Complete quantum-inspired framework for computational fluid dynamics
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | , , , , , , |
|---|---|
| Format: | Preprint |
| Publié: |
2023
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
| _version_ | 1866916776295530496 |
|---|---|
| author | Peddinti, Raghavendra D. Pisoni, Stefano Marini, Alessandro Lott, Philippe Argentieri, Henrique Tiunov, Egor Aolita, Leandro |
| author_facet | Peddinti, Raghavendra D. Pisoni, Stefano Marini, Alessandro Lott, Philippe Argentieri, Henrique Tiunov, Egor Aolita, Leandro |
| contents | Computational fluid dynamics is both a thriving research field and a key tool for advanced industry applications. The central challenge is to simulate turbulent flows in complex geometries, a compute-power intensive task due to the large vector dimensions required by discretized meshes. We present a full-stack method to solve for incompressible fluids with memory and runtime scaling poly-logarithmically in the mesh size. Our framework is based on matrix-product states, a powerful compressed representation of quantum states. It is complete in that it solves for flows around immersed objects of arbitrary geometries, with non-trivial boundary conditions, and self-consistent in that it can retrieve the solution directly from the compressed encoding, i.e. without ever passing through the expensive dense-vector representation. This machinery lays the foundations for a new generation of potentially radically more efficient solvers of real-life fluid problems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2308_12972 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Complete quantum-inspired framework for computational fluid dynamics Peddinti, Raghavendra D. Pisoni, Stefano Marini, Alessandro Lott, Philippe Argentieri, Henrique Tiunov, Egor Aolita, Leandro Fluid Dynamics Chemical Physics Computational Physics Quantum Physics Computational fluid dynamics is both a thriving research field and a key tool for advanced industry applications. The central challenge is to simulate turbulent flows in complex geometries, a compute-power intensive task due to the large vector dimensions required by discretized meshes. We present a full-stack method to solve for incompressible fluids with memory and runtime scaling poly-logarithmically in the mesh size. Our framework is based on matrix-product states, a powerful compressed representation of quantum states. It is complete in that it solves for flows around immersed objects of arbitrary geometries, with non-trivial boundary conditions, and self-consistent in that it can retrieve the solution directly from the compressed encoding, i.e. without ever passing through the expensive dense-vector representation. This machinery lays the foundations for a new generation of potentially radically more efficient solvers of real-life fluid problems. |
| title | Complete quantum-inspired framework for computational fluid dynamics |
| topic | Fluid Dynamics Chemical Physics Computational Physics Quantum Physics |
| url | https://arxiv.org/abs/2308.12972 |