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- Institut für Physik und Astronomie (272) (remove)
We characterize finite-time thermodynamic processes of multidimensional quadratic overdamped systems.
Analytic expressions are provided for heat, work, and dissipation for any evolution of the system covariance matrix.
The Bures-Wasserstein metric between covariance matrices naturally emerges as the local quantifier of dissipation.
General principles of how to apply these geometric tools to identify optimal protocols are discussed.
Focusing on the relevant slow-driving limit, we show how these results can be used to analyze cases in which the experimental control over the system is partial.
Accurately predicting total electron content (TEC) during geomagnetic storms is still a challenging task for ionospheric models. In this work, a neural-network (NN)-based model is proposed which predicts relative TEC with respect to the preceding 27-day median TEC, during storm time for the European region (with longitudes 30 degrees W-50 degrees E and latitudes 32.5 degrees N-70 degrees N). The 27-day median TEC (referred to as median TEC), latitude, longitude, universal time, storm time, solar radio flux index F10.7, global storm index SYM-H and geomagnetic activity index Hp30 are used as inputs and the output of the network is the relative TEC. The relative TEC can be converted to the actual TEC knowing the median TEC. The median TEC is calculated at each grid point over the European region considering data from the last 27 days before the storm using global ionosphere maps (GIMs) from international GNSS service (IGS) sources. A storm event is defined when the storm time disturbance index Dst drops below 50 nanotesla. The model was trained with storm-time relative TEC data from the time period of 1998 until 2019 (2015 is excluded) and contains 365 storms. Unseen storm data from 33 storm events during 2015 and 2020 were used to test the model. The UQRG GIMs were used because of their high temporal resolution (15 min) compared to other products from different analysis centers. The NN-based model predictions show the seasonal behavior of the storms including positive and negative storm phases during winter and summer, respectively, and show a mixture of both phases during equinoxes. The model's performance was also compared with the Neustrelitz TEC model (NTCM) and the NN-based quiet-time TEC model, both developed at the German Aerospace Agency (DLR). The storm model has a root mean squared error (RMSE) of 3.38 TEC units (TECU), which is an improvement by 1.87 TECU compared to the NTCM, where an RMSE of 5.25 TECU was found. This improvement corresponds to a performance increase by 35.6%. The storm-time model outperforms the quiet-time model by 1.34 TECU, which corresponds to a performance increase by 28.4% from 4.72 to 3.38 TECU. The quiet-time model was trained with Carrington averaged TEC and, therefore, is ideal to be used as an input instead of the GIM derived 27-day median. We found an improvement by 0.8 TECU which corresponds to a performance increase by 17% from 4.72 to 3.92 TECU for the storm-time model using the quiet-time-model predicted TEC as an input compared to solely using the quiet-time model.
The quantification of spatial propagation of extreme precipitation events is vital in water resources planning and disaster mitigation. However, quantifying these extreme events has always been challenging as many traditional methods are insufficient to capture the nonlinear interrelationships between extreme event time series. Therefore, it is crucial to develop suitable methods for analyzing the dynamics of extreme events over a river basin with a diverse climate and complicated topography. Over the last decade, complex network analysis emerged as a powerful tool to study the intricate spatiotemporal relationship between many variables in a compact way. In this study, we employ two nonlinear concepts of event synchronization and edit distance to investigate the extreme precipitation pattern in the Ganga river basin. We use the network degree to understand the spatial synchronization pattern of extreme rainfall and identify essential sites in the river basin with respect to potential prediction skills. The study also attempts to quantify the influence of precipitation seasonality and topography on extreme events. The findings of the study reveal that (1) the network degree is decreased in the southwest to northwest direction, (2) the timing of 50th percentile precipitation within a year influences the spatial distribution of degree, (3) the timing is inversely related to elevation, and (4) the lower elevation greatly influences connectivity of the sites. The study highlights that edit distance could be a promising alternative to analyze event-like data by incorporating event time and amplitude and constructing complex networks of climate extremes.
