GAMMA_FLOW: Guided Analysis of Multi-label spectra by MAtrix Factorization for Lightweight Operational Workflows

• URL: http://arxiv.org/abs/2511.09326v1
• Date: Thu, 13 Nov 2025 01:46:36 GMT
• Title: GAMMA_FLOW: Guided Analysis of Multi-label spectra by MAtrix Factorization for Lightweight Operational Workflows
• Authors: Viola Rädle, Tilman Hartwig, Benjamin Oesen, Emily Alice Kröger, Julius Vogt, Eike Gericke, Martin Baron,
• Abstract summary: GAMMA_FLOW is an open-source Python package for real-time analysis of spectral data.<n>It supports classification, denoising, decomposition, and outlier detection of both single- and multi-component spectra.
• Score: 0.19544534628180865
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: GAMMA_FLOW is an open-source Python package for real-time analysis of spectral data. It supports classification, denoising, decomposition, and outlier detection of both single- and multi-component spectra. Instead of relying on large, computationally intensive models, it employs a supervised approach to non-negative matrix factorization (NMF) for dimensionality reduction. This ensures a fast, efficient, and adaptable analysis while reducing computational costs. gamma_flow achieves classification accuracies above 90% and enables reliable automated spectral interpretation. Originally developed for gamma-ray spectra, it is applicable to any type of one-dimensional spectral data. As an open and flexible alternative to proprietary software, it supports various applications in research and industry.

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