computo ergo sum

2026-10-22 · chapter Yang–Mills and the mass gapPart 15 Ultraviolet controlSystematic attempts · Kiichi, Shiori and Rin

The whole book Contents and reading orders
  1. Part 0 Entrance — how to read this book
  2. 0-01 How to read this book
  3. 0-02 One picture
  4. 0-03 Reading the problem statement word by word
  5. 0-04 Four dimensions in mathematics and four dimensions in physics
  6. Part 1 Mathematical preparation
  7. 1-01 Vector spaces and linear maps
  8. 1-02 What a group is
  9. 1-03 Lie groups and Lie algebras
  10. 1-04 SU(2) and SU(3)
  11. 1-05 Manifolds and tangent spaces
  12. 1-06 Differential forms and the exterior derivative
  13. 1-07 Vector bundles and connections
  14. 1-08 Probability and measure
  15. 1-09 Probability in infinite dimensions
  16. 1-10 Hilbert spaces and self-adjoint operators
  17. 1-11 Fourier analysis and distributions
  18. 1-12 Detour: what happens only in four dimensions
  19. Part 2 Physical preparation
  20. 2-01 Lagrangians and the action
  21. 2-02 The idea of a field
  22. 2-03 Electromagnetism is a gauge theory
  23. 2-04 Special relativity and spacetime
  24. 2-05 The bones of quantum mechanics
  25. 2-06 The harmonic oscillator and creation and annihilation
  26. 2-07 The idea of the path integral
  27. 2-08 Statistical mechanics and phase transitions
  28. 2-09 Detour: the gap and the correlation length in the Ising model
  29. 2-10 The relaxation time and the dynamical exponent z
  30. Part 3 Yang–Mills theory (classical)
  31. 3-01 The gauge principle
  32. 3-02 Non-abelian gauge fields
  33. 3-03 The action and the equations
  34. 3-04 Gauge theory as geometry
  35. 3-05 Instantons and topology
  36. 3-06 Detour: Donaldson and exotic R⁴
  37. 3-07 Yang–Mills inside the Standard Model
  38. Part 4 Quantisation
  39. 4-01 Canonical quantisation and the Hamiltonian
  40. 4-02 The path integral and Euclideanisation
  41. 4-03 Perturbation theory and Feynman diagrams
  42. 4-04 Divergences and renormalisation
  43. 4-05 The algebra of divergences
  44. 4-06 Asymptotic freedom
  45. 4-07 Dimensional transmutation and Λ
  46. 4-08 Gauge fixing and Faddeev–Popov
  47. 4-09 The axioms of quantum field theory
  48. 4-10 The Osterwalder–Schrader axioms and reconstruction
  49. 4-11 The definition of the mass gap
  50. 4-12 Detour: the perturbation series diverges
  51. Part 5 Lattice gauge theory
  52. 5-01 Wilson's lattice
  53. 5-02 The strong-coupling expansion
  54. 5-03 Reflection positivity and the transfer matrix
  55. 5-04 The infinite-volume limit and the cluster expansion
  56. 5-05 Weak coupling and the continuum limit
  57. 5-06 How U(1) differs from the non-abelian case
  58. 5-07 The Monte Carlo method
  59. 5-08 Measuring glueballs and the string tension
  60. 5-09 What to hold fixed when taking the limit
  61. 5-10 Lattice gauge theory with finite groups
  62. 5-11 Detour: Bakry–Émery and one-link integration
  63. Part 6 Constructive field theory
  64. 6-01 What constructive field theory is
  65. 6-02 Solvability in two dimensions and the Yang–Mills measure
  66. 6-03 Constructing scalar fields
  67. 6-04 The cluster expansion
  68. 6-05 The sequence of renormalisation group steps
  69. 6-06 Ultraviolet stability of three-dimensional Yang–Mills
  70. 6-07 Four dimensions
  71. 6-08 Triviality of φ⁴ in four dimensions
  72. 6-09 Stochastic quantisation and regularity structures
  73. 6-10 Where four dimensions stops
  74. 6-11 Obstacles other than divergence
  75. 6-12 Detour: "if 1/0 is given a symbol"
  76. Part 7 From the side of physics
  77. 7-01 How physics sees it
  78. 7-02 Mechanisms of confinement
  79. 7-03 The string picture
  80. 7-04 Large N
  81. 7-05 String theory and extra dimensions
  82. 7-06 How extra dimensions become invisible
  83. 7-07 Where gauge fields come from
  84. 7-08 Holography
  85. 7-09 The mass gap becomes geometry
  86. 7-10 Back to four dimensions
  87. 7-11 Supersymmetry and Seiberg–Witten
  88. 7-12 The sentence that plays the role of an equivalence principle
  89. 7-13 Where the way physics digs parts from mathematics
  90. Part 8 A dictionary of two languages — the physical and the mathematical view
  91. 8-01 How to read the dictionary
  92. 8-02 Dictionary A
  93. 8-03 Dictionary B
  94. 8-04 Dictionary C
  95. 8-05 The physical counterparts of our assumptions
  96. The map
  97. Part 9 Where things stand, and open tasks
  98. 9-01 How far the world has come
  99. 9-02 Where the two ways of digging part
  100. 9-03 Candidates for new concepts
  101. 9-04 The list of open tasks
  102. 9-05 Common misconceptions
  103. 9-06 The stages a proof must contain — the table of seven stages
  104. 9-07 A map of the tools — where the known tools used by this book live
  105. The first road — from the direction of time
  106. Part 10 The first road, first half — from the direction of time: the mass gap and the diffusive-relaxation-time assumption
  107. 10-00 Entrance — the staircase, and the random walk, the ruler and the clock
  108. 10-01 The line of construction and Assumption ξ²
  109. 10-02 Roads tried on the four-dimensional lattice, and walls
  110. 10-03 The four steps of the staircase — why we start from 0+1 dimensions
  111. 10-04 The path measure of the double well, and kinks
  112. 10-05 The statement of the first step — four conditions and Proposition 4.5
  113. 10-06 (H1) Local Poincaré within a phase
  114. 10-07 The map of (H2) — seven routes and the seam of the ring
  115. 10-08 What computer-assisted means — the conditions on the chain inside the window
  116. 10-09 The sector framework and the three strands of route 5
  117. 10-10 The list of detour plans — types of breakage
  118. 10-11 (H3)(H4) and the constant of the core
  119. 10-12 The integrated table and the dependency graph
  120. 10-13 Lean statements and the limits of machine checking
  121. 10-14 Reconciliation — the numbers of the record and the known numbers
  122. 10-15 What remains and its cost — the distance to a theorem
  123. 10-16 What is not claimed
  124. 10-17 Insights and small questions
  125. Part 11 The first road, second half — repairing the form of the assumption, making time continuous
  126. 11-00 Further considerations — entrance
  127. 11-01 One form that obstructs Assumption ξ² — a nearly conserved global quantity
  128. 11-02 Choosing the ruler and the coordinates again — the length at which conservation breaks
  129. 11-03 Two ways to repair Assumption ξ² — the sector Assumption ξ² and the local Assumption ξ²
  130. 11-04 Which Assumption ξ² the one-sided bridge needs
  131. 11-05 Making time continuous — the Hamiltonian lattice and the vacuum measure
  132. 11-06 Paying with rarity instead of convexity — renormalisation on groups and log-Sobolev
  133. 11-07 Because it is four dimensions — the dimensionless coupling and topology
  134. 11-08 Questions, and what is not claimed
  135. 11-A1 Table of notation for Part 11
  136. The second road — from the direction of space
  137. Part 12 The second road: from the direction of space — a small twisted T² and confinement
  138. 12-00 Entrance — space, not time
  139. 12-01 The twisted T² and 't Hooft flux
  140. 12-02 Vortices and fractional instantons
  141. 12-03 Containers — conditioning on the frame makes things independent
  142. 12-04 Slab confinement
  143. 12-05 Vortex-insertion identities
  144. 12-06 Driven insertion and the flow lemma
  145. 12-07 Why fixed maps fail
  146. 12-08 The measured record
  147. 12-09 Where this road stops — widening the T² is the band
  148. The crossover band — two roads reach the same wall
  149. Part 13 The crossover band — two roads reach the same wall
  150. 13-00 Entrance — confluence
  151. 13-01 The correct form of the band
  152. 13-02 Reduction to a single inequality
  153. 13-03 The only place where non-abelian enters
  154. 13-04 Structure alone cannot cross
  155. 13-05 The chessboard and simultaneous flips
  156. 13-06 Renormalisation comparison — a comparison that distinguishes groups
  157. 13-07 The band seen from the side of time
  158. 13-08 A map of the roads tried and stopped
  159. 13-09 The measured record
  160. 13-10 Candidate new viewpoints
  161. 13-11 Ultraviolet control — what it means to close at infinitely many steps
  162. Closing
  163. Part 14 Closing — conditional statements
  164. 14-00 Entrance — the promise of this part
  165. 14-01 The conditional statement — the mass gap and confinement, arrow by arrow
  166. 14-02 The ledger of conditions
  167. 14-03 The table of questions (a cross-index)
  168. 14-04 What is not claimed (a cross-index)
  169. The ultraviolet wall — the foundation beneath both roads
  170. Part 15 Ultraviolet control — what it means to close at infinitely many steps
  171. 15-00 Entrance — what ultraviolet control is
  172. 15-01 Why the ultraviolet is hard — dimensionless coupling, group-valued fields, gauge
  173. 15-02 A map of the sources — Bałaban's programme, the BBS chain, two rows absent from the sources
  174. 15-03 The decomposition statement — a class that closes with finitely many parameters, and three remainders
  175. 15-04 The one-link heat-kernel class and the hierarchical model
  176. 15-05 The flux-network theorem — the transverse contraction and the parameter flow in one projection
  177. 15-06 Counting the parameters — couplings by loop shape and the attracting class
  178. 15-07 Background-dependent fluctuations η — absorption step by step
  179. 15-08 The four rows that do not close, and proposals for them
  180. 15-09 What cannot be said, the index of questions, the dependency diagram
  181. 15-10 Systematic attempts — naming the recurring patterns of the record
  182. Appendices
  183. A-01 Table of notation
  184. A-02 Glossary
  185. A-03 Guide to the literature
  186. A-04 Lean and machine checking
  187. A-05 How this book was made
  188. A-06 Index of assumptions
  189. A-07 Papers that came out of this book
  190. A-08 私達の研究における証明までの道標

Systematic attempts — giving names to the recurring patterns of the record

This chapter is this book's study. It is not a component of the proof on the main line of argument. §01–§03 and §05 are restatements in known frameworks, and §04 is at the level of an estimate.

What this chapter shows — We give names and definitions to five pieces of handwork that came up again and again in the record of computations in Part 15. The first is the estimate of a matrix that "exceeds 1 in one step but contracts when several steps are taken together" (the dominant matrix); the second is what is lost when signs are discarded to take an upper bound (the loss from discarding signs); the third is the choice made when a map determined only on a constraint is represented by a local kernel (the local representative); the fourth is the matching of the two expansions at strong and at weak coupling (the double valuation); the fifth is the computation that bounds a polynomial of degree pp by an ℓp\ell^p cone and pulls it back step by step (the cone calculus). For each we write candidate theorems, show row by row which known result each one restates, set out which quantity each number of the record corresponds to, and gather the remaining questions as F-SYS1–F-SYS16.

Reading level — Third year and above. §01 uses the linear algebra of non-negative matrices, §02 inequalities for finite sums, §03 Fourier series on the lattice, §04 only the leading terms of asymptotic series, and §05 inequalities for finite sums and the statements of interpolation theorems. §00 and the opening paragraph of each section alone can be read by second-year students.

Prerequisite chapters — 15-05 Theorem G′ (local representatives and an upper bound uniform in the volume), the corollary in 15-05 (the weighted Stein bound and the ℓ4\ell^4 cone), 15-08 §06 (the W coordinates and the multi-step cone).

Said first — This chapter is not the main line of argument. Its results have no direct effect either on ① ultraviolet control or on ⑦ the crossover band of the ledger (14-02). Many of the candidate theorems are restatements of known facts — the Perron–Frobenius theorem, the Collatz–Wielandt formula, Gelfand's formula, contraction in a weighted maximum norm, the order of multigrid transfer operators, the sum rules of subdivision, the Riesz–Thorin interpolation theorem, the Schur test — and no novelty is claimed. What is new in this chapter lies on the side of the "questions". The aim is to write out which quantity of a known framework each number of the record corresponds to, and where it goes beyond the known framework. Labels are attached row by row: Lean (a statement that passed in a Lean file), Computed (a floating-point computation, not an interval estimate), Reading (only a line of argument on paper, or at the level of the abstract of a source), Cited (a standard known fact), Assumption (an estimate).

