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Quantum Ray Marching for Reformulating Light Transport Simulation

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Author

Logan Mosier (University of Waterloo), Toshiya Hachisuka (University of Waterloo), Morgan McGuire (Roblox + University of Waterloo)

Venue

SIGGRAPH Asia 2023

Abstract

The use of quantum computers in computer graphics has gained interest in recent years, especially for the application to rendering. The current state of the art in quantum rendering relies on Grover’s search for finding ray intersections in 𝑂(√𝑀) for 𝑀 primitives. This quantum approach is faster than the naive approach of 𝑂(𝑀) but slower than 𝑂(log 𝑀) of modern ray tracing with an acceleration data structure. Furthermore, this quantum ray tracing method is fundamentally limited to casting one ray at a time, leaving quantum rendering scales for the number of rays the same as non-quantum algorithms. We present a new quantum rendering method, quantum ray marching, based on the reformulation of ray marching as a quantum random walk. Our work is the first complete quantum rendering pipeline capable of light transport simulation and remains asymptotically faster than non-quantum counterparts. Our quantum ray marching can trace an exponential number of paths with polynomial cost, and it leverages quantum numerical integration to converge in 𝑂(1/𝑁) for 𝑁 estimates as opposed to non-quantum 𝑂(1/√𝑁). These properties led to first quantum rendering that is asymptotically faster than non-quantum Monte Carlo rendering. We numerically tested our algorithm by rendering 2D and 3D scenes.