian d=2 −0.822 −1.0 7.95
Gaussian d=5 −0.359 −0.4 8.21
Gaussian d=10 −0.173 −0.2 13.61
2-D manifold in d=10 −0.826 −0.2 0.010

The exponent approaches −2/d; the d=2 finite-N slope is shallow because N=4096 is not asymptotic and k-means is not the optimal quantizer. The prefactor is 8–14, not 1: the inequality D ≥ σ²N^{−2/d} holds, but it is not tight at these N, and the claimed constant is not achieved. The manifold case is decisive: the ambient dimension is 10 but the slope is −0.83, i.e. the effective dimension controls the cost. Using d=10 would overestimate the repertoire needed by a large factor.

8.4 Prior research and status

Shannon’s rate–distortion theorem and Zador’s asymptotic quantization theory are the prior art. The biology is the open mapping. Status: internally verified (theorem transplant); the constant sub-claim is refined; the effective-dimension caveat is the useful result. No experimental data.

8.5 Falsification and correction

Coverage decaying exponentially in N, or a fitted slope near −1 for a genuinely high-dimensional pathogen space, would contradict the quantizer model. Corrected: D ≈ C_d σ²N^{−2/d} with C_d ≈ 8–14 over the tested range; use the measured effective dimension, not the ambient dimension.


9. H153 — the stemma threshold

9.1 Claim

On a regular b-ary copying tree with per-edge error p, the archetype is reconstructible iff b(1−2p)² > 1 (Kesten–Stigum). The claim is a transplant.

9.2 Test

80–120 trees, root strings of length 24–48, b=2,3,4, depth 4–12, majority reconstruction (ML for the symmetric BSC tree). Locate the 0.5-overlap crossing and compare with p_c=(1−1/√b)/2.

9.3 Results

b p_c (asymptotic) empirical 0.5 crossing (depth)
2 0.1464 0.134 (h=12)
3 0.2113 0.191 (h=9)
4 0.2500 0.248 (h=6)

The finite-depth crossing is below the asymptotic threshold, as expected: at finite depth the transition is smoothed. The depth scan confirms the direction: for b=3, p=0.18 (above threshold) has overlap 0.60→0.51 over h=4→10, while p=0.22 (below) decays 0.45→0.27, and p=0.30 decays to 0.04. The theorem is reproduced with a finite-size correction.

9.4 Prior research and status

Kesten–Stigum (1966); Mossel’s tree-reconstruction work; the Roch lecture notes. Status: independently replicated numerically. The paleographic estimation of b and p is unverified and is the actual open problem.

9.5 Falsification and correction

A tradition below the predicted threshold reconstructed with high confidence, or above it and opaque, would contradict the mapping. Corrected: the threshold is asymptotic; a single-depth 0.5 crossing is biased low by 0.01–0.02 at h≤12. Use the depth scaling (persistence vs decay), not a single crossing.


10. H203 — the impact-loss tail

10.1 Claim

If N(>D) ∝ D^{−b}, E ∝ D³ and L ∝ E^γ, then P(L>x) ∝ x^{−α} with α = b/(3γ). For b=2.7 and γ=2/3, α=1.35: finite mean, infinite variance.

10.2 Test

10.3 Results

Synthetic: b_est = 2.69–2.71, α_L = 1.345–1.356, exact to the estimator’s precision.

Fireball catalogue:

threshold (kt) n tail α_E b_est = 3α_E α_L (γ=2/3)
0.2 517 0.912 2.736 1.368
0.5 221 0.939 2.816 1.408
1.0 109 0.884 2.651 1.325
2.0 59 0.903 2.709 1.354
5.0 28 1.099 3.297 1.648
10.0 12 — — —

For thresholds 0.2–2 kt, b ≈ 2.65–2.82 and α_L ≈ 1.33–1.41, bracketing the predicted 1.35. At 5 kt the tail has only 28 events and the estimate is noisy. The result is a genuine public-data consistency check, not a new measurement: the catalogue is incomplete, the impact energies are model-derived from radiated energy, and the agreement may be partly built into the energy conversion. The actuarial conclusion (variance infinite for 1<α<2) is standard extreme-value theory; it is not tested here against insured losses.

10.4 Prior research and status

Impactor size–frequency laws, the CNEOS fireball survey, and regular variation in catastrophe insurance. Status: experimentally supported (catalogue), conditional. The synthetic part is independently replicated.

10.5 Falsification and correction

An exponential loss tail, or α > 2 at high confidence, or a population with b>2 and γ≈1 producing a finite-variance loss distribution after aggregation. Corrected: α = b/(3γ) is exact given the power laws; the empirical support is b≈2.7 for 0.2–2 kt fireballs, so α≈1.35 with γ=2/3. The claim should cite the threshold range, not a single number.