Order of this chapter
  1. What this chapter shows — the four patterns and how to read this chapter
  2. Dominant matrices and k-step contraction — how to build a weight that contracts in one step (Table 1)
  3. The loss from discarding signs — the loss is the inverse square of the alignment (Tables 2–5)
  4. The geometry of local representatives — the order of folding does not depend on the representative (Tables 6 and 7)
  5. The geometry of the double valuation — a scale-independent κ and the lens (Tables 8–10)
  6. The cone calculus — the window is an interval; the correct form of dilution (Tables 11 and 12)
  7. Dictionary with the known, what can be said, questions (Tables 13–15)

00

What this chapter shows

① Dominant matrixIf it contracts in kk steps, a weight that contracts in one step can be built explicitly"Exceeding 1 in one step" is a transient that depends on the choice of weight. A restatement of the line of Collatz–Wielandt and Varga (Lean)
② The loss from discarding signsThe loss is bounded by the inverse square of the row alignment in the worst directionAgrees at 5.55, 5.13, 5.31 for two to four steps on the 444^4 torus (the inequality in Lean, the numbers computed)
③ Local representativeThe order of folding ordV(F)=2\mathrm{ord}^V(F)=2 does not depend on the choice of representativeWithin the types of the record, the tail norm is bounded only up to D≤4D\le4. A restatement of the sum rules (Reading, Computed)
④ Double valuationThe product of the two leading coefficients κ=s1w1\kappa=s_1w_1 does not depend on the scale of the couplingThe lens of the leading terms opens only when κ≤14\kappa\le\frac14. No payoff theorem yet (Assumption, Computed)
⑤ The cone calculusGives definitions for the pull-back of degree-pp cones, the weighted Stein bound, the composition of steps and affine recursionslog⁡Sp\log S_p is convex in pp and S3≤S2S4S_3\le\sqrt{S_2S_4}. The naive dilution m1−pm^{1-p} does not hold, and Sp≤S2Rp−2S_p\le S_2R^{p-2} is the minimal form (Lean, Reading, Computed)

How to read this chapter. The record of computations in Part 15 contains the same kind of handwork again and again. There are five kinds: measuring the norm of a three-step composite and writing "it exceeds 1 in one step but contracts in three"; taking the absolute value of a signed kernel to build an upper bound; applying a local kernel to a map that is determined only on fields satisfying the Bianchi identity; setting the leading terms of the strong-coupling and weak-coupling series side by side to look for the point where they meet; and pulling a degree-pp cone back step by step and bounding it by the weighted Stein bound. This chapter is an attempt to give each of them a definition and axioms (what can be said under what assumptions). Many of the results are restatements of known facts, and we say so row by row for the candidate theorems of each section. What remains after the restatement — quantities that do not correspond directly to a known framework, and regularities shown by the numbers of the record that have not been made into theorems — are the questions of this chapter. §01–§03 can be read independently of one another. §04 shares no tools with §01–§03; it is an attempt to restate the band of ⑦. §05 extends Candidate 1.4 of §01 to the language of cones and can be read alongside §01.

01

Dominant matrices and k-step contraction

The non-negative matrix that lists the norms of the blocks of an operator split into blocks transfers estimates of powers of the operator to estimates of powers of a non-negative matrix. On the side of non-negative matrices the Perron–Frobenius theory applies as it stands, so "in how many steps does it contract" and "with which weight must we measure for it to contract in one step" can be written in the language of matrices. Everything up to this point is known; the role of this section is to bring the estimates of the record into line with this framework.

Definitions

Definition 1.1 (dominant matrix). Let II be a finite set, EiE_i (i∈Ii\in I) normed spaces, and TT an operator on E=⨁iEiE=\bigoplus_iE_i split into blocks Tij:Ej→EiT_{ij}:E_j\to E_i. A non-negative matrix B∈R≥0I×IB\in\mathbb R_{\ge0}^{I\times I} is a dominant matrix of TT if for all i,ji,j we have ∥Tij∥≤Bij\|T_{ij}\|\le B_{ij}. The smallest one is the matrix of block norms N(T)ij=∥Tij∥N(T)_{ij}=\|T_{ij}\|.

Definition 1.2 (weighted block norm). For a positive weight w∈R>0Iw\in\mathbb R_{\gt0}^I, ∥x∥w,∞=max⁡i∥xi∥/wi\|x\|_{w,\infty}=\max_i\|x_i\|/w_i, and the ℓ2\ell^2 version is ∥x∥w,22=∑i∥xi∥2/wi2\|x\|_{w,2}^2=\sum_i\|x_i\|^2/w_i^2. The operator norm is ∥T∥w,∞=∥W−1TW∥∞\|T\|_{w,\infty}=\|W^{-1}TW\|_\infty (W=diag(w)W={\rm diag}(w)).

Definition 1.3 (kk-step contraction, transient constant). For a non-negative matrix BB put κk(B):=∥Bk∥\kappa_k(B):=\|B^k\|; when κk<1\kappa_k\lt1 for some kk we say that it "contracts in kk steps". The transient constant is Ck(B):=max⁡r<k∥Br∥C_k(B):=\max_{r\lt k}\|B^r\|. By Gelfand's formula ρ(B)=lim⁡n∥Bn∥1/n\rho(B)=\lim_n\|B^n\|^{1/n}, ρ(B)<1\rho(B)\lt1 is equivalent to κk<1\kappa_k\lt1 for some kk Cited.

Definition 1.4 (one-step weight). For B≥0B\ge0, w≥0w\ge0, s>0s\gt0, k≥1k\ge1 we call

w′:=∑r<ks−rBrww' := \sum_{r\lt k}s^{-r}B^rw

the one-step weight built from ww.

Candidate theorems and labels

Candidate 1.1 (from kk-step contraction to a weight that contracts in one step). If B≥0B\ge0, w≥0w\ge0, s>0s\gt0, k≥1k\ge1 and Bkw≤skwB^kw\le s^kw (entrywise), then w≤w′w\le w' and Bw′≤s w′Bw'\le s\,w' Lean (liftWeight_step; lemmas mulVec_pow_succ, pow_mulVec_nonneg).

Bw′=∑r<ks−rBr+1w=s(w′−w+s−kBkw) ≤ s w′Bw' = \sum_{r\lt k}s^{-r}B^{r+1}w = s\bigl(w'-w+s^{-k}B^kw\bigr)\ \le\ s\,w'

Combined with Candidate 1.2 (the one-step estimate), this says that if "the kk-step composite contracts by a factor sks^k in the weight ww", then "measured in the weight w′w' it contracts by a factor ss in every step". The weight ratio w′/ww'/w lies in [1, ∑r<ks−rmax⁡i(Brw)i/wi][1,\ \sum_{r\lt k}s^{-r}\max_i(B^rw)_i/w_i], so the constant of re-measurement does not depend on the number of steps (Candidate 1.3). The content is the constructive half of "ρ(B)<s\rho(B)\lt s ⇔ there is w′>0w'\gt0 with Bw′≤sw′Bw'\le sw'", known from Varga's analysis of iterative methods and from the line of Berman–Plemmons on the characterisation of M-matrices Cited.

Table 1 The candidate theorems of §01. Each is a finite-dimensional form of a known fact, or an elementary consequence of one
CandidateStatement (one line)LabelWhat it restates
1.1Bkw≤skwB^kw\le s^kw ⇒ w≤w′w\le w', Bw′≤sw′Bw'\le sw'LeanThe constructive half of the Varga / Berman–Plemmons characterisation of M-matrices Cited
1.2Bw≤λwBw\le\lambda w (w>0w\gt0) ⇒ ∥T∥w,∞≤λ\|T\|_{w,\infty}\le\lambda. Even with Tn,Bn,λnT_n,B_n,\lambda_n differing from step to step, ∥xn∥w,∞≤(∏kλk)∥x0∥w,∞\|x_n\|_{w,\infty}\le(\prod_k\lambda_k)\|x_0\|_{w,\infty}Lean (weighted_step, weighted_iter)Collatz–Wielandt: inf⁡w>0max⁡i(Bw)i/wi=ρ(B)\inf_{w\gt0}\max_i(Bw)_i/w_i=\rho(B) (the equality itself is not in Lean) Cited
1.2′Given right and left positive Perron vectors x,yx,y, D=diag(y/x)D={\rm diag}(\sqrt{y/x}) gives ∥DBD−1∥2≤ρ(B)\|DBD^{-1}\|_2\le\rho(B), and further ∥DTD−1∥2≤∥DN(T)D−1∥2\|DTD^{-1}\|_2\le\|DN(T)D^{-1}\|_2ReadingThe Schur test applied to q=xyq=\sqrt{xy} Cited
1.3If av≤w≤bvav\le w\le bv (a>0a\gt0), a sequence that contracts by λn\lambda_n in each step in the weight ww satisfies ∥xn∥v≤(b/a)(∏λk)∥x0∥v\|x_n\|_v\le(b/a)(\prod\lambda_k)\|x_0\|_v in the weight vvLean (weight_change)An elementary fact about equivalence of norms
1.4 (a)∥1∥=1\|1\|=1, q:=∥ak∥q:=\|a^k\|, ∥ar∥≤C\|a^r\|\le C (r<kr\lt k) ⇒ ∥an∥≤C q⌊n/k⌋\|a^n\|\le C\,q^{\lfloor n/k\rfloor}Lean (norm_pow_block_le, norm_pow_le_const_mul)A finite version of Gelfand's formula Cited
1.4 (b)q<1q\lt1 ⇒ ∑n<N∥an∥≤kC/(1−q)\sum_{n\lt N}\|a^n\|\le kC/(1-q) (independent of NN)Lean (sum_norm_pow_le; lemmas geom_sum_le_inv, sum_range_mul_eq)An estimate of partial sums of the Neumann series
1.4 (c)c(k+1)≤λc(k)+εc(k+1)\le\lambda c(k)+\varepsilon (0≤λ<10\le\lambda\lt1, ε≥0\varepsilon\ge0) ⇒ c(k)≤max⁡(c(0),ε/(1−λ))c(k)\le\max(c(0),\varepsilon/(1-\lambda))Lean (affine_uniform)An elementary fact about affine recursions
1.4 second halfIf irreducible with a Perron vector w>0w\gt0, then C=max⁡iwi/min⁡iwiC=\max_iw_i/\min_iw_i (∞\infty norm). An explicit formula bounding the ratio of ww by the entries of BBReading (the explicit formula is not written out in full)Minc's ratio estimate Reading
1.5If the J×JJ\times J matrix MM obtained by aggregating blocks with g:I→Jg:I\to J satisfies Mp≤μpMp\le\mu p, the original BB contracts in one step by μ\mu in the weight wjpg(j)w_jp_{g(j)}. If JJ has two points, M=(abcd)M=\begin{pmatrix}a&b\\c&d\end{pmatrix}, a<1a\lt1, d<1d\lt1 and bc<(1−a)(1−d)bc\lt(1-a)(1-d), then in the weight (1,t)(1,t) we have max⁡(a+bt, d+c/t)<1\max(a+bt,\,d+c/t)\lt1Lean (aggregate_step, two_by_two_weight, two_by_two_exists)An elementary fact about the test for ρ<1\rho\lt1 of a two-by-two matrix Cited

Correspondence with the numbers of the record

A question proper to this pattern — the loss from discarding signs

A dominant matrix discards signs. For the actual operator TT and a dominant matrix BB, define the loss at step kk as

Lk:=∥Bk∥∙∥Tk∥∙(same norm; ∥Tk∥=0 then +∞)L_k := \frac{\|B^k\|_\bullet}{\|T^k\|_\bullet}\qquad(\text{same norm; }\|T^k\|=0\text{ then }+\infty)

Then the loss is not necessarily bounded in the number of steps. T=(1−11−1)T=\begin{pmatrix}1&-1\\1&-1\end{pmatrix} has ∣T∣=(1111)|T|=\begin{pmatrix}1&1\\1&1\end{pmatrix} as a dominant matrix, T2=0T^2=0, and every entry of ∣T∣n+1|T|^{n+1} is 2n2^n. Hence Ln=+∞L_n=+\infty for n≥2n\ge2 Lean (absEx_eq, signedEx_sq, absEx_pow). Conversely, if TT is non-negative (T=∣T∣T=|T|) or sign-similar, T=S∣T∣ST=S|T|S (SS a diagonal matrix of ±1\pm1), then Lk=1L_k=1 in the ∞\infty norm with the Perron weight Reading.

