New Scientist
Quantum computers are edging closer to changing the game. Using quirky quantum bits, they promise breakthroughs in drug discovery, energy, and materials science. Though still error-prone and tough to scale, rapid progress is being made. The biggest challenge now? Figuring out exactly which real-world problems they’ll solve better than today’s powerful supercomputers.
What exactly would a full-scale quantum computer be useful for?
Author: Karmela Padavic-Callaghan
QUANTUM physics gets a bad rap. The behaviour of the atoms and particles it describes is often said to be weird, and that weirdness has given rise to all manner of esoteric notions – that we live in a multiverse, say, or that the reality we see isn’t real at all. As a result, we often overlook the fact that quantum physics has had a real effect on our lives: every time you glance at your smartphone, for instance, you are benefiting from quantum phenomena.
But the story of what quantum theory is good for doesn’t end there. As our mastery of quantum phenomena advances, a new of crop of technologies designed to harness them more directly promises to have a huge impact on science and society. While quantum teleportation and quantum sensing sound exotic and intriguing, the technology that holds the most transformative potential is the one you have probably already heard of: quantum computing.
If you believe the hype, quantum computers could accelerate drug development, discover revolutionary new materials and even help mitigate climate change. But while the field has come a long way, its future isn’t entirely clear. Engineering hurdles abound, for starters.
And what often gets lost in the race to overcome these challenges is that the very nature of quantum computing makes it difficult to know exactly what the machines will be useful for. For all the bombast, researchers are quietly confronting the same existential question: if we could build the quantum computer of our dreams tomorrow, what would we actually do with it?
It is easy to overlook the ubiquity of quantum physics in modern technology because of the scales at which it operates. Infinitesimally small things like particles exhibit quantum effects, such as sometimes behaving like waves, that don’t persist in macroscopic stuff. While an orange, for example, is made of atoms, which are quantum, you cannot cajole a piece of fruit to become a wave as you might with a single quantum particle. But when it comes to the many gadgets that we now take for granted, the quantum character of the individual electrons within them is crucial.
Take the transistor, the basic building block of modern electronics. These nanometre-sized semiconductors are how we control the flow of electrons inside of microprocessors. We make them by changing the geometry and makeup of silicon, stacking it in layers and spiking those layers with atoms of other elements. But it would be impossible to make an electron do anything in this way if you didn’t know that it sometimes behaves like a wave, which is about as quantum a behaviour as can be.
It is no exaggeration to say that the seemingly abstruse theory of quantum physics has transformed the way we live. Without quantum theory, there would be no fibre optics, no internet, no smartphones. But physicists have long suspected that another transformation could happen if we become able to build devices that not only benefit from quantum effects, but use them as their main resource.
Examples include quantum teleportation, which relies on a phenomenon called entanglement – where the states of two particles are correlated, regardless of how far apart they are. Researchers have already successfully teleported information over 100 kilometres through optical fibre cables and over 12,900 kilometres via satellite, and the idea is that this ability could underpin a faster, more secure quantum internet.
There is also quantum sensing, which promises orders of magnitude more sensitive measurements of all kinds that could then supercharge navigation, geological exploration and medical diagnostics. But the question remains whether these quantum technologies will ever transcend niche applications. Quantum computers, on the other hand, could have a much wider impact, just as their more traditional predecessors did.
Their potential is a result of the seemingly subtle distinction in the way the two kinds of computers work. In traditional processors, the key role of electrons is to encode information into a series of 1s and 0s, or bits, which can be interpreted as turning electric currents on and off. In a quantum processor, on the other hand, information is encoded into quantum properties of particles or atoms themselves – they are not stage hands that orchestrate computations, but rather its lead actors.
In the last five years, there have been remarkable advances in what’s possible in the lab
This is why quantum computers can handle more information at once than their classical counterparts. Quantum bits, or qubits, offer more encoding choices than just 1 or 0. To be clear, a qubit cannot simultaneously encode both, but it can occupy a “superposition” where it is effectively both and neither until it is measured. If this sounds strange, it is – and working out what quantum theory really means for the nature of reality is an ongoing puzzle (see “The meaning of quantumness”, page 35). In practice, though, these states make quantum computers very powerful. All numbers between 0 and 1023 can be encoded in just 10 qubits, while a traditional computer would need 1024 traditional bits to do the same.
