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very limited. To see the spectacular speedups we have to concentrate on problems not in the<br />

classical computational class P(although quantum algorithms may be faster). Many believe<br />

that quantum algorithms solving NP-complete problems in polynomial time do not exist,<br />

even though no proof of this assertion is available at this time. Shor argues that if we assume<br />

that no polynomial time quantum algorithms exist for solving NP-complete problems, then<br />

the class of problems we have to search for is neither NP-complete, nor P, and the population<br />

of this class is relatively small.<br />

2.6 Classical vs Quantum Error Correction<br />

Classical error correction operates by the judicious use of redundancy, that is, making the<br />

system larger in order to make it more resilient to perturbations. A good encoding should<br />

1. make transmission resilient to errors,<br />

2. reduce the amount of data transmitted through a channel, and<br />

3. ensure information confidentiality.<br />

The type of redundancy, or encoding, employed must be carefully chosen according to<br />

the type of noise it wants to fight. The simplest example is the Repetition Code which is<br />

given by the map 0 → 000, 1 → 111. The information can be decoded with majority logic:<br />

If the majority of the three bits is 0, output 0, otherwise output 1.<br />

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