How far the choice of signs can reach towards the estimate of ρ(∣A∣)\rho(|A|) is treated by Rump's sign-real spectral radius (Rump 1997) Reading. We have not found a source that treats how the loss behaves over steps (not found, which does not mean there is none). In the record the loss grows only slowly, 7.6 in one step and 9.3 in two, and the conditions for making this a theorem are not determined by the information of the dominant matrix alone (the example above shows this). We take up this question in §02.

02

The loss from discarding signs

A closer look at the loss in the record showed that it was of a different type from the counterexample of §01. The Stein bound of the record takes the upper bound after composing the step kernels. The counterexample of §01 is a quantity that composes after taking absolute values. In the former, the upper bound of the composite for the nilpotent example T2=0T^2=0 is also 0. In this section we see from the numbers that the loss with the upper bound taken after composition hardly moves over steps, and we write an inequality that bounds it by a geometric quantity within a single row (the row alignment).

Definitions

Definition 2.1 (composite kernel and loss). Write the composite of the step kernels K0,K1,…K_0,K_1,\dots as Tk=K0K1⋯Kk−1T_k=K_0K_1\cdots K_{k-1}. Let the true ratio be sup⁡θ∥Tkθ∥44/∥θ∥44\sup_\theta\|T_k\theta\|_4^4/\|\theta\|_4^4, and the Stein bound the weighted ℓ2\ell^2 quantity of the form of (11) of 15-05 (weighted by the ℓ1\ell^1 norms ArA_r of the rows of the composite kernel); we put

lossk:=Stein(Tk)true ratio(Tk)\text{loss}_k := \frac{\text{Stein}(T_k)}{\text{true ratio}(T_k)}

The true ratio is replaced by a lower bound from maximisation (the larger of a quasi-Newton method and a maximisation over period-2 fields), so the loss in the tables is an estimate of the loss from above.

Definition 2.2 (row alignment). The Stein bound of a translation-invariant TT has the form sup⁡qλmax⁡(∑rAr2T^r(q)HT^r(q))\sup_q\lambda_{\max}\bigl(\sum_rA_r^2\hat T_r(q)^{\rm H}\hat T_r(q)\bigr); let (q∗,u∗)(q^*,u^*) be its maximiser. Put yr=T^r(q∗)u∗y_r=\hat T_r(q^*)u^*, M=∥u∗∥∞M=\|u^*\|_\infty, and call

κr:=∣yr∣Ar M ≤ 1\kappa_r := \frac{|y_r|}{A_r\,M}\ \le\ 1

the alignment of row rr in the worst direction (κr≤1\kappa_r\le1 is coherence_le_one Lean). ⟨κ−2⟩\langle\kappa^{-2}\rangle is the average weighted by ∣yr∣4|y_r|^4.

The numbers of the record — the loss stops, and falls a little

Table 2 The loss on a common 444^4 torus (periodic operator with the steps cut at R=3R=3) Computed
kSteinLower bound of the true ratio (quasi-Newton / period 2)LossStep ratio: lower boundStep ratio: Stein
13.7080.5903 / 0.55666.28——
20.77460.1405 / 0.14055.510.2380.209
30.076320.014967 / 0.014975.100.1070.0985
40.005760.001095 / 0.001095.260.0730.0755

The true ratio and the Stein bound decrease at the same rate (both step ratios tend to about 0.07), so the loss stops. The shape is the same on larger tori (Table 3). The earlier recorded two-step value 9.3 was due to a weak lower bound of the true ratio, 0.108; with period-2 fields the lower bound becomes 0.1405 Computed. For k≥2k\ge2, 99.8–100% of the energy of the maximiser of the true ratio was at ∣q∣∞=π|q|_\infty=\pi, sitting on period-2 points of type (π,π,π,0)(\pi,\pi,\pi,0) Computed.

Table 3 The loss on larger tori, compared with the product of the per-step upper bounds Computed
kTorusSteinLower bound of the true ratioLossProduct of per-step Stein ÷ lower bound
116416^44.4310.5917.507.5
2848^40.95540.1405 (period 2)6.80182
3848^40.095750.01497 (period 2)6.401.1×1041.1\times10^4
3646^40.090920.0149556.07—

The rightmost column is the product of the one-step upper bounds of each step (4.45, 5.75, 6.50, 6.81) divided by the lower bound of the true ratio; it grows by a factor of 60–90 per step, 7.5 → 182 → 1.1×1041.1\times10^4 → 1.0×1061.0\times10^6 Computed. Only the side that composes after taking absolute values grows exponentially. This column shows how much is gained by taking the upper bound on the composite kernel.

The three hypotheses failed, and they failed in the same way

As reasons for the loss stopping we tried three: (a) composition reduces the proportion of the negative part; (b) the cancellation takes place within a cell; (c) the signs align at the maximiser of the true ratio. None of them holds in the form written. All three, however, failed in the same way: "it does not change over steps".

Table 4 Verdicts on the hypotheses Computed
HypothesisQuantityk=1k=2k=3k=4 (444^4)Verdict
(a)Proportion of the negative part (row signs chosen freely)0.4110.4320.4350.426Does not hold (constant at about 0.43; on 444^4, 0.405, 0.425, 0.427, 0.426)
(b)Inner shell (distance 0.5–1.5): share of ℓ1\ell^1 / negative proportion0.58 / 0.22–0.330.48 / 0.320.44 / 0.31–0.370.53 / 0.32–0.38Does not hold (the cancellation is between the positive centre and the negative ring at distance 1.5–2.5; summing over 242^4 blocks leaves 41–56% of ℓ1\ell^1)
Outer ring (distance 1.5–2.5): share of ℓ1\ell^1 / negative proportion0.33 / 0.59–0.630.38 / 0.56–0.600.40 / 0.53–0.600.46 / 0.53–0.59
(c)Alignment / efficiency at the maximiser0.74 / 4.5% (16416^4)0.56 / 1.3% (848^4)0.57 / 1.5% (646^4)0.60 / 1.8%Does not hold (the alignment stops at around 0.6)
—Row alignment in the worst direction ⟨κ−2⟩\langle\kappa^{-2}\rangle22.9 (16416^4)10.6 (848^4), 5.55 (444^4)10.2 (848^4), 5.13 (444^4)5.31Bounded over steps

That all three quantities hardly move over steps can be read as showing not that "composition brings the kernel closer to positive" but that "composition brings the profile of the kernel (its normalised shape) closer to a single one" Reading. A profile positive at the centre and negative around it, a negative proportion of 0.43 and an alignment of 0.6 are kept independently of the step. This is close to the view of the limit function of subdivision Reading. Note that the signs "positive at the centre, negative around it" depend on the sign convention for the components of the direction; what does not depend on the convention is the negative proportion and the alignment.

The inequality that held — loss ≤ inverse square of the alignment

Candidate 2.1. Suppose Ar≥0A_r\ge0, κ≥0\kappa\ge0, M≥0M\ge0, ∣va∣≤M|v_a|\le M for every component, and κArM≤∣yr∣\kappa A_rM\le|y_r| for every row. Then

κ2(∑rAr2yr2)∑ava4 ≤ (∑ryr4)∑ava2\kappa^2\Bigl(\sum_rA_r^2y_r^2\Bigr)\sum_av_a^4\ \le\ \Bigl(\sum_ry_r^4\Bigr)\sum_av_a^2

Lean (stein_le_inv_sq_mul_test; lemmas stein_form_le, sum_four_le). The bracket on the left is the value of the Stein quadratic form and the right-hand side is the value of the test, so it reads "upper bound ÷ test value ≤κ−2\le\kappa^{-2}".

On the lattice, using as the test the real plane wave in the worst direction θ=Re(eiφu∗e−iq∗⋅X)\theta={\rm Re}(e^{i\varphi}u^*e^{-iq^*\cdot X}), we get

loss ≤ Steintest value = ⟨κ−2⟩×S(u∗)Φ,S(u)=∑a∣ua∣4∣u∣2M2≤1\text{loss}\ \le\ \frac{\text{Stein}}{\text{test value}}\ =\ \langle\kappa^{-2}\rangle\times\frac{S(u^*)}{\Phi},\qquad S(u)=\frac{\sum_a|u_a|^4}{|u|^2M^2}\le1

Φ\Phi is the phase factor; it is 1 if 2q∗≢02q^*\not\equiv0 and 4q∗≢04q^*\not\equiv0, and also 1 at period-2 points (2q∗≡02q^*\equiv0) if u∗u^* is taken real Reading (the average 3/83/8 of cos⁡4\cos^4 cancels between numerator and denominator; this step and the Stein formula itself are not in Lean).

How to read it: on the ℓ2\ell^2 side the Stein bound remembers all the signs; what it forgets is only the "row ℓ1\ell^1" on the ℓ∞\ell^\infty side. So the loss reduces to the amount of cancellation within a row, 1/κ21/\kappa^2 Reading. This gives a conditional statement — if the alignment in the worst direction is bounded below over steps, the loss is bounded over steps — but that the alignment is bounded below is not shown (F-SYS1).

A pattern that did not apply — positive part dominant

For a sign field ss, if the negative part of each row is at most δ\delta times the positive part, then (Ts)i≥1−δ1+δri(Ts)_i\ge\frac{1-\delta}{1+\delta}r_i (rir_i the row ℓ1\ell^1), and combined with the ℓ4\ell^4 Schur test ∑(Tx)4≤A3B∑x4\sum(Tx)^4\le A^3B\sum x^4, loss ≤U(1+δ1−δ)4\le U\bigl(\frac{1+\delta}{1-\delta}\bigr)^4 (UU the non-uniformity factor of the row ℓ1\ell^1). Under composition δ\delta degrades additively (alignment 1−δ1−δ21-\delta_1-\delta_2) Lean (coherent_of_neg_le, schur_four, loss_le_of_coherent, comp_coherent).

The theorem is correct, but it does not apply to the kernels of the record. The δ\delta read from the ℓ4\ell^4-weighted average alignment is about 0.46, 0.39, 0.39, 0.35 and is not small; UU grows as 3.0, 4.5, 8.8, 15.8; and the minimal alignment per row is almost 0 (the assumption of δ\delta on every row is not satisfied) Computed. The Schur test itself was also two orders of magnitude coarser than the Stein bound (Schur ÷ lower bound 437 → 745 → 1453 → 1777) Computed.

The W coordinates — the absolute value after composition stops at a rank-one value

Table 5 The loss for the W coordinates (kernel with the zero mode corrected, 60 types) Computed
kρ(Tk)\rho(T_k)Compose after absolute valueAbsolute value after composingNegative proportion
10.36311.011.010.210
20.12491.081.060.325
30.04221.161.090.387
40.01421.241.100.411
50.00481.331.100.421

The loss is the ratio of ρ\rho's (ρ(∣⋅∣)/ρ\rho(|\cdot|)/\rho). The value 1.10 at which the side taking the absolute value after composition stops almost agrees with the rank-one value ∑∣ui∣∣vi∣/∣∑uivi∣=1.085\sum|u_i||v_i|/|\sum u_iv_i|=1.085 built from the left and right dominant eigenvectors u,vu,v Computed. If the dominant eigenvalue has a gap, Tk/ρk→uvT/(vTu)T^k/\rho^k\to uv^{\rm T}/(v^{\rm T}u), and since ∣⋅∣|\cdot| and ρ\rho are continuous it converges to this value Reading. The side composing after taking absolute values grows as (ρ(∣M∣)/ρ(M))k(\rho(|M|)/\rho(M))^k for powers of a single matrix (here by a factor of 1.070 each time), and is bounded only when ρ(∣M∣)=ρ(M)\rho(|M|)=\rho(M), which for irreducible matrices means M=eiαD∣M∣D−1M=e^{i\alpha}D|M|D^{-1} (Wielandt) Cited. That the absolute value after composition is at most the composition after absolute values (row ℓ1\ell^1) is abs_comp_le, row_l1_comp_le Lean.

