IBM scientists have unveiled two crucial advances toward the creation of a practical quantum computer: an effective way to detect and correct quantum errors, and the design of a silicon chip that can scale up to house a large number of entangled quantum bits.

The power of quantum computing

Transistors in classical computers can only shrink so far. The current generation of transistors is 14 nanometers in size, meaning that only about thirty silicon atoms fit between the transistor's "source" and "drain," the two ends of the electronic switch. Once that number gets reduced to only about four or five silicon atoms, the uncertainty brought on by quantum mechanic effects will make it impossible for such a switch to function properly. Electrons will spontaneously and randomly jump from one end of the other in unpredictable ways, creating a current even when the switch is off.

The idea behind quantum computers? – ?first advanced by Richard Feynmann in 1981? – ?is to harness quantum effects rather than see them as an obstacle. This is done not by building a more advanced transistor, but instead by harnessing the much greater potential of quantum information.

In the weird and wonderful world of quantum computing a quantum bit, or qubit, can assume two values (0 and 1) at the same time. When two or more qubits are linked in a special "entangled" state, this property extends out and the power of qubits grows exponentially. Ten fully entangled qubits would be able to store as much information as 1,024 classical bits; 33 qubits could store one gigabyte; and 300 fully entangled qubits would store as many classical bits as there are atoms in the universe.

Crucially, however, although the information the qubits contain grows exponentially, we'd still be able to manipulate it using a number of operations that is a polynomial function of the number of qubits. In other words – exponential speedups, in a very literal sense.

A quantum computer would not be universally faster for just any algorithm, but it would show exponential speedups for searching and manipulating big data, performing data cryptography, analyzing protein folding to design better drugs, simulating the early Universe, and providing much more accurate weather forecasting, among many other things.

Qubits are finicky

Our success in creating a practical quantum computer will largely depend on our ability to keep all qubits in the very delicate entangled state and correct mistakes effectively and reliably.