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Complexitylib.Metacomplexity.MINKT.Gap.Logarithmic.Defs

Logarithmic-gap MINKT -- definitions #

This is the exact machine-relative form of Hirahara's Gap_tau MINKT promise from Definition 3.3 of Symmetry of Information from Meta-Complexity (CCC 2022). It reuses the canonical (x, 1^t, 1^s) codec from GapMINKT, but fixes the promised sides to

The existing general GapMINKT.Parameters remains useful for optimization search with an arbitrary description transformation sigma(n,s). This module is separate because the paper's exact logarithmic loss depends on the source clock through tau(n,t).

The paper's two-argument clock transformation tau(|x|,t).

  • clock :

    Later primitive clock from output length and source clock.

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    The transformed clock never gives less time than the source clock.

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      One power of the total numeric input controls the clock transformation.

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        A paper-level clock is admissible when it is widening and polynomially bounded. Computability remains a separate implementation property.

        • widening : parameters.IsWidening

          The target clock dominates the source clock.

        • polynomiallyBounded : parameters.IsPolynomiallyBounded

          The target clock has uniform polynomial growth.

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          The identity transformation, giving the zero-blow-up boundary case.

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            Apply the clock transformation to a threshold-free MINKT instance.

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              Base-two logarithmic slack at the transformed clock.

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                @[reducible, inline]

                A threshold-free numerical estimator for ordinary bounded complexity.

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                  def Complexity.GapMINKT.Logarithmic.Estimator.SatisfiesBounds {tapes : } (estimate : Estimator) (machine : TM tapes) (parameters : Parameters) :

                  Fact 3.4's subtraction-free estimator sandwich:

                  B(x,1^t) <= C^t(x) and C^tau(x) <= B(x,1^t) + log_2(tau).

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                    def Complexity.GapMINKT.Logarithmic.Estimator.SatisfiesBoundsOn {tapes : } (estimate : Estimator) (machine : TM tapes) (parameters : Parameters) (eligible : MINKT.InstanceProp) :

                    The estimator sandwich restricted to an explicit set of inputs.

                    Hirahara's Fact 3.4 uses the domain |x| <= t. Keeping the domain explicit lets the machine-relative library state that version without pretending that an arbitrary machine can print every output at every tiny clock.

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                      The input domain |x| <= t used in Fact 3.4.

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                        def Complexity.GapMINKT.Logarithmic.IsNo {tapes : } (inst : Instance) (machine : TM tapes) (parameters : Parameters) :

                        Exact logarithmic no condition C^tau(x) > s + log_2(tau).

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                          def Complexity.GapMINKT.Logarithmic.IsRelaxedWitness {tapes : } (inst : Instance) (machine : TM tapes) (parameters : Parameters) (program : List Bool) :

                          A concrete program forbidden by the exact logarithmic no condition.

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                            The yes language is exactly the existing source-threshold language.

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                              def Complexity.GapMINKT.Logarithmic.noLanguage {tapes : } (machine : TM tapes) (parameters : Parameters) :

                              Canonically encoded exact logarithmic no language.

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                                Total completion obtained by thresholding a numerical estimator.

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                                  Executable thresholding of an ordinary bounded-complexity estimator.

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                                    Add a description threshold to a threshold-free MINKT instance.

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                                      Search the finite interval [0,cap] for the first threshold accepted by a Boolean promise solver. If the solver accepts none of them, return cap.

                                      The fallback makes the operation total. Correctness theorems use an accepted upper bound, so the fallback branch is then unreachable.

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                                        Turn a gap solver into a numerical estimator by bounded threshold search.

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                                          The canonical Fact 3.4 search uses the unary source clock as its threshold cap. Every finite source complexity is at most this value by input locality.

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