Complexity of equivalence relations and preorders from computability theory

We study the relative complexity of equivalence relations and preorders from computability theory and complexity theory. Given binary relations $R, S$, a componentwise reducibility is defined by R\le S \iff \ex f \, \forall x, y \, [xRy \lra f(x) Sf(y)]. Here $f$ is taken from a suitable class of effective functions. For us the relations will be on natural numbers, and $f$ must be computable. We show that there is a $\Pi_1$-complete equivalence relation, but no $\Pi k$-complete for $k \ge 2$. We show that $\Sigma k$ preorders arising naturally in the above-mentioned areas are $\Sigma k$-complete. This includes polynomial time $m$-reducibility on exponential time sets, which is $\Sigma 2$, almost inclusion on r.e.\ sets, which is $\Sigma 3$, and Turing reducibility on r.e.\ sets, which is $\Sigma 4$.Comment: To appear in J. Symb. Logi

Polynomial-time reducibilities and “almost all” oracle sets

AbstractIt is shown for every k>0 and for almost every tally setT, {A|A ⩽Pk−ttT} ≠ {A|A ⩽P(k+1)−ttT}. In contrast, it is shown that for every set A, the following holds: (a) for almost every set B,A ⩽ Pm B if and only if A ⩽ P(logn)−T B; and (b) for almost every set B, A ⩽Ptt B if and only ifA ⩽PTB

Complexity-class-encoding sets

Properties of sets which are complex because they encode complexity classes areexplored. It is shown that not all sets with inherent complexity are of this type, although this is the only type of set for which well-developed techniques exist for proving inherent complexity.Possibilities for the complexity of encoding sets are discussed, first with referenceto an “almost everywhere” vs. “infinitely many arguments” classification, and later with reference to the density of the set of arguments on which the problem is complex.It is shown that relative complexity relationships among sets of this type are highlystructured, in contrast to the wide variation possible among arbitrary recursive sets

On the relative complexity of hard problems for complexity classes without complete problems

AbstractWe show that any recursive sequence of recursive sets which is ascending with respect to the standard polynomial time reducibility notions has no minimal upper bound. As a consequence, any complexity class with certain natural closure properties possesses either complete problems or no easiest hard problems. A further corollary is that, assuming P ≠ NP, the partial ordering of the polynomial time degrees of NP-sets is not complete, and that there are no degree invariant approximations to NP-complete problems

Structural Average Case Complexity

AbstractLevin introduced an average-case complexity measure, based on a notion of “polynomial on average,” and defined “average-case polynomial-time many-one reducibility” among randomized decision problems. We generalize his notions of average-case complexity classes, Random-NP and Average-P. Ben-Davidet al. use the notation of 〈C, F〉 to denote the set of randomized decision problems (L, μ) such thatLis a set in C andμis a probability density function in F. This paper introduces Aver〈C, F〉 as the class of randomized decision problems (L, μ) such thatLis computed by a type-C machine onμ-average andμis a density function in F. These notations capture all known average-case complexity classes as, for example, Random-NP= 〈NP, P-comp〉 and Average-P=Aver〈P, ∗〉, where P-comp denotes the set of density functions whose distributions are computable in polynomial time, and ∗ denotes the set of all density functions. Mainly studied are polynomial-time reductions between randomized decision problems: many–one, deterministic Turing and nondeterministic Turing reductions and the average-case versions of them. Based on these reducibilities, structural properties of average-case complexity classes are discussed. We give average-case analogues of concepts in worst-case complexity theory; in particular, the polynomial time hierarchy and Turing self-reducibility, and we show that all known complete sets for Random-NP are Turing self-reducible. A new notion of “real polynomial-time computations” is introduced based on average polynomial-time computations for arbitrary distributions from a fixed set, and it is used to characterize the worst-case complexity classesΔpkandΣpkof the polynomial-time hierarchy

Notes on conformal invariance of gauge fields

In Lagrangian gauge systems, the vector space of global reducibility parameters forms a module under the Lie algebra of symmetries of the action. Since the classification of global reducibility parameters is generically easier than the classification of symmetries of the action, this fact can be used to constrain the latter when knowing the former. We apply this strategy and its generalization for the non-Lagrangian setting to the problem of conformal symmetry of various free higher spin gauge fields. This scheme allows one to show that, in terms of potentials, massless higher spin gauge fields in Minkowski space and partially-massless fields in (A)dS space are not conformal for spin strictly greater than one, while in terms of curvatures, maximal-depth partially-massless fields in four dimensions are also not conformal, unlike the closely related, but less constrained, maximal-depth Fradkin--Tseytlin fields.Comment: 38 page