Water surface wavelets

• DOI: 10.1145/3197517.3201336
• Publication Date: 2018-07-31T15:56:23Z
• Authors: Stefan Jeschke; Tomáš Skřivan; Matthias Müller-F...; Nuttapong Chentanez; Miles Macklin; Chris Wojtan
• Keywords: Nyquist–Shannon sampling theorem

The current state of the art in real-time two-dimensional water wave simulation requires developers to choose between efficient Fourier-based methods, which lack interactions with moving obstacles, and finite-difference or finite element handle environmental but are significantly more expensive. This paper attempts bridge this long-standing gap complexity performance, by proposing a new method that can faithfully simulate obstacles real time while simultaneously preserving minute details accommodating very large domains. Previous methods for simulating 2D waves directly compute change height surface, strategy imposes limitations based on CFL condition (fast require small steps) Nyquist's limit (small closely-spaced variables). proposes novel wavelet transformation discretizes liquid motion terms amplitude-like functions vary over space, frequency, direction , effectively generalizing local interactions. Because these variables much slowly space than original function, our drastically reduces Nyquist limit, allowing us highly detailed at visual resolutions. Our discretization is amenable fast summation easy parallelize. We also present basic extensions like pre-computed paths two-way solid fluid coupling. Finally, we argue provides convenient set artistic manipulation, illustrate wave-painting interface.