--- _id: '11623' abstract: - lang: eng text: Brightness variations due to dark spots on the stellar surface encode information about stellar surface rotation and magnetic activity. In this work, we analyze the Kepler long-cadence data of 26,521 main-sequence stars of spectral types M and K in order to measure their surface rotation and photometric activity level. Rotation-period estimates are obtained by the combination of a wavelet analysis and autocorrelation function of the light curves. Reliable rotation estimates are determined by comparing the results from the different rotation diagnostics and four data sets. We also measure the photometric activity proxy Sph using the amplitude of the flux variations on an appropriate timescale. We report rotation periods and photometric activity proxies for about 60% of the sample, including 4431 targets for which McQuillan et al. did not report a rotation period. For the common targets with rotation estimates in this study and in McQuillan et al., our rotation periods agree within 99%. In this work, we also identify potential polluters, such as misclassified red giants and classical pulsator candidates. Within the parameter range we study, there is a mild tendency for hotter stars to have shorter rotation periods. The photometric activity proxy spans a wider range of values with increasing effective temperature. The rotation period and photometric activity proxy are also related, with Sph being larger for fast rotators. Similar to McQuillan et al., we find a bimodal distribution of rotation periods. acknowledgement: "The authors thank Róbert Szabó Paul G. Beck, Katrien Kolenberg, and Isabel L. Colman for helping on the classification of stars. This paper includes data collected by the Kepler mission and obtained from the MAST data archive at the Space Telescope Science Institute (STScI). Funding for the Kepler mission is provided by the National Aeronautics and Space Administration (NASA) Science Mission Directorate. STScI is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5–26555. A.R.G.S. acknowledges the support from NASA under grant NNX17AF27G. R.A.G. and L.B. acknowledge the support from PLATO and GOLF CNES grants. S.M. acknowledges the support from the Ramon y Cajal fellowship number RYC-2015-17697. T.S.M. acknowledges support from a Visiting Fellowship at the Max Planck Institute for Solar System Research. This research has made use of the NASA Exoplanet Archive, which is operated by the California Institute of Technology, under contract with the National Aeronautics and Space Administration under the Exoplanet Exploration Program.\r\n\r\nSoftware: KADACS (García et al. 2011), NumPy (van der Walt et al. 2011), SciPy (Jones et al. 2001), Matplotlib (Hunter 2007).\r\n\r\nFacilities: MAST - , Kepler Eclipsing Binary Catalog - , Exoplanet Archive. -" article_number: '21' article_processing_charge: No article_type: original author: - first_name: A. R. G. full_name: Santos, A. R. G. last_name: Santos - first_name: R. A. full_name: García, R. A. last_name: García - first_name: S. full_name: Mathur, S. last_name: Mathur - first_name: Lisa Annabelle full_name: Bugnet, Lisa Annabelle id: d9edb345-f866-11ec-9b37-d119b5234501 last_name: Bugnet orcid: 0000-0003-0142-4000 - first_name: J. L. full_name: van Saders, J. L. last_name: van Saders - first_name: T. S. full_name: Metcalfe, T. S. last_name: Metcalfe - first_name: G. V. A. full_name: Simonian, G. V. A. last_name: Simonian - first_name: M. H. full_name: Pinsonneault, M. H. last_name: Pinsonneault citation: ama: Santos ARG, García RA, Mathur S, et al. Surface rotation and photometric activity for Kepler targets. I. M and K main-sequence stars. The Astrophysical Journal Supplement Series. 2019;244(1). doi:10.3847/1538-4365/ab3b56 apa: Santos, A. R. G., García, R. A., Mathur, S., Bugnet, L. A., van Saders, J. L., Metcalfe, T. S., … Pinsonneault, M. H. (2019). Surface rotation and photometric activity for Kepler targets. I. M and K main-sequence stars. The Astrophysical Journal Supplement Series. IOP Publishing. https://doi.org/10.3847/1538-4365/ab3b56 chicago: Santos, A. R. G., R. A. García, S. Mathur, Lisa Annabelle Bugnet, J. L. van Saders, T. S. Metcalfe, G. V. A. Simonian, and M. H. Pinsonneault. “Surface Rotation and Photometric Activity for Kepler Targets. I. M and K Main-Sequence Stars.” The Astrophysical Journal Supplement Series. IOP Publishing, 2019. https://doi.org/10.3847/1538-4365/ab3b56. ieee: A. R. G. Santos et al., “Surface rotation and photometric activity for Kepler targets. I. M and K main-sequence stars,” The Astrophysical Journal Supplement Series, vol. 244, no. 1. IOP Publishing, 2019. ista: Santos ARG, García RA, Mathur S, Bugnet LA, van Saders JL, Metcalfe TS, Simonian GVA, Pinsonneault MH. 2019. Surface rotation and photometric activity for Kepler targets. I. M and K main-sequence stars. The Astrophysical Journal Supplement Series. 