To Determine an Object You Need Every Other One ── What the Yoneda Lemma Requires and What Is Lost When the Probe Is Weakened: Counted over the 156 Graphs on Six Vertices ── [Paper 244]
Aug 2026· Zenodo (CERN European Organization for Nuclear Research)
Abstract
The Yoneda lemma says that an object is completely determined by its relations to every other object. This paper asks about that word every: where does the separating power fall when the probe is weakened? And the loss turned out not to be governed by the strength of the probe. No new mathematical theorem and no new law is claimed. Scope of this paper (scope note): no new mathematical theorem and no new law is claimed. The Yoneda lemma, the existence of cospectral non-isomorphic graphs, and the coincidence of the character tables of the dihedral group of order eight and the quaternion group are all standard. No measured value is cited; every number is obtained by exhaustive enumeration. No category theory is developed; only the statement of the lemma is used, and neither its proof nor any generalisation is treated. Nothing is said about the complexity of graph isomorphism; this is an exhaustive count in the finite case of six vertices. No representation theory is developed; the character tables are quoted as known. It is not claimed that the Yoneda lemma justifies the method of this body of work; Section 6 exists precisely to stop that claim from being made. The relation to earlier papers. Paper 152 showed that two groups can share a character table without being isomorphic; this paper counts that phenomenon as a function of the strength of the probe. Paper 153 separated three stages of forgetting and exhibited evidence that a right adjoint is absent; this paper treats the neighbouring theorem on the same shelf. Paper 102 treated the question whether one can hear the shape of a drum; Section 3 is its finite version, counted exhaustively. Paper 163 showed that there exists and here it is are different sentences; Section 6 says that determined and computable are different sentences. The setting. Take a collection of objects and a probe, a function applied to an object that returns a value. When a probe returns the same value on two objects it does not separate them. The material is the simple graphs on six vertices, of which there are 32768 labelled ones. Three probes are used: the degree sequence, the spectrum of the adjacency matrix, and the spectrum together with the triangle count. For comparison the isomorphism type itself is included. First, the 32768 labelled graphs fall to 156 isomorphism classes, counted by applying all 720 vertex permutations and taking a canonical form. Second, the degree sequence is not enough. It takes only 102 distinct values and 84 classes survive unseparated in 30 groups. Third, the spectrum is not enough either. It takes 151 values and 10 classes survive in 5 groups. Fourth, this is the core. Adding the triangle count leaves the distinct values at 151 and the unseparated classes at 10. The triangle count is the trace of the cube of the adjacency matrix divided by six, a function of the spectrum, so adding it adds no information. Whether more probes separate more depends on whether the new one can be recovered from the old. Measure more invariants and you will eventually tell them apart is false; dependent invariants advance nothing. Fifth, strength is not a total order on separating power. The smallest pair the spectrum cannot