Compared to the relatively low attention quantum computing received just over a decade ago, it is astounding to see it dominate global headlines and become a conversation starter that can rival top-dollar news stories. So, what has really changed in the quantum universe and why is it suddenly the cynosure of the world?
Looking around at our increasingly digitalised reality can give you some inkling of the why.
Tech-enabled countries around the globe are racing against time to build a viable quantum computer that can exponentially increase the computational power we now have at our disposal to execute several complex challenges that have so far been intractable for classical computers.
Clearly, in a world where speed is of the essence, a quantum computer could be a distinct game-changer in working out permutations and combinations to various scenarios and arriving at the best one instantly. Incredible volumes of data are generated every day 2.5 quintillion bytes of data today and by 2025, this number is projected to surge to 463 exabytes (1,0006 bytes) per day that need to be analysed and quantified. Can you imagine what an imperative solution a quantum computer can be in the future? There is no doubt about it in an era of big data analytics, this is a tool that may well be key to ensuring business perpetuity.
Of course, a quantum computer is not the solution to all ills that ail our world classical computers are much better at tackling some types of data emails and spreadsheets, for instance, and desktop publishing. However, quantum computers are unbeatable when it comes to solving optimisation problems with relevance in a variety of applications, from alleviating climate change to finding the best routes to a certain destination, or even when it comes to scheduling flights at airports.
While a full-fledged quantum computer is still not a reality we now have several algorithms developed for quantum computers including Grover’s for searching an unstructured database and Shor’s for factoring large numbers.
A strategic advantage
Quantum algorithms are expected to offer a strategic advantage over their classical peers in the niche domains of AI and machine learning through solving large systems of equations linear, non-linear and differential.
This bodes well for the UAE’s oil and gas industry, for instance as it includes in its sweep the complicated equations used in fluid dynamical simulations for ground and offshore reservoir explorations with sound waves. Explorers measure the returning signal from the ocean which allows them to topographically reconstruct the ocean soil structure and identify new offshore oil or gas reservoirs. As you can imagine, the predictable challenge here is the extensive computation needed to find the answers quickly and ensure a seamless process. While oil and gas behemoths around the world have already begun to work with these fluid dynamical simulations, non-linear simulations are gaining the interest of the aircraft design industry as well.
Scientists working in the agricultural sector are keenly exploring and applying quantum simulations in the efficient production of fertilisers. The production of FeMoco, the primary cofactor of nitrogenase, an enzyme used to catalyse the conversion of Nitrogen molecules from the atmosphere into ammonia is a case in point. The process used today is an extremely energy-intensive method known as Haber process 2.
Scientists working in the agricultural sector are keenly exploring and applying quantum simulations. (Photo: Getty)
However, certain anaerobic bacteria in the roots of plants are capable of performing the same task with minimal energy costs, suggesting that there might be a more efficient way to synthesize this enzyme at a large scale. While FeMoco’s electronic structure is far too complex for classical simulations, even beyond the capacity of our best supercomputers today, such simulations would be easily quantifiable for even a moderate scale quantum computer able to run around 200 qubits. So many more similar problems related to the simulation of complex molecules such as protein folding are set to explode with the coming of quantum.
In pharmaceuticals, the discovery of new drugs and personalised medicine targeted at an individual’s genome will suddenly become simple. Likewise, research in material science will receive a shot in the arm and likely lead to the discovery of new materials, with a better understanding of room-temperature superconductivity, or more efficient batteries.
A promising and more near-term use case for quantum algorithms is in the world of finance – portfolio optimisation, finding the best selection of assets that maximises the expected return while minimising the risk. With Dubai and the wider UAE vying to become a leading financial hub for the Middle East region, quantum can offer possibilities we could otherwise have only dreamed of. The portfolio optimisation problems can, in principle, be encoded into a quantum state of multiple qubits to seamlessly find a solution at a fraction of the time it can otherwise take.
Possibilities abound for such combinatorial optimisation in the field of logistics a potential growth sector for the future. For instance, supply chain optimisation – the optimal scheduling of automated processes in production lines, and network optimisation – from route planning to crew scheduling – are critical not just to the airline industry but literally, any sector that has a high degree of automation.
At Quantum Research Centre, TII, our effort is to bridge the existing gap between current quantum hardware and abstract quantum software from an algorithmic perspective. We are exploring practical ways to run useful quantum algorithms. Multiple systems today, from physics to finance, are too complex to be analysed with full precision, requiring us to resort to statistics to predict their properties efficiently.
The Monte Carlo methods, as they are known, help generate evolving samples according to the process in question, and then estimate the desired quantity by finding the statistical average of the produced samples. Quantum algorithms allow for quadratic speed-ups in the run-time required to calculate those averages, meaning that classical computers take a time that is quadratically longer.
Unfortunately, they also require unrealistically large quantum circuits, well outside the scope of near-term quantum devices. We are grappling with these and similar problems as we advance towards building the region’s first quantum computer.
With several countries, including China, the US, Canada, Singapore and those in Europe as well as technology leaders, including IBM and Google in the fray, announcing ambitious quantum computers with phenomenal powers, the day when the world does manage to benefit from accrued quantum gains, may not be too far off.