plurigrid/ies/music-topos/.codex/skills/exponential-topology-communication

Exponential Topology Communication

Category: Phase 3 Core - Scalable Communication Status: Skeleton Implementation Dependencies: oriented-simplicial-networks (for topological structure)

Overview

Implements ExpoComm framework for exponentially efficient communication in large-scale systems using hyperbolic embeddings, O(log N) routing, and spectral gap optimization for rapid information dissemination.

Capabilities

• Hyperbolic Embeddings: Embed agents in hyperbolic space
• O(log N) Routing: Greedy routing with logarithmic complexity
• Spectral Gap Optimization: Maximize mixing time via graph structure
• Scalable Broadcast: Efficient all-to-all communication

Core Components

1. Hyperbolic Embeddings (hyperbolic_embeddings.jl)

   • Poincaré disk model
   • Greedy embedding algorithms
   • Distance computation

2. ExpoComm Routing (expocomm_routing.jl)

   • Greedy hyperbolic routing
   • Load balancing strategies
   • Fault tolerance

3. Spectral Optimization (spectral_optimization.jl)

   • Graph Laplacian analysis
   • Spectral gap maximization
   • Expander graph construction

4. Scalability Analysis (scalability_analysis.jl)

   • Communication complexity bounds
   • Scaling experiments
   • Comparison with Euclidean approaches

Integration Points

• Input from: oriented-simplicial-networks (communication topology)
• Output to: emergent-role-assignment (communication structure influences roles)
• Coordinates with: sheaf-theoretic-coordination (consensus over hyperbolic graphs)

Usage

using ExponentialTopologyCommunication

# Create network of N agents
N = 1000
graph = random_power_law_graph(N, exponent=2.5)

# Compute hyperbolic embeddings
embeddings = hyperbolic_embedding(graph, dim=2)

# Route message from source to target
path = greedy_route(embeddings, source=1, target=N)
@assert length(path) <= 2 * log2(N)  # O(log N) guarantee

# Analyze spectral properties
spectral_gap = compute_spectral_gap(graph)
mixing_time = estimate_mixing_time(spectral_gap, N)

References

• Krioukov et al. "Hyperbolic Geometry of Complex Networks" (2010)
• Kleinberg "Navigation in a Small World" (Nature 2000)
• Hoory et al. "Expander Graphs and their Applications" (2006)

Implementation Status

• [x] Basic hyperbolic embeddings
• [x] Greedy routing implementation
• [ ] Full spectral gap optimization
• [ ] Fault-tolerant routing
• [ ] Large-scale benchmarks