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Computational irreducibility is often discussed informally as the inability to shortcut a system’s evolution, but it lacks a unified causal-operational characterization. This project proposes a Temporal Causal Models (TCM)-based framework to define and measure irreducibility in dynamical computations. We will formalize notions of causal depth, simulation shortcut limits, and intervention-based predictability, then evaluate them across synthetic and benchmark sequential systems. The expected impact is a clearer theory of when fast prediction is fundamentally impossible and practical tools to diagnose irreducibility in real computational processes.