separate has degree sequences zero one one one one four and zero zero two two two two, both with four edges and no triangles, sharing the spectrum minus two, zero, zero, zero, zero, two. The degree sequence does separate that pair. A weaker probe separates where a stronger one fails. Sixth, the same happens for groups. The dihedral group of order eight and the quaternion group share a character table and are not isomorphic. Counting the elements whose n-th power is the identity, that is the homomorphisms from a cyclic group, gives six and two at n equal to two, which separates them. The character table failed and counting maps from a single object succeeded. Yet at n equal to four the counts are eight and eight and do not separate. The same shape of probe changes its power when the test object changes, and which object works cannot be known in advance. That is why Yoneda demands every object. Seventh, this is a fence. The lemma reads as saying that a thing is determined by its relations, and the method of this body of work, writing what a thing separates rather than what it is, has a similar shape. Similarity is not justification. The Yoneda lemma is a theorem inside a category, about Hom sets and natural transformations, and a methodology is not such an object, so the lemma says nothing about it. Separate Yoneda as a theorem, where the Hom functor is fully faithful and the statement is proved, from Yoneda as a metaphor, where things are determined by relations and nothing is proved. Speaking the second with the authority of the first is the accident this body of work has spent its time avoiding. And determined does not mean computable: Yoneda says the object is determined and gives no way to find it. Closing. The Yoneda lemma demands every object, and replacing that word by a finite list loses something. What is lost is not governed by the strength of the probe: the degree sequence separated a pair the spectrum missed, and adding triangles gained nothing at all. The separator is whether the new probe can be recovered from the existing ones. Measure more and you will know is correct only when what is measured is independent. On the making of this work: The ideas and content of this work stem from the author's own considerations. Assistance from an AI (a large language model) was used for structuring, English translation, and checking the algebra. Any remaining errors or misinterpretations are solely the author's. Feedback and corrections are sincerely appreciated. ----- 米田の補題は、対象は他のすべての対象との関係で完全に決まると言う。本稿が問うのは、その「すべて」である——テストする相手を減らすと、どこで分離能が落ちるか。しかも落ち方は、プローブの強さでは決まらなかった。新しい数学定理も新しい法則も主張しない。 本稿の射程(射程注記):新しい数学定理も新しい法則も主張しない。米田の補題、同スペクトル非同型グラフの存在、二面体群と四元数群が同じ指標表を持つことは、いずれも標準的である。測定値を引かない——本稿の数はすべて全数え上げで得たものである。圏論を導入しない——米田の補題の主張だけを使い、証明も一般化も扱わない。グラフ同型判定の計算量を論じない——6頂点という有限の場合の全数え上げである。表現論を論じない——指標表を既知として引くだけである。米田の補題が本体系の方法を正当化するとは主張しない——むしろ本稿の第6節は、そう言いたくなることを止めるために書かれている。 既刊との関係。論文152 は「同じ指標表を持ちながら、同型でない」を示した——本稿はその現象を、プローブの強さの関数として数える。論文153 は忘却関手の三段を分け、右随伴が無いことの証拠を挙げた——本稿は同じ圏論の棚の、隣の定理を扱う。論文102 は「太鼓の形は聴き分けられるか」を扱った——本稿の第3節はその有限版の全数え上げである。論文163 は「在る」と「これだ」が別の文だと示した——第6節は「決まる」と「求まる」が別の文だと言う。 設定。対象の集まりと、そこから情報を引き出すプローブを考える。プローブとは、対象に当てて値を返す関数である。プローブが二つの対象に同じ値を返すとき、そのプローブは二つを分離できない。題材は 6 頂点の単純グラフで、ラベル付きで 32768 個ある。プローブは三つ用意する。次数列、隣接行列のスペクトル、そしてスペクトルと三角形の個数を組にしたもの。比較のために、同型類そのものを置く。 第一に、32768 個は同型類 156 に落ちる。720 通りの頂点の並べ替えをすべて当てて正規形を取り、数えた。 第二に、次数列では足りない。相異なる値は 102 しかなく、84 類が 30 の組の中で分離されずに残る。 第三に、スペクトルでも足りない。