Massive stars that become stripped of their hydrogen envelope through binary interaction or winds can be observed either as Wolf-Rayet stars, if they have optically thick winds, or as transparent-wind stripped-envelope stars. We approximate their evolution through evolutionary models of single helium stars, and compute detailed model grids in the initial mass range 1.5-70 M. for metallicities between 0.01 and 0.04, from core helium ignition until core collapse. Throughout their lifetimes some stellar models expose the ash of helium burning. We propose that models that have nitrogen-rich envelopes are candidate WN stars, while models with a carbon-rich surface are candidate WC stars during core helium burning, and WO stars afterwards. We measure the metallicity dependence of the total lifetimes of our models and the duration of their evolutionary phases. We propose an analytic estimate of the wind's optical depth to distinguish models of Wolf-Rayet stars from transparent-wind stripped-envelope stars, and find that the luminosity ranges at which WN-, WC-, and WO-type stars can exist is a strong function of metallicity. We find that all carbon-rich models produced in our grids have optically thick winds and match the luminosity distribution of observed populations. We construct population models and predict the numbers of transparent-wind stripped-envelope stars and Wolf-Rayet stars, and derive their number ratios at different metallicities. We find that as metallicity increases, the number of transparent-wind stripped-envelope stars decreases and the number of Wolf-Rayet stars increases. At high metallicities WC- and WO-type stars become more common. We apply our population models to nearby galaxies, and find that populations are more sensitive to the transition luminosity between Wolf-Rayet stars and transparent-wind helium stars than to the metallicity-dependent mass loss rates.
Suppression of the TeV Pair-beam-Plasma Instability by a Tangled Weak Intergalactic Magnetic Field
(2022)
We study the effect of a tangled sub-fG level intergalactic magnetic field (IGMF) on the electrostatic instability of a blazar-induced pair beam. Sufficiently strong IGMF may significantly deflect the TeV pair beams, which would reduce the flux of secondary cascade emission below the observational limits. A similar flux reduction may result from the electrostatic beam-plasma instability, which operates the best in the absence of IGMF. Considering IGMF with correlation lengths smaller than a kiloparsec, we find that weak magnetic fields increase the transverse momentum of the pair-beam particles, which dramatically reduces the linear growth rate of the electrostatic instability and hence the energy-loss rate of the pair beam. We show that the beam-plasma instability is eliminated as an effective energy-loss agent at a field strength three orders of magnitude below that needed to suppress the secondary cascade emission by magnetic deflection. For intermediate-strength IGMF, we do not know a viable process to explain the observed absence of GeV-scale cascade emission.
We revisited 10 known exoplanetary systems using publicly available data provided by the transiting exoplanet survey satellite (TESS). The sample presented in this work consists of short period transiting exoplanets, with inflated radii and large reported uncertainty on their planetary radii. The precise determination of these values is crucial in order to develop accurate evolutionary models and understand the inflation mechanisms of these systems. Aiming to evaluate the planetary radius measurement, we made use of the planet-to-star radii ratio, a quantity that can be measured during a transit event. We fit the obtained transit light curves of each target with a detrending model and a transit model. Furthermore, we used emcee, which is based on a Markov chain Monte Carlo approach, to assess the best fit posterior distributions of each system parameter of interest. We refined the planetary radius of WASP-140 b by approximately 12%, and we derived a better precision on its reported asymmetric radius uncertainty by approximately 86 and 67%. We also refined the orbital parameters of WASP-120 b by 2 sigma. Moreover, using the high-cadence TESS datasets, we were able to solve a discrepancy in the literature, regarding the planetary radius of the exoplanet WASP-93 b. For all the other exoplanets in our sample, even though there is a tentative trend that planetary radii of (near-) grazing systems have been slightly overestimated in the literature, the planetary radius estimation and the orbital parameters were confirmed with independent observations from space, showing that TESS and ground-based observations are overall in good agreement.
