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DTSTAMP:20260114T163633Z
LOCATION:Darling Harbour Theatre\, Level 2 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231212T093000
DTEND;TZID=Australia/Melbourne:20231212T124500
UID:siggraphasia_SIGGRAPH Asia 2023_sess209_papers_281@linklings.com
SUMMARY:Quantum Ray Marching for Reformulating Light Transport Simulation
DESCRIPTION:Logan Mosier (University of Waterloo); Morgan McGuire (Roblox,
  University of Waterloo); and Toshiya Hachisuka (University of Waterloo)\n
 \nThe use of quantum computers in computer graphics has gained interest in
  recent years, especially for the application to rendering. The current st
 ate of the art in quantum rendering relies on Grover's search for finding 
 ray intersections in $O(\sqrt{M})$ for $M$ primitives. This quantum approa
 ch 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, t
 his quantum ray tracing method is fundamentally limited to casting one ray
  at a time, leaving quantum rendering scales for the number of rays the sa
 me as non-quantum algorithms. We present a new quantum rendering method, q
 uantum ray marching, based on the reformulation of ray marching as a quant
 um random walk. Our work is the first complete quantum rendering pipeline 
 capable of light transport simulation and remains asymptotically faster th
 an non-quantum counterparts. Our quantum ray marching can trace an exponen
 tial number of paths with polynomial cost, and it leverages quantum numeri
 cal integration to converge in $O(1/N)$ for $N$ estimates as opposed to no
 n-quantum $O(1/\sqrt{N})$. 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.\n\nRegistr
 ation Category: Full Access, Enhanced Access, Trade Exhibitor, Experience 
 Hall Exhibitor\n\n
URL:https://asia.siggraph.org/2023/full-program?id=papers_281&sess=sess209
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