One of the most commonly used examples used in schools and colleges to explain the need for quantum computing is the so-called traveling salesman problem, which requires complex combinatorial optimization skills to solve the following question: “Given a list of cities and the distances between each pair of cities, what is the shortest possible route that visits each city exactly once and returns to the origin city?”

The problem also illustrates one faced every day by Amazon, the e-commerce giant, when considering its logistics operations: many customers condition the search for a given product using the tomorrow delivery option. This generates a complex problem of multiple dependencies involving a large amount of computing resources, on which the company has been working since its inception, and which, moreover, must be solved in near real time, at the moment when the user is trying to decide to make a purchase. Quite a challenge, even for the company that probably has near limitless computing resources in its gigantic cloud.

Previous attempts to solve the problem, such as offering the option after purchase, generates all sorts of drawbacks, such as a significant increase in cart abandonment and, in general, customer dissatisfaction, a fundamental variable within what the company considers its founding credo. But to envision such a massive optimization carried out on a global scale, with millions of customers and transactions at the same time, requires the availability of almost unlimited computational resources. And many other logistics companies may find themselves in the same situation as Amazon, for whom solving the problem could provide a cost-saving and competitive advantage.

This probably explains Amazon’s decision to participate in the investment round of IonQ, a quantum computing hardware and software development company founded by two professors from Maryland and Duke universities, who aim to solve the problem and provide Amazon with a computational capacity capable of carrying out such a massive optimization. The company, which competes primarily against big tech companies such as Alphabet, IBM or Microsoft, which have vast amounts of funding, announced in March its intention to go public through a SPAC, and is considered the first company to bring quantum computing to a level where investors are interested in it.

For quantum computing, until now seen by many as a complex conceptual theoretical problem requiring practically unlimited computational resources, but without providing a direct or practical application that would illustrate it in a simple way that anyone could understand, this is quite a breakthrough: now, at least, we can understand what kind of problems it is trying to solve and what leads a company like Amazon to invest millions of dollars in it. Also, the possibility of further accelerating the developments of computing in this area, which has already become a technological race. In many ways, the logistics optimization problem offers quantum computing precisely what it needed: an application scenario that makes immediate sense.

If nothing else, this is a good example for a class on quantum computing, a teaching challenge, especially when we talk about participative methodologies. I am sure my students will appreciate it.

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