03

The geometry of local representatives

Representing by a local kernel a map determined only on fields satisfying the coarse Bianchi identity — this handwork came up as the choice of "representative" in Theorem G′ of 15-05. In this section we separate the overall shape of the representatives (an affine space), the quantities that do not depend on the representative (the value of the zero mode, and the order of folding restricted to the constraint), and the quantities that do (the overall order of folding and the tail norm). The content is a restatement of the order of multigrid transfer operators and of the sum rules of subdivision (conditions of Strang–Fix type).

Definitions

Definition 3.1 (constrained map and extension). We call a quadruple (E,V,W,f)(E,V,W,f) of finite-dimensional spaces E,WE,W over a field KK, a subspace V≤EV\le E and a linear map f:V→Wf:V\to W a constrained map, and a g:E→Wg:E\to W with g∣V=fg|_V=f an extension. Extensions exist (the restriction map resV{\rm res}_V is surjective), any two extensions agree on VV, and the set of extensions is the affine space g0+ker⁡resVg_0+\ker{\rm res}_V, of dimension (dim⁡E−dim⁡V)⋅dim⁡W(\dim E-\dim V)\cdot\dim W Lean (exists_extension, restrict_surjective, IsExtension.eqOn, isExtension_iff_mem_coset, finrank_freedom). The freedom is 0 only when V=EV=E (W≠0W\ne0; freedom_eq_zero_iff).

Definition 3.2 (lattice representative). The coarse plaquette field is θ:Z4→C6\theta:\mathbb Z^4\to\mathbb C^6, the constraint subspace is V=im⁡DcV=\operatorname{im}D_c (fields satisfying the coarse Bianchi identity), and the output is a fine plaquette field with 96=16×696=16\times6 components per coarse cell. A translation-invariant kernel K:Z4→C96×6K:\mathbb Z^4\to\mathbb C^{96\times6} whose symbol satisfies K^(q)D^(q)=R^(q)\hat K(q)\hat D(q)=\hat R(q) for all qq (with R=FDcR=FD_c) is called a representative of FF, and one that has finite range, exponential decay or ℓ1\ell^1 is called a local representative. For q≠0q\ne0, D^(q)\hat D(q) has rank 3, the symbol at each qq is an instance of the template "E=C6E=\mathbb C^6, dim⁡V=3\dim V=3, W=C96W=\mathbb C^{96}", and the freedom is (6−3)⋅96=288(6-3)\cdot96=288-dimensional.

Definition 3.3 (zero mode, moments). We call K^(0)=∑ZK(Z)\hat K(0)=\sum_ZK(Z) the zero mode and Mα(K)=∑ZZαK(Z)M_\alpha(K)=\sum_ZZ^\alpha K(Z) the moments.

Definition 3.4 (order of folding). For η∈{0,1}4\eta\in\{0,1\}^4, pη=(q+2πη)/2p_\eta=(q+2\pi\eta)/2 and the fine position s∈{0,1}4s\in\{0,1\}^4 within a coarse cell, the folded component is C^η(q)[o,a]=∑se−ipη⋅sA^(s,o),a(q)\hat C_\eta(q)[o,a]=\sum_se^{-ip_\eta\cdot s}\hat A_{(s,o),a}(q). We write ord(K)\mathrm{ord}(K) for the minimal order to which C^η(q)\hat C_\eta(q) with η≠0\eta\ne0 vanishes as q→0q\to0, and ordV(K)\mathrm{ord}^V(K) for the minimal order of C^η(q)P(q)\hat C_\eta(q)P(q), multiplied by the projection P(q)P(q) onto the constraint subspace.

Quantities that do not depend on the representative

The zero mode is determined by continuity alone (Candidate 3.1). If KK is an ℓ1\ell^1 representative (continuous symbol), D^(q)=D1(q)+O(∣q∣2)\hat D(q)=D_1(q)+O(|q|^2), R^(q)=R1(q)+O(∣q∣2)\hat R(q)=R_1(q)+O(|q|^2) and ∑νim⁡D1(eν)=C6\sum_\nu\operatorname{im}D_1(e_\nu)=\mathbb C^6, then K^(0)\hat K(0) is the unique solution of K^(0)D1(eν)=R1(eν)\hat K(0)D_1(e_\nu)=R_1(e_\nu) (ν=1,…,4\nu=1,\dots,4) Reading. The last step (maps that agree on a family of subspaces whose sum spans the whole are equal) is eq_of_eqOn_iSup, correction_eq_zero_of_iSup Lean. The value in the record is K^(0)=U/4\hat K(0)=U/4, U=116⊗I6U=\mathbf 1_{16}\otimes I_6 (θ/4\theta/4 uniformly at every position), with deviation ≤3.1×10−10\le3.1\times10^{-10} over four steps Computed. On the torus D^(0)=0\hat D(0)=0, so the zero mode is unconstrained, and for the symmetric representative on finite tori max⁡∣A^(0)−U/4∣=0.250\max|\hat A(0)-U/4|=0.250, 1.47×10−21.47\times10^{-2}, 2.55×10−52.55\times10^{-5} at Lb=8,16,32L_b=8,16,32 Computed. This is the numerical trace of the constraint of locality being lost in a finite box.

The minimal-norm representative is not local (Candidate 3.2). K^MP(q)=R^(q)D^(q)+\hat K_{\rm MP}(q)=\hat R(q)\hat D(q)^+ (the Moore–Penrose representative) does not lie in ℓ1\ell^1 unless the limits along different directions agree, because the projection P(q)P(q) is a function of qq homogeneous of degree 0 and leaves a memory of direction at q=0q=0 Reading. The freedom of local representatives can be seen as the room to repaint this memory of direction into a continuous function. The decay of the kernel has not been measured (F-SYS9).

The order restricted to the constraint does not depend on the representative (Candidate 3.3). With the singular value decomposition D^=UΣVH\hat D=U\Sigma V^{\rm H}, C^η(q)U(q)\hat C_\eta(q)U(q) can be written using only the folding of R^\hat R, so ordV(K)=ordV(F)\mathrm{ord}^V(K)=\mathrm{ord}^V(F) is an invariant of FF. Restriction does not lower the order of vanishing, so for every representative ord(K)≤ordV(F)\mathrm{ord}(K)\le\mathrm{ord}^V(F) Reading.

Table 6 Orders of folding of the representatives in the record (in brackets, how the value decreases as tt is made smaller by one order of magnitude at a time) Computed
RepresentativeConstructionord\mathrm{ord} (whole 6×66\times6)ordV\mathrm{ord}^V (on im⁡D\operatorname{im}D)
symRows of the cone homotopy (finite torus)0 (C^(0)=0.039\hat C(0)=0.039–0.0710.071)0
A3Add the difference of the zero mode at the single point Z=0Z=01 (3.4×10−2→3.4×10−43.4\times10^{-2}\to3.4\times10^{-4} for t=10−1→10−3t=10^{-1}\to10^{-3})1 (5×10−3→5×10−55\times10^{-3}\to5\times10^{-5})
A4Add to A3 a first-moment correction as antisymmetric pairs at Z=±eμZ=\pm e_\mu2 (1.7×10−3→1.7×10−71.7\times10^{-3}\to1.7\times10^{-7})2
FF itselfFrom RR—2 (1.8×10−3→1.8×10−71.8\times10^{-3}\to1.8\times10^{-7})

A4 attains ord(K)=ordV(F)=2\mathrm{ord}(K)=\mathrm{ord}^V(F)=2 on the whole 6×66\times6. That is, within the types of the record, A4 is a representative that reaches the ceiling.

Tail norm and order — D ≤ 4 is the upper limit

Candidate 3.4. In the nn-step map of the W coordinates (Tf)(q)=16−n∑mGm(q)Hf(pm)Gm(q)(Tf)(q)=16^{-n}\sum_mG_m(q)^{\rm H}f(p_m)G_m(q) (mm runs over 16n16^n paths, GmG_m is a product of foldings), suppose that the representatives of all steps satisfy ord(Kk)≥k0\mathrm{ord}(K_k)\ge k_0 and that C^0(0)=4I\hat C_0(0)=4I. (a) If D≤2k0D\le2k_0, TT is bounded in the norm on the symbol side ∥⋅∥D=sup⁡q≠0∥⋅∥2/∣q^∣D\|\cdot\|_D=\sup_{q\ne0}\|\cdot\|_2/|\hat q|^D. (b) If D>2k0D\gt2k_0 and the leading coefficient SS of the paths with m≠0m\ne0 is non-zero, then for a peaked input near q0q_0 it diverges at the rate ∣q0∣2k0−D|q_0|^{2k_0-D} Reading (a line of argument assuming constants uniform in the number of steps; uniformity over infinitely many steps is not treated). In the version restricted to the constraint, k0k_0 is replaced by ordV(F)\mathrm{ord}^V(F).

Table 7 Tail norm (D=4D=4, input along the axis q=2π/Lq=2\pi/L, four points L=24L=24–192192) Computed
Representativeord\mathrm{ord}ValuesType in Candidate 3.4
A311.486, 5.88, 23.5, 93.8 (grows as L2L^2)∣q∣2⋅1−4|q|^{2\cdot1-4}
A420.01638, 0.01640, 0.01643, 0.01643 (bounded)∣q∣2⋅2−4=|q|^{2\cdot2-4}= constant

From RR (ordV=2\mathrm{ord}^V=2) it was bounded at D=4D=4, q−2q^{-2} at D=6D=6, and q−3q^{-3} at D=7D=7 Computed. All cases in the record fit the types (a)(b). Since ordV(F)=2\mathrm{ord}^V(F)=2, the D=6D=6 tail on im⁡D\operatorname{im}D diverges however the representative is chosen, and this reads as: within the types of the record, D≤4D\le4 is the upper limit for the tail of sup/∣q^∣D/|\hat q|^D Reading.

The 2 in "2⋅ord2\cdot\mathrm{ord}" comes from the map of the W coordinates being a congruence GHfGG^{\rm H}fG with the same representative on both sides. In multigrid the orders of prolongation and restriction can be chosen separately, and there is the rule "order of prolongation + order of restriction ≥ order of the equation" (Hemker 1990) Reading. Here a single representative plays both roles.

Representatives with matched first moments, and the sum rules

Candidate 3.5 (order and shifted jets). Putting Js(q):=e−iq⋅s/2K^s(q)J_s(q):=e^{-iq\cdot s/2}\hat K_s(q) (K^s\hat K_s the symbol of the 6 rows at position ss), ord(K)≥k\mathrm{ord}(K)\ge k ⇔ the Taylor polynomial of Js(q)J_s(q) up to degree k−1k-1 does not depend on ss Reading. The line of argument is C^η(q)=∑s(−1)η⋅sJs(q)\hat C_\eta(q)=\sum_s(-1)^{\eta\cdot s}J_s(q) together with the orthogonality of the 15 non-trivial characters of (Z/2)4(\mathbb Z/2)^4 (inner product 0 with all of them ⇔ constant).

The target BB is determined from the q2q^2 term of RR. Against 24 unknowns per row (4 directions × 6), the part determined by RR had rank 20, leaving 4 dimensions of freedom Computed. This count is of the type of a finite-dimensional "extension with conditions": if (resV,C)({\rm res}_V,C) is surjective, there is a gg satisfying both g∣V=fg|_V=f and C(g)=yC(g)=y, and the remaining freedom is dim⁡E⋅dim⁡W−dim⁡V⋅dim⁡W−dim⁡Y\dim E\cdot\dim W-\dim V\cdot\dim W-\dim Y Lean (exists_extension_with_conditions, finrank_freedom_with_conditions, conditions_count_le). The remaining 4 dimensions were fixed by linear programming to minimise the increase of ℓ1\ell^1; the moments matched the target to within 1.1×10−161.1\times10^{-16}, and the row ℓ1\ell^1 went from 2.26 to 2.34 (first step) Computed.

Composition of representatives and compatibility

If (E1,V1,E,f1)(E_1,V_1,E,f_1) and (E,V2,W,f2)(E,V_2,W,f_2) are compatible (f1(V1)⊆V2f_1(V_1)\subseteq V_2), the composite of representatives is a representative of the composite, and its value on V1V_1 does not depend on the choice of representatives. If they are not compatible (W≠0W\ne0), the value of the composite changes with the choice Lean (comp_extension_eqOn, comp_isExtension, comp_depends_of_not_le). The chain of W coordinates in the record composes representatives, but whether the output of the representative at step kk lies in the constraint subspace of step k+1k+1 has not been checked (F-SYS8). The difference between the chain on im⁡D\operatorname{im}D, 0.3426, and the 6×66\times6 chain, 0.3446, is a clue to this Computed. As examples of norms changing with the representative: the zero-mode correction moved the three-step Stein bound from 0.09743 to 0.09868, and the signed Stein bound went from 4.25 for A3 to 4.48 for A4 (first step) Computed.

