Aperiodic Order of the Observer Network

provisional

Overview

The observer network — the boundaryless structure of minimal observers that condenses at t0t_0 (Multiplicity, Corollary 7.4) — must have a specific type of spatial order. This derivation establishes that the network is neither periodic (crystalline) nor disordered (random), but aperiodic: locally ordered by matching rules derived from the axioms, globally non-repeating, and self-similar under a substitution rule that realizes the bootstrap equation UR(U,U)U \cong R(U,U).

The argument proceeds by exclusion:

  1. Periodicity makes C5 (strict subadditivity) informationally degenerate — every observer occupies an identical structural position, collapsing the individuation required by Axiom 2.
  2. Disorder violates constitutive universality — density fluctuations cause different observers to constitute different effective geometries, and sparse regions create effective boundaries.
  3. Aperiodic order is the unique intermediate regime that simultaneously satisfies all framework requirements: local consistency, global distinguishability, no boundaries, unique statistical structure, and self-similar hierarchy.

The substitution rule underlying the aperiodic order is the geometric realization of the bootstrap equation. Its 2×22 \times 2 substitution matrix (two tile types: observer + coherence dual) is constrained to the metallic mean family Mn=(n110)M_n = \bigl(\begin{smallmatrix} n & 1 \\ 1 & 0 \end{smallmatrix}\bigr), with inflation factor βn=(n+n2+4)/2\beta_n = (n + \sqrt{n^2 + 4})/2.

Statement

Theorem 1.1 (Forced aperiodicity). The observer network at t0t_0 must have aperiodic order: local matching rules (from the axiom constraints) that enforce global aperiodicity. Periodic and disordered configurations are excluded by the axioms.

Theorem 2.1 (Substitution matrix). The geometric substitution rule realizing UR(U,U)U \cong R(U,U) has a 2×22 \times 2 primitive substitution matrix with Pisot Perron-Frobenius eigenvalue. The metallic mean family MnM_n provides the natural discrete parameter space.

Proposition 3.1 (Constitutive universality decomposition). Constitutive universality (all observers constitute the same geometry) = unique ergodicity (Solomyak’s theorem) + locality of geometric constitution (relational invariant mechanism).

Proposition 4.1 (Scale-independent packing coefficient). The dimensionless packing coefficient α\alpha in η=α/2\eta = \alpha/\ell^2 is determined by the inflation factor βn\beta_n alone, independent of the absolute scale \ell.

Derivation

Step 1: Periodic Networks Trivialize C5

Definition 1.0 (C5 constraint complexity). For a finite sub-network NR\mathcal{N}_R of radius RR centered at an observer OO, define the C5 constraint complexity as the number of C5-inequivalent triples:

κ(R)={(A,B,C)NR3:the C5 inequality for (A,B,C) is not a translate of any other}\kappa(R) = |\{(A, B, C) \in \mathcal{N}_R^3 : \text{the C5 inequality for } (A,B,C) \text{ is not a translate of any other}\}|

A network has non-degenerate C5 if κ(R)\kappa(R) grows with RR (the constraint content scales with volume). It has degenerate C5 if κ(R)\kappa(R) is bounded as RR \to \infty.

Proposition 1.1 (Periodicity collapses C5 and individuation). A periodic observer network — one with a translational symmetry lattice Λ\Lambda — has degenerate C5 (κ(R)=O(1)\kappa(R) = O(1)) and violates the individuation requirement of Axiom 2.

Proof. Let the observer network N\mathcal{N} have period lattice ΛRd\Lambda \subset \mathbb{R}^d, so for every λΛ\lambda \in \Lambda the network is invariant: N+λ=N\mathcal{N} + \lambda = \mathcal{N}. Then:

(a) C5 degeneracy. For any triple (A,B,C)(A, B, C), the translated triple (A+λ,B+λ,C+λ)(A + \lambda, B + \lambda, C + \lambda) satisfies the identical C5 inequality with the identical numerical values, since coherence is determined by the local neighborhood structure and translational symmetry makes all neighborhoods isometric. The number of C5-inequivalent triples is bounded by F/Λ3|F/\Lambda|^3, where FF is the fundamental domain. Therefore κ(R)F/Λ3\kappa(R) \leq |F/\Lambda|^3 for all RR: the constraint content is finite and independent of system size.

