Quantum Dynamic Programming Algorithm for DAGs. Applications for AND-OR DAG Evaluation and DAG's Diameter Search

04/26/2018
by   Kamil Khadiev, et al.
0

In this paper, we present Quantum Dynamic Programming approach for problems on directed acycling graphs (DAGs). The algorithm has time complexity O(√(n̂m)n̂) comparing to a deterministic one that has time complexity O(n+m). Here n is a number of vertexes, n̂ is a number of vertexes with at least one outgoing edge; and m is a number of edges. We show that we can solve problems that have OR, AND, NAND, MAX and MIN functions as the main transition step. The approach is useful for a couple of problems. One of them is computing Boolean formula that represented by DAG with AND and OR boolean operations in vertexes. Another one is DAG's diameter search.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
07/13/2018

Quantum Speedups for Exponential-Time Dynamic Programming Algorithms

In this paper we study quantum algorithms for NP-complete problems whose...
research
10/18/2021

Diameter constrained Steiner tree and related problems

We give a dynamic programming solution to find the minimum cost of a dia...
research
05/03/2007

Multiresolution Approximation of Polygonal Curves in Linear Complexity

We propose a new algorithm to the problem of polygonal curve approximati...
research
04/29/2021

Quantum speedups for dynamic programming on n-dimensional lattice graphs

Motivated by the quantum speedup for dynamic programming on the Boolean ...
research
05/08/2022

DPMS: An ADD-Based Symbolic Approach for Generalized MaxSAT Solving

Boolean MaxSAT, as well as generalized formulations such as Min-MaxSAT a...
research
01/31/2018

QRMW: Quantum representation of multi wavelength images

In this study, we propose quantum representation of multi wavelength ima...
research
05/17/2022

DPO: Dynamic-Programming Optimization on Hybrid Constraints

In Bayesian inference, the most probable explanation (MPE) problem reque...

Please sign up or login with your details

Forgot password? Click here to reset