• authenticated data structure that represents a path in a graph as a balanced or biased binary tree of hash digests
  • internal nodes store hashes of concatenated sub-paths
  • enables logarithmic-size cryptographic proofs for graph properties: connectivity, distance, type queries
  • core building block of authenticated_graphs
  • how it works
    • given a path v₀ → v₁ → ... → vₖ in a graph
    • build a binary tree over the path edges
    • each leaf is the hash of an edge label or vertex attribute
    • each internal node is H(left_child || right_child)
    • the root digest commits to the entire path
    • to prove a sub-path or property, reveal the sibling hashes along the tree (logarithmic in path length)
  • comparison with Merkle trees
    • Merkle trees authenticate sets or sequences of data
    • hash path accumulators authenticate paths in graphs specifically
    • both use binary tree structure with hash nodes
    • hash path accumulators are optimized for path queries (connectivity, reachability, shortest path)
  • role in folding and incrementally verifiable computation
    • accumulators serve as the “running digest” in folding schemes
    • in Nova and related schemes, the accumulator absorbs each new proof instance without fully verifying it
    • the final accumulated value is then checked once via a single decider proof
    • this is what makes IVC efficient: fold instead of verify at each step
  • dynamic variants
    • dynamic authenticated forests support link/cut operations with O(log n) proofs and O(n) space
    • paths are partitioned into solid and dashed segments whose accumulators are linked
    • enables real-time updates as the cybergraph evolves
  • applications in cyber
    • cybergraph path verification: prove that two particles are connected through a specific chain of cyberlinks without transmitting the full path
    • authenticated_graphs with fractional cascading: hash path accumulators form the per-shard layer, with fractional cascading overlay for cross-shard queries
    • focus proof infrastructure: every random-walk step in the relevance machine publishes its proof against the attention root, enabling anyone to recompute focus
    • light client verification: neurons verify shard integrity with logarithmic bandwidth using path proofs
    • negative proofs: prove that a forbidden relationship is absent via authenticated complement paths
  • zero-knowledge friendly variants
    • when using hash functions like Poseidon, the accumulator tree can be verified inside a ZK circuit efficiently
    • each hash costs ~300 constraints vs ~1 constraint per field operation
    • this is why hash function choice (see ADR-001) is critical for accumulator performance in proof systems
  • related