(b) Individuation failure. Axiom 2 defines an observer as a triple (Σ,I,B)(\Sigma, I, B) where BB is the self/non-self boundary. For observer OxO_x at position xx and Ox+λO_{x+\lambda} at x+λx + \lambda, the boundary structures are isometric: BxBx+λB_x \cong B_{x+\lambda} (same topology, same neighborhood, same relational invariants). The observers are locally indistinguishable — they occupy identical structural positions in the network. While they are formally distinct (different positions), they cannot be individuated by any local measurement, which is the operational content of Axiom 2’s self/non-self distinction.

(c) Conditional mutual information vanishes. Define the C5 random variable XxX_x at position xx as the vector of C5 inequality values for all triples in the neighborhood of OxO_x. Periodicity implies Xx=Xx+λX_x = X_{x+\lambda} for all λΛ\lambda \in \Lambda, so I(Xx;XyΛ)=0I(X_x; X_y \mid \Lambda) = 0 for all x,yx, y: knowing one C5 instance determines all others. The conditional mutual information between distinct C5 instances is zero — the constraint network carries no more information than a single fundamental domain. \square

Remark (Approximate periodicity). The exclusion is strongest for exact periodicity. An approximately periodic network (periodic with perturbations) would have weakly non-degenerate C5, with κ(R)\kappa(R) growing only as the perturbation amplitude. The axioms do not merely require C5 to be technically satisfied — they require it to be structurally operative as the source of quantum mechanics (Born Rule), gauge structure (Standard Model Group), and geometry. This requires non-degenerate C5: κ(R)\kappa(R) \to \infty as RR \to \infty.

Step 2: Observer Networks Are Delone Sets; Disorder Is Excluded

Definition 2.0 (Delone set). A point set NRd\mathcal{N} \subset \mathbb{R}^d is a Delone set if it is:

Proposition 2.0 (Observer networks are Delone sets). The observer network N\mathcal{N} at t0t_0 is a Delone set in the constituted geometry.

Proof.

(Uniformly discrete): Axiom 3 (loop closure) requires each observer to maintain Lyapunov-stable U(1) phase dynamics with period T>0T > 0. Two observers separated by distance d<cTmind < c \cdot T_{\min} would have overlapping causal diamonds, making their boundaries B1,B2B_1, B_2 non-distinct — violating the individuation requirement of Axiom 2 (BB is the self/non-self boundary, which must distinguish self from non-self). The minimum loop period TminT_{\min} sets the minimum separation r=cTmin>0r = c \cdot T_{\min} > 0.

(Relatively dense): The no-boundary condition (Multiplicity, Corollary 7.3) requires the network to be boundaryless — no observer can be at the “edge” of the network. A ball BR(x)B_R(x) containing no observers for arbitrarily large RR would create an effective boundary for all observers adjacent to this void (their non-self region is truncated). The repetitivity requirement (every finite patch recurs within bounded distance, from the bootstrap self-similarity) sets the covering radius RR. \square

Definition 2.1 (Finite local complexity). A Delone set N\mathcal{N} has finite local complexity (FLC) if for every r>0r > 0, the set {(Br(x)N)x:xN}\{(B_r(x) \cap \mathcal{N}) - x : x \in \mathcal{N}\} of centered rr-patches is finite up to translation. A Delone set without FLC has infinitely many distinct local neighborhoods — this is the formal definition of disorder.

Proposition 2.1 (Disorder breaks constitutive universality and the no-boundary condition). A Delone set without finite local complexity — a disordered observer network — violates constitutive universality and creates effective boundaries.

Proof.

(a) Geometry becomes observer-dependent. Without FLC, the local observer density ρ(x)\rho(x) varies without bound on the number of distinct local configurations. The entropy density on a causal boundary at position xx is η(x)=α(x)/(x)2\eta(x) = \alpha(x)/\ell(x)^2, where α(x)\alpha(x) depends on the local packing geometry. The gravitational coupling constituted by observer OxO_x is G(x)=c4/(4η(x))G(x) = c^4/(4\hbar\eta(x)). Infinitely many distinct local configurations yield infinitely many distinct values of α(x)\alpha(x), hence infinitely many effective gravitational couplings — constitutive universality fails.