相異なる値は 151 で、10 類が 5 組で残る。 第四に、これが本稿の芯である。三角形の個数を足しても、相異なる値は 151 のまま、分離できない類は 10 のままであった。三角形の個数は隣接行列の三乗のトレースを 6 で割ったものであり、スペクトルの関数である。したがって足しても情報が増えない。プローブを増やしたときに分離能が上がるかどうかは、増やしたものが既存のプローブから復元できるかで決まる。「もっと多くの不変量を測れば、いつかは分かる」は正しくない——独立でない不変量をいくら足しても、一歩も進まない。 第五に、強さは分離能の全順序を与えない。スペクトルで分離できない最小の組を取り出すと、次数列が 0,1,1,1,1,4 のものと 0,0,2,2,2,2 のものであり、どちらも辺が 4 本、三角形が0 個で、共有しているスペクトルはマイナス 2、0、0、0、0、2 である。この二つは次数列では分離される。弱いプローブが分けて、強いプローブが分けない。 第六に、群でも同じことが起きる。二面体群 D4 と四元数群 Q8 は同じ指標表を持ち、同型でない。ところが n 乗して単位元になる元の個数、すなわち巡回群からの準同型の個数を数えると、n が 2 のとき 6 と 2 になり、二つを分ける。指標表は分けられなかったのに、たった一つの相手からの写像を数えるだけで分かれた。ところが n が 4 のときは 8 と 8 で、分けない。同じ形のプローブでも、相手を取り替えると分離能が変わる。どの相手が効くかは、あらかじめ分からない。だから米田は「すべての相手」を要求する。 第七に、これは柵である。米田の補題は「対象は、他との関係で決まる」と読める。本体系の方法——ものが何かではなく、何と何を分けるかで書く——と形が似ている。しかし似ていることは正当化ではない。米田の補題は圏の内部の定理であり、Hom 集合と自然変換という具体的な対象についての主張である。方法論はその対象ではないので、補題は方法論について何も言っていない。定理としての米田と、比喩としての米田を分ける。後者を前者の権威で語ることが、本体系がずっと避けてきた事故である。そして「決まる」は「求まる」を意味しない——米田は対象が決まると言うだけで、求め方を与えない。 結び。米田の補題が要求しているのは「すべての相手」である。その「すべて」を有限で置き換えると、落ちるものがある。しかも落ちるかどうかは、プローブの強さでは決まらない——次数列が分ける組をスペクトルが分けず、三角形を足しても一つも増えなかった。分離子は、そのプローブが既存のプローブから復元できるかである。「もっと測れば分かる」は、独立なものを測るときだけ正しい。 作成にあたって:本稿の着想と内容は、著者自身の考察に基づくものです。文章の構成整理や英訳、数式の確認には AI(大規模言語モデル)の助力を得ました。最終的な内容の解釈や誤りがあれば、それらはすべて著者の責に帰します。お気づきの点があれば、ご教示いただければ幸いです。
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The deflated-Welch statistic: a closed-form, guaranteed-level test for heteroscedastic one-way ANOVA William J. Dwyer, MD, MPH, FAAP — Department of Mathematics and Statistics, University of Massachusetts Lowell. ORCID 0009-0004-0855-7222. Concept DOI (always resolves to the latest version): 10.5281/zenodo.21908169. What this is The reproducibility deposit for the deflated-Welch statistic T_BB, a closed-form, guaranteed-level test for heteroscedastic one-way ANOVA (the Behrens–Fisher problem for k ≥ 3 groups). Welch's test becomes liberal under skew and unstable variance weights at small samples; T_BB = Q(s²)·exp(−R) keeps the ordinary group means and buys a guaranteed level by deflating the Welch quadratic by a Berger–Boos scale-inflation radius R. Three operating points are provided: a fixedcalibrated radius (κ_s), a design-adaptive near-guarantee radius (closed-form polygamma Cornish–Fisher with a finite-nkurtosis guard), and a fully proved smallest-eigenvalue radius R_eig (Gaussian, extended under bounded kurtosis). What the deposit contains Manuscript (author + anonymized) and a derivations supplement (DA1–DA13) plus a long-form derivations companion, covering: why Welch fails under skew in closed form; the Berger–Boos deflation and its exact worst-case radius; the polygamma-cumulant Cornish–Fisher radius with saddlepoint-exact normal backbone; the excess-kurtosis tail term with its finite-n upper-confidence guard; the imbalance correction; the fully proved smallest-eigenvalue radius (with the k-group multiplicity fix, free-β optimization, and the proved-under-bounded-kurtosis widening); and the k-sample Behrens–Fisher null distribution. Interactive demonstrator rerun_cochran/honest_anova.html — computes raw-mean Welch, the fixed / adaptive / proved T_BB radii, the estimand-changing transform routes, and the full routing receipt in the browser, reproducing the deposited Python. Its engine is extracted as a standalone Node module (m01A_anova_engine.js) and checked cell-by-cell against Python across an 84-design taxonomy (verify_anova_engine_taxonomy.py/.js, max |Δp| = 0.00000). Reproducibility scripts (rerun_cochran/, rerun/) — every reported number traces to a named, deterministically-seeded script (size/power/surface, the calibration and information-limit decompositions, the proved-radius verification, the imbalance calibration, the skew-router branch, and the figures). Real-data evidence — anova_flip_scan.py scans 2,783 public one-way layouts (254 datasets): guaranteed T_BBwithholds ~41% of Welch-significant calls, concentrated where the weight-instability screen fires, and never manufactures significance (Table 7 / Figure 15). Figures and the deterministic deposit builder (fixed timestamps → stable md5). All evaluation is simulation-based; the one empirical component is the public-dataset scan, which uses only openly distributed data. Code is released under the MIT License; text and figures under CC BY 4.0. Version history (consolidated changelog) Published version DOIs are marked ✅; the concept DOI above always resolves to the latest. Staged versions were rolled into the next published one unless noted. v1.0.77 ✅ 10.5281/zenodo.22167690 (2026-08-30): CSDA guide-for-authors conformance — abstract trimmed to 247 words (from 284), keywords cut to 7 (from 11), the withholding highlight shortened to ≤85 characters, and the arXiv PDF/source regenerated. No change to methods, results, figures, or code. v1.0.76 ✅ 10.5281/zenodo.22167536 (2026-08-30) — AI-disclosure heading aligned to Elsevier. The manuscript's declaration heading is now "Declaration of generative AI and AI-assisted technologies in the manuscript preparation process" (was "Use of generative AI"); the disclosure body is unchanged. Prepared alongside an Elsevier-compliant cover-letter variant and an EM suggested-reviewer sheet (both kept outside the deposit). docx/pdf rebuilt; deterministic md5 refreshed. v1.0.75 ✅ 10.5281/zenodo.22167304 (2026-08-30) — Submission-sharpening pass. Graphical abstract + Elsevier Highlights; figures and tables renumbered into reading order with per-table Source clauses; the validity–power frontier (Figure 8) now carries the proved R_eig operating point (100% validity, size-adjusted power 0.613, merge_tbb_proved_frontier.py); new Section 7 "Recovering power by design" + Table 8 (rc_anova_power_by_design.py); and a live required-n calculator in honest_anova.html (per-group and total n for 80% power, "power now @ total n"), with a numeric-heading CSS fix and the engine re-verified against Python at 0.00000. v1.0.74 ✅ 10.5281/zenodo.22165892 (2026-08-29) — Proved-under-bounded-kurtosis radius (DA12.6). The proved non-normal widening now keys on excess kurtosis, √(1 + κ̂·(n−1)/(2n)), from the exact Var(s²/σ²) = 2/(n−1) + κ/n, so symmetric heavy tails (Student-t) are covered where the old skew form √(1 + 0.75·skew²) under-covered; tbbProvedswitched to the kurtosis form across the demonstrator, engine, and Python truth (re-verified JS-vs-Python at 0.00000); new rc_anova_kurtosis_proof.py + deep-dive. v1.0.73 ✅ 10.5281/zenodo.22165709 (2026-08-29) — Reconstructed & verified demonstrator engine (standalone Node module + taxonomy verifier, max |Δp| = 0.00000 across 84 designs; Yuen zero-variance fix; T_BB-routed presets both directions); series-impact deep-dive (the corrected R_eig k-group multiplicity gap also reaches m03 and m01t). v1.0.72 (2026-08-29) — Title set to "The deflated-Welch statistic…"; corrected + optimized proved radius R_eig (β/k multiplicity fix + β-optimization, DA12); real-data Welch-vs-T_BB flip scan (2,783 