Andrey Markov
1856–1922 — Markov chains and dependent sequences
Author
Russian mathematician; Markov chains formalise memoryless stochastic processes — the structure assumed when information-theoretic processing limits apply along a pipeline.
Andrey Markov (1856–1922) studied sequences where each step depends only on the immediately preceding state — now called Markov chains. Genesis cites the Markov property not as a claim about all real-world systems, but as the structural assumption under which Claude Shannon’s data processing inequality bounds how much mutual information a derived artifact can retain about ground truth.
What we cite
- Markov chain — processing step Y is sufficient statistic for Z relative to source X; enables I(X ; Z) ≤ I(X ; Y).
- Broken Markov structure — hidden side inputs, uncited merges, or inconsistent cross-stream joins invalidate the bound and are architectural defects, not mere uncertainty.
Corpus stance
Adopt — formal vocabulary for when processing-chain limits apply; see What Information Theory Says.