Nonlinear reduction strategies for data compression: a comprehensive comparison from diffusion to advection problems

Fuente: arXiv
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Main Authors: Gonnella, Isabella Carla, Pichi, Federico, Rozza, Gianluigi
Format: Preprint
Published: 2025
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author Gonnella, Isabella Carla
Pichi, Federico
Rozza, Gianluigi
author_facet Gonnella, Isabella Carla
Pichi, Federico
Rozza, Gianluigi
contents This work presents an overview of several nonlinear reduction strategies for data compression from various research fields, and a comparison of their performance when applied to problems characterized by diffusion and/or advection terms. We aim to create a common framework by unifying the notation referring to a common two-stage pipeline. At the same time, we underline their main differences and objectives by highlighting the diverse choices made for each stage. We test the considered approaches on three test cases belonging to the family of Advection-Diffusion problems, also focusing on the pure Advection and pure Diffusion benchmarks, studying their reducibility while varying the latent dimension. Finally, we interpret the numerical results under the lens of the discussed theoretical considerations, offering a comprehensive landscape for nonlinear reduction methods for general Advection-Diffusion dynamics.
format Preprint
id arxiv_https___arxiv_org_abs_2501_12816
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Nonlinear reduction strategies for data compression: a comprehensive comparison from diffusion to advection problems
Gonnella, Isabella Carla
Pichi, Federico
Rozza, Gianluigi
Numerical Analysis
This work presents an overview of several nonlinear reduction strategies for data compression from various research fields, and a comparison of their performance when applied to problems characterized by diffusion and/or advection terms. We aim to create a common framework by unifying the notation referring to a common two-stage pipeline. At the same time, we underline their main differences and objectives by highlighting the diverse choices made for each stage. We test the considered approaches on three test cases belonging to the family of Advection-Diffusion problems, also focusing on the pure Advection and pure Diffusion benchmarks, studying their reducibility while varying the latent dimension. Finally, we interpret the numerical results under the lens of the discussed theoretical considerations, offering a comprehensive landscape for nonlinear reduction methods for general Advection-Diffusion dynamics.
title Nonlinear reduction strategies for data compression: a comprehensive comparison from diffusion to advection problems
topic Numerical Analysis
url https://arxiv.org/abs/2501.12816