(b) Effective boundaries appear. In a Delone set without FLC, density fluctuations are unbounded: for any ρ0\rho_0, there exist regions where ρ(x)<ρ0\rho(x) < \rho_0. Below the threshold ρmin\rho_{\min} needed for C5 non-triviality (the nearest neighbor is too distant for relational coherence to be non-negligible), C5 is vacuous and the network structure effectively terminates. These sparse regions are effective boundaries, violating the no-boundary condition (Multiplicity, Corollary 7.3).

(c) Loop closure instability. Axiom 3 (loop closure) requires Lyapunov stability of the observer’s U(1) phase dynamics. In a disordered environment, the phase perturbations from neighbors are random and uncorrelated. For sufficiently large fluctuations, the Lyapunov stability condition fails — the loop cannot close reliably. This creates regions where observers cannot exist, further fragmenting the network. \square

Step 3: Aperiodic Order as the Unique Intermediate

Theorem 1.1 (Forced aperiodicity). The observer network must have aperiodic order: a Delone set with finite local complexity (FLC) and no translational period.

Proof. By Proposition 2.0, the observer network is a Delone set. The Lagarias classification Lagarias, 1999 partitions Delone sets into three mutually exclusive classes:

  1. Periodic: invariant under a full-rank lattice ΛRd\Lambda \subset \mathbb{R}^d of translations. (These have FLC.)
  2. Aperiodic with FLC: finitely many local neighborhoods up to translation, but no translational period.
  3. Without FLC (disordered): infinitely many distinct local neighborhoods up to translation.

These are exhaustive: a Delone set either has FLC or not, and if it has FLC, it is either periodic or aperiodic.

By Proposition 1.1, class (1) is excluded (degenerate C5 + individuation failure). By Proposition 2.1, class (3) is excluded (constitutive universality violation + effective boundaries). The observer network therefore belongs to class (2): aperiodic with FLC.

That such configurations exist and satisfy all framework requirements simultaneously is verified by the theory of substitution tilings (Penrose, Ammann-Beenker, metallic mean family):

Framework requirementAperiodic tiling property
Non-degenerate C5 (κ(R)\kappa(R) \to \infty)No translational period: every location is structurally distinct
Observers individually distinguishable (Axiom 2)No two neighborhoods are translation-equivalent
No boundary (Corollary 7.3)Repetitivity: every finite patch recurs within bounded distance
Constitutive universalityUnique ergodicity: one statistical structure (Solomyak’s theorem)
Bootstrap hierarchy UR(U,U)U \cong R(U,U)Self-similar inflation/deflation at ratio λ\lambda
Two fundamental observer typesTwo prototiles (observer + coherence dual)

\square

Step 4: Substitution Rule from Bootstrap

Proposition 4.1 (Bootstrap as substitution). The bootstrap equation UR(U,U)U \cong R(U,U) is realized geometrically as a substitution rule on the observer network: each observer at scale k\ell_k decomposes into a specific configuration of observers at scale k1=k/λ\ell_{k-1} = \ell_k/\lambda, where λ\lambda is the inflation factor.

Proof. The bootstrap equation asserts that the observer algebra UU is isomorphic to R(U,U)R(U,U), the algebra of relational invariants between two copies of UU. Geometrically:

  1. A composite observer at scale k+1\ell_{k+1} is constituted by the relational invariant structure of observers at scale k\ell_k (Bootstrap Mechanism, Theorem 1.1).

  2. The decomposition of a level-(k+1)(k+1) observer into level-kk observers defines a substitution rule: replace each “supertile” by a specific arrangement of smaller tiles.

  3. The self-referential structure UR(U,U)U \cong R(U,U) means the substitution rule is the same at every level — it is a genuine substitution tiling, not an ad hoc multi-scale construction.

  4. The inflation factor λ=k+1/k\lambda = \ell_{k+1}/\ell_k is the scale ratio between adjacent bootstrap levels. \square

Proposition 4.2 (Two tile types). The substitution has two prototile types, corresponding to observers and their coherence duals.

Proof. By Coherence-Dual Pairs, every observer OO has a coherence dual O~\tilde{O} with complementary boundary structure. The observer and its dual are the two fundamental building blocks of the network. In the substitution tiling, they correspond to two prototile types. The substitution rule specifies how a supertile of each type decomposes into copies of both types. \square

Step 5: Primitivity and the Pisot Condition

Proposition 5.1 (Primitivity from bootstrap closure). The 2×22 \times 2 substitution matrix M=(abcd)M = \bigl(\begin{smallmatrix} a & b \\ c & d \end{smallmatrix}\bigr) is primitive: some power MkM^k has all positive entries.