H203 fireball tail
H203. The CNEOS fireball energy tail gives b≈2.7 and α≈1.35 for thresholds 0.2–2 kt.

11. H541 — craze cells as a Poisson–Voronoi tessellation

11.1 Claim

E[A]=1/λ for a homogeneous Poisson nucleation process; the area CV is ≈0.53; the earlier exponential-area guess is false.

11.2 Test

Periodic Voronoi tessellation (3×3 tiling, convex-hull cell areas), 200–3,200 nuclei, 8 repetitions, plus Thomas-clustered and regular-grid controls.

11.3 Results

Poisson: mean-area ratio 1.000 at n=3,200; CV 0.530 (n=3,200), 0.519 (n=800), 0.543 (n=200). The exponential fit is rejected (KS p≈0). Thomas-clustered: CV 0.993 at n=200, 0.727 at n=800, 0.585 at n=3,200 (approaching Poisson as the density rises). Regular grid: CV≈0. The mean-area identity is exact; the CV is a diagnostic for Poisson nucleation, not a universal constant of glaze chemistry.

11.4 Prior research and status

Meijering’s theorem; the Gilbert/Voronoi model of craze cells. Status: internally verified; the exponential guess is contradicted. No glaze images were measured.

11.5 Falsification and correction

Mean area not scaling as 1/λ, or a CV far from 0.53 with no change in chemistry. Corrected: E[A]=1/λ is exact; CV≈0.53 is the Poisson benchmark; a CV near 1 indicates clustering, near 0 indicates a regular grid.


12. H346 — opening a book is a bending problem

12.1 Claim

F ≈ E w t³ θ/(6H²); the force scales as the cube of spine thickness.

12.2 Test

A 2-D plane-stress finite-element model: a cantilever strip of length H, thickness t, unit width, clamped at x=0, loaded by a pure end moment M. The effective stiffness EI_eff = MH/θ is measured from the end-face rotation. A fixed rotational compliance c_j models the joint.

12.3 Results

The fitted slope of log EI_eff vs log t is 2.99975 over t = 0.005–0.08, confirming the cubic scaling. The absolute value is 0.648× the beam formula t³/12 across the whole range (a constant 2-D/end-effect factor), so the dossier’s 1/6 is a boundary-condition convention, not a universal prefactor; the elastic-strip value is 1/12.

The joint changes the exponent. With a fixed rotational compliance c_j, the log–log slope of F/θ vs t is 3.0 for c_j=0, 1.84 for c_j=10⁶, 0.26 for c_j=10⁸, and 0.04 for c_j=10⁹. When the joint dominates, the force is nearly thickness-independent. A measured slope below 3 is therefore evidence for joint compliance, not a refutation of elasticity.

12.4 Prior research and status

Euler–Bernoulli beam theory is textbook. Status: internally verified; the absolute constant is refined. No bench measurements.

12.5 Falsification and correction

A slope significantly different from 3 after controlling for width, height and joint compliance; or a force independent of thickness in a joint-free strip. Corrected: F ∝ t³ in the elastic-strip limit; the prefactor is geometry-dependent (0.648× the beam formula in this 2-D model); a joint-dominated binding shows a slope near 0–1.


13. Cross-cutting findings

Four failure modes recur across the ten investigations, and they are more transferable than any single number.

  1. Normalisation is often the result. The 22.9% edge bias is the mean over 25 inset patches; it becomes 16.7% at M=9 and 26.9% at M=100. The 136× I2 spread becomes 356× on a wider grid. The “2.000” is a rounded 1.9999999999993. A number quoted without its layout, range, or estimator is not reproducible.

  2. Estimator dependence is not a nuisance; it is the systematic. T₂ varies by a factor of 7 between the first-crossing and area definitions on the same curve. κ_app varies by a factor of 3.45 between the amplitude and intensity beam radii. The Hill tail index varies by 0.25 between thresholds. Pre-registering the estimator is part of the test.

  3. A proof that assumes its conclusion is worse than no proof. P1’s filter-function model multiplies the coherence by exp(−T/2T₁), so it cannot return T₂ > 2T₁. The calculation is internally consistent and physically irrelevant to the universality question. This is the clearest negative result of the round.

  4. Model-relative optimisation can be worse than random. D-optimal witness placement for a quadratic field is worse than maximin or a grid on both adversarial fields (18.1% vs 9.8% on the rim; 2.8% vs 1.1% on boundary-null). The same lesson applies to the I2 two-spot design: two spots chosen without regard to λ can be unidentifiable.


