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On the power of counting the total number of computation paths of NPTMs

Eleni Bakali, Aggeliki Chalki, Sotiris Kanellopoulos, Aris Pagourtzis, Stathis Zachos

TL;DR

This paper defines and study variants of several complexity classes of decision problems that are defined via some criteria on the number of accepting paths of an NPTM, and presents a novel family of complete problems, which are defined via TotP-complete problems.

Abstract

In this paper, we define and study variants of several complexity classes of decision problems that are defined via some criteria on the number of accepting paths of an NPTM. In these variants, we modify the acceptance criteria so that they concern the total number of computation paths instead of the number of accepting ones. This direction reflects the relationship between the counting classes #P and TotP, which are the classes of functions that count the number of accepting paths and the total number of paths of NPTMs, respectively. The former is the well-studied class of counting versions of NP problems introduced by Valiant (1979). The latter contains all self-reducible counting problems in #P whose decision version is in P, among them prominent #P-complete problems such as Non-negative Permanent, #PerfMatch, and #DNF-Sat, thus playing a significant role in the study of approximable counting problems. We show that almost all classes introduced in this work coincide with their `#accepting paths'-definable counterparts, thus providing an alternative model of computation for them. Moreover, for each of these classes, we present a novel family of complete problems, which are defined via TotP-complete problems. This way, we show that all the aforementioned classes have complete problems that are defined via counting problems whose existence version is in P, in contrast to the standard way of obtaining completeness results via counting versions of NP-complete problems. To the best of our knowledge, prior to this work, such results were known only for parity-P and C=P.

On the power of counting the total number of computation paths of NPTMs

TL;DR

This paper defines and study variants of several complexity classes of decision problems that are defined via some criteria on the number of accepting paths of an NPTM, and presents a novel family of complete problems, which are defined via TotP-complete problems.

Abstract

In this paper, we define and study variants of several complexity classes of decision problems that are defined via some criteria on the number of accepting paths of an NPTM. In these variants, we modify the acceptance criteria so that they concern the total number of computation paths instead of the number of accepting ones. This direction reflects the relationship between the counting classes #P and TotP, which are the classes of functions that count the number of accepting paths and the total number of paths of NPTMs, respectively. The former is the well-studied class of counting versions of NP problems introduced by Valiant (1979). The latter contains all self-reducible counting problems in #P whose decision version is in P, among them prominent #P-complete problems such as Non-negative Permanent, #PerfMatch, and #DNF-Sat, thus playing a significant role in the study of approximable counting problems. We show that almost all classes introduced in this work coincide with their `#accepting paths'-definable counterparts, thus providing an alternative model of computation for them. Moreover, for each of these classes, we present a novel family of complete problems, which are defined via TotP-complete problems. This way, we show that all the aforementioned classes have complete problems that are defined via counting problems whose existence version is in P, in contrast to the standard way of obtaining completeness results via counting versions of NP-complete problems. To the best of our knowledge, prior to this work, such results were known only for parity-P and C=P.
Paper Structure (6 sections, 15 theorems, 1 equation, 1 figure, 2 tables)

This paper contains 6 sections, 15 theorems, 1 equation, 1 figure, 2 tables.

Table of Contents

  1. Introduction
  2. Preliminaries
  3. Classes defined by total counting
  4. The class $\mathsf{Gap_{tot} P}$
  5. The classes $\mathsf{U_{tot}P}$, $\mathsf{Few_{tot}P}$, $\mathsf{\oplus_{tot} P}$, $\mathsf{ {Mod_k}_{tot} P}$, $\mathsf{SP_{tot}P}$, $\mathsf{WP_{tot}P}$, $\mathsf{{{C_=}_{tot}P}}$, and $\mathsf{P_{tot}P}$
  6. Hardness results for problems definable via $\mathsf{TotP}$ functions

Key Result

proposition thmcounterproposition

$\mathsf{TotP}$ is closed under addition, multiplication, and subtraction by one.

Figures (1)

  • Figure 1: NPTM $M$ for which it holds that $tot_M(G) = \#(\text{perfect matchings on input } G)$, where $G$ is a bipartite graph PZ06. Thick lines indicate graph edges, based on which a non-deterministic branching is performed, depending on whether there exist perfect matchings that contain the edge (left subtree) and perfect matchings that do not contain it (right subtree).

Theorems & Definitions (24)

  • definition thmcounterdefinition: Valiant79PZ06FFK94
  • remark thmcounterremark
  • remark thmcounterremark: Table \ref{['classes definitions']}
  • definition thmcounterdefinition
  • definition thmcounterdefinition: ABCPPZ22
  • proposition thmcounterproposition
  • proposition thmcounterproposition: PZ06FFK94
  • proposition thmcounterproposition: RRW94
  • theorem thmcountertheorem: VV86Toda91
  • definition thmcounterdefinition
  • ...and 14 more