The essential relationship between time, space, and information and the mapping of computational theory 🧵 Time and space are the two major storage dimensions of matter. Space storage of deterministic and consistent, meaningless Shannon information; Time storage is complete, meaningful, but possibly contradictory G ö del information. Meaning exists in time, and it truly exists in space. Space carries material entities, while time carries the dynamic relationship of material unfolding. Shannon information is an abstraction of space with replicable and verifiable properties; G ö del information is an abstraction of time, carrying complex dynamic calculations and semantics, and cannot be fully restored, that is, irreversible. The traditional Turing machine theory addresses the processing of deterministic information that can be restored in space; The ultra poor iterative technique based on dissipative structure deals with unpredictable and non reducing G ö del information in time. The difficulty in solving NP problems stems from the difference between time and space The solving process occurs in the time dimension, which is complex and difficult to reproduce; The verification process occurs in the spatial dimension, is deterministic and fast. 6/In Bitcoin mining, nonce solving is a temporal resonance of degrees of freedom and a dissipative structure iteration; The final nonce result is stored in space and can be verified by Turing machines. Overall, time and space carry two completely different forms of information, Turing machines are suitable for spatial reconstruction calculations, And the ordinal logic system of dissipative structures breaks through the processing limits of time information. This perspective profoundly reveals the nature of computational complexity, information philosophy, and the Bitcoin system. Computational Theory, Information Theory, Blockchain, Bitcoin, Turing Machine, Dissipative Structure, Time and Space