Pierre Fromholz

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.