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We combine ultrafast X-ray diffraction (UXRD) and time-resolved Magneto-Optical Kerr Effect (MOKE) measurements to monitor the strain pulses in laser-excited TbFe2/Nb heterostructures. Spatial separation of the Nb detection layer from the laser excitation region allows for a background-free characterization of the laser-generated strain pulses. We clearly observe symmetric bipolar strain pulses if the excited TbFe2 surface terminates the sample and a decomposition of the strain wavepacket into an asymmetric bipolar and a unipolar pulse, if a SiO2 glass capping layer covers the excited TbFe2 layer. The inverse magnetostriction of the temporally separated unipolar strain pulses in this sample leads to a MOKE signal that linearly depends on the strain pulse amplitude measured through UXRD. Linear chain model simulations accurately predict the timing and shape of UXRD and MOKE signals that are caused by the strain reflections from multiple interfaces in the heterostructure.
We develop an approach for the description of the dynamics of large populations of phase oscillators based on "circular cumulants" instead of the Kuramoto-Daido order parameters. In the thermodynamic limit, these variables yield a simple representation of the Ott-Antonsen invariant solution [E. Ott and T. M. Antonsen, Chaos 18, 037113 (2008)] and appear appropriate for constructing perturbation theory on top of the Ott-Antonsen ansatz. We employ this approach to study the impact of small intrinsic noise on the dynamics. As a result, a closed system of equations for the two leading cumulants, describing the dynamics of noisy ensembles, is derived. We exemplify the general theory by presenting the effect of noise on the Kuramoto system and on a chimera state in two symmetrically coupled populations.
Tasking machine learning to predict segments of a time series requires estimating the parameters of a ML model with input/output pairs from the time series. We borrow two techniques used in statistical data assimilation in order to accomplish this task: time-delay embedding to prepare our input data and precision annealing as a training method. The precision annealing approach identifies the global minimum of the action (-log[P]). In this way, we are able to identify the number of training pairs required to produce good generalizations (predictions) for the time series. We proceed from a scalar time series s(tn);tn=t0+n Delta t and, using methods of nonlinear time series analysis, show how to produce a DE>1-dimensional time-delay embedding space in which the time series has no false neighbors as does the observed s(tn) time series. In that DE-dimensional space, we explore the use of feedforward multilayer perceptrons as network models operating on DE-dimensional input and producing DE-dimensional outputs.
Context:
About a third of the hot subdwarfs of spectral type B (sdBs), which are mostly core-helium-burning objects on the extreme horizontal branch, are found in close binaries with cool, low-mass stellar, substellar, or white dwarf companions. They can show light variations due to di fferent phenomena.
Aims:
Many hot subdwarfs now have space-based light curves with a high signal-to-noise ratio available. We used light curves from the Transiting Exoplanet Survey Satellite and the K2 space mission to look for more sdB binaries. Their light curves can be used to study the hot subdwarf primaries and their companions, and obtained orbital, atmospheric, and absolute parameters for those systems, when combined with other analysis methods.
Methods:
By classifying the light variations and combining these with the fit of the spectral energy distribution, the distance derived by the parallaxes obtained by Gaia, and the atmospheric parameters, mainly from the literature, we could derive the nature of the primaries and secondaries in 122 (75%) of the known sdB binaries and 82 newly found reflection e ffect systems. We derived absolute masses, radii, and luminosities for a total of 39 hot subdwarfs with cool, low-mass companions, as well 29 known and newly found sdBs with white dwarf companions.
Results:
The mass distribution of hot subdwarfs with cool, low-mass stellar and substellar companions, di ffers from those with white dwarf companions, implying they come from di fferent populations. By comparing the period and minimum companion mass distributions, we find that the reflection e ffect systems all have M dwarf or brown dwarf companions, and that there seem to be several di fferent populations of hot subdwarfs with white dwarf binaries - one with white dwarf minimum masses around 0.4 M-circle dot, one with longer periods and minimum companion masses up to 0.6 M-circle dot, and at the shortest period, another with white dwarf minimum masses around 0.8 M-circle dot. We also derive the first orbital period distribution for hot subdwarfs with cool, low-mass stellar or substellar systems selected from light variations instead of radial velocity variations. It shows a narrower period distribution, from 1.5 h to 35 h, compared to the distribution of hot subdwarfs with white dwarfs, which ranges from 1 h to 30 days. These period distributions can be used to constrain the previous common-envelope phase.
