In June, an IBM computing executive claimed that quantum computers were entering the “utility phase,” where high-tech experimental devices become useful. In September, Australia’s chief scientist Cathy Foley went so far as to declare the “dawn of quantum time”.
This week, Australian physicist Michelle Simmons won the country’s top science prize for her work developing silicon-based quantum computers.
Clearly, quantum computers are having a moment. But – to take a step back a bit – what exactly is the?
What is a quantum computer?
One way to think about computers is in terms of the kind of numbers they work with.
The digital computers we use every day rely on integers (or integer), which represent information as strings of zeros and ones that they rearrange according to complicated rules. There are also analog computers, which represent information as continuously varying numbers (or real numbers), manipulated via electrical circuits or spinning rotors or moving fluids.
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In the 16th century, the Italian mathematician Girolamo Cardano invented another kind of number called complex numbers to solve seemingly impossible tasks such as finding the square root of a negative number. In the 20th century, with the advent of quantum physics, it turned out that complex numbers also naturally describe the fine details of light and matter.
In the 1990s, physics and computer science collided when it was discovered that some problems could be solved much faster with algorithms that work directly with complex numbers encoded in quantum physics.
The next logical step was to build devices that work with light and matter to do these calculations for us automatically. This was the birth of the quantum computer.
Why is quantum computing important?
We tend to think of the things our computers do in terms that matter to us—balance my spreadsheet, broadcast my live video, find my ride to the airport. But all of these are ultimately computational problems, formulated in mathematical language.
Because quantum computers are still a nascent field, most of the problems we know quantum computers will solve are couched in abstract mathematics. Some of these will have “real world” applications that we cannot yet predict, but others will have a more immediate impact.
An early application will be cryptography. Quantum computers will be able to crack today’s internet encryption algorithms, so we will need quantum-resistant cryptographic technology. Certainly secure cryptography and a full quantum internet would use quantum computing technology.
In materials science, quantum computers will be able to simulate molecular structures at the atomic scale, making it faster and easier to discover new and interesting materials. This could have significant applications in batteries, pharmaceuticals, fertilizers, and other chemistry-based domains.
Quantum computers will also speed up many hard optimization problems, where we want to find the “best” way to do something. This will allow us to tackle larger problems in areas such as logistics, finance and weather forecasting.
Machine learning is another area where quantum computers can accelerate progress. This could happen indirectly, by speeding up subroutines in digital computers, or directly if quantum computers can be reimagined as learning machines.
What is the current landscape?
By 2023, quantum computing will move out of the basement laboratories of university physics departments and into industrial research and development facilities. The move is backed by checkbooks from multinationals and venture capitalists.
Contemporary quantum computing prototypes—built by IBM, Google, IonQ, Rigetti, and others—are still a long way from perfection.
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Today’s machines are modest in size and prone to error, in what has been called the “noisy mesoscale quantum phase” of development. The sensitive nature of small quantum systems makes them prone to many sources of error, and correcting these errors is a major technical hurdle.
The holy grail is a large-scale quantum computer that can correct its own errors. An entire ecosystem of research factions and commercial enterprises is pursuing this goal via various technological approaches.
Superconductors, ions, silicon, photons
The current conductive method uses loops of electric current inside superconducting circuits to store and manipulate information. This is the technology adopted by Google, IBM, Rigetti and others.
Another method, “trapped ion” technology, works with groups of electrically charged atomic particles, using the particles’ inherent stability to reduce errors. This approach has been led by IonQ and Honeywell.
A third avenue of exploration is to confine electrons in tiny particles of semiconductor material, which can then be fused into the well-established silicon technology for classical computing. Silicon Quantum Computing pursues this angle.
Another direction is to use individual light particles (photons), which can be manipulated with high reliability. A company called PsiQuantum designs intricate “controlled light” circuits to perform quantum computations.
There is no clear winner yet among these technologies, and it may well be a hybrid strategy that ultimately prevails.
Where does the quantum future take us?
Trying to predict the future of quantum computing today is akin to predicting flying cars and ending up with cameras in our phones instead. Still, there are some milestones that many scientists agree are likely to be reached in the next decade.
Better error correction is a big one. We expect to see a transition from an era of noisy devices to small devices that can sustain computations through active error correction.
Another is the advent of post-quantum cryptography. This involves the establishment and adoption of cryptographic standards that cannot be easily broken by quantum computers.
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Commercial spin-offs of technologies such as quantum sensing are also on the horizon.
The demonstration of a real “quantum advantage” will also be a likely development. This presents a compelling application where a quantum device is arguably superior to the digital alternative.
And a stretch goal for the next decade is the creation of a large-scale error-free quantum computer (with active error correction).
Once this is achieved, we can be sure that the 21st century will be the “quantera”.
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