With quantum computing emerging as a possible outlet for uncharted business innovation, the new ‘Quantum Tortoise and the Classical Hare‘ framework from MIT cites the notion that quantum computers must meet two conditions to yield an improvement on classical machines.
Firstly, says the study, quantum computers must be powerful enough to solve an issue (feasibility); their currently small size by comparison only allows for solutions to experiment-orientated, so-called ‘toy problems’ such as factoring numbers so low that using a classical computer makes more sense.
Second, such machines must gain enough of an advantage from their algorithm that problems can be solved in less time than it would take traditional computers.
Adhering to these conditions enables businesses looking to invest in quantum going forward to determine whether such spending and usage would drive value in the long run.
According to researchers, the new framework will be able to be used across multiple sectors, including automotive, chemistry, and finance.
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“Many business leaders are looking to quantum computing as the promising successor to classical computing, but research shows — and leaders in quantum computing agree — it will continue to underperform classical computing in many areas,” said co-author Neil Thompson, research scientist at MIT Sloan and the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL).
“As a result, to understand where quantum computing will perform better first requires understanding why it can be.
“We need to consider the speed of the computer versus the route. Thinking of it like a race, in getting from point A to point B, the algorithm is the route.
“If the race is short, it may not be worth investing in better route planning. For it to be worth it, it has to be a longer race.”
As well as being smaller across the board, quantum computers need to be kept at near absolute zero Kelvin, or -273.15°C in order to function, and hardware tends to runs slower, completing fewer operations per second.
However, companies across many industries have been found to be exploring how Shor’s algorithm — among the few quantum-specific systems that are widely known — can fare versus classical computers, with possible near-term advantage currently deemed limited to large-scale challenges.
This work is part of a larger collaboration between Accenture and the MIT Initiative on the Digital Economy, and is funded by Accenture.
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