A Gaussian process guide for signal regression in magnetic fusion

Michoski, Craig; Oliver, Todd A.; Hatch, David R.; Diallo, Ahmed; Kotschenreuther, Mike; Eldon, David; Waller, Matthew; Groebner, Richard; Nelson, Andrew Oakleigh

doi:10.1088/1741-4326/ad1af5

Title: A Gaussian process guide for signal regression in magnetic fusion

Journal Article · Fri Feb 09 00:00:00 EST 2024 · Nuclear Fusion

DOI:https://doi.org/10.1088/1741-4326/ad1af5· OSTI ID:2294124

;

; Kotschenreuther, Mike;

; Waller, Matthew;

; Nelson, Andrew Oakleigh

Abstract Extracting reliable information from diagnostic data in tokamaks is critical for understanding, analyzing, and controlling the behavior of fusion plasmas and validating models describing that behavior. Recent interest within the fusion community has focused on the use of principled statistical methods, such as Gaussian process regression (GPR), to attempt to develop sharper, more reliable, and more rigorous tools for examining the complex observed behavior in these systems. While GPR is an enormously powerful tool, there is also the danger of drawing fragile, or inconsistent conclusions from naive GPR fits that are not driven by principled treatments. Here we review the fundamental concepts underlying GPR in a way that may be useful for broad-ranging applications in fusion science. We also revisit how GPR is developed for profile fitting in tokamaks. We examine various extensions and targeted modifications applicable to experimental observations in the edge of the DIII-D tokamak. Finally, we discuss best practices for applying GPR to fusion data.

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Research Organization:: Princeton Plasma Physics Laboratory (PPPL), Princeton, NJ (United States)

Sponsoring Organization:: USDOE Advanced Research Projects Agency - Energy (ARPA-E); USDOE Office of Science (SC), Fusion Energy Sciences (FES); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR). Scientific Discovery through Advanced Computing (SciDAC)

Grant/Contract Number:: AR0001265; FC02-04ER54698; SC0022164; FG02-04ER54742; SC0018429

OSTI ID:: 2294124

Alternate ID(s):: OSTI ID: 2278860; OSTI ID: 2326055

Journal Information:: Nuclear Fusion, Journal Name: Nuclear Fusion Vol. 64 Journal Issue: 3; ISSN 0029-5515

Publisher:: IOP PublishingCopyright Statement

Country of Publication:: IAEA

Language:: English

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70 PLASMA PHYSICS AND FUSION TECHNOLOGY
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