SciPost logo

Unraveling complexity: Singular value decomposition in complex experimental data analysis

Judith F. Stein, Aviad Frydman, Richard Berkovits

SciPost Phys. Core 7, 061 (2024) · published 11 September 2024

Abstract

Analyzing complex experimental data with multiple parameters is challenging. We propose using Singular Value Decomposition (SVD) as an effective solution. This method, demonstrated through real experimental data analysis, surpasses conventional approaches in understanding complex physics data. Singular values and vectors distinguish and highlight various physical mechanisms and scales, revealing previously challenging elements. SVD emerges as a powerful tool for navigating complex experimental landscapes, showing promise for diverse experimental measurements.


Authors / Affiliation: mappings to Contributors and Organizations

See all Organizations.
Funders for the research work leading to this publication