Speaker
Description
Efficient database operations are crucial for processing inherently structured data. We investigate the transfer of classical database operations to their counterparts on uniform quantum superposition states of quantum data. Such data may originate from future experiments that incorporate quantum sensors and quantum memories, or by using quantum encoded classical data. Since quantum states cannot, in general, be copied or perfectly cloned due to the no-cloning theorem, and because certain operations may entangle subsystems, the transferred classical database operations become non-trivial. The algorithms we present are of interest for efficient state preparation and allow for online update mechanisms, enabling one to utilize an initially prepared state and incoming time series data. We consider indexed superposition states as our database model, with indices being in superposition. For this state, we evaluate the scaling in gate count and circuit depth of our extension method, which doubles the number of indices in superposition each time an ancilla is added while preserving existing data.