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The work is devoted to the use of electrokinetic phenomena in liquid crystals to create a new class of microfluidics devices - optofluidics, designed to control electromagnetic radiation, including the THz frequency range.
To achieve the goal, an optical method is used to study changes in the orientational structure in LC layers caused by a shear flow generated by electroosmotic pumps. Simula-tion of LC behaviour in an experimental cell containing electroosmotic pumps and flat layers of a nematic liquid crystal is fulfilled.
The experimental depend-ences of the intensity of polarized radiation passing through flat LC layers on the control voltage applied to the electroosmotic pump and the results of calcu-lations of the hydrodynamic and mechano-optical characteristics of the experi-mental LC cell are presented.
The propagation of THz irradiation across the multilayer structure of the optofluidic cell is considered taking into account the minimum number of re-reflections of waves from different layers and the ab-sorption of THz irradiation in a propylene and a liquid crystal.
We report on the effect of spatially correlated noise on the velocities of self-propelled particles.
Correlations in the random forces acting on self-propelled particles can induce directed collective motion, i.e., swarming.
Even with repulsive coupling in the velocity directions, which favors a disordered state, strong correlations in the fluctuations can align the velocities locally leading to a macroscopic, turbulent velocity field.
On the other hand, while spatially correlated noise is aligning the velocities locally, the swarming transition to globally directed motion is inhibited when the correlation length of the noise is nonzero, but smaller than the system size.
We analyze the swarming transition in d-dimensional space in a mean field model of globally coupled velocity vectors.
For the first time, synchrotron X-ray refraction radiography (SXRR) has been paired with in-situ heat treatment to monitor microstructure and porosity evolution as a function of temperature.
The investigated material was a laser powder bed fusion (LPBF) manufactured AlSi10Mg, where the initial eutectic Si network is known to disintegrate and spherodize into larger particles with increasing temperature.
Such alloy is also prone to ther-mally induced porosity (TIP).
We show that SXRR allows detecting the changes in the Si-phase morphology upon heating, while this is currently possible only using scanning electron microscopy. SXRR also allows observing the growth of pores, usually studied via X-ray computed tomography, but on much smaller fields-of-view.
Our results show the great potential of in-situ SXRR as a tool to gain in-depth knowledge of the susceptibility of any material to thermally induced damage and/or microstructure evolution over statistically relevant volumes.
In the soil bacterium Pseudomonas putida, the motor torque for flagellar rotation is generated by the two stators MotAB and MotCD.
Here, we construct mutant strains in which one or both stators are knocked out and investigate their swimming motility in fluids of different viscosity and in heterogeneous structured environments (semisolid agar).
Besides phase-contrast imaging of single-cell trajectories and spreading cultures, dual-color fluorescence microscopy allows us to quantify the role of the stators in enabling P. putida's three different swimming modes, where the flagellar bundle pushes, pulls, or wraps around the cell body.
The MotAB stator is essential for swimming motility in liquids, while spreading in semisolid agar is not affected. Moreover, if the MotAB stator is knocked out, wrapped mode formation under low-viscosity conditions is strongly impaired and only partly restored for increased viscosity and in semisolid agar.
In contrast, when the MotCD stator is missing, cells are indistinguishable from the wild type in fluid experiments but spread much more slowly in semisolid agar.
Analysis of the microscopic trajectories reveals that the MotCD knockout strain forms sessile clusters, thereby reducing the number of motile cells, while the swimming speed is unaffected. Together, both stators ensure a robust wild type that swims efficiently under different environmental conditions.
IMPORTANCE
Because of its heterogeneous habitat, the soil bacterium Pseudomonas putida needs to swim efficiently under very different environmental conditions. In this paper, we knocked out the stators MotAB and MotCD to investigate their impact on the swimming motility of P. putida.
While the MotAB stator is crucial for swimming in fluids, in semisolid agar, both stators are sufficient to sustain a fast-swimming phenotype and increased frequencies of the wrapped mode, which is known to be beneficial for escaping mechanical traps. However, in contrast to the MotAB knockout, a culture of MotCD knockout cells spreads much more slowly in the agar, as it forms nonmotile clusters that reduce the number of motile cells.
