Optical Solver of Combinatorial Problems: Nano-Technological Approach

TL;DR

This paper explores an innovative optical computing system that employs nano-scaled masks to solve NP-hard problems efficiently, combining exponential space complexity with polynomial-time preprocessing and solution phases.

Contribution

It introduces a novel nano-technological approach to optical computing for NP-hard problems, reducing mask size and demonstrating feasibility through simulations and implementations.

Findings

Feasibility of nano-scaled masks for optical computing

Simulation results guiding mask design

Experimental validation of the approach

Abstract

We report the first steps in creating an optical computing system. This system may solve NP-Hard problems by utilizing a setup of exponential sized masks. This is exponential space complexity but the production of those masks is done with a polynomial time preprocessing. These masks are later used to solve the problem in polynomial time. We propose to reduced the size of the masks to nano-scaled density. Simulations were done to choose a proper design, and actual implementations show the feasibility of such a system.