Algorithms for preparing quantum states

State preparation is an essential part of quantum computing and much more complex than its analog in classical computing. For this reason, it is a topic in quantum computing that has attracted much attention since many algorithms need to recreate the initial state repeatedly during execution - which can compromise their efficiency. In contrast to dense states, many relevant states have the property that only a tiny part of the base states have non-zero coefficients (sparse quantum states). Many quantum algorithms need to prepare initial states or an instance of a problem. Depending on the problem instance, these states are also sparse; this includes solving quantum linear systems, for example. The project’s main objective is to investigate/propose methods to prepare sparse and dense states more efficiently and for various purposes.

Research supported by FACEPE (APQ 1621)