Dictionary

04

The geometry of the double valuation

There is no payoff theorem yet. This section is an attempt to restate ⑦ the crossover band of the ledger (13-06) in the language of two valuations, those of the strong-coupling expansion and the weak-coupling expansion. The definitions and the computation of the leading terms are done, but there is as yet no theorem that this view newly says about the band. The labels are mainly Assumption and Computed.

Definitions

The space of couplings K\mathcal K: the space of character coefficients (ar)(a_r) of the plaquette weight f(U)=1+∑rdrarχr(U)f(U)=1+\sum_rd_ra_r\chi_r(U). Its coordinates are β\beta and the shape coordinates.

Two valuations. vsv_s (strong coupling) is the order on the side ar→0a_r\to0 (the order in β\beta for the Wilson action), and vwv_w (weak coupling) is the order in 1/β1/\beta on the side β→∞\beta\to\infty. Terms of type e−cβe^{-c\beta} are treated as vw=∞v_w=\infty (another branch of the transseries).

Two coordinates. For an observable OO with values in [0,1][0,1] (O(0)=0O(0)=0, O(∞)=1O(\infty)=1; the plaquette PP, for example), the coordinate on the strong-coupling side is OO and the coordinate on the weak-coupling side is 1−O1-O. We write the leading coefficients as O≈s1βO\approx s_1\beta (strong coupling) and 1−O≈w1/β1-O\approx w_1/\beta (weak coupling).

Tie sets. (i) the complementary tie {s1β=w1/β}\{s_1\beta=w_1/\beta\}; (ii) the same-coordinate tie {s1β=1−w1/β}\{s_1\beta=1-w_1/\beta\}; (iii) the error tie {K\{K-term optimal truncations have equal errors}\}. We call the region between the two roots of (ii), {s1β≤1−w1/β}\{s_1\beta\le1-w_1/\beta\}, the lens.

The invariant κ and the lens

Candidate 4.1 (a scale-independent quantity). Changing the scale of the coupling as β↦cβ\beta\mapsto c\beta gives s1↦s1/cs_1\mapsto s_1/c, w1↦cw1w_1\mapsto cw_1, so

κ:=s1w1\kappa := s_1w_1

does not depend on the scale. The complementary tie is at β∗=w1/s1\beta^*=\sqrt{w_1/s_1}, where the value of the leading terms is κ\sqrt\kappa. The same-coordinate tie is at the roots of s1β2−β+w1=0s_1\beta^2-\beta+w_1=0, whose discriminant is 1−4κ1-4\kappa, so the lens opens only when κ≤14\kappa\le\frac14. The geometric mean of the two roots is always β∗\beta^*. A tie for the string tension σ=−log⁡u\sigma=-\log u exists only when κ≤1/e\kappa\le1/e Reading (the elementary fact of the discriminant of a quadratic).

Looking at the leading term on one side only, the difference between groups is absorbed into the scale. Looking at the leading terms on both sides at once, a change of scale is only a translation in the (log⁡O,log⁡(1−O))(\log O,\log(1-O)) plane, and the height κ\sqrt\kappa at which they cross does not move. The view is that the information about the group remains in "the height of the crossing" Assumption.

Examples

Table 8 Series and ties for a single plaquette (exact solution in two dimensions; the material of one Migdal–Kadanoff step) Computed
QuantitySU(2)SU(2)U(1)U(1)
Strong-coupling series uuβ4−β396+β51536−β723040+⋯\frac\beta4-\frac{\beta^3}{96}+\frac{\beta^5}{1536}-\frac{\beta^7}{23040}+\cdotsβ2−β316+β596−11β76144+⋯\frac\beta2-\frac{\beta^3}{16}+\frac{\beta^5}{96}-\frac{11\beta^7}{6144}+\cdots
Weak-coupling series 1−u1-u32β−1−38β−2−38β−3−63128β−4⋯\frac32\beta^{-1}-\frac38\beta^{-2}-\frac38\beta^{-3}-\frac{63}{128}\beta^{-4}\cdots12β−1+18β−2+18β−3+25128β−4⋯\frac12\beta^{-1}+\frac18\beta^{-2}+\frac18\beta^{-3}+\frac{25}{128}\beta^{-4}\cdots
κ=s1w1\kappa=s_1w_13/83/8 (the lens is empty, 1−4κ=−121-4\kappa=-\frac12)1/41/4 (the lens is the single point β=1\beta=1)
s3/s13s_3/s_1^3, w2/w12w_2/w_1^2−2/3-2/3, −1/6-1/6−1/2-1/2, +1/2+1/2
Complementary tie β∗\beta^* and the true u(β∗)u(\beta^*)6=2.4495\sqrt6=2.4495, u=0.5004u=0.5004 (β\beta at u=12u=\frac12 is 2.4469)1.0000, u=0.4464u=0.4464 (β\beta at u=12u=\frac12 is 1.1593)
Tie for σ\sigmaNone (maximum of the difference −log⁡κ−1=−0.019-\log\kappa-1=-0.019)0.232 and 1.399
Error tie (K=40K=40)3.274 (error 4.8×10−44.8\times10^{-4})2.124 (error 2.9×10−32.9\times10^{-3})
Fisher zeros (imaginary axis)±i 3.832\pm i\,3.832, ±i 7.016\pm i\,7.016, …±i 2.405\pm i\,2.405, ±i 5.520\pm i\,5.520, …

The specific heat β2u′\beta^2u' has a peak (0.680) at β=2.48\beta=2.48 for U(1)U(1), while for SU(2)SU(2) it rises monotonically to 3/23/2 Computed. This difference goes in the same direction as the difference in the sign of w2/w12w_2/w_1^2 (−1/6-1/6 and +1/2+1/2), and can be read as: the difference between groups lives not in the leading terms of the valuations but in the sign of the next term Assumption. That u(6)=0.5004≈12u(\sqrt6)=0.5004\approx\frac12 for SU(2)SU(2) does not hold for U(1)U(1) (0.446), so it is not a general law.

The lens of the leading terms alone in four dimensions. Using equipartition w1=dim⁡G/dw_1=\dim G/d, κ=s1dim⁡G/d\kappa=s_1\dim G/d.

Table 9 The lens of the leading terms alone in dd dimensions Computed
dGroupκ\kappaComplementary tie β∗\beta^*Lens
2SU(2)SU(2)3/83/82.449None
2U(1)U(1)1/41/41.000Single point [1,1][1,1]
3SU(2)SU(2)1/41/42.000Single point [2,2][2,2]
3U(1)U(1)1/61/60.816[0.423,1.577][0.423,1.577]
4SU(2)SU(2)3/163/161.732[1.000,3.000][1.000,3.000]
4U(1)U(1)1/81/80.707[0.293,1.707][0.293,1.707]

The transition of four-dimensional U(1)U(1), βc≈1.01\beta_c\approx1.01 (13-06), lies inside the lens [0.293,1.707][0.293,1.707] (not at its centre 0.707). The SU(2)SU(2) lens [1,3][1,3] contains the range in the table of 13-06 over which β−β′\beta-\beta' moves from the strong-coupling value to the one-loop value, and also overlaps 1.5<β<2.51.5\lt\beta\lt2.5, where the literature says "neither the strong-coupling nor the weak-coupling expansion works well" (abstract of arXiv:0807.0185) Reading. These are numbers derived only from first-order leading terms and equipartition, without the true four-dimensional series. The overlaps may include coincidence Assumption.

Tie sets under the Migdal–Kadanoff flow

We followed the level lines Ln(c)L_n(c) of the fundamental-representation coefficient un(β)u_n(\beta) after nn steps of flow from the Wilson action. A level line is an object that does not depend on how β\beta is read.

Table 10 Movement of the level lines Ln(c)L_n(c) Computed
GroupccL0L_0L6L_6Difference at step 6, L6−L5L_6-L_5
SU(2)SU(2)0.15750.6412.2300.259
SU(2)SU(2)0.52.4473.5350.2553
SU(2)SU(2)0.914.7315.580.2511
U(1)U(1)0.15750.3190.5820.017 (positive while decreasing)
U(1)U(1)0.51.1590.8444.5×10−44.5\times10^{-4}
U(1)U(1)0.72.0141.5101−3.5×10−7-3.5\times10^{-7} (stops)
U(1)U(1)0.95.3054.8478−3.7×10−7-3.7\times10^{-7} (stops)

Why the candidate theorem does not stand, and a weakened form

The form "a comparison that distinguishes groups is needed only near the codimension-one skeleton of the tie sets" is not expected to hold as it stands Assumption. This is because the distinction between groups already appears at the level of the leading terms, over the whole weak-coupling coordinate, as the valuation of the flow (vw=0v_w=0 for SU(2)SU(2), vw=∞v_w=\infty for U(1)U(1); that is, the presence or absence of b0b_0).

Candidate B (weakened form) Assumption. For a family of observables and groups G,G′G,G', assume three things: (B1) the maps of the valuations of the strong-coupling coordinate agree for GG and G′G' under matching of the scale by s1s_1; (B2) the valuations of the flow of the weak-coupling coordinate differ; (B3) regions Ds(η)D_s(\eta), Dw(η)D_w(\eta) can be taken in which the error of each coordinate is at most η\eta times the leading term of that coordinate. Then information beyond the leading terms is needed to decide the direction of the comparison (whether β′≤β\beta'\le\beta) only on K∖(Ds(η)∪Dw(η))\mathcal K\setminus(D_s(\eta)\cup D_w(\eta)), and this set shrinks to the lens as η→0\eta\to0.

Relation to the known

05

The cone calculus

The record of Part 15 contains the following handwork again and again: bounding a polynomial of degree pp by an ℓp\ell^p cone ∣f(θ)∣≤c ∥θ∥pp|f(\theta)|\le c\,\|\theta\|_p^p, pulling it back by a linear map (the local representative of the blocking), bounding the pull-back factor from above by the weighted Stein bound, checking that it contracts in a composite of several steps even if it does not contract in one step, and absorbing the terms that the loops add at each step into an affine recursion to obtain a bound valid at every step (the corollary in 15-05, 15-08 §06). Like §01–§03, this section is an attempt to give this handwork definitions. Much of the content is a restatement of known facts — the Riesz–Thorin interpolation theorem, Stein–Weiss interpolation with change of measure, the Schur test, Hölder's inequality, and the log-convexity of operator norms in the exponent — and no novelty is claimed. What is new lies on the side of the questions: after setting out which quantity each number of the record corresponds to, we pose as questions the "window" and the "bundle number" as the exponent pp is varied.

Setting

V,WV,W are finite-dimensional real vector spaces, and we fix one set of coordinates. ℓp\ell^p is the ℓp\ell^p of the coordinates. In the lattice case, VV is the plaquette field on the coarse torus (6 components per point), WW is the fine plaquette field arranged as 96 components per cell, and K:V→WK:V\to W commutes with coarse translations. The supremum of the cone is taken over all of VV (it is not restricted to the image of the Bianchi identity). Hence the quantities here are upper bounds for the restricted quantities.

Definitions

Definition 5.1 (cone constant). When f:V→Rf:V\to\mathbb R is a homogeneous polynomial of degree pp (or grows no faster than that),

cp(f):=sup⁡θ≠0∣f(θ)∣∥θ∥pp.c_p(f):=\sup_{\theta\ne0}\frac{|f(\theta)|}{\|\theta\|_p^p}.

In Lean this is written IsCone f N c (∣f θ∣≤c⋅Nθ|f\,\theta|\le c\cdot N\theta for all θ\theta), with an abstract NN playing the role of ∥⋅∥pp\|\cdot\|_p^p.

Definition 5.2 (pp-contraction). For a linear map K:V→WK:V\to W,

μp(K):=sup⁡θ≠0∥Kθ∥pp∥θ∥pp=∥K∥p→p p.\mu_p(K):=\sup_{\theta\ne0}\frac{\|K\theta\|_p^p}{\|\theta\|_p^p}=\|K\|_{p\to p}^{\,p}.

In Lean this is written Contracts K N μ (N(Kθ)≤μ NθN(K\theta)\le\mu\,N\theta for all θ\theta) and read as "μp(K)≤μ\mu_p(K)\le\mu".

