Many computing applications with large datasets are poised to benefit from the advent of the quantum computer and much of what the world does is based on the principles of mathematics – from simulation to application.
The trouble is, maths can be hard. Some calculations required for the effective simulation of real-life scenarios are simply beyond the capability of classical computers – what’s known as intractable problems.
Quantum computers, with their huge computational power, are ideally suited to solving these problems. Indeed, some problems, like factoring, are “hard” on a classical computer, but are “easy” on a quantum computer. This creates a world of opportunities, across almost every aspect of modern life.
Classical computers are limited in terms of the size and complexity of molecules they can simulate and compare (an essential process in early drug development). If we have an input of size N, N being the number of atoms in the researched molecules, the number of possible interactions between these atoms is exponential (each atom can interact with all the others).
Quantum computers will allow much larger molecules to be simulated. At the same time, researchers will be able to model and simulate interactions between drugs and all 20,000+ proteins encoded in the human genome, leading to greater advancements in pharmacology.
Quantum technologies could be used to provide faster, more accurate diagnostics with a variety of applications. Boosting AI capabilities will improve machine learning – something that is already being used to aid pattern recognition. High-resolution MRI machines will provide greater levels of detail and also aid clinicians with screening for diseases.
Targeted treatments, such as radiotherapy, depend upon the ability to rapidly model and simulate complex scenarios to deliver the optimal treatment. Quantum computers would enable therapists to run more simulations in less time, helping to minimise radiation damage to healthy tissue.
One potential application for quantum technologies is algorithmic trading – the use of complex algorithms to automatically trigger share dealings based on a wide variety of market variables. The advantages, especially for high-volume transactions, are significant.
Like diagnostics in healthcare, fraud detection is reliant upon pattern recognition. Quantum computers could deliver a significant improvement in machine learning capabilities; dramatically reducing the time taken to train a neural network and improving the detection rate.
Quantum computers will have the ability to aggregate and analyse huge volumes of consumer data, from a wide variety of sources. Big data analytics will allow commerce and government to precisely target individual consumers, or voters, with communications tailored to their preferences; helping to influence consumer spending and the outcome of elections.
With so many variables to consider, accurate weather forecasts are difficult to produce. Machine learning using quantum computers will result in improved pattern recognition, making it easier to predict extreme weather events and potentially saving thousands of lives a year.
Climatologists will also be able to generate and analyse more detailed climate models; proving greater insight into climate change and how we can mitigate its negative impact.
Improved data analysis and modelling will enable a wide range of industries to optimise workflows associated with transport, logistics and supply-chain management. The calculation and recalculation of optimal routes could impact on applications as diverse as traffic management, fleet operations, air traffic control, freight and distribution.