Quantum Natural Language Generation on Near-Term Devices

The emergence of noisy medium-scale quantum devices has led to proof-of-concept applications for quantum computing in various domains. Examples include Natural Language Processing (NLP) where sentence classification experiments have been carried out, as well as procedural generation, where tasks such as geopolitical map creation, and image manipulation have been performed. We explore applications at the intersection of these two areas by designing a hybrid quantum-classical algorithm for sentence generation. Our algorithm is based on the well-known simulated annealing technique for combinatorial optimisation. An implementation is provided and used to demonstrate successful sentence generation on both simulated and real quantum hardware. A variant of our algorithm can also be used for music generation. This paper aims to be self-contained, introducing all the necessary background on NLP and quantum computing along the way.

Investigating the usefulness of Quantum Blur

Though some years remain before quantum computation can outperform conventional computation, it already provides resources that be used for exploratory purposes in various fields. This includes certain tasks for procedural generation in computer games, music and art. The Quantum Blur method was introduced as a proof-of-principle example, to show that it can be useful to design methods for procedural generation using the principles of quantum software. Here we analyse the effects of the method and compare it to conventional blur effects. We also determine how the effects seen derive from the manipulation of quantum superposition and entanglement.