Quantum computing promises to revolutionize industries from AI to drug discovery, but significant … More engineering challenges remain before we see practical applications.<\/p>\n
Adobe Stock<\/p>\n
From where we’re sitting today, it’s increasingly likely that quantum computing will be one of the most disruptive technologies on the medium-term horizon.<\/p>\n
Here\u2019s why: Harnessing the properties of matter as it behaves at the sub-atomic level \u2013 by taking advantage of strange phenomena like entanglement and superposition means certain types of computation can be vastly accelerated.<\/p>\n
These include:<\/p>\n
Solving vital real-world challenges such as artificial intelligence, drug and materials discovery, and cyber security all rely on these calculations. So, the impact of quantum computing is likely to be immense.<\/p>\n
There are some, though, who believe the reality is still some way off. Nvidia CEO Jensen Huang\u2019s views on this recently caused a mini-crash<\/a> in the stock price of quantum computing providers. His belief is that \u201cvery useful quantum computers\u201d could be 30 years away.<\/p>\n On the other hand, evidence shows that quantum computing is increasingly accessible. Most of the big cloud providers\u2014Google, Amazon, Microsoft\u2014offer quantum-as-a-service, along with a growing ecosystem of startups and disruptors such as D-Wave and IonQ.<\/p>\n So, what\u2019s the difference between what\u2019s available today and what will be available when quantum becomes really useful?<\/p>\n Today\u2019s Quantum Computers \u2013 The NISQ Era<\/strong><\/p>\n Although they\u2019re incredible feats of engineering, quantum computers today are plagued by a number of limitations. For this reason, the current era of quantum computing is dubbed the Noisy Intermediate Scale Quantum<\/a> (NISQ) era. Although improvements and breakthroughs are being made constantly, systems that are accessible today suffer from low fault tolerance, high rates of error caused by qubits decaying out of their quantum state, and extreme sensitivity to interference.<\/p>\n Most systems still rely on classical computing architecture to handle many tasks, which creates speed bottlenecks.<\/p>\n And while today\u2019s most powerful quantum computers have around 1,000 qubits, some predict that a scale of hundreds of thousands or even millions could be needed for advanced problems.<\/p>\n Adding new qubits isn\u2019t as easy as it sounds. In fact, it\u2019s a hugely complex engineering problem, as qubits have to be isolated from the outside world so they don’t decohere, and they have to be frozen to temperatures millionths of a degree above absolute zero.<\/p>\n In simple terms, today\u2019s technologies are largely experimental, proof-of-concept or prototypes. Although they are constantly improving, they aren\u2019t the scalable, robust systems needed for industrial applications.<\/p>\n Towards Quantum Supremacy <\/strong><\/p>\n While big challenges remain, some hugely significant strides have been taken in recent years.<\/p>\n Google recently announced<\/a> that it had developed revolutionary methods of improving the error tolerance of quantum computing by combining multiple qubits to make logical qubits.<\/p>\n New types of qubits, like photonic qubits and trapped ion qubits, are also showing promise when it comes to improving stability.<\/p>\n And breakthroughs have been made in the development of room-temperature qubits<\/a>, which could remove the expense of super-cooling from the equations.<\/p>\n Progress is also ongoing in building the infrastructure that needs to be in place for quantum to be truly useful once the power is available.<\/p>\n This involves creating quantum programming languages like Microsoft Q#, IBM Qiskit, or the open-source PennyLane<\/a>, as well as operating systems.<\/p>\n