Digital Volume Correlation (DVC) is a powerful set of techniques used to compute the local shifts of 3D images obtained, for instance, in tomographic experiments. It is utilized to analyze the geometric changes of the investigated object as well as to correct the corresponding image misalignments for further analysis. It can therefore be used to evaluate the local density changes of the same regions of the inspected specimens, which might be shifted between measurements. In recent years, various approaches and corresponding pieces of software were introduced. Accuracies for the computed shift vectors of up to about 1 parts per thousand of a single voxel size have been reported. These results, however, were based either on synthetic datasets or on an unrealistic setup. In this work, we propose two simple methods to evaluate the accuracy of DVC-techniques using more realistic input data and apply them to several DVC programs. We test these methods on three materials (tuff, sandstone, and concrete) that show different contrast and structural features. Published under license by AIP Publishing.
For both Lévy flight and Lévy walk search processes we analyse the full distribution of first-passage and first-hitting (or first-arrival) times. These are, respectively, the times when the particle moves across a point at some given distance from its initial position for the first time, or when it lands at a given point for the first time. For Lévy motions with their propensity for long relocation events and thus the possibility to jump across a given point in space without actually hitting it ('leapovers'), these two definitions lead to significantly different results. We study the first-passage and first-hitting time distributions as functions of the Lévy stable index, highlighting the different behaviour for the cases when the first absolute moment of the jump length distribution is finite or infinite. In particular we examine the limits of short and long times. Our results will find their application in the mathematical modelling of random search processes as well as computer algorithms.
The lives of more than 1/6 th of the world population is directly affected by the caprices of the South Asian summer monsoon rainfall. India receives around 78 % of the annual precipitation during the June-September months, the summer monsoon season of South Asia. But, the monsoon circulation is not consistent throughout the entire summer season. Episodes of heavy rainfall (active periods) and low rainfall (break periods) are inherent to the intraseasonal variability of the South Asian summer monsoon. Extended breaks or long-lasting dryness can result in droughts and hence trigger crop failures and in turn famines. Furthermore, India's electricity generation from renewable sources (wind and hydro-power), which is increasingly important in order to satisfy the rapidly rising demand for energy, is highly reliant on the prevailing meteorology. The major drought years 2002 and 2009 for the Indian summer monsoon during the last decades, which are results of the occurrence of multiple extended breaks, emphasise exemplary that the understanding of the monsoon system and its intraseasonal variation is of greatest importance. Although, numerous studies based on observations, reanalysis data and global model simulations have been carried out with the focus on monsoon active and break phases over India, the understanding of the monsoon intraseasonal variability is only in the infancy stage. Regional climate models could benefit the comprehension of monsoon breaks by its resolution advantage.
This study investigates moist dynamical processes that initiate and maintain breaks during the South Asian summer monsoon using the atmospheric regional climate model HIRHAM5 at a horizontal resolution of 25 km forced by the ECMWF ERA Interim reanalysis for the period 1979-2012. By calculating moisture and moist static energy budgets the various competing mechanisms leading to extended breaks are quantitatively estimated. Advection of dry air from the deserts of western Asia towards central India is the dominant moist dynamical process in initiating extended break conditions over South Asia. Once initiated, the extended breaks are maintained due to many competing mechanisms: (i) the anomalous easterlies at the southern flank of this anticyclonic anomaly weaken the low-level cross-equatorial jet and thus the moisture transport into the monsoon region, (ii) differential radiative heating over the continental and the oceanic tropical convergence zone induces a local Hadley circulation with anomalous rising over the equatorial Indian Ocean and descent over central India, and (iii) a cyclonic response to positive rainfall anomalies over the near-equatorial Indian Ocean amplifies the anomalous easterlies over India and hence contributes to the low-level divergence over central India.