The promise of quantum computing, then, is that in a scenario where a traditional computer runs out of resources while working on a calculation, a quantum machine would do just fine. Researchers have dreamed of such capabilities since the 1980s, and they have spent decades painstakingly building prototypes.
Quantum Supremacy
Now, their work seems to be paying off. The best quantum computers in existence today – some of which boast 1000 qubits, compared with the 50 we could muster a few years ago – can solve a select few proof-of-principle problems that would indeed be impossible for even the world’s best supercomputers, a feat of what researchers call “quantum supremacy”.
“In the last five years, there really have been pretty remarkable advances in what’s possible in the lab,” says David DiVincenzo at Forschungszentrum Jülich, a national research institution in Germany. “The bar keeps going up.” Almost 20 years ago, he proposed seven conditions for constructing a working quantum computer, now known as DiVincenzo criteria, and hundreds of researchers are racing to check them all off.
The pace of progress has been startling. “I’m surprised that in 2025 we’ve reached this point [of advancement],” says Brian DeMarco at the University of Illinois Urbana-Champaign. But standing in our way is the fact that quantum states are inherently fragile. A qubit left on its own is liable to lose its special properties when exposed to even the tiniest disturbance in its environment. This means quantum computers tend to accumulate lots of small errors as they perform calculations, rendering their outputs unreliable. So, the race to build a useful quantum computer is, to a great extent, the race to build one that is “fault-tolerant”. Scaling up the number of qubits involved will be important too, because the computational power of a quantum computer increases with the number of reliable qubits.
The good news is that several different ways of making qubits – from assembling them out of superconducting circuits to using cold atoms controlled by lasers – have made a big difference to how well we can stabilise them. “There have been a lot of really creative developments,” says DeMarco.
More will surely be needed. When he imagines a million-qubit device, DiVincenzo says he envisages whole rooms filled with machinery, not unlike those in particle-collider facilities like the Large Hadron Collider at CERN in Switzerland. A quantum computer comprising a million superconducting qubits would have to be housed in a massive fridge because those qubits only work at incredibly low temperatures, and its control system would require thousands of wires. Similarly, scaling up a quantum computer made from extremely cold atoms could require thousands of lasers. One solution may be to connect many smaller quantum computers into one machine instead.
But what may really hold us back from truly transformative applications – and what often gets overlooked in coverage of fault-tolerant quantum computers – is that we don’t know what sorts of problems these devices will be best suited to tackle. That’s difficult to divine because the details of the quantum laws that govern qubits make it hard to take full advantage of a quantum computer’s seemingly gargantuan computational power. Superposition states, where a qubit is neither encoding just 1 nor just 0 at once, invites the mental image of the quantum computer running calculations with both values in parallel. The reality is much more subtle and practically challenging, says Māris Ozols at the University of Amsterdam in the Netherlands.
What really sets apart a qubit in a superposition from a classical bit is that it is possible to tell whether a bit is encoding 1 or 0 with 100 per cent probability. Whereas for the qubit, it may only be possible to say that upon measuring it, you will find 1, say, 30 per cent of the time. Calculations on quantum computers are sequences of changes to their qubits’ states. If those states are superpositions, and if they are correlated with each other, that can benefit the computation. But to read out what the quantum computer did, you have to measure those states. The measurement will produce different answers with different probabilities, but never all of them at once.
This means there are problems for which the quantum approach doesn’t guarantee a faster path to a solution. In determining whether a random string of 0s and 1s has an odd or even number of 1s, for instance, a classical and a quantum computer would both take the same amount of time. Choosing the correct problem, and the correct algorithm for implementing it, is crucial for making the most of quantum computers’ potential. It also happens to be very difficult.
Mathematical disciplines such as complexity theory may offer some hints about what sort of problems may be solved on quantum computers with the most significant speed-ups compared with the classical approach. But the truly great quantum algorithms “are sort of rare jewels that one stumbles upon from time to time”, says Ozols. “There is no simple, unified method for building quantum algorithms. It’s more of an art.”
Until we have bigger quantum computers that make fewer errors, we are in something of a catch-22 situation. “We cannot run cutting-edge quantum algorithms yet, so development is happening in this kind of theory world where you’re developing algorithms and proving that they should work, but you are never able to practically check,” he says.