14. Known vs potentially novel

Investigation What is already known What might be new here
I2 2-D heat spreading with a substrate conductance; two-spot identifiability Zero-bias λ*=0.4348; the beam-width factor-2 trap; the failure map for two spots when both are substrate-dominated
H0199 Regression extrapolation; space-filling designs; kriging Matched head-to-head with the actual interleaved layout; the M-dependence of the 22.9%; D-optimal worse than random under misspecification
P1 T₂ ≤ 2T₁ for the standard qubit; estimator dependence of T₂ The circularity of the Discovery07 proof; 37 degenerate (β,A) pairs at fixed ratio
P2 Sheet-current 1/d dilution; interface BPVE The antisymmetry protocol; the 100× unit correction; the conditioning map
P3 FDT; thermal dephasing; squeezed-bath noise reduction Scope statement; 4.34 µK crossover at 100 kHz; the “bound is an equality” reading
H123 Rate–distortion; Zador The prefactor 8–14 for k-means at accessible N; effective-dimension falsification
H153 Kesten–Stigum; tree reconstruction Finite-depth bias of the 0.5 crossing (0.01–0.02)
H203 Regular variation; impactor size–frequency Fireball-catalogue b≈2.7 and α≈1.35 for 0.2–2 kt
H541 Meijering; Poisson–Voronoi CV diagnostic separating clustered/regular nucleation at fixed mean
H346 Euler–Bernoulli 2-D FEM constant 0.648×; joint-compliance slope transition 3→0

None of the “potentially novel” items is a new physical law. They are corrections, protocols, and scope statements. That is the appropriate output of a validation round.


15. Falsification criteria, compact

ID The claim dies if…
I2 a sample with known κ, G does not follow R(λ) at the stated s, d; or a two-spot fit with max λ<10 errs >10%
H0199 an edge-only layout reaches <2% on a boundary-null field at any N
P1 a same-conditions device has exponential T₂ > 2T₁ with verified T₁, or the ratio is one-to-one with β at unknown A
P2 J is thickness-independent in a centrosymmetric film; or the illumination-side half-difference is not 1/d
P3 a thermal-bath oscillator exceeds 1/[γ(n_th+1/2)] with verified Q, T
H123 coverage decays exponentially in N; or a high-dimensional source shows slope ≈−1
H153 a below-threshold tradition is reconstructed with high confidence, or an above-threshold one is opaque
H203 an exponential loss tail, or α>2 at high confidence
H541 mean area ≠ 1/λ; or CV≈0.53 is not reproduced for Poisson nucleation
H346 slope ≠ 3 after controlling for joint compliance; or force independent of t in a joint-free strip

16. Remaining uncertainty


17. Reproducing this round

Environment: Python 3.14, numpy 2.5.4, scipy 1.18.1, matplotlib 3.11.2. All runs fixed-seed. Total runtime under five minutes on the machine that produced this report; the fireball catalogue is cached in data/fireballs.json.

cd code
python3 t01_i2.py        # I2
python3 t02_h0199.py     # H0199
python3 t03_p1.py        # P1
python3 t04_p2.py        # P2
python3 t05_p3.py        # P3
python3 t06_h123.py      # H123
python3 t07_h153.py      # H153
python3 t08_h203.py      # H203 (uses data/fireballs.json)
python3 t09_h541.py      # H541
python3 t10_h346.py      # H346

Each script writes data/tNN_*.json and figures/tNN_*.png. The summary numbers in this report are read from those JSON files; no number was typed by hand without a corresponding field.

Originals: orig/ contains the unmodified source, the Discovery07 proof text, and SHA256SUMS.txt. The original folders in the workspace were not modified.


18. Sources and verification status

Source Used for Status
Refined optothermal Raman, MoS₂/MoSe₂ I2 prior art peer-reviewed, abstract-level check
Variable-spot-size laser-flash Raman I2 prior art peer-reviewed, abstract-level check
Interface BPVE in MoS₂/Ta₂NiSe₅ P2 prior art 2026 Nature Communications; metadata check
Centrosymmetric ultrathin BPVE P2 prior art peer-reviewed, metadata check
Spectral Bottleneck Constraint P3 prior art preprint, single author, not peer reviewed
Induced coherence, arXiv:2609.35523 P3 literature search September 2026 preprint, not a counterexample to P3
Kesten–Stigum notes H153 lecture notes
Zador quantization H123 survey/thesis extract
CNEOS fireball API H203 live public data, fetched 2026-11-03
Poisson–Voronoi statistics H541 reference notes

The 2026 sources are flagged as preprints or metadata-level checks; they were not read in full. No source is used to claim experimental support for a claim that this round did not test.


If one sentence survives: the numbers that were wrong were wrong by factors of 2 to 100, and the proofs that were circular were circular because they multiplied by a factor that could never exceed 1. Both are cheaper to catch than to publish.


Download the release ZIP (code, data, figures, originals, 1.3 MB) · Back to the research hub

Status vocabulary: unsupported, contradicted, internally verified, independently replicated, experimentally supported. No claim on this page is experimentally supported by a new experiment.