Modeling still matters: a surprising instance of catastrophic floating point errors in mathematical biology and numerical methods for ODEs
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2023
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| _version_ | 1866913981003726848 |
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| author | Reisch, Cordula Ranocha, Hendrik |
| author_facet | Reisch, Cordula Ranocha, Hendrik |
| contents | We guide the reader on a journey through mathematical modeling and numerical analysis, emphasizing the crucial interplay of both disciplines. Targeting undergraduate students with basic knowledge in dynamical systems and numerical methods for ordinary differential equations, we explore a model from mathematical biology where numerical methods fail badly due to catastrophic floating point errors. We analyze the reasons for this behavior by studying the steady states of the model and use the theory of invariants to develop an alternative model that is suited for numerical simulations. Our story intends to motivate combining analytical and numerical knowledge, even in cases where the world looks fine at first sight. We have set up an online repository containing an interactive notebook with all numerical experiments to make this study fully reproducible and useful for classroom teaching. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2304_02365 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Modeling still matters: a surprising instance of catastrophic floating point errors in mathematical biology and numerical methods for ODEs Reisch, Cordula Ranocha, Hendrik History and Overview Numerical Analysis 37M05, 65L06, 65L20, 65P40, 97D40 We guide the reader on a journey through mathematical modeling and numerical analysis, emphasizing the crucial interplay of both disciplines. Targeting undergraduate students with basic knowledge in dynamical systems and numerical methods for ordinary differential equations, we explore a model from mathematical biology where numerical methods fail badly due to catastrophic floating point errors. We analyze the reasons for this behavior by studying the steady states of the model and use the theory of invariants to develop an alternative model that is suited for numerical simulations. Our story intends to motivate combining analytical and numerical knowledge, even in cases where the world looks fine at first sight. We have set up an online repository containing an interactive notebook with all numerical experiments to make this study fully reproducible and useful for classroom teaching. |
| title | Modeling still matters: a surprising instance of catastrophic floating point errors in mathematical biology and numerical methods for ODEs |
| topic | History and Overview Numerical Analysis 37M05, 65L06, 65L20, 65P40, 97D40 |
| url | https://arxiv.org/abs/2304.02365 |