Even the most famous quantum computing algorithm (discovered by mathematician Peter Shor in 1994), which researchers are certain could break encryption keys that no traditional algorithm can, cannot be practically implemented on existing quantum computers because they are too small and error-prone. “We don’t have the ability to play around with algorithms on hardware,” says Ozols.
So what applications, and what impact on society, should we expect from quantum computers as they keep advancing? There is a case for optimism. In the past couple of years, several teams have made significant progress towards error-corrected quantum computers. For example, researchers at Google Quantum AI showed they can increase the number of qubits in their Willow quantum computer in such a way that the bigger machine actually makes fewer errors. This is exactly what is necessary to make large fault-tolerant machines. If that momentum continues, within a few years, quantum computers might be able to handle problems in chemistry and materials science with real-world applications, especially if used as part of a larger computing ecosystem, says DeMarco.
They could find use in figuring out the properties of molecules that could upgrade the catalysts in fuel cells or that may become an ingredient for the next generation of solar panels. In the field of materials science, they could help model and create better superconductors that transmit electricity losslessly, without having to be cooled.
Quantum computers could also boost drug discovery. In fact, they are already being used for calculations that help identify the best ways for drugs to bind to biological molecules and to predict which potential drug molecules may ultimately prove to be toxic. More ambitiously still, some researchers even want to run artificial intelligence programs on quantum computing hardware. Such programs aren’t a natural fit for quantum computers in the way that, say, chemistry is, and there is no consensus on how practical the proposal may be.
While those kind of advances may be a long way off, quantum computers are already making some progress. John Preskill at the California Institute of Technology in Pasadena says there have already been dozens of discoveries filling gaps in how we understand the inner workings of our world – what he calls “discoverinos”. These include insights into how chains of atoms develop magnetism, simulations of exotic “time crystals” that seem to stay in motion forever and studies of systems that can selectively resist the universe’s march towards increased disorder, or entropy.
For Aziza Suleymanzade at the University of California, Berkeley, quantum computing is worth pursuing regardless of what applications we can find in the near term. She points to the example of the Laser Interferometer Gravitational-Wave Observatory, which detects ripples in space-time made by cataclysmic events like black hole collisions. Adapting quantum methods for controlling light, not unlike those used in some quantum computer designs, led to a large increase in the frequency of these detections. The continued push to master quantum effects so comprehensively that we can build a million-qubit quantum computer is bound to have similar secondary effects, she says.
Ultimately, DeMarco says the uncertainty about which kinds of algorithms will work best on quantum computers makes it difficult to predict what impact they will have. Which isn’t to say they won’t change the world – more that we just aren’t quite certain how yet. DeMarco compares the question to asking someone who was building personal computers in the 1970s to predict the existence of the iPhone. “I’m actually the most excited about the things that we can’t foresee,” he says.
New Scientist video
Theorists discuss the past, present and future of quantum physics newscientist.com/video
1919 Physicist Hendrika Johanna van Leeuwen writes a thesis proposing that magnetism is also a quantum mechanical phenomenon.
1925 On the windswept island of Helgoland, Werner Heisenberg carries out a calculation that treats the electron’s characteristics not as single values, but as tables of values. In this, his supervisor, Max Born, spots a key truth of quantum mechanics (see “Quantum theory’s unsung hero”, page 29).
1926 Erwin Schrödinger develops an alternative quantum framework that paints electrons as waves using a mathematical construct called the wave function.
1935 Schrödinger devises a thought experiment in which a cat in a closed box may be considered both alive and dead while it is unobserved. Einstein, Nathan Rosen and Boris Podolsky write a paper on quantum entanglement, which links two particles even when separated by vast distances. They argue that entanglement implies quantum mechanics is incomplete.
1938 Using ideas from quantum theory, Lise Meitner and Otto Hahn discover nuclear fission, the process that would undergird the development of nuclear power – and nuclear bombs.
1950 Julian Schwinger, Richard Feynman, Freeman Dyson and Shinichiro Tomonaga develop the modern form of quantum electrodynamics, explaining how light and matter interact. It forms the basis of modern particle physics.
Credits: TCA, LLC.