Definition 5.3 (row and column ℓ1\ell^1). Put Ar:=∑j∣Krj∣A_r:=\sum_j|K_{rj}|, R(K):=max⁡rAr=∥K∥∞→∞R(K):=\max_rA_r=\|K\|_{\infty\to\infty}, C(K):=max⁡j∑r∣Krj∣=∥K∥1→1C(K):=\max_j\sum_r|K_{rj}|=\|K\|_{1\to1}. Then μ1=C\mu_1=C, and μp1/p→R\mu_p^{1/p}\to R (p→∞p\to\infty) Cited.

Definition 5.4 (the weighted Stein bound for general p≥2p\ge2). For a positive weight uu put

Sp(K;u):=max⁡rArpur⋅λmax⁡(KTDu/A2K),Sp(K):=Sp(K;Ap)=λmax⁡(KTDAp−2K)S_p(K;u):=\max_r\frac{A_r^p}{u_r}\cdot\lambda_{\max}\bigl(K^{\mathsf T}D_{u/A^2}K\bigr),\qquad S_p(K):=S_p(K;A^p)=\lambda_{\max}\bigl(K^{\mathsf T}D_{A^{p-2}}K\bigr)

(DvD_v is the matrix with vv on the diagonal). The standard form Sp(K)S_p(K) becomes the bare ∥K∥22\|K\|_2^2 at p=2p=2, DAD_A at p=3p=3 and DA2D_{A^2} at p=4p=4, recovering the ℓ3\ell^3 and ℓ4\ell^4 formulas of the record. For KK commuting with translations, λmax⁡\lambda_{\max} is replaced by sup⁡qλmax⁡(K^(q)HDK^(q))\sup_q\lambda_{\max}(\hat K(q)^{\mathsf H}D\hat K(q)).

Definition 5.5 (bundle number). For a sequence of step maps (Kk)(K_k) and a bundle length nn, put K(k,n):=KkKk+1⋯Kk+n−1K^{(k,n)}:=K_kK_{k+1}\cdots K_{k+n-1} and

np:=min⁡{n: sup⁡kμp(K(k,n))<1}(if none, ∞)n_p:=\min\Bigl\{n:\ \sup_k\mu_p\bigl(K^{(k,n)}\bigr)\lt1\Bigr\}\quad(\text{if none, }\infty)

If the upper-bound version with μp\mu_p replaced by SpS_p is n~p\tilde n_p, then np≤n~pn_p\le\tilde n_p.

Definition 5.6 (window). Fixing the bundle length nn, put Wn:={p≥1: μp(K(n))<1}W_n:=\{p\ge1:\ \mu_p(K^{(n)})\lt1\}.

Definition 5.7 (affine recursion). ck+1≤μkck+εkc_{k+1}\le\mu_kc_k+\varepsilon_k (μk≥0\mu_k\ge0, ck≥0c_k\ge0). The bundle version is ck+m≤μ ck+εc_{k+m}\le\mu\,c_k+\varepsilon. ckc_k corresponds to the cone constant at step kk, and εk\varepsilon_k to the size of the degree-pp terms newly born at that step.

Definition 5.8 (Schur threshold exponent). When R(K)<1R(K)\lt1, put p∗(K):=1+log⁡C/log⁡(1/R)p^*(K):=1+\log C/\log(1/R). The bound μp≤Rp−1C\mu_p\le R^{p-1}C of Candidate 5.6 below falls below 1 when p>p∗p\gt p^*.

Candidate theorems and labels

Candidate 5.1 (pull-back and submultiplicativity). If c≥0c\ge0, then cp(f∘K)≤cp(f) μp(K)c_p(f\circ K)\le c_p(f)\,\mu_p(K) Lean (cone_pullback; a map V→WV\to W, and NV,NWN_V,N_W may differ). On a single space, μp(K1K2)≤μp(K1)μp(K2)\mu_p(K_1K_2)\le\mu_p(K_1)\mu_p(K_2) (μ1≥0\mu_1\ge0), μp(Kn)≤μp(K)n\mu_p(K^n)\le\mu_p(K)^n and cp(f∘Kn)≤cp(f) μnc_p(f\circ K^n)\le c_p(f)\,\mu^n Lean (contracts_comp, contracts_iterate, cone_pullback_iterate; μ≥0\mu\ge0).

Candidate 5.2 (exceeding in one step, contracting in a bundle). If μp(K)≤M\mu_p(K)\le M in one step (M>1M\gt1 is allowed) and μp(Kn)≤μ\mu_p(K^n)\le\mu in nn steps, then μp(Kqn+r)≤Mrμq\mu_p(K^{qn+r})\le M^r\mu^q Lean (block_decay; M≥0M\ge0, μ≥0\mu\ge0). This is the cone version of Candidate 1.4 (a) of §01. The upper bound SpS_p itself is not necessarily submultiplicative, so the SpS_p of a composite is computed directly from the composite kernel Reading.

Candidate 5.3 (log-convexity of the upper bound). log⁡Sp(K)\log S_p(K) is convex in pp Reading. This is because Sp=sup⁡∥x∥=1∑r(Kx)r2Arp−2S_p=\sup_{\|x\|=1}\sum_r(Kx)_r^2A_r^{p-2}, and for each xx the right-hand side is a positive sum of exponential functions of pp and hence log-convex (Cauchy–Schwarz), and the supremum of log-convex functions is log-convex. What is in Lean is a discrete midpoint version Lean:

As a consequence, S3≤S2S4S_3\le\sqrt{S_2S_4}. What looked in the record like "S2S4\sqrt{S_2S_4} is a little above S3S_3" was not a comparison of two different upper bounds but the margin of the curvature of a single function log⁡Sp\log S_p. S2S4/S3−1\sqrt{S_2S_4}/S_3-1 is one number measuring the size of that curvature (Table 12).

Candidate 5.4 (log-convexity of the true pp-contraction). log⁡μp\log\mu_p is also convex in p>0p\gt0. By Riesz–Thorin, ψ(s):=log⁡∥K∥1/s→1/s\psi(s):=\log\|K\|_{1/s\to1/s} is convex for s∈[0,1]s\in[0,1] Cited, and log⁡μp=p ψ(1/p)\log\mu_p=p\,\psi(1/p) is the perspective of ψ\psi and hence convex Reading. Candidate 5.3 is what can be said directly about the upper bound SpS_p (as a sum of exponentials), while Candidate 5.4 is what can be said about the true μp\mu_p from convexity in 1/p1/p through the perspective. They rest on different things. There are two consequences Reading.

Candidate 5.5 (bundle number and spectral radius). For a fixed finite-dimensional operator K:V→VK:V\to V, Gelfand's formula gives lim⁡nμp(Kn)1/n=ρ(K)p\lim_n\mu_p(K^n)^{1/n}=\rho(K)^p, and ρ\rho does not depend on pp Cited. Hence "np<∞n_p\lt\infty ⇔ ρ(K)<1\rho(K)\lt1", and only the smallest nn changes with pp. This is the same fact as Definition 1.3 of §01, said in terms of the pp-contraction. The blocking map, however, is a map from the coarse lattice to the fine lattice, not a single operator on one space. Identifying the fine lattice back with Z4\mathbb Z^4 gives the type "dilation by 2 and convolution" (a subdivision operator), and for this type the ℓp\ell^p spectral radius depends on pp Reading.

Candidate 5.6 (the correct form of dilution). The naive form "if the row sums are 1, the entries are non-negative and each entry is ≤1/m\le1/m, then μp≤m1−p\mu_p\le m^{1-p}" does not hold in general Reading. An averaging map preserves constant fields, so if it is square, μp≥1\mu_p\ge1 (a constant field is a counterexample). What holds is the following.

Candidate 5.7 (affine recursion). There are the following five Lean. They extend Candidate 1.4 (c) of §01 (affine_uniform) to coefficients that vary with the step and to bundles.

Table 11 The candidate theorems of §05. Each is a finite-dimensional form of a known fact, or an elementary consequence of one
CandidateStatement (one line)LabelWhat it restates
5.1cp(f∘K)≤cp(f)μp(K)c_p(f\circ K)\le c_p(f)\mu_p(K), μp(K1K2)≤μp(K1)μp(K2)\mu_p(K_1K_2)\le\mu_p(K_1)\mu_p(K_2), μp(Kn)≤μp(K)n\mu_p(K^n)\le\mu_p(K)^nLean (cone_pullback, contracts_comp, contracts_iterate, cone_pullback_iterate)Submultiplicativity of operator norms
5.2One step ≤M\le M, nn steps ≤μ\le\mu ⇒ qn+rqn+r steps ≤Mrμq\le M^r\mu^qLean (block_decay)A finite version of Gelfand's formula (Candidate 1.4 (a) of §01)
5.3log⁡Sp\log S_p is convex in pp; in particular S3≤S2S4S_3\le\sqrt{S_2S_4}Continuous version Reading, discrete midpoint version Lean (weighted_rpow_midpoint, stein_form_midpoint, sup_midpoint, midpoint_below_one)Hölder's (Cauchy–Schwarz) inequality; the supremum of log-convex functions
5.4log⁡μp\log\mu_p is convex in pp, WnW_n is an interval, μp≤μp0Rp−p0\mu_p\le\mu_{p_0}R^{p-p_0} (p≥p0p\ge p_0). Upper-bound version Sp≤Rp−p0Sp0S_p\le R^{p-p_0}S_{p_0}True μp\mu_p: Cited + Reading; upper-bound version: Lean (weighted_rpow_shift, sup_shift)Riesz–Thorin (convexity in 1/p1/p) and the perspective
5.5For a fixed operator, np<∞n_p\lt\infty ⇔ ρ(K)<1\rho(K)\lt1. The blocking map is of subdivision type, and its ℓp\ell^p spectral radius depends on pp. The ratio for a constant field is about 24−2p2^{4-2p} per stepCited, Reading, numbers ComputedGelfand's formula; the LpL^p theory of subdivision
5.6The naive dilution μp≤m1−p\mu_p\le m^{1-p} does not hold (constant field). What holds is μp≤Rp−1C\mu_p\le R^{p-1}C (with equality cases), Mp−1M^{p-1} for δ\delta fields, and Sp≤S2Rp−2S_p\le S_2R^{p-2}Counterexample Reading; the three forms Lean (row_rpow_le, lp_schur, lp_schur_sharp, delta_dilution, weighted_rpow_shift); μp≤μ2Rp−2\mu_p\le\mu_2R^{p-2} ReadingThe Schur test; finite sums for Riesz–Thorin between (1,∞)(1,\infty) and (2,∞)(2,\infty)
5.7Affine recursion: constant coefficients, coefficients varying with the step, invariant interval, upper limit, bundles of mm stepsLean (affine_const, affine_varying, affine_invariant, affine_eventually, affine_block)An elementary fact about affine recursions (Candidate 1.4 (c) of §01)

Correspondence with the numbers of the record

One step is the step-0 kernel K0K_0 on the 848^4 torus (no truncation); two steps is K0K1K_0K_1 (coarse 16416^4, kernels truncated at R=3R=3, with the ℓ1\ell^1 lost being 0.8% for K0K_0 and 1.9% for K1K_1); three steps is K0K1K2K_0K_1K_2 (coarse 12412^4, R=3R=3). The one-step lower bound is the value of the true ratio from a quasi-Newton method (L-BFGS, two starting points); for p≥12p\ge12 it was replaced by the value for the sign field of the largest row. The lower bound is not shown to be the maximum. All are floating-point computations, not interval estimates Computed.

Table 12 The weighted Stein bound SpS_p and the one-step lower bound Computed
ppOne step SpS_pOne step lower boundOne step constant fieldTwo steps SpS_pThree steps SpS_p
21.98061.98061.0803.01893.6658
2.52.36261.41060.5512.2358—
32.86411.02330.28071.66420.57864
3.53.54420.77300.14311.2501—
44.44570.64700.07300.97070.09599
57.84740.73280.01900.6144—
614.9101.23260.00490.4093—
865.1605.01550.00030.2197—
163.91e418.2 (sign field)0.0598—
321.71e107.96e6 (sign field)0.0143—
∞\infty (Sp1/p→RS_p^{1/p}\to R)R=2.2524R=2.2524R=0.9283R=0.9283R=0.3318R=0.3318

In the language of windows, the window given by SpS_p contains [≈4,∞)[\approx4,\infty) for two steps and [3,4][3,4] for three steps. For one step the window given by SpS_p is empty, and the true window is undetermined. Since μ2=S2\mu_2=S_2 is 1.98, 3.02, 3.67 for n≤3n\le3, all at least 1, each WnW_n (n≤3n\le3), being an interval, does not straddle 2 Reading.

