Quantum Computing: tools from the future

It powered up at Politecnico di Torino on May 22, 2025: it's the “Lagrange” computer, the first IQM quantum computer in Italy, yet one of only a handful in the world. A major resource for students, researchers, and local companies that collaborate with the University. An essential tool for learning to master the ongoing full-scale technological revolution in the field of computing. It is a wave worth riding, the alternative being overwhelmed.

Let's imagine a new computer, billions of times faster than today's fastest ones. Capable of solving exponentially complex problems that are beyond the reach of traditional computers. This computer, in nuce, already exists: one has recently been activated at Politecnico di Torino.
Strongly desired—and not by chance—by the university that inaugurated Italy's first degree course in Quantum Engineering in 2023, the IQM quantum computer, named after the mathematician Lagrange, has brought Politecnico di Torino to the forefront of a crucial sector. It is a 5-qubit quantum computer supplied by IQM Quantum Computers, acquired thanks to a partnership between Politecnico di Torino, the LINKS Foundation, and the National Institute of Metrological Research (INRiM).
The new quantum computing technology is based on a novel computing paradigm for solving complex problems in engineering and science, which will enable machines to speed up calculations billions of times faster than traditional HPC (High-Performance Computing) computers.
This will have a profound impact on all aspects of our lives, affecting not only the field of scientific research but also the fields of communication, finance, security, energy, medicine, and artificial intelligence.

With the help of Bartolomeo Montrucchio, full professor of Computer Engineering at the Department of Control and Computer Engineering at Politecnico di Torino, let's try to provide some figures: " Whereas with a current HPC system, using 32 classic computers in parallel, we can expect to speed up calculations by a factor of 32, using 32 quantum computers connected in the right way, we can expect to speed up calculations exponentially, i.e., by a factor of 2³²: this implies a computing speed that is about four billion times faster. An intrinsic leap in performance that no traditional computer can handle. Just think that today's most powerful computer has 11 million processors: to have a quantum computer with the same power, you would only need about 24."

That is why Politecnico decided to acquire this sort of machine. To study and fully understand how it works, its applications, and developments. But what is the secret that allows quantum computers to achieve such performance?

The vast potential of quantum computing has not been fully explored: it is a technology that is still in its infancy, yet rapidly evolving.

Matteo Cocuzza, full professor of Experimental Physics of Matter and Applications at the Department of Applied Science and Technology and coordinator of the new degree course in Quantum Engineering, explains that a first critical aspect is the volatility of results: "A quantum computer does not produce deterministic results, but probabilistic ones. While a classical computer will always yield the same result when faced with identical data, a quantum computer does not deliver a precise, exact, deterministic result, but rather a spectrum of probabilistic results... it performs the same calculation thousands of times and yields a slightly different result each time. Ultimately, we are faced with a distribution of results, in which the peak is the exact result. Qubits are not 100% accurate because, in order to be so, they would have to operate in an ideal environment in which they are perfectly isolated from everything: temperature changes, electromagnetic disturbances, microwaves, mechanical vibrations... The better they are shielded from external environmental disturbances, the more accurate they become. It is impossible to isolate them perfectly today, even if we make them work in conditions close to perfect isolation: the Quantum Processor Unit (QPU) of the Turin computer, the heart of the calculator, operates at a very low temperature, 18 millikelvin, or -273.13 degrees Celsius, a temperature close to absolute zero, achieved thanks to a cryogenic system that uses helium and liquid nitrogen circuits.

Scalability is also an issue that needs to be addressed: currently, quantum computers become increasingly unstable as the number of qubits and the amount of data to be analyzed increase. Cocuzza explains: “Smaller computers are much more stable. A five-qubit computer, like the one in Turin, is less powerful but more stable than machines with a larger number of qubits. And this can show benefits, especially from an educational point of view.” However, to tackle complex problems, more powerful computers are needed, but they must also be made sufficiently stable.

Furthermore, quantum computing is currently subject to significant time constraints: today's technology is capable of producing qubits that remain active for an extremely limited period of time, which undoubtedly represents a limitation. However, this time frame is increasing: from nanoseconds to microseconds, an increment of thousands of times. Work is underway to develop ever more efficient systems.

It must be clear that the issue is not about replacing traditional computers with quantum computers, but rather integrating the two systems. Part of the research today is aimed precisely at understanding which applications each system is best suitable for, and transforming data so that it can be transferred from one system to another.
Quantum computing is well-suited to very complex problems, particularly optimization problems.

Matteo Cocuzza further explains: "It would not make sense to use a quantum computer for simple problems: it would be like using a Ferrari to plow a field. There are relatively simple problems—and consequently algorithms needed to solve these problems—whose complexity increases linearly with the number of variables. For instance, if I want to sort the population of Turin in alphabetical order, when the population doubles, the problem doubles (in the best-case scenario). But there are also problems whose complexity increases exponentially because the variable factors involved multiply among themselves: a traditional computer, however powerful, is not capable of solving this sort of problem. A quantum computer, once it has a sufficient number of qubits, can.

Montrucchio and Giovanna Turvani, professor at the Department of Electronics and Telecommunications at Politecnico, help us with a concrete example: “Let's say we want to improve traffic in a city like Turin by optimizing the operation of traffic lights through sensors that regulate the duration of red and green lights. Although there are only a few hundred traffic lights in Turin, this is an exponentially complex problem. If we want to optimize traffic throughout the city, we must consider all the other traffic lights in order to regulate each individual one. If there are, say, 400 traffic lights, the problem becomes exponentially more complicated: it does not increase 400 times, but 2⁴⁰⁰ times. A traditional computer cannot do this, but a quantum computer can. Another classic example of an optimization problem suitable for solving with quantum computers is the so-called traveling salesman problem: optimizing the route for visiting customers, considering all the variables involved (availability and experience of the salesperson, distance, location, individual customer needs, etc.). Again, the complexity of the problem is exponential.

Turvani further explains how to apply quantum technology to the study of options related to pandemic management: "Exploiting the quantum advantage means completely reframing a problem differently than in classical computing: for pandemic management, this involves identifying all the variables involved, such as the number of infected people, the economic consequences of business closures, the average recovery time, etc. The problem must be formulated in mathematical terms, considering all the variables and making them processable with a quantum optimizer; the result will be an optimized view, in this case, of the number of areas that need to be isolated to prevent the infection from spreading. Another healthcare-related application we are studying is dedicated to optimizing the scheduling of visits and therapies in a hospital, considering many variables such as the equipment available, the number and needs of patients, their time constraints, staff availability, etc. Again, all variables will be processed by the quantum computer, which will optimize the visit schedule.