Treffer: AstroGeoFit. A Genetic Algorithm and Bayesian Approach for the Astronomical Calibration of the Geological Timescale.

Variations in Earth's orbit and axial tilt induce climatic changes which are recorded in sedimentary deposits. The frequencies of these cyclical variations are integer combinations of the main secular frequencies of the solar system. Analyzing these cycles in sedimentary records can help establish an astronomical time scale for the geological record by correlating geological proxies with computed variations in insolation on the Earth's surface that follows the gravitational laws. When the astronomical solution becomes uncertain when going back in time, the analysis of stratigraphic records can provide insights into the past states of the planetary system and the evolution of the Earth‐Moon system. A critical aspect of this analysis is the estimation of the sedimentary deposition rate, which determines the time‐depth transfer function, relating geological depth to relative or absolute time. We propose a novel approach for constructing astronomical time scales for geological stratigraphic records. The AstroGeoFit method establishes a time‐depth transfer function throughout the record, accommodating variable sedimentation rates, and extracts the primary astronomical signal from the geological sequence. This is achieved using a genetic algorithm that adapts to a wide range of sedimentation rate variations. This statistical analysis enables the reconstruction of an astronomical signal (e.g., eccentricity and/or precession) purely from the stratigraphic sequence with minimal subjective bias. When this template is correlated with an astronomical solution, an absolute time scale is obtained for the entire record. In addition, we show that uncertainties can be estimated at each stage of the AstroGeoFit process. Plain Language Summary: AstroGeoFit is a cutting‐edge tool designed to uncover the ancient climate history of the Earth by analyzing sedimentary layers in rock formations. These layers contain patterns influenced by changes in the orbit and tilt of Earth over millions of years, which affect the climate of the planet. AstroGeoFit combines two advanced techniques: (a) Genetic Algorithms: These are used to model how sediment was deposited over time, accounting for changes in deposition rates. The process mimics natural selection, refining models through iterations until they match observed patterns. (b) Bayesian analysis: This is used to estimate the best astronomical signal in the data and its uncertainties, ensuring that the extracted information is reliable and includes error margins. This method allows researchers to: (a) Reconstruct how sedimentation rates have changed over time. (b) Extract key astronomical cycles such as the eccentricity and tilt of the Earth from sedimentary records without the use of a pre‐computed astronomical solution. By applying AstroGeoFit to synthetic data sets and real‐world geological cores, the study shows that it can create accurate timelines and link sediment records to Earth's orbital history. This helps improve our understanding of climate patterns and refine geological timescales. AstroGeoFit is also an open source Python library. Key Points: AstroGeoFit uses a genetic algorithm and Bayesian Monte Carlo Markov Chains for an integrated analysis of cyclostratigraphic records with uncertainty estimatesAstroGeoFit facilitates the extraction of astronomical signals from geological recordsIt also enables the derivation of local and global timescales for these records [ABSTRACT FROM AUTHOR]

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