From 98b393700c6efd486eaf4d7a9120a80688dea709 Mon Sep 17 00:00:00 2001 From: "did:key:z6MkmBZkXGPJpw81cNsuCoq2wJ3zYGQ2addNU7qWgdKGGtEs" Date: Fri, 12 Jun 2026 20:11:36 +0000 Subject: [PATCH] Level 10 Math Upgrade v2: Peer Review Corrections --- .../armada_3_jmp/paper_1c_math_JMP.tex | 10 +++++++--- 1 file changed, 7 insertions(+), 3 deletions(-) diff --git a/papers/project_paper_1_relativity/armada_3_jmp/paper_1c_math_JMP.tex b/papers/project_paper_1_relativity/armada_3_jmp/paper_1c_math_JMP.tex index 3a7018f3..738b862f 100644 --- a/papers/project_paper_1_relativity/armada_3_jmp/paper_1c_math_JMP.tex +++ b/papers/project_paper_1_relativity/armada_3_jmp/paper_1c_math_JMP.tex @@ -55,6 +55,10 @@ The poset possesses an emergent \emph{topological dimension} $d$ if the cardinal \end{definition} This definition naturally mirrors the volumetric boundary growth of a $d$-dimensional continuous space, where the cross-sectional area at radial time $t$ scales as $t^{d-1}$. +\begin{definition}[Spatial Homogeneity Condition] +A graded poset satisfies the \emph{spatial homogeneity condition} if, for any origin vertex $v_0$, the forward causal future $J^+(v_0) \cap L_t$ asymptotically covers the entire layer $L_t$ as $t \to \infty$, such that a random walk rapidly mixes and the transition probabilities uniformly distribute across the layer volume. +\end{definition} + \begin{definition}[Distinguished Maximal Chain] A \emph{distinguished maximal chain} $\gamma$ is a sequence of vertices $\gamma = \{v_0, v_1, v_2, \dots\}$ such that $v_t \in L_t$ and $(v_t, v_{t+1}) \in E$ for all $t \ge 0$. This chain represents a localized, persistent geometric observer or structural reference trajectory. \end{definition} @@ -69,7 +73,7 @@ The forward difference operator $\nabla^+: \mathcal{H}_V \to \mathcal{H}_E$ and \end{align} \begin{definition}[Discrete d'Alembertian] -The discrete d'Alembertian operator $\square_{\mathcal{P}}: \mathcal{H}_V \to \mathcal{H}_V$ is given by the weighted composition: +The discrete d'Alembertian operator $\square_{\mathcal{P}}: \mathcal{H}_V \to \mathcal{H}_V$ is constructed from the directed divergence of the gradient ($\propto \nabla^- \nabla^+$) and is given by the weighted composition: \begin{equation} \square_{\mathcal{P}} f(v) = \frac{1}{\deg_{\mathrm{out}}(v)} \sum_{w: (v,w)\in E} f(w) - f(v). \end{equation} @@ -114,8 +118,8 @@ The expected number of intersections $\mathbb{E}[I]$ over the infinite walk is g \end{equation} This sum converges or diverges as a standard $p$-series with $p = d - 1$: \begin{enumerate} - \item If $d \ge 3$, then $p \ge 2 > 1$. The expected number of intersections is finite, $\sum G_R < \infty$. By the first Borel-Cantelli lemma, the probability that infinitely many events $E_t$ occur is strictly zero. The walk is transient. - \item If $d \le 2$, then $p \le 1$. The sum diverges, $\sum G_R = \infty$. Assuming Markovian mixing ensures the events $E_t$ at disparate times are sufficiently independent, the extended Borel-Cantelli lemma forces the probability of infinite intersections to one. The walk is chain-recurrent. + \item If $d \ge 3$, then $p \ge 2 > 1$. The expected number of intersections is finite, $\sum G_R < \infty$. By the first Borel-Cantelli lemma, the probability that infinitely many events $E_t$ occur is strictly zero. The walk is strictly transient. + \item If $d \le 2$, then $p \le 1$. The expected number of visits diverges, $\sum G_R = \infty$. According to standard Markov chain potential theory~\cite{Woess2000}, a state (or distinguished chain) is recurrent if and only if the sum of the transition probabilities (the Green's function trace) diverges. Therefore, the walk is chain-recurrent with probability one. \end{enumerate} Therefore, stable chain-recurrence is strictly bounded to $d \le 2$. \end{proof}