PhilSci Archive

Unrealistic Models for Realistic Computations: How Idealisations Help Represent Mathematical Structures and Found Scientific Computing

Papayannopoulos, Philippos (2020) Unrealistic Models for Realistic Computations: How Idealisations Help Represent Mathematical Structures and Found Scientific Computing. [Preprint]

[img]
Preview
Text
Papayannopoulos_Unrealistic-Models-Realistic-Computations.pdf

Download (263kB) | Preview

Abstract

We examine two very different approaches to formalising real computation, commonly referred to as "Computable Analysis" and "the BSS approach". The main models of computation underlying these approaches ---bit computation (or Type-2 Effectivity) and BSS, respectively--- have also been put forward as appropriate foundations for scientific computing. The two frameworks offer useful computability and complexity results about problems whose underlying domain is an uncountable space (such as R or C). Since typically the problems dealt with in physical sciences, applied mathematics, economics, and engineering are also defined in uncountable domains, it is fitting that we choose between these two approaches a foundational framework for scientific computing. However, the models are incompatible as to their results. What is more, the BSS model is highly idealised and unrealistic; yet, it is the de facto implicit model in various areas of computational mathematics, with virtually no problems for the everyday practice.

The paper serves three purposes. First, we attempt to delineate what the goal of developing foundations for scientific computing exactly is. We distinguish between two very different interpretations of that goal, and on the separate basis of each one, we put forward answers about the appropriateness of each framework. Second, we provide an account of the fruitfulness and wide use of BSS, despite its unrealistic assumptions. Third, according to one of our proposed interpretations of the scope of foundations, the target domain of both models is a certain mathematical structure (namely, floating-point arithmetic). In a clear sense, then, we are using idealised models to study a purely mathematical structure (actually a class of such structures). The third purpose is to point out and explain this intriguing (perhaps unique) phenomenon and attempt to make connections with the typical case of idealised models of empirical domains.


Export/Citation: EndNote | BibTeX | Dublin Core | ASCII/Text Citation (Chicago) | HTML Citation | OpenURL
Social Networking:
Share |

Item Type: Preprint
Creators:
CreatorsEmailORCID
Papayannopoulos, Philipposfpapagia@uwo.ca
Keywords: BSS/Real-RAM Model; Computable Analysis; Bit computation; Foundations of Scientific Computing; Idealisations; Real Complexity; Unrealistic Models; Well-posed, Ill-posed Physical Problems; Stability; Floating-Point Arithmetic
Subjects: Specific Sciences > Mathematics > Methodology
Specific Sciences > Mathematics > Practice
Specific Sciences > Computer Science
General Issues > Models and Idealization
Depositing User: Philippos Papayannopoulos
Date Deposited: 03 Oct 2021 15:05
Last Modified: 03 Oct 2021 15:05
Item ID: 19634
Official URL: https://doi.org/10.1007/s11229-020-02654-8
DOI or Unique Handle: 10.1007/s11229-020-02654-8
Subjects: Specific Sciences > Mathematics > Methodology
Specific Sciences > Mathematics > Practice
Specific Sciences > Computer Science
General Issues > Models and Idealization
Date: 2020
URI: http://philsci-archive.pitt.edu/id/eprint/19634

Monthly Views for the past 3 years

Monthly Downloads for the past 3 years

Plum Analytics

Altmetric.com

Actions (login required)

View Item View Item