A question proper to this pattern — the window, the bundle number, the threshold exponent

Dictionary

Handwork of the recordKnown frameworkLabel
Interpolation between ℓ2\ell^2 and ℓ∞\ell^\infty; convexity of log⁡∥K∥p→p\log\|K\|_{p\to p}The Riesz–Thorin interpolation theorem (M. Riesz 1927, G. O. Thorin 1939): log⁡∥K∥p→p\log\|K\|_{p\to p} is convex in 1/p1/pCited
Interpolation that changes the weight on the range (Definition 5.4)Stein–Weiss, Interpolation of operators with change of measures (Trans. AMS 87, 1958). If the measures at both ends are fixed, Riesz–Thorin sufficesCited, bibliography Reading
Upper bound by the row and column ℓ1\ell^1 (Candidate 5.6)The Schur test (I. Schur 1911). The weighted version (positive test functions) is known in the forms of Aronszajn and Halmos–SunderCited, bibliography Reading
Pointwise inequalities of the cone; the midpoint inequality (Candidate 5.3)Hölder's inequality, Cauchy–Schwarz, the arithmetic–geometric mean inequalityCited
Convexity of log⁡μp\log\mu_p in pp (Candidate 5.4)Log-convexity of operator norms (Riesz–Thorin) and the perspective function of convex analysis (Boyd–Vandenberghe, Convex Optimization §3.2.6)Cited, Reading
Computing μp\mu_p itselfFor p≠1,2,∞p\ne1,2,\infty, approximating the p→pp\to p norm of a matrix is NP-hard (Hendrickx–Olshevsky, SIAM J. Matrix Anal. Appl. 2010). For lower bounds, Boyd's power method (D. W. Boyd 1974, Linear Algebra Appl. 9). This is the reason for using the upper bound SpS_pReading
Contracting in a bundle (Candidate 5.5)Gelfand's spectral radius formula. For operators involving dilation there is the LpL^p theory of subdivision (R.-Q. Jia, Subdivision schemes in LpL_p spaces, Adv. Comput. Math. 1995), in which convergence is decided by the pp-norm joint spectral radiusCited, Reading

The bibliography is at the level of abstracts and has not been checked against the texts of the original sources. Every candidate theorem of this section is a finite-dimensional form of one of the frameworks above, or an elementary consequence of one.

06

Dictionary with the known, what can be said, questions

Summary of the five grades

Table 13 The main rows of this chapter (labels as in the rows of the text; conditions on the same row)
SectionClaimLabelConditions
§01Dominant matrices are closed under products and powersLeanFinitely many blocks with values in a normed ring. For powers, the identity has norm 1
§01Candidate 1.1: if it contracts in kk steps, there is a weight w′w' that contracts in one stepLeanB≥0B\ge0, w≥0w\ge0, s>0s\gt0, k≥1k\ge1, Bkw≤skwB^kw\le s^kw
§01Candidates 1.2–1.5 (one-step estimate, change of weight, finite Gelfand, affine recursion, aggregation of blocks and the two-by-two test)LeanFinite-dimensional. The Collatz–Wielandt equality, Gelfand's formula itself and the existence of Perron vectors are not included
§01Candidate 1.2′ (ℓ2\ell^2 weight, the Schur test), explicit formula for the transient constantReadingRight and left positive Perron vectors exist
§01The loss from discarding signs is not necessarily bounded over steps (nilpotent example)LeanThe quantity that composes after taking absolute values
§01Perron–Frobenius, Collatz–Wielandt, Gelfand, the max-plus bounds, the characterisation of M-matricesCited—
§02The loss stops from two steps on and falls a little (6.28, 5.51, 5.10, 5.26)Computed444^4 torus, steps cut at R=3R=3, the true ratio is a lower bound, k≤4k\le4
§02Candidate 2.1: upper bound ÷ test value ≤κ−2\le\kappa^{-2}LeanκArM≤∣yr∣\kappa A_rM\le|y_r| for every row, ∣va∣≤M|v_a|\le M
§02Loss =⟨κ−2⟩=\langle\kappa^{-2}\rangle (5.55, 5.13, 5.31)Computed444^4, k=2,3,4k=2,3,4, shape and phase factors equal to 1
§02Phase factor Φ=1\Phi=1, the formula for the plane-wave testReading2q∗≢02q^*\not\equiv0 and 4q∗≢04q^*\not\equiv0, or period 2 with u∗u^* real
§02Hypotheses (a)(b)(c) fail, and the way they fail is constant over stepsComputedk≤3k\le3 (larger tori), k≤4k\le4 (444^4)
§02The profile of the composite kernel approaches a single one over stepsReadingA reading from the numbers
§02Upper bound of the positive-part-dominant type (Schur and degradation under composition)LeanNegative ≤δ\le\delta positive on every row. The assumption is not satisfied for the kernels of the record
§02The loss for the W coordinates stops at 1.10, close to the rank-one value 1.085ComputedKernel with the zero mode corrected, 60 types, k≤5k\le5
§03Existence of extensions, affine structure, dimension of the freedom, extension with conditions, compatibility of compositionLeanFinite-dimensional linear algebra
§03Candidates 3.1–3.5 (uniqueness of the zero mode, the Moore–Penrose representative is not local, invariance of ordV\mathrm{ord}^V, the rule for the order of the tail, shifted jets)ReadingThe lattice steps are lines of argument on paper. Candidate 3.4 assumes constants uniform in the steps
§03ord\mathrm{ord}: sym 0, A3 1, A4 2; ordV(F)=2\mathrm{ord}^V(F)=2; the tail is bounded for D≤4D\le4ComputedRepresentatives of the record, axial input at D=4D=4, L≤192L\le192
§03Correspondence with sum rules, high-frequency order and Strang–FixCited, ReadingDetails of how the original sources count orders (±1) not checked
§04κ=s1w1\kappa=s_1w_1 does not depend on the scale, and the lens opens for κ≤14\kappa\le\frac14ReadingA count with the leading coefficients only
§04Single-plaquette series, ties, error ties, the lens in dd dimensions, MK level linesComputedSingle plaquette, leading terms with equipartition, the approximate MK map
§04Information about the group remains in the height of the crossing and the sign of the next term; overlap of the four-dimensional lens with the bandAssumptionLeading terms only; may include coincidence
§04Candidate B (the comparison that carries the distinction is localised in the lens)AssumptionAssumes (B1)(B2)(B3). Statement only
§05Candidates 5.1, 5.2, 5.7 (pull-back of cones, submultiplicativity, exceeding in one step and contracting in a bundle, five forms of affine recursion)LeanStatements written with an abstract NN (in the role of ∥⋅∥pp\|\cdot\|_p^p). Theorem-specific assumptions such as μ≥0\mu\ge0, 0≤μ<10\le\mu\lt1, ε≥0\varepsilon\ge0. The supremum of the operator norm itself is not included
§05Candidates 5.3 and 5.6: midpoint convexity of log⁡Sp\log S_p, Schur's μp≤Rp−1C\mu_p\le R^{p-1}C and its equality, dilution of δ\delta fields, Sp≤S2Rp−2S_p\le S_2R^{p-2}LeanFinite sums. w≥0w\ge0, a>0a\gt0, a≤Ra\le R, p≥1p\ge1. Convexity in continuous pp and the formula for SpS_p itself (interpolation) are not included
§05Derivation of the weighted Stein bound for general pp, convexity of the true log⁡μp\log\mu_p, the window WnW_n is an interval, counterexample to the naive dilution (constant field)Reading, Citedp≥2p\ge2 (t=1−2/p≥0t=1-2/p\ge0). Convexity via Riesz–Thorin and the perspective
§05Second difference quotients of log⁡Sp\log S_p all positive; S2S4/S3=1.016\sqrt{S_2S_4}/S_3=1.016–1.0361.036; Sp1/p→RS_p^{1/p}\to R (2.252, 0.928, 0.332); upper bounds on the bundle number (3 at p=3p=3; 2 for p=4p=4–3232 and ∞\infty); the true one-step μp\mu_p is undecided for 3.5≤p≤53.5\le p\le5 (lower bound 0.65–0.77, upper bound 3.5–7.8); if W1W_1 is non-empty, a single interval inside (3.04,5.67)(3.04,5.67)ComputedOne step 848^4 without truncation; two steps coarse 16416^4; three steps coarse 12412^4; truncated at R=3R=3; the lower bound is not shown to be the maximum
§05npn_p diverges like c/(p−2)c/(p-2) as p↓2p\downarrow2, or there is a lower end pc>2p_c\gt2 of W∞W_\inftyAssumptionAn estimate from the dimension count 24−2p2^{4-2p} of the constant field alone

The Lean of this chapter

None of the five files contains sorry or uses native_decide, and the axioms printed at the end were the three standard ones (propext, Classical.choice, Quot.sound) or a subset of them. None of the files contains lattices, groups, measures, minimisation or the Fourier transform itself.

Table 14 The Lean files of this chapter Lean
File (namespace)Number of theoremsMain theorems and assumptionsPlace in the textNot included
DominantMatrixContraction (DominantMatrix)21dominant_mul, dominant_pow (the identity has norm 1), weighted_step, weighted_iter (Bw≤λwBw\le\lambda w), weight_change (av≤w≤bvav\le w\le bv, a>0a\gt0), liftWeight_step (B≥0B\ge0, w≥0w\ge0, s>0s\gt0, k≥1k\ge1, Bkw≤skwB^kw\le s^kw), norm_pow_le_const_mul, sum_norm_pow_le, affine_uniform (0≤λ<10\le\lambda\lt1, ε≥0\varepsilon\ge0), aggregate_step, two_by_two_weight, two_by_two_exists, signedEx_sq, absEx_pow§01The Collatz–Wielandt equality, Gelfand's formula itself, the existence of Perron vectors, Candidate 1.2′ (ℓ2\ell^2 weight), the max-plus bounds
SignLossBound (SignLoss)16jensen_four, schur_four (row ℓ1≤A\ell^1\le A, column ℓ1≤B\ell^1\le B), coherent_of_neg_le (negative ≤δ\le\delta positive), loss_le_of_coherent, comp_coherent, coherence_le_one, sum_four_le (∣va∣≤M|v_a|\le M), stein_form_le, stein_le_inv_sq_mul_test (κArM≤∣yr∣\kappa A_rM\le|y_r|), abs_comp_le, row_l1_comp_le§02The Stein formula itself (Plancherel and interpolation), the average of the plane-wave phase, Wielandt's theorem, convergence to rank one, the numbers of the loss
ConstrainedExtension (ConstrainedExtension)20exists_extension, isExtension_iff_mem_coset, finrank_freedom (finite-dimensional), freedom_eq_zero_iff (W≠0W\ne0), exists_extension_with_conditions ((resV,C)({\rm res}_V,C) surjective), finrank_freedom_with_conditions, eq_of_eqOn_iSup (the sum of the family of subspaces is the whole), comp_isExtension (f1(V1)⊆V2f_1(V_1)\subseteq V_2), comp_depends_of_not_le§03Lattices, continuity of symbols, the order of folding, moments, the lattice steps of Candidates 3.1–3.5
ConeCalculus (ConeCalculus)20Definitions IsCone, Contracts. cone_pullback (c≥0c\ge0), contracts_comp, contracts_iterate, cone_pullback_iterate (μ≥0\mu\ge0), block_decay (M≥0M\ge0, μ≥0\mu\ge0), row_rpow_le, lp_schur (p≥1p\ge1, row ℓ1≤R\ell^1\le R, column ℓ1≤C\ell^1\le C), lp_schur_sharp (row sums constant at R>0R\gt0, column sums constant at CC), delta_dilution, weighted_rpow_midpoint (w≥0w\ge0, a>0a\gt0), stein_form_midpoint, weighted_rpow_shift (0<a≤R0\lt a\le R, p0≤pp_0\le p), sup_shift, sup_midpoint, midpoint_below_one, affine_const (0≤μ<10\le\mu\lt1, ε≥0\varepsilon\ge0), affine_varying, affine_invariant, affine_eventually, affine_block§05The operator norm (the supremum of the true ℓp\ell^p norm) itself, the formula for the Stein bound (interpolation and Plancherel), Riesz–Thorin, convexity in continuous pp, Gelfand's formula, lattices and kernels, the numbers of the record
OneStepWindow (LatticeGauge.OneStepWindow)20holder_dual_ratio, norm_conj_rpow, exists_lpRatio_ge_row (the one-coordinate Hölder lower bound, p>1p\gt1), lamMax_mono, lamMax_smul (λmax⁡\lambda_{\max} is defined as the supremum of the Rayleigh quotient), steinWeighted_ge, stein_row_weight_saturation (the family of row weights saturates at u=Ap−2u=A^{p-2}), window_ordConnected, window_ordConnected_of_logConvex (convexity of log⁡μp\log\mu_p is assumed)§05Courant–Fischer, the number prow=5.874p_{\rm row}=5.874 and the interval (3.04,5.67)(3.04,5.67) (computed), the operator norm itself

What is not said

(a) We do not claim to have set up a new theory or new theorems. The candidate theorems of §01–§03 and §05 are all finite-dimensional forms of known facts, elementary consequences of them, or restatements in known frameworks (Perron–Frobenius, multigrid orders, sum rules, Riesz–Thorin interpolation, the Schur test). What this chapter adds is the correspondence that reads the numbers of the record as those quantities, and the questions that come out of it.