A sensitivity experiment that mimics a scenario of higher atmospheric aerosol concentrations over South Asia addresses a current issue of large uncertainty: the role aerosols play in suppressing monsoon rainfall and hence in triggering breaks. To study the indirect aerosol effects the cloud droplet number concentration was increased to imitate the aerosol's function as cloud condensation nuclei. The sensitivity experiment with altered microphysical cloud properties shows a reduction in the summer monsoon precipitation together with a weakening of the South Asian summer monsoon. Several physical mechanisms are proposed to be responsible for the suppressed monsoon rainfall: (i) according to the first indirect radiative forcing the increase in the number of cloud droplets causes an increase in the cloud reflectivity of solar radiation, leading to a climate cooling over India which in turn reduces the hydrological cycle, (ii) a stabilisation of the troposphere induced by a differential cooling between the surface and the upper troposphere over central India inhibits the growth of deep convective rain clouds, (iii) an increase of the amount of low and mid-level clouds together with a decrease in high-level cloud amount amplify the surface cooling and hence the atmospheric stability, and (iv) dynamical changes of the monsoon manifested as a anomalous anticyclonic circulation over India reduce the moisture transport into the monsoon region. The study suggests that the changes in the total precipitation, which are dominated by changes in the convective precipitation, mainly result from the indirect radiative forcing. Suppression of rainfall due to the direct microphysical effect is found to be negligible over India. Break statistics of the polluted cloud scenario indicate an increase in the occurrence of short breaks (3 days), while the frequency of extended breaks (> 7 days) is clearly not affected. This disproves the hypothesis that more and smaller cloud droplets, caused by a high load of atmospheric aerosols trigger long drought conditions over central India.
The best organic solar cells (OSCs) achieve comparable peak external quantum efficiencies and fill factors as conventional photovoltaic devices. However, their voltage losses are much higher, in particular those due to nonradiative recombination. To investigate the possible role of triplet states on the donor or acceptor materials in this process, model systems comprising Zn- and Cu-phthalocyanine (Pc), as well as fluorinated versions of these donors, combined with C-60 as acceptor are studied. Fluorination allows tuning the energy level alignment between the lowest energy triplet state (T-1) and the charge-transfer (CT) state, while the replacement of Zn by Cu as the central metal in the Pcs leads to a largely enhanced spin-orbit coupling. Only in the latter case, a substantial influence of the triplet state on the nonradiative voltage losses is observed. In contrast, it is found that for a large series of typical OSC materials, the relative energy level alignment between T-1 and the CT state does not substantially affect nonradiative voltage losses.
Starting from the observation that the reduced state of a system strongly coupled to a bath is, in general, an athermal state, we introduce and study a cyclic battery-charger quantum device that is in thermal equilibrium, or in a ground state, during the charge storing stage. The cycle has four stages: the equilibrium storage stage is interrupted by disconnecting the battery from the charger, then work is extracted from the battery, and then the battery is reconnected with the charger; finally, the system is brought back to equilibrium. At no point during the cycle are the battery-charger correlations artificially erased. We study the case where the battery and charger together comprise a spin-1/2 Ising chain, and show that the main characteristics-the extracted energy and the thermodynamic efficiency-can be enhanced by operating the cycle close to the quantum phase transition point. When the battery is just a single spin, we find that the output work and efficiency show a scaling behavior at criticality and derive the corresponding critical exponents. Due to always present correlations between the battery and the charger, operations that are equivalent from the perspective of the battery can entail different energetic costs for switching the battery-charger coupling. This happens only when the coupling term does not commute with the battery's bare Hamiltonian, and we use this purely quantum leverage to further optimize the performance of the device.
Wealth and income distributions are known to feature country-specific Pareto exponents for their long power-law tails. To propose a rationale for this, we introduce an agent-based dynamic model and use Monte Carlo simulations to unveil the wealth distributions in closed and open economical systems. The standard money-exchange scenario is supplemented with the position-exchange agent dynamics that vitally affects the Pareto law. Specifically, in closed systems with position-exchange dynamics the power law changes to an exponential shape, while for open systems with traps the Pareto law remains valid.