FINKER: Frequency Identification through Nonparametric KErnel Regression in astronomical time series
Abstract
Optimal frequency identification in astronomical datasets is crucial for variable star studies, exoplanet detection, and asteroseismology. Traditional period-finding methods often rely on specific parametric assumptions, employ binning procedures, or overlook the regression nature of the problem, limiting their applicability and precision. We aim to introduce a universal, nonparametric kernel regression method for optimal frequency determination that is generalizable, efficient, and robust across various astronomical data types. FINKER uses nonparametric kernel regression on folded datasets at different frequencies, selecting the optimal frequency by minimizing squared residuals. This technique inherently incorporates a weighting system that accounts for measurement uncertainties and facilitates multiband data analysis. We evaluate our method's performance across a range of frequencies pertinent to diverse data types and compare it with an established period-finding algorithm, conditional entropy. The method demonstrates superior performance in accuracy and robustness compared to existing algorithms, requiring fewer observations to identify significant frequencies reliably. It exhibits resilience against noise and adapts well to datasets with varying complexity.
Authors 5
-
Affiliation as printed
Department of Astrophysics/IMAPP , Radboud University , PO Box 9010 , 6500 GL Nijmegen , The Netherlands
Department of Mathematics/IMAPP , Radboud University , PO Box 9010 , 6500 GL Nijmegen , The Netherlands
Department of Astrophysics/IMAPP, Radboud University, PO Box 9010, 6500 GL Nijmegen, The Netherlands
Department of Mathematics/IMAPP, Radboud University, PO Box 9010, 6500 GL Nijmegen, The Netherlands
-
Radboud University Nijmegen · Max Planck Institute for Astrophysics · KU Leuven
Affiliation as printed
Department of Astrophysics/IMAPP, Radboud University, PO Box 9010, 6500 GL Nijmegen, The Netherlands
Institute of Astronomy, KU Leuven, Celestijnenlaan 200D, B-3001 Leuven, Belgium
Max-Planck-Institut für Astrophysik, Karl-Schwarzschild-Straße 1, 85741 Garching bei München, Germany
-
Affiliation as printed
Department of Mathematics/IMAPP , Radboud University , PO Box 9010 , 6500 GL Nijmegen , The Netherlands
Department of Mathematics/IMAPP, Radboud University, PO Box 9010, 6500 GL Nijmegen, The Netherlands
-
Radboud University Nijmegen · Space Research Organisation Netherlands · KU Leuven
Affiliation as printed
Department of Astrophysics/IMAPP, Radboud University, PO Box 9010, 6500 GL Nijmegen, The Netherlands
Institute of Astronomy, KU Leuven, Celestijnenlaan 200D, B-3001 Leuven, Belgium
SRON, Netherlands Institute for Space Research, Sorbonnelaan 2, NL-3584 CA Utrecht, The Netherlands
-
Radboud University Nijmegen · University of Cape Town · Inter-university Institute for Data Intensive Astronomy · South African Astronomical Observatory
Affiliation as printed
Department of Astronomy and Inter-University Institute for Data Intensive Astronomy, University of Cape Town, Private Bag X3, Rondebosch, 7701, South Africa
Department of Astrophysics/IMAPP, Radboud University, PO Box 9010, 6500 GL Nijmegen, The Netherlands
South African Astronomical Observatory, P.O. Box 9, Observatory, 7935, South Africa
Cited by 0 stored of 0
No patents citing this paper on Lens.org (checked 2026-10-11).