IBM has created a 17-qubit quantum computer and is making plans to timeshare the machine with other companies via cloud computing. While this is an important step, it isn`t quite enough to make quantum computers truly competitive compared to supercomputers. What will it take to bring quantum computing into the commercial realmand how long until we get there?
Classical computing has been around for many years and has completely transformed the human race. Near instant communication between any two individuals used to be a dream. The idea of large calculations being done faster than you can blink was unimaginable. The concept of free information and education was too much for any University to handle.
But it comes as no surprise that, now that these concepts are a reality, we`ve become dependent on them. This dependence places pressure on the industry to produce more powerful devices with every passing year. This was not an issue in the past since silicon devices were easy to scale down. But, with transistor gates as small as one-atom thick, shrinking may no longer be possible. Silicon, the building block of modern semiconductors, is already being phased out by Intel and future devices using feature sizes of 7nm and smaller will instead be made from materials such as Indium-Gallium-Arsenide (InGaAs).
One solution for increasing computational power is the use of quantum computers (though their creation isn`t likely to allow faster consumer devices). A common application is reliant on control flow, discrete mathematics, and IO handling. A quantum computer, however, is designed to solve statistical problems and scenarios which involve large amounts of data. The best way to understand it is to compare a classical processor (such as an i7) to an imaginary quantum processor (iQ7 for example). The i7 could add 1000 numbers together much faster than the q7, but the q7 could solve a game (such as checkers) much faster than the i7 due to the possible number of moves that the game possesses.
So why are quantum computers so good at parallel data crunching?
A classical computer is made up of transistors which handle two possible states: on (1) and off (0). For each additional bit, the amount of information that can be represented is equal to 2n where n is the number of bits. For example, four bits can represent one of 16 possible states and eight bits can represent one of 256 possible states.
By comparison, a quantum bitor qubitcan hold three states: on (1), off (0), and a superposition state. While the on and off states behave in an identical manner to classical bits, the superposition is what drives quantum computation. This superposition is a linear probability that lies between 0 and 1, allowing four qubits to represent all 16 different states at the same time where each one of those 16 states has a complex amplitude reflecting its probability of being observed.
IBM`s 17-Qubit Computer
So it`s pretty obvious that quantum computing provides many advantages over classical computers for complex, parallel data processing. While such tasks are not commonly found in the everyday device, they are almost too common in many different industries, including financial data processing, insurance, scientific models, oil reserves, and research. Currently, supercomputers are used for such parallel data processing but, if a quantum option were available, it`s a safe bet that each of these sectors would do anything to get one.
This has been one of the major drives in quantum computer technology with many companies trying to produce such a machine. For example, D-Wave Systems have their series of specialized quantum annealing processors, while many other researchers and companies are trying to find methods of producing universal quantum gates.
However, IBM has just taken the lead with their 17-qubit quantum computer.
What makes the IBM quantum computer a game changer is that it is a universal quantum computer as opposed to being a highly specialized device. Many other quantum systems currently available are usually of the annealing persuasion, which is good for optimization problems but not for other quantum problems such as database searches. The IBM machine, however, can be configured to execute just about any quantum problem.
IBM has decided to sell time on the computers to business and researchers alike through their IBM Q program accessed via the internet (i.e., over the cloud). This will allow developers and researchers to create a quantum program anywhere around the world and then have it executed with the press of a button.
50 Is the Magic Number
IBM`s made strides with its previous 5-qubit quantum computer. This 17-qubit machine is obviously yet another milestone. However, many say that even a 17-qubit computer is not good enough because classical computers can still process the same information in a smaller time frame. In fact, it has been stated that classical computers can model quantum computers up to 50 qubits in size. This means that, for a quantum computer to become better at solving quantum related problems than a classical computer, it has to contain at least 50 qubits. Of course, this assumes that such quantum computer simulations on classical computers do not improve.
So Google is ambitiously planning to release a 49-qubit quantum computer by the end of this year. Considering the size difference between the IBM machine and the proposed Google machine, however, it`s likely safe to assume that Googles machine may not be entirely universal.
An Attainable Future
It`s safe to say that quantum computers, despite becoming increasingly more powerful, are still very far away from being commercially available. IBM`s cloud-based scheme, however, does technically place quantum computing into the commercial realm.
Supercomputers are still very powerful compared to quantum computers and their cost-to-performance ratio makes them highly economical. But, unlike fusion power (which is always 20 years away), quantum computers really could make their debut when either IBM or Google release the world`s first 50-qubit computer.
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