{"id":2063648,"date":"2026-06-22T13:24:36","date_gmt":"2026-06-22T11:24:36","guid":{"rendered":"https:\/\/www.luxsure.fr\/2026\/06\/22\/quantum-physics-is-no-longer-waiting-for-a-miracle-it-is-seeking-practical-applications\/"},"modified":"2026-06-22T13:25:30","modified_gmt":"2026-06-22T11:25:30","slug":"quantum-physics-is-no-longer-waiting-for-a-miracle-it-is-seeking-practical-applications","status":"publish","type":"post","link":"https:\/\/www.luxsure.fr\/en\/2026\/06\/22\/quantum-physics-is-no-longer-waiting-for-a-miracle-it-is-seeking-practical-applications\/","title":{"rendered":"Quantum physics is no longer waiting for a miracle; it is seeking practical applications"},"content":{"rendered":"\n

Some technologies emerge through proof. Others through anticipation. Quantum computing still straddles both worlds: mature enough to leave the lab, but not yet clear enough to be fully incorporated into corporate financial statements. <\/p>\n\n

For a long time, quantum computing existed in a kind of perpetual future. \u201cIn five years,\u201d people used to say. Then another five years. The promise remained intact, but the horizon seemed to be receding gracefully. That window of time may now be closing\u2014not because a universal quantum computer has suddenly solved the problem, but because the industry is beginning to shift its definition of success. The real question is no longer: When will the quantum advantage be demonstrated? It has become: In which workflow does a quantum machine create value that other forms of computing cannot produce? <\/p>\n\n

This shift is decisive. It strips quantum physics of some of its almost metaphysical mystique and brings it back to a more down-to-earth discipline: that of practical application. <\/p>\n\n

The End of the Great Quantum Night<\/h2>\n\n

The quantum advantage has long been described as a theatrical scene: one day, a machine would clearly prove that it outperforms any classical approach. This definition retains its scientific validity, but it is no longer enough for businesses. For an industrialist, the advantage is not measured solely in terms of mathematical elegance. It is measured in time saved, in a better understanding of materials, in a more accurately simulated portfolio, and in a better prediction of molecular behavior. <\/p>\n\n

This is where the debate gets more interesting. Today\u2019s machines are not yet those fault-tolerant computers capable of performing billions of logical operations without failure. But they have already crossed a threshold: they allow us to explore certain physical systems on a scale that classical computation can no longer accurately reproduce. IBM claims to have deployed more than 90 quantum systems since its first five-qubit processor became available in the cloud. On the French side, Pasqal is working on neutral-atom machines stemming from a scientific legacy that originated in Saclay, in the wake of the work of Alain Aspect, the 2022 Nobel laureate in Physics. <\/p>\n\n

The weak signal, therefore, is not merely a technological issue. It is a cultural one. Quantum computing is no longer the exclusive domain of a handful of physicists capable of communicating directly with the machine. It is beginning to become an accessible computing resource\u2014still specialized, still demanding, but available. <\/p>\n\n

Details<\/h2>\n\n

IBM is aiming to have a fault-tolerant quantum computer with 200 logical qubits by 2029, capable of performing up to 100 million operations. By the mid-2030s, the announced goal rises to 2,000 logical qubits and several billion operations. The difference is crucial: current physical qubits remain fragile; logical qubits address this fragility through their architecture. <\/p>\n\n

The Real Issue: Hybridization<\/h2>\n\n

It would be a mistake to think of quantum computing as a straightforward successor to classical computing. The first industrial applications will likely not involve tasks entrusted entirely to a quantum processor. Instead, they will take the form of hybrid systems combining CPUs, GPUs, supercomputers, and QPUs. <\/p>\n\n

This architecture says a lot about our current technological era. Artificial intelligence has established GPUs as the engines of mass computing, capable of processing immense volumes of data. Quantum computing, on the other hand, operates on a different playing field. Its strength lies instead in highly complex problems with relatively limited inputs and outputs: molecular simulation, material behavior, correlated systems, and partial differential equations. <\/p>\n\n

In other words, AI devours the visible world. Quantum computing seeks to calculate the invisible. <\/p>\n\n

Complementarity could become one of the most fruitful areas of research. AI sometimes lacks reliable data when it comes to chemistry or materials, because the underlying reality of these systems is, at its core, quantum. A quantum processor can generate new data\u2014data that more closely reflects the actual mechanics of a molecule or material\u2014before classical models can make use of it. This isn\u2019t a replacement. It\u2019s a bridge between two forms of computational intelligence. <\/p>\n\n

The First High-Value Territories<\/h2>\n\n

The sectors that are most proactive have already been identified: chemicals, materials, pharmaceuticals, finance, energy, and logistics. However, not all of them are at the same level of maturity. <\/p>\n\n

The simulation of materials and molecules seems to align most naturally with quantum physics. The promise here is almost organic: using a machine based on quantum laws to understand objects governed by those same laws. Research on proteins, catalysts, corrosion-resistant materials, and energy components fits into this framework. <\/p>\n\n

Finance, on the other hand, operates in a more ambiguous realm. Portfolio optimization, correlation modeling, and risk simulation involve complex structures that are sometimes similar to many-body problems in physics. But classical methods are already quite powerful in these areas. Quantum methods will therefore need to deliver more than just a marginal improvement. <\/p>\n\n

As for logistics and industrial production, they offer vast potential for optimization, but here again, the bar is set high. Conventional solutions are not weak; they are often very good. Quantum technology will not prevail simply because it is more fascinating; it will prevail when it becomes indisputably useful. <\/p>\n\n

Sovereignty as a Negotiating Position<\/h2>\n\n

Europe cannot treat quantum technology as merely a technological option. Part of its industrial sovereignty is at stake here, but this sovereignty must not be confused with self-sufficiency. The right model is that of a competent partner: having its own hardware, software, and scientific capabilities, while remaining integrated into the global ecosystem. <\/p>\n\n

This distinction is important. In the quantum realm, no one wins alone. Value chains span lasers, cryogenics, semiconductors, software, supercomputers, cloud platforms, and scientific talent. But those who bring nothing to the table don\u2019t negotiate\u2014they buy. <\/p>\n\n

Europe has real strengths: world-class laboratories, industrial players, data centers, and applied excellence. What it still needs to build is continuity between research, machines, use cases, and adoption by various industries. <\/p>\n\n

The Preparation Phase<\/h2>\n\n

Quantum computing is not yet an everyday tool. It\u2019s more like AI before it went mainstream: known to specialists, underestimated by many organizations, and difficult to translate into business practices. That is precisely why waiting would be a mistake. <\/p>\n\n

The companies that will reap the first benefits won\u2019t necessarily be the ones that buy the best machine. They will be the ones that have identified the right problems, built the right teams, and forged the right connections between research, IT, business units, and senior management. Quantum computing demands a new set of rules. These cannot be improvised once the machine becomes profitable. <\/p>\n\n

Herein lies the paradox: quantum computing has not yet realized its full potential, but the window of opportunity to learn about it is already open. In five years, it may be too late to explore the subject\u2014not because everything will have been figured out, but because the most advanced organizations will have already learned to ask the right questions. <\/p>\n\n

Quantum computing may not make a splash when it truly enters the corporate world. It will be hidden behind a simulation, an agent, a model, or a decision. Like GPUs before it, it will fade into the background as it becomes commonplace. And perhaps that is how truly transformative technologies really succeed: not when we admire them, but when we stop noticing them. <\/p>\n\n

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