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| Autori principali: | , , , , , , , , , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Accesso online: | https://arxiv.org/abs/2508.05862 |
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| _version_ | 1866915434397171712 |
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| author | Davenport, James R. A. Barra, Francisca Chabour Bostroem, K. Azalee Tuttle, Sarah Torres, Josue Birky, Jessica Tzanidakis, Anastasios Kadlec, Kal Wang, Yuankun Hawley, Suzanne L. Dorn-Wallenstein, Trevor Z. Ketzeback, William Elias, Julene Korra, Abdullah Panova, Anna Devine, Kathryn Covey, Kevin R. |
| author_facet | Davenport, James R. A. Barra, Francisca Chabour Bostroem, K. Azalee Tuttle, Sarah Torres, Josue Birky, Jessica Tzanidakis, Anastasios Kadlec, Kal Wang, Yuankun Hawley, Suzanne L. Dorn-Wallenstein, Trevor Z. Ketzeback, William Elias, Julene Korra, Abdullah Panova, Anna Devine, Kathryn Covey, Kevin R. |
| contents | Here we present an automated method for obtaining wavelength calibrations for one-dimensional spectra, using Dynamic Time Warping (DTW). DTW is a flexible and well-understood algorithm for pattern matching, which has not been widely used in astronomy data analysis. Employing a calibrated template spectrum as a reference, DTW can recover non-linear and even discontinuous dispersion solutions without an initial guess. The algorithm is robust against differing spectral resolution between the template and sample data, and can accommodate some spurious or missing features. We demonstrate the effectiveness of DTW in an automated data reduction workflow, using both simulated and real arc lamp spectra in a Python data reduction framework. Finally, we provide a discussion on the utility and best practices with the DTW algorithm for wavelength calibration. We also introduce the PyKOSMOS data reduction toolkit, which includes our DTW calibration methods. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_05862 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Automated Spectroscopic Wavelength Calibration using Dynamic Time Warping Davenport, James R. A. Barra, Francisca Chabour Bostroem, K. Azalee Tuttle, Sarah Torres, Josue Birky, Jessica Tzanidakis, Anastasios Kadlec, Kal Wang, Yuankun Hawley, Suzanne L. Dorn-Wallenstein, Trevor Z. Ketzeback, William Elias, Julene Korra, Abdullah Panova, Anna Devine, Kathryn Covey, Kevin R. Instrumentation and Methods for Astrophysics Here we present an automated method for obtaining wavelength calibrations for one-dimensional spectra, using Dynamic Time Warping (DTW). DTW is a flexible and well-understood algorithm for pattern matching, which has not been widely used in astronomy data analysis. Employing a calibrated template spectrum as a reference, DTW can recover non-linear and even discontinuous dispersion solutions without an initial guess. The algorithm is robust against differing spectral resolution between the template and sample data, and can accommodate some spurious or missing features. We demonstrate the effectiveness of DTW in an automated data reduction workflow, using both simulated and real arc lamp spectra in a Python data reduction framework. Finally, we provide a discussion on the utility and best practices with the DTW algorithm for wavelength calibration. We also introduce the PyKOSMOS data reduction toolkit, which includes our DTW calibration methods. |
| title | Automated Spectroscopic Wavelength Calibration using Dynamic Time Warping |
| topic | Instrumentation and Methods for Astrophysics |
| url | https://arxiv.org/abs/2508.05862 |