Top three: Quantum computing applications
Yesterday, Google confirmed the contents of a memo posted to (and then removed from) the NASA website in September, revealing that a team of researchers led by John Martinis had achieved “quantum supremacy”.
Quantum Supremacy is the development point at which a quantum computer is shown to be able to perform a task beyond the capabilities of even the most powerful supercomputer.
A calculation that reportedly would have taken IBM’s Summit - the world’s most powerful commercially available computer - around 10,000 years to complete was allegedly cracked in under four minutes by Google’s 53-qubit Sycamore machine. For unknown reasons, the computation wasn’t made with Google’s larger, more powerful 72-qubit Bristlecone machine.
Today, IBM (Google’s biggest rival in the quantum race) responded, casting doubt on Google’s achievement. Rather than 10,000 years, IBM argues that the task that Google used to benchmark quantum supremacy could have been accomplished in under three days on a classical computer, “and with far greater fidelity.”
IBM’s point is that the original definition of quantum supremacy given in 2012 by physicist John Preskill describes the point where quantum computers can do things that classical computers can’t. Therefore, IBM argues, this threshold has not been met.
Regardless of which company is ahead, or even if the race has been won already, widespread commercial applications for quantum computing that make IBM Watson look like a TI-82 are coming.
So, what do we even use them for?
Just like graphics processors are good at rendering lush, particle-packed digital worlds, but wouldn't know what to what to do with a simple data analysis task, there are some things that quantum computers are going to do better than anything else, and some things they cannot. Here’s Gigabit’s breakdown of the three applications for quantum computers that could have the biggest impact on everything from our day to day lives to the fate of hyperscale enterprises.
The biggest disruption - and why the finance industry is most nervous about a quantum dawn before it’s ready for one - would most likely be in the field of encryption. The increased power stemming from quantum computers’ ability to process computations in parallel - rather than sequentially like conventional machines - could render modern standards of encryption ineffective against a quantum cyber attack (single handedly the coolest three words I’ve ever strung together) potentially laying bare every aspect of the financial sector, the state secrets of world governments and the personal information of billions.
As a result of a growing unease over the potential obsolescence of modern security measures, the global quantum cybersecurity market is predicted to grow from around $101mn in 2018 to more than $506mn by 2023.
Currently, conventional computer analysis of weather conditions can sometimes take longer than the weather itself does to change. In the US, the head of the National Oceanic and Atmospheric Association’s Chief Economist, Rodney F. Weiher said estimated back in 2008 that nearly 30% of the country’s GDP (about $6trn) was directly or indirectly affected by the weather, which can impact agriculture, logistics, retail commerce and more.
A quantum computer’s ability to crunch vast amounts of data could lead to the sort of weather system modeling that could allow scientists to predict the changing weather patterns with never before seen accuracy - something that could become essential as climate change radically rewrites the predictable meteorology of our world.
According to IBM, one of the first and most promising applications of quantum computing will be in the field of chemistry. Even for simple molecules like caffeine, the number of quantum states in the molecule can be astoundingly large - so large that all the conventional computing memory and processing power that could ever be built couldn’t model it.
The ability for quantum machines to entertain the existence of both 1 and 0 simultaneously could provide the necessary power to successfully map and model increasingly simple molecules, catapulting our understanding of interactions forward dramatically, potentially opening a new era of pharmaceutical research.
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