Boolean hierarchy

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The boolean hierarchy is the hierarchy of boolean combinations (intersection, union and complementation) of NP sets. Equivalently, the boolean hierarchy can be described as the class of boolean circuits over NP predicates. A collapse of the boolean hierarchy would imply a collapse of the polynomial hierarchy. [1]

Contents

Formal definition

BH is defined as follows: [2]

Derived classes

Equivalent definitions

Defining the conjunction and the disjunction of classes as follows allows for more compact definitions. The conjunction of two classes contains the languages that are the intersection of a language of the first class and a language of the second class. Disjunction is defined in a similar way with the union in place of the intersection.

According to this definition, DP = NP coNP. The other classes of the Boolean hierarchy can be defined as follows.

The following equalities can be used as alternative definitions of the classes of the Boolean hierarchy: [4]

Alternatively, [5] for every k 3:

Hardness

Hardness for classes of the Boolean hierarchy can be proved by showing a reduction from a number of instances of an arbitrary NP-complete problem A. In particular, given a sequence {x1, ... xm} of instances of A such that xi A implies xi-1 A, a reduction is required that produces an instance y such that y B if and only if the number of xi A is odd or even: [4]

Such reductions work for every fixed k. If such reductions exist for arbitrary k, the problem is hard for PNP[O(log n)].

Related Research Articles

In computational complexity theory, a branch of computer science, bounded-error probabilistic polynomial time (BPP) is the class of decision problems solvable by a probabilistic Turing machine in polynomial time with an error probability bounded by 1/3 for all instances. BPP is one of the largest practical classes of problems, meaning most problems of interest in BPP have efficient probabilistic algorithms that can be run quickly on real modern machines. BPP also contains P, the class of problems solvable in polynomial time with a deterministic machine, since a deterministic machine is a special case of a probabilistic machine.

<span class="mw-page-title-main">BQP</span> Computational complexity class of problems

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<span class="mw-page-title-main">NP (complexity)</span> Complexity class used to classify decision problems

In computational complexity theory, NP is a complexity class used to classify decision problems. NP is the set of decision problems for which the problem instances, where the answer is "yes", have proofs verifiable in polynomial time by a deterministic Turing machine, or alternatively the set of problems that can be solved in polynomial time by a nondeterministic Turing machine.

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<span class="mw-page-title-main">PSPACE</span> Set of decision problems

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<span class="mw-page-title-main">Complexity class</span> Set of problems in computational complexity theory

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<span class="mw-page-title-main">PH (complexity)</span> Class in computational complexity theory

In computational complexity theory, the complexity class PH is the union of all complexity classes in the polynomial hierarchy:

In computational complexity theory, the polynomial hierarchy is a hierarchy of complexity classes that generalize the classes NP and co-NP. Each class in the hierarchy is contained within PSPACE. The hierarchy can be defined using oracle machines or alternating Turing machines. It is a resource-bounded counterpart to the arithmetical hierarchy and analytical hierarchy from mathematical logic. The union of the classes in the hierarchy is denoted PH.

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<span class="mw-page-title-main">IP (complexity)</span>

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<span class="mw-page-title-main">Boolean circuit</span> Model of computation

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<span class="mw-page-title-main">Circuit complexity</span> Model of computational complexity

In theoretical computer science, circuit complexity is a branch of computational complexity theory in which Boolean functions are classified according to the size or depth of the Boolean circuits that compute them. A related notion is the circuit complexity of a recursive language that is decided by a uniform family of circuits .

<span class="mw-page-title-main">Post's lattice</span>

In logic and universal algebra, Post's lattice denotes the lattice of all clones on a two-element set {0, 1}, ordered by inclusion. It is named for Emil Post, who published a complete description of the lattice in 1941. The relative simplicity of Post's lattice is in stark contrast to the lattice of clones on a three-element set, which has the cardinality of the continuum, and a complicated inner structure. A modern exposition of Post's result can be found in Lau (2006).

References

  1. Chang, R.; Kadin, J. (1996). "The Boolean Hierarchy and the Polynomial Hierarchy: A Closer Connection". SIAM J. Comput. 25 (25): 340–354. CiteSeerX   10.1.1.77.4186 . doi:10.1137/S0097539790178069.
  2. Complexity Zoo : Class BH
  3. Complexity Zoo : Class DP
  4. 1 2 Wagner, K. (1987). "More Complicated Questions About Maxima and Minima, and Some Closures of NP". Theoret. Comput. Sci. 51: 53–80. doi: 10.1016/0304-3975(87)90049-1 .
  5. Riege, T.; Rothe, J. (2006). "Completeness in the Boolean Hierarchy: Exact-Four-Colorability, Minimal Graph Uncolorability, and Exact Domatic Number Problems - a Survey". J. Univers. Comput. Sci. 12 (5): 551–578.