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IEEE International Conference on Quantum Computing and Engineering (QCE)

Towards Hybrid Spatial Structure Rendering Models Using Quantum Orthographic Ray Casting

Zirui Zhang

Published Aug 30, 2025• 0 citations

Abstract

Ray tracing is a fundamental technique in computer graphics used to render realistic images by simulating light interactions with objects, known as primitives. With the rise in popularity of quantum computing, new techniques have been developed to accelerate these computationally intensive tasks, with the potential of significant speedup over classical approaches. Traditional ray tracing relies on detailed ray casting and intersection tests between rays and scene primitives, which can be extremely time-consuming for complex scenes. Grover's algorithm for unordered search has demonstrated potential quadratic speedups in unstructured search problems, creating novel approaches to accelerate intersection detection in graphics. This work aims to contribute to the practicality of quantum search techniques for hybrid ray tracing pipelines to accelerate intersection tests. We propose two hybrid approaches: a uniform spatial division method employing a 3D Digital Differential Analyzer (DDA) for rapid grid traversal and an octree traversal scheme that recursively refines the search space using hybrid leaf node detection. Our methods build upon existing quantum orthographic ray-casting algorithms to efficiently identify cells or primitives where intersections occur before applying classical refinement through detailed intersection tests using orthographic projection. Our approach extends previous quantum ray casting techniques by adapting them to complex spatial data structures and scene representations, offering theoretical runtime improvements in optimal cases. These results demonstrate how quantum computing can enhance traditional computational rendering pipelines. As quantum hardware continues to evolve, we hope these hybrid techniques will offer alternative solutions for realistic rendering, inspiring further interdisciplinary research for quantum computation in computer graphics.

DOI: 10.1109/qce65121.2025.00261

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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 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 . 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.

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Quantum computing holds the potential to solve problems that are practically unsolvable by classical computers due to its ability to significantly reduce time complexity. We aim to harness this potential to enhance ray casting, a pivotal technique in computer graphics for simplifying the rendering of 3D objects. To perform ray casting in a quantum computer, we need to encode the defining parameters of primitives into qubits. However, during the current noisy intermediate-scale quantum (NISQ) era, challenges arise from the limited number of qubits and the impact of noise when executing multiple gates. Through logic optimization, we reduced the depth of quantum circuits as well as the number of gates and qubits. As a result, the event count of correct measurements from an IBM quantum computer significantly exceeded that of incorrect measurements.