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Claimed extension to nonnegative weighted graphs
PDF p. 10: Section 2 opening paragraph
Statement
The article states that “all results in the paper can be extended to graphs with weighted edges, provided that all the weights are non-negative” (Section 2, PDF p. 10). Retain this as an attributed extension assertion, with network terminology from Finite symmetric networks and loop removal. Its energy and rotating-frame differential expressions extend to every finite symmetric nonnegative matrix, including arbitrary loops. Common positive rescaling of weights and the reference degree preserves the normalized centered spectral inequalities. However, an unchanged unit-loop degree bound is not valid for arbitrary loop weights: the correct general envelope contains the actual maximal loop weight. The five local results Loop removal in the weighted Kuramoto calculus, Covariance under a common positive rescaling of weights, Weighted spectral bounds control the degree without loops, Loop-dependent weighted degree envelope and A complete weighted network distinguishes a loop cap from spectral control establish these precise assertions. They do not specify or prove every weighted probabilistic or construction analogue covered by the article's informal sentence.
Facts & Assumptions
Networks allow arbitrary nonnegative loop weights and count a loop once in a row degree (Finite symmetric networks and loop removal).
Loop removal preserves the weighted energy, its derivatives, the rotating-frame vector field and the Laplacian (Loop removal in the weighted Kuramoto calculus).
Common positive rescaling preserves dimensionless spectral bounds (Covariance under a common positive rescaling of weights).
The pointwise degree without loops is bounded directly by the centered Laplacian (Weighted spectral bounds control the degree without loops); restoring loops gives the loop-dependent row-degree envelope (Loop-dependent weighted degree envelope).
The explicit two-vertex network has both centered matrices zero but violates the fixed unit-cap upper degree expression (A complete weighted network distinguishes a loop cap from spectral control).
Proof
Given: The data in the Statement.
Goal: Establish the stated conclusions.
Apply [F2] to the nonnegative weighted network in [F1]. This gives exactly the weighted gradient and Hessian formulas and diagonal cancellation, without a cap on loop weights. Apply [F3] to obtain the stated common-rescaling convention for the centered inequalities. These are precise deterministic weighted transfers.
By [F4], the weighted degree statement is obtained by keeping the actual diagonal entry, or its maximum, in the upper envelope. By [F5], replacing that maximum by need not be sound even when both centered spectral residuals vanish and the spectral parameters have strict positive and negative slack. Thus a weighted extension must adapt that formula or cap the loops; the example gives no failure of synchronization and does not decide unspecified weighted analogues. This establishes the local claims while preserving the broader sentence as article attribution.
Source notes
The quoted extension sentence occurs in the opening of Section 2, PDF p. 10. Under the original binary convention in Section 1.2, Lemma 3.1 on PDF p. 18 is valid: its proof explicitly uses . Footnote 7 states that self-loops do not affect Kuramoto dynamics. The local example is therefore a counterexample only to retaining that displayed degree conclusion unchanged after allowing arbitrary nonnegative loop weights. It does not refute the original binary lemma, the existence of suitably modified weighted extensions, or any synchronization conclusion. The corrected envelope supplies such a weighted extension for this lemma. The full scope of unspecified weighted random-graph models and construction results remains outside the established local assertions; no universal proof is claimed.
Depends on
- Finite symmetric networks and loop removal
- Loop removal in the weighted Kuramoto calculus
- Covariance under a common positive rescaling of weights
- Weighted spectral bounds control the degree without loops
- Loop-dependent weighted degree envelope
- A complete weighted network distinguishes a loop cap from spectral control
Dependency tree · 2 levels
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Sources
- Expander graphs are globally synchronizing · PDF p. 10, Section 2 opening paragraph; PDF pp. 6–8, Definitions 1.3 and 1.9 and notation; PDF p. 18, Lemma 3.1 and footnote 7