On the Baltimore Light RailLink into the quantum future

TL;DR

This paper explores leveraging noise in NISQ quantum devices to solve complex train scheduling problems, demonstrating the first quantum application to tramway and railway rescheduling.

Contribution

It introduces a novel approach to use quantum noise as a resource for optimization in transportation systems, applying NISQ devices to real-world railway management.

Findings

Quantum noise can be harnessed for optimization.

First quantum application to tramway and railway rescheduling.

NISQ devices show potential in complex stochastic problems.

Abstract

In the current era of noisy intermediate-scale quantum (NISQ) technology, quantum devices present new avenues for addressing complex, real-world challenges including potentially NP-hard optimization problems. Acknowledging the fact that quantum methods underperform classical solvers, the primary goal of our research is to demonstrate how to leverage quantum noise as a computational resource for optimization. This work aims to showcase how the inherent noise in NISQ devices can be leveraged to solve such real-world problems effectively. Utilizing a D-Wave quantum annealer and IonQ's gate-based NISQ computers, we generate and analyze solutions for managing train traffic under stochastic disturbances. Our case study focuses on the Baltimore Light RailLink, which embodies the characteristics of both tramway and railway networks. We explore the feasibility of using NISQ technology to model the stochastic nature of disruptions in these transportation systems. Our research marks the inaugural application of both quantum computing paradigms to tramway and railway rescheduling, highlighting the potential of quantum noise as a beneficial resource in complex optimization scenarios.