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Late-type stars are by far the most frequent stars in the universe and of fundamental interest to various fields of astronomy – most notably to Galactic archaeology and exoplanet research. However, such stars barely change during their main sequence lifetime; their temperature, luminosity, or chemical composition evolve only very slowly over the course of billions of years. As such, it is difficult to obtain the age of such a star, especially when it is isolated and no other indications (like cluster association) can be used. Gyrochronology offers a way to overcome this problem.
Stars, just like all other objects in the universe, rotate and the rate at which stars rotate impacts many aspects of their appearance and evolution. Gyrochronology leverages the observed rotation rate of a late-type main sequence star and its systematic evolution to estimate their ages. Unlike the above-mentioned parameters, the rotation rate of a main sequence star changes drastically throughout its main sequence lifetime; stars spin down. The youngest stars rotate every few hours, whereas much older stars rotate only about once a month, or – in the case of some late M-stars – once in a hundred days. Given that this spindown is systematic (with an additional mass dependence), it gave rise to the idea of using the observed rotation rate of a star (and its mass or a suitable proxy thereof) to estimate a star’s age. This has been explored widely in young stellar open clusters but remains essentially unconstrained for stars older than the sun, and K and M stars older than 1 Gyr.
This thesis focuses on the continued exploration of the spindown behavior to assess, whether gyrochronology remains applicable for stars of old ages, whether it is universal for late-type main sequence stars (including field stars), and to provide calibration mileposts for spindown models. To accomplish this, I have analyzed data from Kepler space telescope for the open clusters Ruprecht 147 (2.7 Gyr old) and M 67 (4 Gyr). Time series photometry data (light curves)
were obtained for both clusters during Kepler’s K2 mission. However, due to technical limitations and telescope malfunctions, extracting usable data from the K2 mission to identify (especially long) rotation periods requires extensive data preparation.
For Ruprecht 147, I have compiled a list of about 300 cluster members from the literature and adopted preprocessed light curves from the Kepler archive where available. They have been cleaned of the gravest of data artifacts but still contained systematics. After correcting them for said artifacts, I was able to identify rotation periods in 31 of them.
For M 67 more effort was taken. My work on Ruprecht 147 has shown the limitations imposed by the preselection of Kepler targets. Therefore, I adopted the time series full frame image directly and performed photometry on a much higher spatial resolution to be able to obtain data for as many stars as possible. This also means that I had to deal with the ubiquitous artifacts in Kepler data. For that, I devised a method that correlates the artificial flux variations with the ongoing drift of the telescope pointing in order to remove it. This process was a large success and I was able to create light curves whose quality match and even exceede those that were created by the Kepler mission – all while operating on higher spatial resolution and processing fainter stars. Ultimately, I was able to identify signs of periodic variability in the (created) light curves for 31 and 47 stars in Ruprecht 147 and M 67, respectively. My data connect well to bluer stars of cluster of the same age and extend for the first time to stars redder than early-K and older than 1 Gyr. The cluster data show a clear flattening in the distribution of Ruprecht 147 and even a downturn for M 67, resulting in a somewhat sinusoidal shape. With that, I have shown that the systematic spindown of stars continues at least until 4 Gyr and stars continue to live on a single surface in age-rotation periods-mass space which allows gyrochronology to be used at least up to that age. However, the shape of the spindown – as exemplified by the newly discovered sinusoidal shape of the cluster sequence – deviates strongly from the expectations.
I then compiled an extensive sample of rotation data in open clusters – very much including my own work – and used the resulting cluster skeleton (with each cluster forming a rip in color-rotation period-mass space) to investigate if field stars follow the same spindown as cluster stars. For the field stars, I used wide binaries, which – with their shared origin and coevality – are in a sense the smallest possible open clusters. I devised an empirical method to evaluate the consistency between the rotation rates of the wide binary components and found that the vast majority of them are in fact consistent with what is observed in open clusters. This leads me to conclude that gyrochronology – calibrated on open clusters – can be applied to determine the ages of field stars.
Groundwater levels are monitored by environmental agencies to support the sustainable use of groundwater resources. For this purpose continuous and spatially comprehensive monitoring in high spatial and temporal resolution is desired. This leads to large datasets that have to be checked for quality and analysed to distinguish local anthropogenic influences from natural variability of the groundwater level dynamics at each well. Both technical problems with the measurements as well as local anthropogenic influences can lead to local anomalies in the hydrographs. We suggest a fast and efficient screening method for the identification of well-specific peculiarities in hydrographs of groundwater head monitoring networks. The only information required is a set of time series of groundwater heads all measured at the same instants of time. For each well of the monitoring network a reference hydrograph is calculated, describing expected “normal” behaviour at the respective well as is typical for the monitored region. The reference hydrograph is calculated by multiple linear regression of the observed hydrograph with the “stable” principal components (PCs) of a principal component analysis of all groundwater head series of the network as predictor variables. The stable PCs are those PCs which were found in a random subsampling procedure to be rather insensitive to the specific selection of the analysed observation wells, i.e. complete series, and to the specific selection of measurement dates. Hence they can be considered to be representative for the monitored region in the respective period. The residuals of the reference hydrograph describe local deviations from the normal behaviour. Peculiarities in the residuals allow the data to be checked for measurement errors and the wells with a possible anthropogenic influence to be identified. The approach was tested with 141 groundwater head time series from the state authority groundwater monitoring network in northeastern Germany covering the period from 1993 to 2013 at an approximately weekly frequency of measurement.
Background: Agility in general and change-of-direction speed (CoD) in particular represent important performance determinants in elite soccer.
Objectives: The objectives of this study were to determine the effects of a 6-week neuromuscular training program on agility performance, and to determine differences in movement times between the slower and faster turning directions in elite soccer players. Materials and Methods: Twenty male elite soccer players from the Stade Rennais Football Club (Ligue 1, France) participated in this study. The players were randomly assigned to a neuromuscular training group (NTG, n = 10) or an active control (CG, n = 10) according to their playing position. NTG participated in a 6-week, twice per week neuromuscular training program that included CoD, plyometric and dynamic stability exercises. Neuromuscular training replaced the regular warm-up program. Each training session lasted 30 min. CG continued their regular training program. Training volume was similar between groups. Before and after the intervention, the two groups performed a reactive agility test that included 180° left and right body rotations followed by a 5-m linear sprint. The weak side was defined as the left/right turning direction that produced slower overall movement times (MT). Reaction time (RT) was assessed and defined as the time from the first appearance of a visual stimulus until the athlete’s first movement. MT corresponded to the time from the first movement until the athlete reached the arrival gate (5 m distance).
Results: No significant between-group baseline differences were observed for RT or MT. Significant group x time interactions were found for MT (p = 0.012, effect size = 0.332, small) for the slower and faster directions (p = 0.011, effect size = 0.627, moderate). Significant pre-to post improvements in MT were observed for NTG but not CG (p = 0.011, effect size = 0.877, moderate). For NTG, post hoc analyses revealed significant MT improvements for the slower (p = 0.012, effect size = 0.897, moderate) and faster directions (p = 0.017, effect size = 0.968, moderate).
Conclusion: Our results illustrate that 6 weeks of neuromuscular training with two sessions per week included in the warm-up program, significantly enhanced agility performance in elite soccer players. Moreover, improvements were found on both sides during body rotations. Thus, practitioners are advised to focus their training programs on both turning directions.