---
_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'
...