slug: godsil-2023-average-mixing-trace-maximum bibkey: godsil2023diagonal doi: 10.48550/arXiv.1910.02039 url: https://arxiv.org/abs/1910.02039v1 triage: theorem motivation_gids:
- D5/S3/Quantum/Dynamics/AverageMixingTraceMaximum.result
The complete graph maximizes the trace of the average mixing matrix
Problem
Chris Godsil, Krystal Guo and Mariia Sobchuk, Diagonal entries of the average mixing matrix, arXiv:1910.02039v1, Section 9 (Conjecture 9.1 of Australas. J. Combin. 86(3) (2023) 373–386), write:
Based on the computations summarized in Table 2 and on Corollary 6.3, we also make the following conjecture. The complete graph on vertices attains the maximum trace with respect to the for all .
For a graph with adjacency matrix over its distinct eigenvalues, the orthogonal projection onto the -eigenspace, the average mixing matrix of the continuous quantum walk is (Schur product), and .
The precise question, preregistered in issue #11821, is whether for every and every connected graph on vertices. Over all graphs the statement is false: the empty graph has and trace . The paper’s Laplacian results on the maximum trace are stated for connected graphs, and A. Mohan, C. Tamon, Y. Xu and H. Zhan (arXiv:2608.20739, 2026) restate the conjecture over connected graphs.
Motivation
The diagonal entry is the long-run average
probability that the walk started at is found at , so the trace
measures how lazy the walk is. The frozen declaration
D5/S3/Quantum/Dynamics/AverageMixingTraceMaximum.result proves that
among connected graphs on vertices the complete graph is the laziest
for the adjacency Hamiltonian, the counterpart of the paper’s Laplacian
result.
Gap
Issue #11821 classifies the question as Tier 1 and records the bounded
literature check before any Lean: the four citing works listed by
Semantic Scholar (arXiv:2608.20739, 2404.02236, 2308.16378, 2211.02037)
were searched; arXiv:2608.20739 restates the conjecture as open and proves
Laplacian results only, and the others cite the paper generally. Web
searches for the average mixing matrix with trace, maximum and complete
graph, for the coauthor’s thesis, and for vertex bounds on graph angles
found no proof; google-deepmind/formal-conjectures has no entry.
These are orchestrator-reported literature readings,
not-found-in-searched-scope; they do not establish exhaustive worldwide
novelty or exclude an independent answer. The graph-angle literature
(Cvetković–Rowlinson–Simić, Eigenspaces of Graphs) was not read.
Route
- For a vertex with a neighbour and an eigenvalue , put and . Then , and , so the coordinates of off have squared norm .
- Cauchy–Schwarz on the eigen-equation at gives . At a neighbour of , is a combination over vertices other than , so .
- Eliminating gives , hence and .
- The numbers are nonnegative with sum and each is at most , so $(\widehat M_A){aa}=\sum\theta(E_\theta)_{aa}^2\le 1-2/n+2/n^2n\ge2$ has a neighbour, so ; for the trace is .
- For with , : an eigenvector with eigenvalue other than is constant with eigenvalue , and leaves exactly one such eigenbasis vector, so , and .
Falsifier
A connected graph on vertices whose average mixing matrix with respect
to the adjacency matrix has trace greater than would
falsify the conjecture; the kernel-checked result excludes it. Replacing
the adjacency matrix by another Hamiltonian, or dropping connectivity,
changes the question.
Evidence
The canonical source is
D5/S3/Quantum/Dynamics/AverageMixingTraceMaximum.lean; the only public
theorem is result : claim. The public definitions are the spectral
idempotent idempotent, the average mixing matrix avgMixing and
claim.
- Module statement identity:
sha256:e9ed4aafa0539ad392a8da26418ae5af60eaf51671d3d661f56e05577edd7ac5. result:sha256:543de5ce995d1f90520172a150daffb22fe40d8024fbab20b31098cb15fd7dd0.claim:sha256:6886baf6f8f18b6815d1b15135636c68dd967e4517343a3140921b3dd9f47e86.avgMixing:sha256:7611a60f0f8b9b05283e0dfe4e1ecda2ba69c0aa90a6b731bbba19c013596049.idempotent:sha256:64ed2f0892f8f978123e3bf15ad51c0d5ff7dc5b38413a148671ba2d3f512d5a.- Freeze event:
sha256:4219620e5a540f5ea48ae5ee766904b8e95a474f3e74c4ec82c1208c48408599.
The proof uses only propext, Classical.choice and Quot.sound, with
no native_decide, sorry or new axiom. Inside result, the local fact
vertex_bound proves steps 1–3 for any vector with and
; the local fact simplex_bound proves step 4; the local fact
complete_diag proves step 5.
Triage
Tier 1 published conjecture; resolution Proved by
D5/S3/Quantum/Dynamics/AverageMixingTraceMaximum.result.
proof_shape: content; admission_basis: open-problem-resolution
(issue #11821). Utility none: the result is a theorem over every .
What the settlement shows
- Proved inside
result, as local facts:vertex_boundgives at every vertex with a neighbour, for every simple graph on vertices, andsimplex_boundturns it into ; neither assumes connectivity, whichresultuses only to give every vertex a neighbour. - Follows from those local facts, not stated as a declaration: the trace bound holds for every graph on vertices without isolated vertices. Isolated vertices are exactly where the literal all-graphs reading fails, each contributing to the trace.
- Proved in this module: the per-vertex bound is attained at every vertex of , where and .
- Computed, not formalized: over every graph of the NetworkX atlas with at most vertices, the maximum of the vertex bound equals and the maximum trace over connected graphs is attained only by (issue #11821).
- Open: uniqueness of the maximizer. Equality in the trace bound forces equality in step 3 at every vertex, hence every vertex adjacent to all others; this equality analysis is not formalized here. The paper’s companion questions on the minimum trace and on graphs with constant diagonal remain open here.
- Open follow-up: whether the second laziest connected graph is the star , which arXiv:2608.20739 raises from data on at most 9 vertices. No additional theorem is included in this settlement.
ASSUMED-UNVERIFIED
The bounded literature check does not establish worldwide priority or
absence of an independent solution; in particular the vertex bound may be
known in the graph-angle literature, which was not read. The Lean kernel
verifies the encoded statement and its axiom closure; correspondence to
the external paper is checked by reading the source, the definitions and
the mirror. The independence of idempotent from the chosen orthonormal
eigenbasis is a standard fact stated in its docstring and not formalized
in this module.