Simulating the space weather in the AU Mic system: stellar winds and extreme coronal mass ejections
(2022)
Two close-in planets have been recently found around the M-dwarf flare star AU Microscopii (AU Mic). These Neptune-sized planets (AU Mic b and c) seem to be located very close to the so-called "evaporation valley" in the exoplanet population, making this system an important target for studying atmospheric loss on exoplanets. This process, while mainly driven by high-energy stellar radiation, will be strongly mediated by the space environment surrounding the planets. Here we present an investigation of this last area, performing 3D numerical modeling of the quiescent stellar wind from AU Mic, as well as time-dependent simulations describing the evolution of a highly energetic coronal mass ejection (CME) event in this system. Observational constraints on the stellar magnetic field and properties of the eruption are incorporated in our models. We carry out qualitative and quantitative characterizations of the stellar wind, the emerging CMEs, as well as the expected steady and transient conditions along the orbit of both exoplanets. Our results predict extreme space weather for AU Mic and its planets. This includes sub-Alfvenic regions for the large majority of the exoplanet orbits, very high dynamic and magnetic pressure values in quiescence (varying within 10(2)-10(5) times the dynamic pressure experienced by Earth), and an even harsher environment during the passage of any escaping CME associated with the frequent flaring observed in AU Mic. These space weather conditions alone pose an immense challenge for the survival of exoplanetary atmospheres (if any) in this system.
We present a catalogue of 362 million stellar parameters, distances, and extinctions derived from Gaia's Early Data Release (EDR3) cross-matched with the photometric catalogues of Pan-STARRS1, SkyMapper, 2MASS, and All WISE. The higher precision of the Gaia EDR3 data, combined with the broad wavelength coverage of the additional photometric surveys and the new stellar-density priors of the StarHorse code, allows us to substantially improve the accuracy and precision over previous photo-astrometric stellar-parameter estimates. At magnitude G = 14 (17), our typical precisions amount to 3% (15%) in distance, 0.13 mag (0.15 mag) in V-band extinction, and 140 K (180 K) in effective temperature. Our results are validated by comparisons with open clusters, as well as with asteroseismic and spectroscopic measurements, indicating systematic errors smaller than the nominal uncertainties for the vast majority of objects. We also provide distance- and extinction-corrected colour-magnitude diagrams, extinction maps, and extensive stellar density maps that reveal detailed substructures in the Milky Way and beyond. The new density maps now probe a much greater volume, extending to regions beyond the Galactic bar and to Local Group galaxies, with a larger total number density. We publish our results through an ADQL query interface (gaia . aip . de) as well as via tables containing approximations of the full posterior distributions. Our multi-wavelength approach and the deep magnitude limit render our results useful also beyond the next Gaia release, DR3.
Spin precession in magnetic materials is commonly modelled with the classical phenomenological Landau-Lifshitz-Gilbert (LLG) equation. Based on a quantized three-dimensional spin + environment Hamiltonian, we here derive a spin operator equation of motion that describes precession and includes a general form of damping that consistently accounts for memory, coloured noise and quantum statistics. The LLG equation is recovered as its classical, Ohmic approximation. We further introduce resonant Lorentzian system-reservoir couplings that allow a systematic comparison of dynamics between Ohmic and non-Ohmic regimes. Finally, we simulate the full non-Markovian dynamics of a spin in the semi-classical limit. At low temperatures, our numerical results demonstrate a characteristic reduction and flattening of the steady state spin alignment with an external field, caused by the quantum statistics of the environment. The results provide a powerful framework to explore general three-dimensional dissipation in quantum thermodynamics.
Active matter broadly covers the dynamics of self-propelled particles.
While the onset of collective behavior in homogenous active systems is relatively well understood, the effect of inhomogeneities such as obstacles and traps lacks overall clarity.
Here, we study how interacting, self-propelled particles become trapped and released from a trap.
We have found that captured particles aggregate into an orbiting condensate with a crystalline structure. As more particles are added, the trapped condensates escape as a whole.
Our results shed light on the effects of confinement and quenched disorder in active matter.