We hear more and more about quantum computing, yet many people still know little about it. Quantum physics, however, has been part of our daily lives for decades, in mobile phone chips, lasers and MRI scanners. Quantum computing goes one step further: it is a new way of computing that harnesses the laws governing the world of atoms and subatomic particles, with the potential to solve certain types of problems that are beyond the reach of today’s computers.
This technology is one of the most promising of the so-called second quantum revolution. Although it is still maturing, it is attracting growing interest from businesses. In sectors such as chemicals and drug development, logistics and finance, specific applications are already being studied and tested.
Eurecat has been supporting companies through this transition since 2021 and, with the new QuantIA Lab, aims to bring quantum computing within their reach through emulation and optimisation tools, so that they can start exploring its possibilities today.
Shor’s algorithm, the starting point
The foundations of quantum computing were laid in the late 20th century, and one of its key milestones came in 1994 with Shor’s algorithm. The mathematician Peter Shor showed theoretically that a quantum computer could factor large integers, that is, break them down into their prime factors, at a speed beyond the reach of today’s classical computers.
This development put the spotlight on quantum computing and, even though no device capable of running the algorithm existed yet, it accelerated the race to build the first real quantum computers. At the same time, it raised the alarm about the threat it could pose to many of today’s cryptographic systems, which protect our communications with protocols based precisely on factoring large numbers.
From bit to qubit
To understand how this technology works, we need to go down to its basic building block, the qubit, and to the rules of quantum mechanics that govern its behaviour. A quantum computer is not a faster classical computer, but a machine that processes information using physical principles and programming approaches completely different from those of binary logic.
A bit can only be 0 or 1. A qubit, on the other hand, can represent both states at once thanks to superposition, and can be linked to other qubits through entanglement. These two properties of quantum physics make it possible to work with a vast number of combinations of states, and a third phenomenon, interference, increases the probability of obtaining correct answers and reduces that of incorrect ones.
Quantum technology, however, goes far beyond computing power and rests on three pillars advancing in parallel. The first is quantum computing, which makes it possible to tackle problems that are extremely complex for conventional computing, such as molecular simulation and design, or optimisation. The second is quantum communications and cryptography, which offer new ways of protecting transmitted information. And the third is quantum sensing, which measures physical quantities with extraordinary precision and opens up new possibilities in medicine, geology, and positioning and navigation systems, even without coverage from satellite systems such as GPS or Galileo.
Alongside these three pillars, and as a consequence of the potential of quantum computing, comes post-quantum cryptography. It is not a quantum technology but a classical one, and it develops new cryptographic systems able to withstand the threat that Shor anticipated.
The business potential of quantum computing
In the short term, companies’ interest is focused, on the one hand, on quantum computing, for the opportunities it can offer, and, on the other, on post-quantum cryptography, given the urgency of protecting corporate information systems.
In the case of quantum computing, the possibilities lie in problems with so many variables and constraints that classical computing cannot solve them in a reasonable time. This is the case with some optimisation problems, such as modelling and balancing electricity distribution networks.
This potential takes shape in three main areas. Quantum optimisation tackles planning problems with many simultaneous constraints, such as organising production at a chemical plant or designing hundreds of delivery routes. Quantum machine learning, by contrast, works with large volumes of data to classify, detect patterns and anticipate behaviour. And quantum simulation makes it possible to study how molecules and materials behave before they are synthesised or manufactured.
All of this could have an impact on a wide range of sectors: from health and biotechnology, through drug discovery and genomic analysis, to chemicals and advanced materials, robotics and manufacturing, and energy and the environment.
Quantum advantage in industry is still on the horizon
That said, much of this potential has yet to materialise. The term quantum advantage refers to the point at which quantum computers will solve real problems with better performance than conventional ones, measured in computing time or energy cost.
In most cases, we are not there yet: qubits are fragile and error-prone, and developing the error correction needed to build fault-tolerant computers remains one of the great scientific and engineering challenges.
The fact that quantum advantage is not yet a reality does not mean we have to wait. Making use of this technology does not require owning a quantum computer, but rather learning to formulate problems in quantum language, and that can already be done today with classical hardware.
