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Simulation of Turing machines with analytic discrete ODEs: FPTIME and FPSPACE over the reals characterised with discrete ordinary differential equations

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arxiv 2307.11747 v2 pith:4SU3VTAT submitted 2023-07-21 cs.CC cs.LOmath.DSmath.LO

classification cs.CCcs.LOmath.DSmath.LO
keywords complexitydiscretetimedifferentialequationsfunctionsordinaryreals
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We prove that functions over the reals computable in polynomial time can be characterised using discrete ordinary differential equations (ODE), also known as finite differences. We also provide a characterisation of functions computable in polynomial space over the reals. In particular, this covers space complexity, while existing characterisations were only able to cover time complexity, and were restricted to functions over the integers. We prove furthermore that no artificial sign or test function is needed even for time complexity. At a technical level, this is obtained by proving that Turing machines can be simulated with analytic discrete ordinary differential equations. We believe this result opens the way to many applications, as it opens the possibility of programming with ODEs, with an underlying well-understood time and space complexity.

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  1. Analog classical simulation of closed quantum systems

    quant-ph 2025-02 conditional novelty 5.0 of 10

    A mapping from the Schrödinger equation to real second-order ODEs lets analog classical devices, such as spring-mass systems, simulate quantum dynamics and run quantum algorithms like QAOA, at exponential hardware cost.

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