244(1), 21. mla: Santos, A. R. G., et al. “Surface Rotation and Photometric Activity for Kepler Targets. I. M and K Main-Sequence Stars.” The Astrophysical Journal Supplement Series, vol. 244, no. 1, 21, IOP Publishing, 2019, doi:10.3847/1538-4365/ab3b56. short: A.R.G. Santos, R.A. García, S. Mathur, L.A. Bugnet, J.L. van Saders, T.S. Metcalfe, G.V.A. Simonian, M.H. Pinsonneault, The Astrophysical Journal Supplement Series 244 (2019). date_created: 2022-07-19T09:21:58Z date_published: 2019-09-19T00:00:00Z date_updated: 2022-08-22T08:10:38Z day: '19' doi: 10.3847/1538-4365/ab3b56 extern: '1' external_id: arxiv: - '1908.05222' intvolume: ' 244' issue: '1' keyword: - Space and Planetary Science - Astronomy and Astrophysics - 'methods: data analysis' - 'stars: activity' - 'stars: low-mass' - 'stars: rotation' - starspots - 'techniques: photometric' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1908.05222 month: '09' oa: 1 oa_version: Preprint publication: The Astrophysical Journal Supplement Series publication_identifier: issn: - 0067-0049 publication_status: published publisher: IOP Publishing quality_controlled: '1' scopus_import: '1' status: public title: Surface rotation and photometric activity for Kepler targets. I. M and K main-sequence stars type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 244 year: '2019' ... --- _id: '11627' abstract: - lang: eng text: 'For a solar-like star, the surface rotation evolves with time, allowing in principle to estimate the age of a star from its surface rotation period. Here we are interested in measuring surface rotation periods of solar-like stars observed by the NASA mission Kepler. Different methods have been developed to track rotation signals in Kepler photometric light curves: time-frequency analysis based on wavelet techniques, autocorrelation and composite spectrum. We use the learning abilities of random forest classifiers to take decisions during two crucial steps of the analysis. First, given some input parameters, we discriminate the considered Kepler targets between rotating MS stars, non-rotating MS stars, red giants, binaries and pulsators. We then use a second classifier only on the MS rotating targets to decide the best data analysis treatment.' article_number: '1906.09609' article_processing_charge: No author: - first_name: S. N. full_name: Breton, S. N. last_name: Breton - first_name: Lisa Annabelle full_name: Bugnet, Lisa Annabelle id: d9edb345-f866-11ec-9b37-d119b5234501 last_name: Bugnet orcid: 0000-0003-0142-4000 - first_name: A. R. G. full_name: Santos, A. R. G. last_name: Santos - first_name: A. Le full_name: Saux, A. Le last_name: Saux - first_name: S. full_name: Mathur, S. last_name: Mathur - first_name: P. L. full_name: Palle, P. L. last_name: Palle - first_name: R. A. full_name: Garcia, R. A. last_name: Garcia citation: ama: Breton SN, Bugnet LA, Santos ARG, et al. Determining surface rotation periods of solar-like stars observed by the Kepler mission using machine learning techniques. arXiv. doi:10.48550/arXiv.1906.09609 apa: Breton, S. N., Bugnet, L. A., Santos, A. R. G., Saux, A. L., Mathur, S., Palle, P. L., & Garcia, R. A. (n.d.). Determining surface rotation periods of solar-like stars observed by the Kepler mission using machine learning techniques. arXiv. https://doi.org/10.48550/arXiv.1906.09609 chicago: Breton, S. N., Lisa Annabelle Bugnet, A. R. G. Santos, A. Le Saux, S. Mathur, P. L. Palle, and R. A. Garcia. “Determining Surface Rotation Periods of Solar-like Stars Observed by the Kepler Mission Using Machine Learning Techniques.” ArXiv, n.d. https://doi.org/10.48550/arXiv.1906.09609. ieee: S. N. Breton et al., “Determining surface rotation periods of solar-like stars observed by the Kepler mission using machine learning techniques,” arXiv. . ista: Breton SN, Bugnet LA, Santos ARG, Saux AL, Mathur S, Palle PL, Garcia RA. Determining surface rotation periods of solar-like stars observed by the Kepler mission using machine learning