Reproducibility, Methodological Robustness, and Synthetic-Domain Selection Properties of AFINO for TESS Stellar-Flare QPP Analysis
Abstract
Quasi-periodic pulsation (QPP) searches in stellar flares depend on methodological choices that can affect both classification and the interpretation of recovered periods. A defensible assessment therefore requires explicit separation of reproducibility, robustness, and known-truth performance. We characterize the reproducibility, methodological robustness, numerical behavior, and synthetic-ground-truth selection properties of a frozen public AFINO implementation in the TESS context while keeping observational reference evidence separate from known synthetic truth. The frozen baseline reproduced five published TESS detections in the initial reproduction cohort. A ten-event observational pilot and a catalogue-scale robustness experiment then tested prospectively specified temporal-window and processing perturbations. At catalogue scale, 51 of 61 published-QPP references did not reproduce their frozen reference state under the F3A baseline, so robustness claims were conditioned on baseline-concordant references rather than interpreted as accuracy. In a separately developed synthetic programme, the untouched AFINO 0.5 rule was evaluated once on an independent HELDOUT set: 152 of 1800 synthetic positives were selected and no false selections were observed among 1800 synthetic nulls, with finite Wilson uncertainty. The resulting 156-stratum selection surface and period-recovery summaries remain conditional on the frozen synthetic domain and, for period recovery, on selection; they therefore provide a bounded characterization of methodological robustness and synthetic-domain selection behavior without establishing observational validation or a population-level correction.
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BibTeX
@misc{corominas2026reproducibility,
title = {{Reproducibility, Methodological Robustness, and Synthetic-Domain Selection Properties of AFINO for TESS Stellar-Flare QPP Analysis}},
author = {Marc Balboa Corominas},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.34627},
eprint = {2610.34627},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.34627},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Reproducibility, Methodological Robustness, and Synthetic-Domain Selection Properties of AFINO for TESS Stellar-Flare QPP Analysis
AU - Marc Balboa Corominas
PY - 2026
DA - 2026/10/25
PB - arXiv
DO - 10.48550/arxiv.2610.34627
UR - https://arxiv.org/abs/2610.34627
AB - Quasi-periodic pulsation (QPP) searches in stellar flares depend on methodological choices that can affect both classification and the interpretation of recovered periods. A defensible assessment therefore requires explicit separation of reproducibility, robustness, and known-truth performance. We characterize the reproducibility, methodological robustness, numerical behavior, and synthetic-ground-truth selection properties of a frozen public AFINO implementation in the TESS context while keeping observational reference evidence separate from known synthetic truth. The frozen baseline reproduced five published TESS detections in the initial reproduction cohort. A ten-event observational pilot and a catalogue-scale robustness experiment then tested prospectively specified temporal-window and processing perturbations. At catalogue scale, 51 of 61 published-QPP references did not reproduce their frozen reference state under the F3A baseline, so robustness claims were conditioned on baseline-concordant references rather than interpreted as accuracy. In a separately developed synthetic programme, the untouched AFINO 0.5 rule was evaluated once on an independent HELDOUT set: 152 of 1800 synthetic positives were selected and no false selections were observed among 1800 synthetic nulls, with finite Wilson uncertainty. The resulting 156-stratum selection surface and period-recovery summaries remain conditional on the frozen synthetic domain and, for period recovery, on selection; they therefore provide a bounded characterization of methodological robustness and synthetic-domain selection behavior without establishing observational validation or a population-level correction.
ER -