(b) What passed in Lean is only the 77 theorems of Table 14. Candidate 1.2′, the explicit formula for the transient constant, the phase factor, the lattice steps of Candidates 3.1–3.5, all of §04, the derivation of the Stein bound for general pp in §05, the convexity of the true log⁡μp\log\mu_p, and Candidate 5.5 are lines of argument on paper or estimates.

(c) The numbers are not estimates in the rigorous sense. The numbers in §02–§04 are floating-point computations, not interval estimates. The true ratio is a lower bound from maximisation and is not shown to be the maximum (for one step on 16416^4, two starting points stopped at 0.5767, short of the recorded 0.591).

(d) That the loss is bounded at every step is not shown. What is shown is only the numbers for k≤4k\le4 (444^4) and k≤3k\le3 (848^4), and the conditional inequality "if the alignment is bounded below, the loss is bounded". The 444^4 torus wraps the support of the kernel heavily, so "loss =⟨κ−2⟩=\langle\kappa^{-2}\rangle" there is a fact about the operator of that period.

(e) The tail rule of Candidate 3.4 is a line of argument assuming constants uniform in the steps. Uniformity over infinitely many steps is not treated. Whether compatibility of composition holds in the chain of the record has not been checked.

(f) The four-dimensional numbers of §04 are derived only from first-order leading terms and equipartition. The true four-dimensional series is not used. The overlaps with the band and the transition may include coincidence. MK is an approximate map, and whether the stopping level lines of U(1)U(1) are true fixed lines has not been distinguished. Candidate B is a restatement and does not claim to make the band easier.

(g) The results of this chapter have no direct effect on ① or ⑦. The table of correspondence with the record in §01 is a rereading of the record.

(h) Much of the literature was read at the level of abstracts and excerpts. For Hemker, Charina–Conti, Jia, Donatelli, Rump, Varga, Bertsekas–Tsitsiklis, arXiv:1005.1993, arXiv:0807.0185, Stein–Weiss, Hendrickx–Olshevsky and Boyd (power method), the details of the definitions in the original sources have not been checked.

(i) The windows and bundle numbers of §05 are windows of upper bounds. The window given by SpS_p contains [≈4,∞)[\approx4,\infty) for two steps and [3,4][3,4] for three steps, but the values of the ends of the window of the true μp\mu_p have not been obtained. The one-step range 3.5≤p≤53.5\le p\le5 is undecided, and the dependence of the two- and three-step numbers on truncation and on the size of the coarse torus has not been assessed. The behaviour of npn_p as p↓2p\downarrow2 is an estimate.

Remaining questions

Table 15 The questions of this chapter, F-SYS1–F-SYS16
No.QuestionSection
F-SYS1Can the lower bound κ0\kappa_0 of the row alignment in the worst direction be estimated on the limiting kernel of the steps, and the amount by which κ\kappa moves under perturbation of the steps be bounded row by row, so as to say loss ≤κ0−2\le\kappa_0^{-2} at every step?§02
F-SYS2If the part by which the maximiser of Stein moves away from period 2 on larger tori (upper bound 10.2 against a loss of 6.4) is measured by splitting into Stein restricted to period-2 points and the other qq, where does the difference come from?§02
F-SYS3If one quantity measuring the cancellation on the side of the true operator is fixed (for example, the ratio of ∥Tk∥\|T^k\| and ∥∣T∣k∥\||T|^k\| divided by its minimum over the sign-similarity class), what can the regularity of the loss growing only slowly over steps be said to come from?§01, §02
F-SYS4Aggregating the finite types and the remaining returns into a two-by-two matrix, does bc<(1−a)(1−d)bc\lt(1-a)(1-d) hold for the matrix of the record? If so, can it be raised to an interval estimate?§01
F-SYS5The record for the W coordinates measures in ℓ2\ell^2. Reread with Candidate 1.2′ (the weight of the Schur test), what does the one-step contraction constant become?§01
F-SYS6The upper limit of constrained sum rules: for any k≤ordV(F)k\le\mathrm{ord}^V(F), can a local representative with ord(K)≥k\mathrm{ord}(K)\ge k be taken with finite range? Is there a general form for cases where ordV\mathrm{ord}^V rises with other steps or other blockings?§03
F-SYS7A canonical choice of the freedom: does a representative minimising a Stein-type norm exist, is it unique, and is it local?§03
F-SYS8Compatibility of composition: does the output of the representative at step kk lie in the constraint subspace of step k+1k+1 (the image of Bianchi on the fine side)? If not, how much does the freedom outside im⁡D\operatorname{im}D affect the chain?§03
F-SYS9At what rate does the kernel of the Moore–Penrose representative decay (of type ∣Z∣−4|Z|^{-4}, from a discontinuous symbol homogeneous of degree 0)?§03
F-SYS10Why does the zero mode of the symmetric representative on finite tori appear to approach U/4U/4 faster than exponentially?§03
F-SYS11In a triple valuation with a third valuation (the exponent of the transseries) added, does the distinction stand that the band of U(1)U(1) is a tie between the weak-coupling and exponential valuations, while that of SU(2)SU(2) is a tie between the strong-coupling and weak-coupling valuations? What does the MK slope 13–14 for U(1)U(1) tend to?§04
F-SYS12If the error tie is found with the genuine four-dimensional series (higher strong-coupling terms and higher-loop weak-coupling coefficients), how does the lens overlap the band of 13-06?§04
F-SYS13In the space of the two couplings, fundamental and adjoint, (βF,βA)(\beta_F,\beta_A), does the codimension-one skeleton of the tie sets become a non-trivial polyhedral complex? How does it line up with the end point of the line of first-order transitions?§04
F-SYS14For the sequence of blocking maps, how does the lower end of the window Wn={p:μp(K(n))<1}W_n=\{p:\mu_p(K^{(n)})\lt1\} move with nn? Does the true μp(K0)\mu_p(K_0) fall below 1 for one step at 3.5≤p≤53.5\le p\le5 (decide whether W1W_1 is empty, either by tightening the upper bound by optimising the Stein weight uu beyond ApA^p, or by raising the lower bound with starting points that mix localised and spread-out fields or with the power method)? Answer (partial): if W1W_1 is non-empty, a single interval inside (3.04,5.67)(3.04,5.67). The family of row weights saturates at u=Ap−2u=A^{p-2}, and weighted Stein tightens no further (Lean: OneStepWindow). The one-step lower bound at p=4p=4 has risen to 0.6470, but the gap to 1 is undecided§05
F-SYS15How does the bundle number npn_p diverge as p↓2p\downarrow2? Is the limit of μp(K(n))1/n\mu_p(K^{(n)})^{1/n} determined by the dimension count 24−2p2^{4-2p} of the constant field, giving np≈c/(p−2)n_p\approx c/(p-2), or is the lower end pc>2p_c\gt2 of W∞W_\infty determined by the geometry of the lattice?§05
F-SYS16Does the gap between the Schur threshold exponent p∗p^* (about 66.5 for two steps) and the lower end of the Stein window (about 4 for two steps) come from the size of the column ℓ1\ell^1 or from the cancellation of signs? How far can p∗p^* be lowered by a weighted Schur test (positive test functions)?§05, §01

Sources

ItemKindSource
Perron–Frobenius, Collatz–Wielandt, comparison by domination ρ(A)≤ρ(∣A∣)≤ρ(B)\rho(A)\le\rho(|A|)\le\rho(B)CitedThe chapter on non-negative matrices in R. A. Horn, C. R. Johnson, Matrix Analysis (Reading)
Contraction in weighted maximum norms and iterative methods, M-matricesCited (Reading)R. S. Varga, Matrix Iterative Analysis. A. Berman, R. J. Plemmons, Nonnegative Matrices in the Mathematical Sciences. D. P. Bertsekas, J. N. Tsitsiklis, Parallel and Distributed Computation (1989)
Max-plus eigenvalues and boundsCitedS. Friedland (1986). F. Baccelli, G. Cohen, G. J. Olsder, J.-P. Quadrat (1992). P. Butkovič (2010). M. Akian, S. Gaubert, A. Marchesini, arXiv:1309.7319 (Reading)
Sign-real spectral radiusReadingS. M. Rump (1997)
Order of transfer operatorsReadingP. W. Hemker, On the order of prolongations and restrictions in multigrid procedures, J. Comput. Appl. Math. 32 (1990) 423–429. M. Donatelli, arXiv:0807.2565. U. Trottenberg, C. W. Oosterlee, A. Schüller, Multigrid (local Fourier analysis)
Sum rules, Strang–Fix conditions, order of approximationCited (Reading)G. Strang, G. Fix (1973). R.-Q. Jia, Math. Comp. 67 (1998). M. Charina, C. Conti, arXiv:1202.3931. I. Daubechies, Ten Lectures on Wavelets
Fisher zeros and the strong-coupling basin, crossoverReading (abstracts)A. Denbleyker, D. Du, Y. Liu, Y. Meurice, H. Zou, arXiv:1005.1993. arXiv:1112.2734. arXiv:0807.0185
Riesz–Thorin, Stein–Weiss, the Schur test, the difficulty of computing p→pp\to p norms, the LpL^p theory of subdivisionCited (Reading)M. Riesz (1927), G. O. Thorin (1939). E. M. Stein, G. Weiss, Trans. AMS 87 (1958). I. Schur (1911). J. M. Hendrickx, A. Olshevsky, SIAM J. Matrix Anal. Appl. (2010). D. W. Boyd, Linear Algebra Appl. 9 (1974). R.-Q. Jia, Adv. Comput. Math. (1995). S. Boyd, L. Vandenberghe, Convex Optimization §3.2.6
The numbers of §02–§05ComputedThe record of computations of this book's study (cross-check of the direct action of the rows of the composite kernel against the step-by-step action; two routes, quasi-Newton and period-2 fields; the single-plaquette series built in rational numbers; the SpS_p of §05 computed directly from the composite kernels)
The theorems of Table 14LeanThe Lean files DominantMatrixContraction, SignLossBound, ConstrainedExtension, ConeCalculus, OneStepWindow

Words used in this chapter — dominant matrix, weighted block norm, kk-step contraction, transient constant, one-step weight, the loss from discarding signs, row alignment, constrained map, extension, local representative, freedom, zero mode, moments, the order of folding ord\mathrm{ord} and ordV\mathrm{ord}^V, shifted jets, double valuation, complementary tie, same-coordinate tie, error tie, lens, κ=s1w1\kappa=s_1w_1, cone constant cpc_p, pp-contraction μp\mu_p, weighted Stein bound SpS_p, bundle number npn_p, window WnW_n, Schur threshold exponent p∗p^*.

Revised 2026-10-22: first version. 2026-10-22 (revision): added §05 The cone calculus with Tables 11 and 12, renumbered the tables of §06 as Tables 13–15, and added §05 rows to the five grades, the Lean, the questions (F-SYS14–F-SYS16), what is not said (i) and the sources.
2026-10-22 (second revision): added to §05 the location of the one-step window (inside (3.04,5.67)(3.04,5.67)) and the saturation of the family of weights, and revised the one-step lower bounds of Table 12, the current state of the answer to F-SYS14 and Table 14 (OneStepWindow).

← 15-09 What cannot be said, the index of questions, the dependency diagramContentsA-01 Table of notation →