techniques. arXiv, 1906.09609. mla: Breton, S. N., et al. “Determining Surface Rotation Periods of Solar-like Stars Observed by the Kepler Mission Using Machine Learning Techniques.” ArXiv, 1906.09609, doi:10.48550/arXiv.1906.09609. short: S.N. Breton, L.A. Bugnet, A.R.G. Santos, A.L. Saux, S. Mathur, P.L. Palle, R.A. Garcia, ArXiv (n.d.). date_created: 2022-07-20T11:18:53Z date_published: 2019-06-23T00:00:00Z date_updated: 2022-08-22T08:16:53Z day: '23' doi: 10.48550/arXiv.1906.09609 extern: '1' external_id: arxiv: - '1906.09609' keyword: - asteroseismology - rotation - solar-like stars - kepler - machine learning - random forest language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1906.09609 month: '06' oa: 1 oa_version: Preprint publication: arXiv publication_status: submitted status: public title: Determining surface rotation periods of solar-like stars observed by the Kepler mission using machine learning techniques type: preprint user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2019' ... --- _id: '11630' abstract: - lang: eng text: 'The second mission of NASA’s Kepler satellite, K2, has collected hundreds of thousands of lightcurves for stars close to the ecliptic plane. This new sample could increase the number of known pulsating stars and then improve our understanding of those stars. For the moment only a few stars have been properly classified and published. In this work, we present a method to automaticly classify K2 pulsating stars using a Machine Learning technique called Random Forest. The objective is to sort out the stars in four classes: red giant (RG), main-sequence Solar-like stars (SL), classical pulsators (PULS) and Other. To do this we use the effective temperatures and the luminosities of the stars as well as the FliPer features, that measures the amount of power contained in the power spectral density. The classifier now retrieves the right classification for more than 80% of the stars.' article_number: '1906.09611' article_processing_charge: No author: - first_name: A. Le full_name: Saux, A. Le last_name: Saux - first_name: Lisa Annabelle full_name: Bugnet, Lisa Annabelle id: d9edb345-f866-11ec-9b37-d119b5234501 last_name: Bugnet orcid: 0000-0003-0142-4000 - first_name: S. full_name: Mathur, S. last_name: Mathur - first_name: S. N. full_name: Breton, S. N. last_name: Breton - first_name: R. A. full_name: Garcia, R. A. last_name: Garcia citation: ama: Saux AL, Bugnet LA, Mathur S, Breton SN, Garcia RA. Automatic classification of K2 pulsating stars using machine learning techniques. arXiv. doi:10.48550/arXiv.1906.09611 apa: Saux, A. L., Bugnet, L. A., Mathur, S., Breton, S. N., & Garcia, R. A. (n.d.). Automatic classification of K2 pulsating stars using machine learning techniques. arXiv. https://doi.org/10.48550/arXiv.1906.09611 chicago: Saux, A. Le, Lisa Annabelle Bugnet, S. Mathur, S. N. Breton, and R. A. Garcia. “Automatic Classification of K2 Pulsating Stars Using Machine Learning Techniques.” ArXiv, n.d. https://doi.org/10.48550/arXiv.1906.09611. ieee: A. L. Saux, L. A. Bugnet, S. Mathur, S. N. Breton, and R. A. Garcia, “Automatic classification of K2 pulsating stars using machine learning techniques,” arXiv. . ista: Saux AL, Bugnet LA, Mathur S, Breton SN, Garcia RA. Automatic classification of K2 pulsating stars using machine learning techniques. arXiv, 1906.09611. mla: Saux, A. Le, et al. “Automatic Classification of K2 Pulsating Stars Using Machine Learning Techniques.” ArXiv, 1906.09611, doi:10.48550/arXiv.1906.09611. short: A.L. Saux, L.A. Bugnet, S. Mathur, S.N. Breton, R.A. Garcia, ArXiv (n.d.). date_created: 2022-07-21T06:57:10Z date_published: 2019-06-23T00:00:00Z date_updated: 2022-08-22T08:20:29Z day: '23' doi: 10.48550/arXiv.1906.09611 extern: '1' external_id: arxiv: - '1906.09611' keyword: - asteroseismology - methods - data analysis - thecniques - machine learning - stars - oscillations language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.1906.09611 month: '06' oa: 1 oa_version: Preprint publication: arXiv publication_status: submitted status: public title: Automatic classification of K2 pulsating stars using machine learning techniques type: preprint user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2019' ... --- _id: '11826' abstract: - lang: eng text: "The diameter, radius and eccentricities are natural graph parameters. While these problems have been studied extensively, there are no known dynamic algorithms for them beyond the ones that follow from trivial recomputation after each update or from solving dynamic All-Pairs Shortest Paths (APSP), which is very computationally intensive. This is the situation for dynamic approximation algorithms as well, and even if only edge insertions or edge deletions need to be supported.