A gateway: quantum emulation and quantum-inspired technologiess
Quantum emulation makes it possible to learn, research and develop use cases as you would with a real quantum computer, but using classical electronic processors. Emulators reproduce the behaviour of qubits as if they were running on an ideal quantum computer, that is, without errors or noise. This makes it possible to design quantum circuits and validate algorithms before taking them to real hardware.
In addition to emulation, there are quantum-inspired technologies, such as the digital annealer: classical hardware designed to reproduce some of the optimisation strategies of quantum computers specialised in this task, known as quantum annealers. Its aim is to find optimal solutions among a vast number of possible combinations.
According to Adan Garriga, Principal Investigator of Eurecat’s Quantum Computing Research Line, there is no need to wait for the future to benefit from quantum: by combining these two technologies with high-performance computing (HPC), computationally complex business challenges can already be tackled today.
There is no need to wait for the quantum computers of the future: today we can already tackle computationally complex business challenges.
—Adan Garriga, Principal Investigator of Eurecat’s Quantum Computing Research Line
How businesses can start applying quantum computing
The key, however, is not just having these technologies, but knowing how to apply them. This is where Eurecat comes in, drawing on years of experience working with companies on quantum computing projects.
This collaboration starts long before any algorithm: the first step is to identify the use cases where quantum can add value, draw up a roadmap and train the in-house team. From there, applications vary depending on each company’s challenge, and the outcome can range from a feasibility study or proof of concept to custom-built software.
The benefits can be reaped over two timeframes. Today, quantum-inspired methods and hybrid systems, which combine quantum or emulated tools with HPC, can already reduce computing time and costs in specific optimisation problems. In addition, companies can validate their use cases before investing and upskill their teams before investing in hardware, so that they will be ready when quantum hardware reaches maturity.
An infrastructure open to business innovation
All these technologies come together at the QuantIA Lab, Eurecat’s quantum emulation and optimisation infrastructure in Cerdanyola del Vallès, the only one of its kind in Catalonia and open to businesses.
The facility, which will be fully in place in early 2027, combines a 34-qubit quantum gate emulator, a digital annealer capable of handling combinatorial problems of up to 100,000 variables, and a high-performance computing (HPC) cluster that enables hybrid solutions.
As Joan Mas, Scientific Director of Eurecat’s Digital Area, explains, many current quantum systems require very demanding operating conditions, such as temperatures close to absolute zero, and are prone to errors due to qubit instability. The emulator and the digital annealer, by contrast, run on conventional semiconductor electronics.
The emulator and the digital annealer run on conventional electronics, without the extreme temperatures or the errors of today’s quantum systems.
—Joan Mas, Scientific Director of Eurecat’s Digital Area
The investment in the QuantIA Lab exceeds €7 million, of which €1.4 million comes from the Singulars Institucionals programme of the Catalan Government’s Department of Research and Universities, and €2.1 million is co-financed by the European Regional Development Fund (ERDF) through the Quant-IA project.
Alongside the infrastructure, Eurecat provides a multidisciplinary team combining quantum physics, artificial intelligence and software, which helps with the hardest translation of all: turning a business problem into an algorithm.
We are not starting from scratch
Behind the QuantIA Lab lie five years of experience. The centre opened an R&D line in quantum programming in 2021 and has since taken part in a number of collaborative projects.
One of the most significant has been the Cervera network ARQA, with CTIC and ITG, which between 2023 and 2025 developed demonstrators in satellite image classification, energy distribution optimisation and fraud detection. Eurecat coordinated the first of these: a tool that identifies and classifies features such as rivers, forests and cities in Sentinel-2 satellite images, comparing conventional, simulated quantum and pure quantum computing.
It has been succeeded by ARQADE, which is extending this work to security and defence until 2028, and in which Eurecat takes part through the QuantIA Lab. In parallel, the team is working on post-quantum cryptography and hybrid quantum machine learning.
How far it can take us
Once quantum computers are fully operational and fault-tolerant, the leap will be of a different order of magnitude: new drugs, unprecedented sustainable materials and optimisation on a scale unimaginable today.
That is why quantum computing applied to industry is no longer a question of waiting. It is a question of preparation. Companies that learn today to formulate their problems in quantum terms, validate use cases and upskill their teams will be better placed to benefit from quantum advantage when it arrives. With the QuantIA Lab, Eurecat is strengthening its research capacity to support them on this journey.
