[spsp-members] Helen Meskhidze @ PCFS Seminar Series

André Curtis-Trudel ae.trudel at gmail.com
Mon Mar 20 02:03:45 UTC 2023

We are pleased to announce that Helen Meskhidze (UC Irvine) will present at
the Philosophy of Contemporary and Future Science Seminar Series this week.
All are welcome to attend. Details below.

*Title: *(What) Do we learn from code comparisons? A case study of
self-interacting dark matter implementations
*Date: *Thursday, March 23 @ 8:30PM PDT (Friday, March 24 @ 11:30AM HKT)
*Zoom link:* https://lingnan.zoom.us/j/97330350037
*Abstract: *There has been much interest in the recent philosophical
literature on increasing the reliability and trustworthiness of computer
simulations. One method used to investigate the reliability of computer
simulations is code comparison. Gueguen, however, has offered a convincing
critique of code comparisons, arguing that they face a critical tension
between the diversity of codes required for an informative comparison and
the similarity required for the codes to be comparable. In this talk, I
will present the scientific and philosophical results of a recent
collaboration that was designed to address Gueguen's critiques. Our
interdisciplinary team conducted a code comparison to study two different
implementations of self-interacting dark matter.  I first present the
results of the code comparison itself. I then turn to investigating its
methodology and argue that the informativeness of this particular code
comparison was due to its targeted approach and narrow focus. Its targeted
approach (i.e., only the dark matter modules) allowed for simulation
outputs that were diverse enough for an informative comparison and yet
still comparable. Understanding the comparison as an instance of
eliminative reasoning narrowed the focus: we could investigate whether
code-specific differences in implementation contributed significantly to
the results of self-interacting dark matter simulations. Based on this case
study, I argue that code comparisons can be conducted in such a way that
they serve as a method for increasing our confidence in computer
simulations being, as Parker defines, adequate-for-purpose.
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