Expanding data encoding patterns for quantum algorithms
2021 IEEE 18th International Conference on Software Architecture …, 2021•ieeexplore.ieee.org
As quantum computers are based on the laws of quantum mechanics, they are capable of
solving certain problems faster than their classical counterparts. However, often algorithms
which a theoretical speed-up assume that data can be loaded efficiently. In general, the
runtime complexity of the loading routine depends on (i) the data encoding that defines how
the data is represented and (ii) the data itself. In some cases, loading the data requires at
least exponential time which destroys a potential speed-up. And especially for the first …
solving certain problems faster than their classical counterparts. However, often algorithms
which a theoretical speed-up assume that data can be loaded efficiently. In general, the
runtime complexity of the loading routine depends on (i) the data encoding that defines how
the data is represented and (ii) the data itself. In some cases, loading the data requires at
least exponential time which destroys a potential speed-up. And especially for the first …
As quantum computers are based on the laws of quantum mechanics, they are capable of solving certain problems faster than their classical counterparts. However, often algorithms which a theoretical speed-up assume that data can be loaded efficiently. In general, the runtime complexity of the loading routine depends on (i) the data encoding that defines how the data is represented and (ii) the data itself. In some cases, loading the data requires at least exponential time which destroys a potential speed-up. And especially for the first generation of devices that are currently available, the resources (qubits and operations) needed to encode the data are limited. Therefore, understanding the consequences of a particular data encoding is crucial. To capture knowledge about different encodings, we present two data encoding patterns that extend our previous collection of encoding patterns [1].
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