Solving the One-dimensional Distance Geometry Problem by Optical Computing

TL;DR

This paper introduces an optical computing method for solving the one-dimensional distance geometry problem, demonstrating promising results within classical computing frameworks.

Contribution

It presents a novel optical computing approach specifically designed for the one-dimensional distance geometry problem, highlighting its potential advantages over traditional methods.

Findings

Optical computing can efficiently solve the 1D distance geometry problem.

The proposed method shows promising results in classical computing regimes.

Potential for extending optical approaches to more complex geometric problems.

Abstract

Distance geometry problem belongs to a class of hard problems in classical computation that can be understood in terms of a set of inputs processed according to a given transformation, and for which the number of possible outcomes grows exponentially with the number of inputs. It is conjectured that quantum computing schemes can solve problems belonging to this class in a time that grows only at a polynomial rate with the number of inputs. While quantum computers are still being developed, there are some classical optics computation approaches that can perform very well for specific tasks. Here, we present an optical computing approach for the distance geometry problem in one dimension and show that it is very promising in the classical computing regime.