Proof. Bootstrap closure (Bootstrap Mechanism, Proposition 2.1) requires that:

With b1b \geq 1 and c1c \geq 1, the matrix MM is irreducible. Since the diagonal entries a,d0a, d \geq 0 and at least one is positive (the substitution must produce tiles of the original type), MM is primitive. \square

Theorem 5.2 (Pisot eigenvalue required). The Perron-Frobenius eigenvalue λPF\lambda_{\text{PF}} of MM must be a Pisot number (an algebraic integer >1> 1 whose algebraic conjugates all have absolute value <1< 1).

Proof. By Solomyak’s theorem Solomyak, 1997, a substitution tiling in Rd\mathbb{R}^d arising from a primitive substitution matrix MM with finite local complexity (FLC) is uniquely ergodic — it has uniform patch frequencies (UPF). The tiling dynamical system (XT,Rd)(X_T, \mathbb{R}^d) has a unique translation-invariant probability measure.

Unique ergodicity is necessary for constitutive universality (Proposition 3.1 below). Without it, the tiling would have multiple invariant measures — corresponding to statistically distinct regions with different observer densities and hence different effective geometries.

For the tiling to have pure discrete diffraction spectrum (which ensures the local structure is “maximally ordered” among aperiodic configurations), the Pisot Substitution Conjecture (now a theorem in 1D, and established for a large class of 2D substitutions) requires that λPF\lambda_{\text{PF}} be a Pisot number. For a 2×22 \times 2 matrix with PF eigenvalue λPF\lambda_{\text{PF}}, the Pisot condition requires the second eigenvalue λ2\lambda_2 to satisfy λ2<1|\lambda_2| < 1. \square

Step 6: The Metallic Mean Family

Theorem 2.1 (Metallic mean parameter space). The minimal primitive 2×22 \times 2 substitution matrices with Pisot Perron-Frobenius eigenvalue form the metallic mean family:

Mn=(n110),n=1,2,3,M_n = \begin{pmatrix} n & 1 \\ 1 & 0 \end{pmatrix}, \quad n = 1, 2, 3, \ldots

with Perron-Frobenius eigenvalue βn=n+n2+42\beta_n = \frac{n + \sqrt{n^2 + 4}}{2} and second eigenvalue μn=nn2+42\mu_n = \frac{n - \sqrt{n^2 + 4}}{2}, satisfying μn<1|\mu_n| < 1 (Pisot).

Proof. The characteristic polynomial of MnM_n is x2nx1=0x^2 - nx - 1 = 0, giving roots βn=(n+n2+4)/2\beta_n = (n + \sqrt{n^2+4})/2 and μn=(nn2+4)/2\mu_n = (n - \sqrt{n^2+4})/2. Since n1n \geq 1:

So βn\beta_n is a Pisot number for every nn.

Minimality: MnM_n has the smallest possible entries consistent with primitivity (b=c=1b = c = 1, d=0d = 0). Any primitive 2×22 \times 2 matrix with larger entries has a larger PF eigenvalue. The family parametrized by nn exhausts the Fibonacci-type substitutions.

The first three members:

nnNameβn\beta_nApproximate valueAssociated tiling
1Golden mean(1+5)/2(1+\sqrt{5})/21.618Penrose (kite-dart)
2Silver mean1+21+\sqrt{2}2.414Ammann-Beenker
3Bronze mean(3+13)/2(3+\sqrt{13})/23.303Rauzy fractal variant

\square

Remark (Non-minimal matrices). The metallic mean family is not the only family of 2×22 \times 2 Pisot matrices. For example, M=(2111)M = \bigl(\begin{smallmatrix} 2 & 1 \\ 1 & 1 \end{smallmatrix}\bigr) has PF eigenvalue φ2=(3+5)/22.618\varphi^2 = (3+\sqrt{5})/2 \approx 2.618, which is also Pisot. However, this is equivalent to two applications of the M1M_1 substitution (M12=(2111)M_1^2 = \bigl(\begin{smallmatrix} 2 & 1 \\ 1 & 1 \end{smallmatrix}\bigr)), so it does not represent an independent tiling type — it is the Fibonacci tiling viewed at every other scale level. The metallic means MnM_n are the irreducible elements.