\r\nThis paper provides a comprehensive study of the dynamic approximation of Diameter, Radius and Eccentricities, providing both conditional lower bounds, and new algorithms whose bounds are optimal under popular hypotheses in fine-grained complexity. Some of the highlights include:\r\n- Under popular hardness hypotheses, there can be no significantly better fully dynamic approximation algorithms than recomputing the answer after each update, or maintaining full APSP.\r\n- Nearly optimal partially dynamic (incremental/decremental) algorithms can be achieved via efficient reductions to (incremental/decremental) maintenance of Single-Source Shortest Paths. For instance, a nearly (3/2+epsilon)-approximation to Diameter in directed or undirected n-vertex, m-edge graphs can be maintained decrementally in total time m^{1+o(1)}sqrt{n}/epsilon^2. This nearly matches the static 3/2-approximation algorithm for the problem that is known to be conditionally optimal." alternative_title: - LIPIcs article_number: '13' article_processing_charge: No author: - first_name: Bertie full_name: Ancona, Bertie last_name: Ancona - first_name: Monika H full_name: Henzinger, Monika H id: 540c9bbd-f2de-11ec-812d-d04a5be85630 last_name: Henzinger orcid: 0000-0002-5008-6530 - first_name: Liam full_name: Roditty, Liam last_name: Roditty - first_name: Virginia Vassilevska full_name: Williams, Virginia Vassilevska last_name: Williams - first_name: Nicole full_name: Wein, Nicole last_name: Wein citation: ama: 'Ancona B, Henzinger MH, Roditty L, Williams VV, Wein N. Algorithms and hardness for diameter in dynamic graphs. In: 46th International Colloquium on Automata, Languages, and Programming. Vol 132. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2019. doi:10.4230/LIPICS.ICALP.2019.13' apa: 'Ancona, B., Henzinger, M. H., Roditty, L., Williams, V. V., & Wein, N. (2019). Algorithms and hardness for diameter in dynamic graphs. In 46th International Colloquium on Automata, Languages, and Programming (Vol. 132). Patras, Greece: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPICS.ICALP.2019.13' chicago: Ancona, Bertie, Monika H Henzinger, Liam Roditty, Virginia Vassilevska Williams, and Nicole Wein. “Algorithms and Hardness for Diameter in Dynamic Graphs.” In 46th International Colloquium on Automata, Languages, and Programming, Vol. 132. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2019. https://doi.org/10.4230/LIPICS.ICALP.2019.13. ieee: B. Ancona, M. H. Henzinger, L. Roditty, V. V. Williams, and N. Wein, “Algorithms and hardness for diameter in dynamic graphs,” in 46th International Colloquium on Automata, Languages, and Programming, Patras, Greece, 2019, vol. 132. ista: 'Ancona B, Henzinger MH, Roditty L, Williams VV, Wein N. 2019. Algorithms and hardness for diameter in dynamic graphs. 46th International Colloquium on Automata, Languages, and Programming. ICALP: International Colloquium on Automata, Languages, and Programming, LIPIcs, vol. 132, 13.' mla: Ancona, Bertie, et al. “Algorithms and Hardness for Diameter in Dynamic Graphs.” 46th International Colloquium on Automata, Languages, and Programming, vol. 132, 13, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2019, doi:10.4230/LIPICS.ICALP.2019.13. short: B. Ancona, M.H. Henzinger, L. Roditty, V.V. Williams, N. Wein, in:, 46th International Colloquium on Automata, Languages, and Programming, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2019. conference: end_date: 2019-07-12 location: Patras, Greece name: 'ICALP: International Colloquium on Automata, Languages, and Programming' start_date: 2019-07-09 date_created: 2022-08-12T08:14:51Z date_published: 2019-07-04T00:00:00Z date_updated: 2023-02-16T10:48:24Z day: '04' doi: 10.4230/LIPICS.ICALP.2019.13 extern: '1' external_id: arxiv: - '811.12527' intvolume: ' 132' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.4230/LIPIcs.ICALP.2019.13 month: '07' oa: 1 oa_version: Published Version publication: 46th International Colloquium on Automata, Languages, and Programming publication_identifier: isbn: - 978-3-95977-109-2 issn: - 1868-8969 publication_status: published publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik quality_controlled: '1' scopus_import: '1' status: public title: Algorithms and hardness for diameter in dynamic graphs type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 132 year: '2019' ... --- _id: '11850' abstract: - lang: eng text: 'Modern networked systems are increasingly reconfigurable, enabling demand-aware infrastructures whose resources can be adjusted according to the workload they currently serve. Such dynamic adjustments can be exploited to improve network utilization and hence performance, by moving frequently interacting communication partners closer, e.g., collocating them in the same server or datacenter. However, dynamically changing the embedding of workloads is algorithmically challenging: communication patterns are often not known ahead of time, but must be learned. During the learning process, overheads related to unnecessary moves (i.e., re-embeddings) should be minimized. This paper studies a fundamental model which captures the tradeoff between the benefits and costs of dynamically collocating communication partners on l servers, in an online manner. Our main contribution is a distributed online algorithm which is asymptotically almost optimal, i.e., almost matches the lower bound (also derived in this paper) on the competitive ratio of any (distributed or centralized) online algorithm.' article_processing_charge: No author: - first_name: Monika H full_name: Henzinger, Monika H id: 540c9bbd-f2de-11ec-812d-d04a5be85630 last_name: Henzinger orcid: 0000-0002-5008-6530 - first_name: Stefan full_name: Neumann, Stefan last_name: Neumann - first_name: Stefan full_name: Schmid, Stefan last_name: Schmid citation: ama: 'Henzinger MH, Neumann S, Schmid S. Efficient distributed workload (re-)embedding. In: SIGMETRICS’19: International Conference on Measurement and Modeling of Computer Systems. Association for Computing Machinery; 2019:43–44. doi:10.1145/3309697.3331503' apa: 'Henzinger, M. H., Neumann, S., & Schmid, S. (2019). Efficient distributed workload (re-)embedding. In SIGMETRICS’19: International Conference on Measurement and Modeling of Computer Systems (pp. 43–44). Phoenix, AZ, United States: Association for Computing Machinery. https://doi.org/10.1145/3309697.3331503' chicago: 'Henzinger, Monika H, Stefan Neumann, and Stefan Schmid. “Efficient Distributed Workload (Re-)Embedding.” In SIGMETRICS’19: International Conference on Measurement and Modeling of Computer Systems, 43–44. Association for Computing Machinery, 2019. https://doi.org/10.1145/3309697.3331503.' ieee: 'M. H. Henzinger, S. Neumann, and S. Schmid, “Efficient distributed workload (re-)embedding,” in SIGMETRICS’19: International Conference on Measurement and Modeling of Computer Systems, Phoenix, AZ, United States, 2019, pp. 43–44.' ista: 'Henzinger MH, Neumann S, Schmid S. 2019. Efficient distributed workload (re-)embedding. SIGMETRICS’19: International Conference on Measurement and Modeling of Computer Systems. SIGMETRICS: International Conference on Measurement and Modeling of Computer Systems, 43–44.' mla: 'Henzinger, Monika H., et al. “Efficient Distributed Workload (Re-)Embedding.” SIGMETRICS’19: International Conference on Measurement and Modeling of Computer Systems, Association for Computing Machinery, 2019, pp. 43–44, doi:10.1145/3309697.3331503.' short: 'M.H. Henzinger, S. Neumann, S. Schmid, in:, SIGMETRICS’19: International Conference on Measurement and Modeling of Computer Systems, Association for Computing Machinery, 2019, pp. 43–44.' conference: end_date: 2019-06-28 location: Phoenix, AZ, United States name: 'SIGMETRICS: International Conference on Measurement and Modeling of Computer Systems' start_date: 2019-06-24 date_created: 2022-08-16T07:14:57Z date_published: 2019-06-20T00:00:00Z date_updated: 2023-02-17T09:41:45Z day: '20' doi: 10.1145/3309697.3331503 extern: '1' external_id: arxiv: - '1904.05474' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1904.05474 month: '06' oa: 1 oa_version: Preprint page: 43–44 publication: 'SIGMETRICS''19: International Conference on Measurement and Modeling of Computer Systems' publication_identifier: isbn: - 978-1-4503-6678-6 publication_status: published publisher: Association for Computing Machinery quality_controlled: '1' scopus_import: '1' status: public title: Efficient distributed workload (re-)embedding type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2019' ...