Philosophy of Astrophysics by Unknown

Author:Unknown
Language: eng
Format: epub, pdf
ISBN: 9783031266188
Publisher: Springer International Publishing

9.5 Conclusion

In this paper, I have presented a survey of the verification tests used in selected MHD codes, and drawn lessons about simulation justification on the basis of this real-world scientific practice. Notably, the pattern observed does not fit with the V&V framework’s prescriptions, and a careful examination of the development and deployment of these tests shows that they serve epistemic functions beyond simply checking for numerical errors—they can be used to probe the differences between different code types and come to a deeper understanding of their strengths and weaknesses. By examining the case study of fluid-mixing instability tests, I traced this process in action and showed that the creation of these tests, the subsequent analysis, and the development of improved simulation codes is deeply entangled with our understanding of the underlying physics, not merely the numerics.

On the basis of this survey and case study, I argued that this process of improving our understanding of the target phenomena and the space of simulation code types can be understood to follow a pattern of incremental improvement similar to ordinary scientific theories in ordinary experimental contexts. I also addressed a skeptical objection that might be leveled by those convinced by the strict V&V approach—in particular, given this expanded understanding of how verification tests can inform our investigations, we can be reasonably confident that we are not exposing ourself to any severe underdetermination risks.

This wider understanding of the role of verification tests also has significant implications for how we characterize the role of the simulationist—in particular, the simulationist’s knowledge of simulation methods and techniques is not merely instrumental for the goal of learning about the target phenomenon, because the simulationist’s understanding of the target phenomenon is developed in tandem with their knowledge of simulation methods and techniques. This entanglement suggests that merely reproducing some target phenomenon by simulation is not sufficient for a full understanding of that phenomenon—the simulationist must also understand the principles by which the different specifics of the various code types yield this common result.

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