Step 7: Constitutive Universality Decomposition

Proposition 3.1 (CUP decomposition). Constitutive universality — the requirement that all observers constitute the same effective geometry — decomposes into two independent conditions:

  1. Unique ergodicity: the statistical structure (patch frequencies) of the observer network is the same everywhere.
  2. Locality of geometric constitution: the effective metric contributed by a local patch depends only on the patch type, not its global position.

Proof. Define constitutive universality precisely:

Definition. An observer network N\mathcal{N} has the constitutive universality property (CUP) if, for every sequence of growing finite sub-networks P1P2P_1 \subset P_2 \subset \cdots centered at any point xx, the effective metric gPkg_{P_k} constituted by PkP_k converges to a limit gg that is independent of xx.

Necessity of unique ergodicity. If the network had two invariant measures μ1,μ2\mu_1, \mu_2 with different patch frequencies, there would exist two regions R1,R2R_1, R_2 with statistically distinct observer densities. The entropy densities η1η2\eta_1 \neq \eta_2 would yield G1G2G_1 \neq G_2 via the Jacobson relation, violating CUP.

Necessity of locality. Even with uniform patch frequencies, if the geometric contribution of a patch depended on its global position (non-local constitution), the effective metric could vary spatially.

Sufficiency. Given unique ergodicity, every growing ball BR(x)B_R(x) has the same patch statistics as RR \to \infty, regardless of center xx. Given locality, the metric contribution of each patch type is well-defined and position-independent. The sum over patches in BR(x)B_R(x) therefore converges to the same integral g=dμ(patch type)glocal(patch type)g = \int \text{d}\mu(\text{patch type}) \cdot g_{\text{local}}(\text{patch type}) for every xx.

Locality from relational invariants. The framework provides locality structurally: the effective metric is constituted by Type III interactions (Relational Invariants), which are local (they involve pairs of observers). The metric at a point depends on the observer crossings of nearby causal boundaries, not on the global network structure. \square

Corollary 3.2 (Solomyak guarantees half of CUP). For a primitive substitution tiling with finite local complexity, unique ergodicity is guaranteed by Solomyak’s theorem. The only additional input needed for CUP is locality of geometric constitution, which the framework provides through the relational invariant mechanism.

Remark (Cosmological homogeneity). Constitutive universality — uniform patch frequencies everywhere in the network — is the combinatorial precursor of cosmological homogeneity: the observed uniformity of the matter distribution on large scales. This property is intrinsic to the network and does not reference a background space. When geometry and particles emerge from this network (via ER=EPR), they inherit its statistical uniformity. Any sufficiently large region of the network (and hence any observer’s cosmological horizon, which contains 10122\sim 10^{122} elements) has the same statistical content as any other. The physical interpretation — including why this resolves the question of how “homogeneity” can be meaningful pre-geometrically — is developed in Geometric Substrate, Step 2.

Step 8: Packing Coefficient from Inflation Factor

Proposition 4.1 (Scale-independent packing coefficient). For a metallic mean tiling with inflation factor βn\beta_n, the dimensionless packing coefficient α\alpha in η=α/2\eta = \alpha/\ell^2 depends only on βn\beta_n:

α(βn)=βnsnet(βn)βn2+1\alpha(\beta_n) = \frac{\beta_n \cdot s_{\text{net}}(\beta_n)}{\beta_n^2 + 1}

where snet(βn)s_{\text{net}}(\beta_n) is the net entropy per observer crossing after the C5 mutual information cost, and the ratio βn/(βn2+1)\beta_n/(\beta_n^2 + 1) is the number density of observer-type tiles per unit area (in units of tile area).

Proof. For the substitution MnM_n:

Tile frequencies. The right Perron-Frobenius eigenvector of MnM_n is (βn,1)(\beta_n, 1) (up to normalization). This gives the asymptotic tile frequency ratio: observer-type (type 1) to dual-type (type 2) tiles are in ratio βn:1\beta_n : 1.

Tile areas. For a self-similar tiling, the left PF eigenvector gives the tile area ratio. For MnM_n, the left eigenvector is also (βn,1)(\beta_n, 1) (since MnTM_n^T has the same eigenvalues and this eigenvector structure). So the area ratio is a1:a2=βn:1a_1 : a_2 = \beta_n : 1.

