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.
João S. Ferreira, Spencer S. Topel, Pierre Fromholz et al.
Traditional light rendering techniques treat the optical properties of materials as static, yet this assumption breaks down in cases where these properties dynamically evolve in response to incident illumination. We present a novel shading framework that combines classical ray-tracing with a quantum collision model to explore the effect of coherent light-matter interactions in rendering. By treating incident light and material excitations as quantized modes, we model sub-surface scattering as a sequence of symmetry-constrained unitary collisions. This formulation allows for the incorporation of non-integrable dynamics and chaotic optical responses due to multi-layer interference effects. We demonstrate how these collision operators can be pre-computed using near-term quantum computers to generate standard BSDFs, enabling the rendering of new physics-inspired materials with distinct optical signatures.
João S. Ferreira, Pierre Fromholz, Hari Shaji et al.
Reservoir computing is a form of machine learning particularly suited for time series analysis, including forecasting predictions. We take an implementation of \emph{quantum} reservoir computing that was initially designed to generate variants of musical scores and adapt it to create levels of Super Mario Bros. Motivated by our analysis of these levels, we develop a new Roblox \textit{obby} where the courses can be generated in real time on superconducting qubit hardware, and investigate some of the constraints placed by such real-time generation.
Though some years remain before quantum computation can fully outperform conventional computation, it already provides resources that can be used for exploratory purposes in various fields. This includes certain tasks for procedural generation in computer games, music and art. The so-called `Quantum Blur' method represents the first step on this journey, providing a simple proof-of-principle example of how quantum software can be useful in these areas today. Here we analyse the `Quantum Blur' method and compare it to conventional blur effects. This investigation was guided by discussions with the most prominent user of the method, to determine which features were found most useful. In particular we determine how these features depend on the quantum phenomena of superposition and entanglement.