Signature-free protocols avoid the cost of post-quantum signatures. We present two simple signature-free blockchain consensus protocols for eventual synchrony with optimal good-case commit latency (three message delays for \(f<n/3\) and two for \(f<n/5\)), optimistic responsiveness, a block time of only two message delays without speculation, and \(O(n^2)\) communication per view. They instantiate Generic Simplex, a blockchain consensus construction parameterized by a new abstraction called view agreement. The same construction also captures Simplex, Minimmit, and a new synchronous signature-free protocol with optimal good-case commit latency of two message delays for \(f<n/4\).

கடைசித் திருத்தம்: 26 செப்., 2026. ஆய்வுக் கட்டுரையையும் பதிப்பு வரலாற்றையும் வாசிக்கவும் ↗

Contemporary on-chain artificial intelligence (AI) encounters an intractable Von Neumann memory and latency wall. Storing static floating-point neural weight matrices inside Ethereum Virtual Machine (EVM) storage costs millions of gas, rendering direct on-chain inference impossible. While Zero-Knowledge Machine Learning (ZK-ML) offloads matrix tensor multiplications to off-chain provers, it introduces fatal constraints: 10 to 300 seconds of SNARK proving latency and 250,000 to 500,000 gas per proof verification. Because decentralized finance (DeFi) exploits - such as uncollateralized flash-loan attacks, predatory sandwich MEV, and toxic loss-versus-rebalancing (LVR) flow - occur atomically inside a single block, ZK-ML oracles cannot react in time. Here, we present Werracle, a production-grade, zero-storage on-chain AI decision oracle fitting inside a single 32-byte EVM storage slot (bytes32). Leveraging foundational procedural Mandelbrot escape dynamics (z_{n+1} = z_n^2 + c) established by Dagli et al. (arXiv:2609.25498), Werracle derives continuous non-linear decision hyperplanes from a 24-byte coordinate triplet Theta = (c_x, c_y, zoom). Implemented in pure Solidity bytecode using fixed-point Q16.16 arithmetic (WerrMath.sol), Werracle evaluates a 16-point Pareto micro-grid in only 21,438 gas (under 0.0005 USD on Layer-2 rollups like Base and Arbitrum) with sub-millisecond execution latency. We demonstrate real-world DeFi efficacy via WerracleFeeHook.sol, a Uniswap v4 dynamic swap fee governor that measures orderbook turbulence on-the-fly and atomically adjusts liquidity provider fees between 0.05% and 0.50%. The protocol is formally verified against a 1,000-test cryptographically sealed deterministic verification suite (100.0% pass rate) with telemetry permanently disabled, operating live on a dedicated EVM devnet sandbox (Chain ID 4242).

கடைசித் திருத்தம்: 25 செப்., 2026. ஆய்வுக் கட்டுரையையும் பதிப்பு வரலாற்றையும் வாசிக்கவும் ↗

The Ethereum blockchain utilizes the EIP-1559 algorithm to manage transaction inclusion and block assembly. However, EIP-1559 and much of the existing literature study this problem from a static perspective, focusing on price evolution without modelling transaction dynamics within the mempool. Motivated by this limitation, we study a dynamic transaction scheduling problem in which transactions with heterogeneous sizes and per-unit values arrive over time and remain in the mempool until scheduled. To capture the stochastic mempool evolution, we formulate the problem as a Markov Decision Process (MDP) whose state represents the mempool configuration and whose actions correspond to block prices. We first provide a primal-dual interpretation of the static EIP-1559 mechanism, showing that block prices arise naturally as dual variables of a social-welfare maximization problem. Building on this perspective, we extend the framework to the dynamic setting and formulate an objective that maximizes long-run discounted reward while incorporating holding costs and overshoot penalties. We then employ a Natural Policy Gradient (NPG) algorithm to compute the optimal policy. Our results show that dynamic pricing stabilizes the mempool while maximizing long-run discounted reward. In particular, as the overshoot penalty increases, the average scheduled transaction volume converges to the target block capacity, and the resulting NPG updates closely resemble the EIP-1559 price update rule. Finally, we study two special cases of the MDP formulation: homogeneous transactions and uniform arrivals. In the homogeneous setting, where the protocol directly controls scheduled volume, we show that the optimal policy has a threshold structure. We then propose a bang-bang pricing mechanism for uniform arrivals and derive a lower bound on the block capacity needed to ensure system stability.

கடைசித் திருத்தம்: 28 செப்., 2026. ஆய்வுக் கட்டுரையையும் பதிப்பு வரலாற்றையும் வாசிக்கவும் ↗

Despite holding over $1.7T in value, Bitcoin scales poorly: Layer-1 (L1) processes only a few transactions per second, and Layer-2 (L2) solutions suffer from operational and liquidity fragmentation that requires external bridges for cross-chain connectivity. We present Bitcoin-IPC, a protocol that horizontally scales Bitcoin via permissionless, interconnected, programmable Proof-of-Stake L2 subnets staked in L1 BTC. Subnets leverage Bitcoin L1 for interconnectivity, settlement, and security, including Sybil protection, equivocating validator slashing, unilateral exit for honest stake, long-range attack protection, and compromised subnet firewalling. Bitcoin-IPC cross-subnet transfers involve only source/destination subnet validators and L1, with no external bridges or per-path liquidity lock-up. Embedded and batched in Bitcoin's witness mechanism, cross-subnet settlements can approach 6 vB per transfer, 23x less than a native L1 payment. Filling Bitcoin blocks with such batches corresponds to L1 monetary throughput of about 273 transfers per second, without modifying Bitcoin.

கடைசித் திருத்தம்: 29 செப்., 2026. ஆய்வுக் கட்டுரையையும் பதிப்பு வரலாற்றையும் வாசிக்கவும் ↗