How does Kaspa adjust mining difficulty fairly?

Kaspa adjusts mining difficulty by sampling a representative subset of blocks from its history, rather than examining every block. The sampling method is designed to meet four key properties: it is deterministic (every node calculates the same result from the same DAG), uniformly distributed (all blocks have a similar chance of being selected), incremental (it does not depend on any single block's point of view and can be inherited by future blocks), and secure (a miner cannot cheaply manipulate whether their block gets sampled — the cost of doing so is comparable to simply discarding a valid block). Understanding difficulty adjustment matters because it is the mechanism that keeps mining competitive and the network stable as more or fewer miners join.