The Quantum Advantage

Why the Nobel Physics Prize arrives at a pivotal moment for quantum sciences, including computer-aided drug design

The 2025 Nobel Prize in Physics was awarded to John Clarke, Michel Devoret, and John Martinis “for the discovery of macroscopic quantum mechanical tunnelling and energy quantisation in an electric circuit”. This recognition arrived at a pivotal moment for quantum sciences, with several research groups recently claiming verifiable quantum advantage¹. 

This Nobel Prize builds directly on the themes and breakthroughs that were recognized by the 2022 prize, which was awarded to Alain Aspect, John Clauser, and Anton Zeilinger “for experiments with entangled photons, establishing the violation of Bell inequalities and pioneering quantum information science”. Their experiments demonstrated that quantum entanglement, a phenomenon in which particles remain correlated across distances, was a real, measurable effect and not just a theoretical curiosity. Whilst the work recognised by the 2022 award validated the existence and controllability of quantum entanglement, the research behind the 2025 award went on to demonstrate that quantum mechanical behaviours, like tunnelling and quantization, which were previously thought to be confined to atomic or subatomic scales, could be observed and harnessed in macroscopic systems. 

Quantum tunneling to the future

Quantum mechanics is a domain of physics that is defined by counterintuitive behaviours, many of which become observable only at the microscopic scale. Among these behaviours, quantum tunnelling stands out as one of the most accessible and easily visualisable. Often introduced early in quantum mechanics courses, tunnelling can be effectively illustrated through thought experiments and relatively friendly mathematics, making it a good entry point into understanding the quantum world. 

Put simply, quantum tunnelling shows that quantum objects can overcome potential energy barriers, even if they lack the energy to do so according to the laws of classical physics. However, this remarkable ability decays exponentially with the object’s mass and the height of the energy barrier. That’s why you won’t see a football passing through a wall anytime soon!

Tunnelling is used to explain subatomic phenomena, such as nuclear decay, and is exploited in technological applications, such as the scanning tunnelling microscope. In the 1980s, Clarke, Devoret, and Martinis at Berkeley proposed the revolutionary hypothesis that tunnelling could be observed not only at the atomic scale but also in macroscopic systems. To test this hypothesis, they designed an experiment involving two superconductors separated by a thin insulating barrier. In this setup, the electrons behave collectively and can be modelled by a shared wavefunction as a single particle. According to the laws of quantum mechanics, this wave function can travel through the barrier and exist on either side of it, allowing an electric current to flow between the superconductors with zero voltage. This is the defining feature of superconductivity, which was recognised by the 1973 Nobel Prize in Physics.

The Berkeley team demonstrated that when the current in the system reaches a critical threshold, a measurable voltage appears. This indicates a shift in the quantum state of the system, and this change was transmitted across the barrier separating the superconductors. The results demonstrated that quantum mechanics can be applied universally across different scales, and that the quantum states can be stable and observable in macroscopic systems.

The recognition of Clarke, Devoret, and Martinis by the Nobel Committee celebrated a landmark moment in quantum physics, but it also underscored the profound technological implications of their work. Their demonstration of macroscopic quantum tunnelling was a critical step towards developing scalable quantum computers, as well as other quantum technologies, from the first short-lived coherent quantum oscillations observed in 1999 to present-day quantum processors with multiple qubits. 

The field of quantum computing is quickly translating academic fundamental research into revolutionary applications, and in recent years, there have been several claims of quantum advantage, which is the ability of quantum computers to solve problems that traditional computers could not solve in a reasonable/realistic amount of time. However, it can be challenging to prove that true quantum advantage has been achieved and that a classical algorithm could never be used to solve the problem. In 2019, Google’s Sycamore quantum computer completed a task in under three and a half minutes that it was claimed would take a classical computer ten thousand years to perform, but in 2024, a powerful, classical supercomputer was able to complete the same task in under 15 seconds.

In September, researchers at the University of Texas at Austin and Quantinuum reported an unconditional quantum advantage by demonstrating that a task that required 12 qubits for a quantum computer would require 62–382 classical bits to replicate. They proved that no classical algorithm could close this gap, even with future improvements, and termed this form of quantum advantage “quantum information supremacy”. This work was quickly followed by a paper from an international group from Denmark, the US, Canada, and South Korea that reported the first proven quantum advantage for a photonic system, using entangled light to perform a learning task 11.8 orders of magnitude faster than any classical method. More recently, Google Quantum AI has announced the first verifiable (on another quantum system) quantum advantage on real hardware, using a 105-qubit chip called Willow and an algorithm known as Quantum Echoes to perform a computation about 13,000 times faster than the same task could be achieved on the most powerful classical supercomputers.

Benefits for drug discovery

These achievements suggest that quantum computing has the potential to fulfill its boldest promise: to make simulations that would be considered infeasible within the frameworks of classical computing accessible within reasonable time scales. The implications of quantum computing applied to a variety of technological and scientific fields are unprecedented, and drug discovery, specifically computer-aided drug design (CADD), would clearly benefit from the application of quantum computing.

Many typical CADD tasks can be classified as optimizations in high-dimensional spaces, analysis of large datasets to generate predictions, or simulations of complex biomolecules. Quantum computing could have a significant impact in this field, enabling the fast exploration of huge chemical spaces to hunt for new drugs, allowing the simulations of biomolecules at larger timescales than those currently accessible, or performing quantum simulations of molecular interactions that could enable more accurate modelling of protein-ligand binding. The CADD world is keenly awaiting this revolution, and many companies are exploring the application of quantum computing, as we discussed previously.

Despite the exciting possibilities of quantum computing, the current limitations, such as the fragility of qubits or the difficulties in efficiently developing algorithms tailored for quantum computing, remain a considerable obstacle to the application of this technology on a large scale. Nonetheless, those limitations are not insurmountable, and research will continue to push the boundaries of knowledge and expand the fields of technological feasibility. As the 2025 Nobel Prize for Physics demonstrates, the path connecting fundamental discoveries to large-scale applications is often perilous, but certainly not impossible, to walk.

Endnote: 1) The term “quantum supremacy” was originally used. This term was coined by John Preskill in 2011, but the name proved controversial, with many claiming that it raised distasteful comparisons with the racist white supremacy. The alternative term “quantum advantage” was proposed and is now the term most commonly used.