On this page
Authorization Lattice
What It Solves#
Capability-based execution with mathematical permission composition. Permissions are not strings or ACLs — they’re lattice elements with precise algebraic structure.
Key Insight#
Permissions as p-adic Numbers:
The same p-adic / ultrametric structure underlying CRT encoding appears in capability lattices. This is not a coincidence — it’s the same mathematics appearing in two different domains.
Why Lattices?#
A lattice is a partially ordered set where any two elements have a unique greatest lower bound and least upper bound. For permissions:
- Join (∨): Greatest lower bound = most permissive common permission
- Meet (∧): Least upper bound = most restrictive combined permission
Prime Weighting in Capabilities#
Each capability receives a prime weight. The divisibility relation determines permission inheritance:
This is exact — no ambiguity, no override rules, no special cases.
Lock-Preserving Semantics#
The same “lock-preserving” property from Geometry of Conditional Logic applies:
- Locked commitments (root capabilities) are never changed
- Only invalid regions are repaired
- The CRT safe-corridor maps to the lattice “meet” operation
The Essay#
The Authorization Lattice blog post explores:
- “Authorization Lattice Mathematics and the Ownerless Object Problem”
- How to have permissions without an owner
- The algebraic structure of capability systems
Website#
Live: sethuiyer.github.io/authorization-lattice
Key Files#
authorization-lattice/index.html— Full blog postauthorization-lattice/LICENSE— GPL v3
Connection to Core Vision#
Authorization Lattice extends the Arithmetic Manifold to security and permissions. The same principles apply:
- Prime factorization provides unique capability identity
- CRT provides invariant-preserving repair
- Lattice structure ensures compositional correctness
The p-adic numbers are already lurking in CRT — Authorization Lattice makes the connection explicit.
In the Factor Agent runtime, this permission algebra becomes an operational rule: retrieval is filtered before model context construction, and tool calls are checked as capability requests. See Agentic AI as a Distributed System for the full runtime architecture.
See Also#
- All Projects — project overview
- Geometry of Conditional Logic — CRT and p-adic ultrametrics
- Factor Agent — capability decomposition via prime factorization
- Agentic AI as a Distributed System — runtime governance for capability-filtered agents
- Prime Weighting — how primes compose in capability systems
- The Arithmetic Manifold — the unified theory