layouts; Table 7 / Figure 15) + demonstrator imbalance-factor fix; long-form derivations companion. v1.0.71 / v1.0.70 (2026-08-21) — Zhang normal-reference comparator benchmarked on the efficiency frontier (valid on only 24% of designs, in the calibrated-liberal cluster); k = 2 adaptive-radius case-study fold (design-scaling vs shape-keying distinction). v1.0.69 ✅ 10.5281/zenodo.22035826 (2026-08-20) — HTML R1/R2 presentation pass + Figure 9 adaptive per-cluster label merge. v1.0.68 ✅ 10.5281/zenodo.22033737 (2026-08-20) — Companion consolidation into a single six-column Table 6; Figures 11–14 harmonized into one story. v1.0.67 / v1.0.65 / v1.0.60 (2026-08-19/20) — Guarded-reference naming-collision fix; the 40,000-replication expanded-frontier pin (Table 3 + Figure 8) with the symmetric-heteroscedastic skew-router branch; the mean-preserving lightened-R_eig do-not-use fallback. v1.0.59 ✅ 10.5281/zenodo.21995320 (2026-08-18) — Reporting standard + honest_anova.html demonstrator re-aligned to the current T_BB methods paper. v1.0.57 ✅ 10.5281/zenodo.21986847 (2026-08-17) — Reviewer-comprehension pass (multi-paragraph abstract, contributions list, trimmed captions); proved radius R_eig added as a Table 3 scorecard row; corner tail-index correction (N−k)/2 (low-order moments exist in every deployed design). v1.0.56–v1.0.49 (2026-08-16) — The k-sample Behrens–Fisher corner-distribution program: two-moment scaled-χ² corner reference, derived corner cumulants, the secular-eigenvalue law + closed CGF + power-law tail, consolidated into derivations DA13 with a prior-art/novelty audit. v1.0.48 ✅ 10.5281/zenodo.21963458 (2026-08-16) — The unifying λ(z) correction (a smooth instability-keyed deflation strength). v1.0.45 ✅ 10.5281/zenodo.21962965 (2026-08-16) — Atomic sparsity index + bootstrap-t edge hardening + shape-aware pooled standardized-residual bootstrap (SA-PSRB); multivariate transfer to m03. v1.0.44–v1.0.41 (2026-08-16) — Shape-moment re-injection order (skew is the sweet spot), validated and hardened pooled standardized-residual bootstrap, atomic weight-noise probes. v1.0.40 ✅ 10.5281/zenodo.21961667 (2026-08-16) — Log-domain weight-stabilization probe (negative for stabilization; clarifies the size-adjusted oracle ceiling); includes the oracle-power gap decomposition (≈92% conservatism, ≈8% estimation). v1.0.37 ✅ 10.5281/zenodo.21961327 (2026-08-16) — Residual-bootstrap qualification of the shoot-out + the first proved Gaussian smallest-eigenvalue radius R_eig (DA12, the p = 1 specialization of the m03 theorem). v1.0.36 (2026-08-15) — Figure 11 T_BB-region colour fix (amber, matching the routing figures). v1.0.27 ✅ 10.5281/zenodo.21908170 — Earlier published baseline of the deposit. Provenance: every number traces to a named, deterministically-seeded script listed in the manuscript Declarations; the demonstrator engine reproduces the deposited Python to max |Δp| = 0.00000 across the taxonomy verification. License. Code and scripts in the deposit are released under the MIT License; text and figures under CC BY 4.0. Reuse is permitted with attribution to the author and citation of the concept DOI above. How to cite. Dwyer, W. J. The deflated-Welch statistic: a closed-form, guaranteed-level test for heteroscedastic one-way ANOVA. Reproducibility deposit, Zenodo. https://doi.org/10.5281/zenodo.21908169
William Dwyer· Zenodo (CERN European Organi...· 2 citations
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