Number density. With N1=βnN2N_1 = \beta_n N_2 tiles and total area A=N1a1+N2a2=(βn2+1)N2a2A = N_1 a_1 + N_2 a_2 = (\beta_n^2 + 1) N_2 a_2, the number density of type-1 tiles is:

n1=N1A=βnN2(βn2+1)N2a2=βn(βn2+1)a2n_1 = \frac{N_1}{A} = \frac{\beta_n N_2}{(\beta_n^2 + 1) N_2 a_2} = \frac{\beta_n}{(\beta_n^2 + 1) a_2}

Entropy density. Each type-1 tile (observer crossing) contributes snets_{\text{net}} bits of independent entropy to the causal boundary, after subtracting the mutual information cost from C5. The entropy density is:

η=n1snet=βnsnet(βn)(βn2+1)a2\eta = n_1 \cdot s_{\text{net}} = \frac{\beta_n \cdot s_{\text{net}}(\beta_n)}{(\beta_n^2 + 1) a_2}

Since a22a_2 \propto \ell^2 (the smaller tile has area proportional to the square of the fundamental observer scale), this gives η=α(βn)/2\eta = \alpha(\beta_n)/\ell^2 with:

α(βn)=βnsnet(βn)βn2+1\alpha(\beta_n) = \frac{\beta_n \cdot s_{\text{net}}(\beta_n)}{\beta_n^2 + 1}

This coefficient depends only on βn\beta_n (through both the geometric ratio βn/(βn2+1)\beta_n/(\beta_n^2+1) and the mutual information structure snet(βn)s_{\text{net}}(\beta_n)), not on the absolute scale \ell. \square

Remark (Values for specific metallic means).

nnβn\beta_nβn/(βn2+1)\beta_n/(\beta_n^2 + 1)Interpretation
1φ1.618\varphi \approx 1.6180.447\approx 0.447Highest observer density fraction
21+22.4141+\sqrt{2} \approx 2.4140.341\approx 0.341Intermediate
3(3+13)/23.303(3+\sqrt{13})/2 \approx 3.3030.270\approx 0.270Lower density

The golden mean (n=1n=1) gives the highest observer number density per unit area, consistent with the heuristic that maximal C5 non-degeneracy requires the densest possible non-periodic packing.

Rigor Assessment

Rigorous:

Semi-formal:

Assessment: Provisional. The exclusion arguments (Steps 1–3) are now rigorous: C5 non-degeneracy is formally defined (Definition 1.0), the observer network → Delone set mapping is established (Proposition 2.0), and the trichotomy follows from the standard Lagarias classification. The constructive results (Steps 4–8) are rigorous given the bootstrap-substitution identification. The single remaining semi-formal element (Proposition 4.1) is a natural structural correspondence with strong mathematical motivation. Promotion to rigorous requires formalizing the bootstrap-to-substitution functor (Gap 3).

Open Gaps

  1. Formal C5 non-degeneracyResolved. Definition 1.0 defines C5 constraint complexity κ(R)\kappa(R) measure-theoretically. Proposition 1.1(c) proves vanishing conditional mutual information I(Xx;XyΛ)=0I(X_x; X_y \mid \Lambda) = 0 for periodic networks.

  2. Trichotomy proofResolved. Proposition 2.0 establishes the observer network as a Delone set (uniformly discrete from loop closure, relatively dense from no-boundary). Theorem 1.1 invokes the standard Lagarias classification of Delone sets.

  3. Bootstrap-substitution identification: Prove that the abstract bootstrap equation UR(U,U)U \cong R(U,U) admits a geometric realization as a substitution tiling in Rd\mathbb{R}^d. This requires constructing an explicit functor from the observer category to a tiling space, showing that the recursive structure of observer composition maps to a self-similar spatial decomposition. The single remaining semi-formal element.

  4. Metallic mean selection: Determine which nn is selected by the multi-scale self-consistency condition (Gravitational Coupling, Theorem 12.6). The golden mean (n=1n = 1) is the simplest candidate (maximal aperiodicity, highest observer density), but a proof requires solving the renormalization-group fixed-point equation.

  5. Net entropy snet(βn)s_{\text{net}}(\beta_n): Derive the mutual information cost function from the axioms rather than assuming a Gaussian profile. This would fix α(βn)\alpha(\beta_n) numerically.