Collection, Analysis, Dissemination
One application where quantum information science (QIS) can have an effective influence is in the logistics and transportation industries. The technology for cars and other forms of transport are slowly changing by way of the data we have at our fingertips. The only downside to the amount of data we have — and how to use it properly — is in how we process it. Current methods, which adopt classical methods of computation, have their uses but as the data grows exponentially quicker methods of collection, analysis and overall dissemination will be required: that is where quantum technologies will come in useful.
AI is already a good way of doing this, but it too can have its limitations. Realizing the problems that will be encountered in the future, many of the world’s biggest companies in the automotive and aerospace industries have started researching ways to use quantum mechanics to solve logistical and other problems with QIS. Volkswagen, Toyota and Airbus are just three of dozens that already have quantum strategies up and running.
For a few years now Volkswagen has already been using quantum computers for their novel traffic management system that hopes to optimize traffic flow to take over from the outdated forecast systems of urban traffic volumes and travel times by using accurate quantum algorithms.
Airbus, too, is adopting a similar approach to control the flow in the skies and make for a better travel experience.
And it’s not only the big players like Volkswagen and Airbus that are working tirelessly to address such problems but smaller players as well.
AlphaRail, a Nashville, Tennessee based startup is working with ML and quantum-inspired computing approaches to enhance network rail systems across the North American continent.
The startup’s proprietary technology, Computational Railroading™, has been designed ‘to leverage the mathematics of railroading to optimize rail operations of all sizes’.
Leverage The Mathematics
Computational Railroading™, an operational learning system model, exploits ML techniques to analyze the performance of rail networks by continuously evaluating their behavioural patterns. The end result is a high level of accuracy optimization for the anomalies in the network patterns.
Railroads that operate accurately™ are better railroads
— AlphaRail
The founder and CEO of AlphaRail is Alex Luna, a graduate founder of the Creative Destruction Lab’s (QDL) Quantum Stream program. With a BS in dual concentration in business analytics and supply chain management from Haslam Business College at the University of Tennessee and an MBA from Vanderbilt University almost completed, he has all the skills needed to lead AlphaRail in logistical solutions for network rail problems.
The startup’s inclusion in QDL’s Quantum Stream program should be validation enough that Luna and his team are onto something big, but it’s not only backing from one of Canada’s finest startup incubators that AlphaRail has secured but support from the likes of leading shortline railroad and transportation company Carload Express, the University of Toronto, QC company 1QBit, as well as Luna’s own alma mater the Owen Graduate School of Management at the University of Tennessee.
The list of things QIS could solve in the future is a very long one, with routing and scheduling optimization problems just one of them. Leveraging the power of mathematics and quantum mechanics offers novel, though unproven, ways of improving our lot in this industry.
AlphaRail is a pioneer in all of this. TQD wishes them all the best.