Because of its heterogeneous habitat, the soil bacterium Pseudomonas putida needs to swim efficiently under very different environmental conditions. In this paper, we knocked out the stators MotAB and MotCD to investigate their impact on the swimming motility of P. putida.
The BAMline at the BESSY II synchrotron X-ray source has enabled research for more than 20 years in widely spread research fields such as materials science, biology, cultural heritage and medicine.
As a nondestructive characterization method, synchrotron X-ray imaging, especially tomography, plays a particularly important role in structural characterization.
A recent upgrade of key equipment of the BAMline widens its imaging capabilities: shorter scan acquisition times are now possible, in situ and op erando studies can now be routinely performed, and different energy spectra can easily be set up.
In fact, the upgraded double-multilayer monochromator brings full flexibility by yielding different energy spectra to optimize flux and energy resolution as desired.
The upgraded detector (based on an sCMOS camera) also allows exploiting the higher flux with reduced readout times.
Furthermore, an installed slip ring allows the sample stage to continuously rotate.
The latter feature enables tomographic observation of processes occurring in the time scale of a few seconds.
Laser induced switching offers an attractive possibility to manipulate small magnetic domains for prospective memory and logic devices on ultrashort time scales. Moreover, optical control of magnetization without high applied magnetic fields allows manipulation of magnetic domains individually and locally, without expensive heat dissipation. One of the major challenges for developing novel optically controlled magnetic memory and logic devices is reliable formation and annihilation of non-volatile magnetic domains that can serve as memory bits in ambient conditions. Magnetic skyrmions, topologically nontrivial spin textures, have been studied intensively since their discovery due to their stability and scalability in potential spintronic devices. However, skyrmion formation and, especially, annihilation processes are still not completely understood and further investigation on such mechanisms are needed. The aim of this thesis is to contribute to better understanding of the physical processes behind the optical control of magnetism in thin films, with the goal of optimizing material parameters and methods for their potential use in next generation memory and logic devices.
First part of the thesis is dedicated to investigation of all-optical helicity-dependent switching (AO-HDS) as a method for magnetization manipulation. AO-HDS in Co/Pt multilayer and CoFeB alloys with and without the presence of Dzyaloshinskii-Moriya interaction (DMI), which is a type of exchange interaction, have been investigated by magnetic imaging using photo-emission electron microscopy (PEEM) in combination with X-ray magnetic circular dichroism (XMCD). The results show that in a narrow range of the laser fluence, circularly polarized laser light induces a drag on domain walls. This enables a local deterministic transformation of the magnetic domain pattern from stripes to bubbles in out-of-plane magnetized Co/Pt multilayers, only controlled by the helicity of ultrashort laser pulses. The temperature and characteristic fields at which the stripe-bubble transformation occurs has been calculated using theory for isolated magnetic bubbles, using as parameters experimentally determined average size of stripe domains and the magnetic layer thickness.
The second part of the work aims at purely optical formation and annihilation of magnetic skyrmions by a single laser pulse. The presence of a skyrmion phase in the investigated CoFeB alloys was first confirmed using a Kerr microscope. Then the helicity-dependent skyrmion manipulation was studied using AO-HDS at different laser fluences. It was found that formation or annihilation individual skyrmions using AO-HDS is possible, but not always reliable, as fluctuations in the laser fluence or position can easily overwrite the helicity-dependent effect of AO-HDS. However, the experimental results and magnetic simulations showed that the threshold values for the laser fluence for the formation and annihilation of skyrmions are different. A higher fluence is required for skyrmion formation, and existing skyrmions can be annihilated by pulses with a slightly lower fluence. This provides a further option for controlling formation and annihilation of skyrmions using the laser fluence. Micromagnetic simulations provide additional insights into the formation and annihilation mechanism.
The ability to manipulate the magnetic state of individual skyrmions is of fundamental importance for magnetic data storage technologies. Our results show for the first time that the optical formation and annihilation of skyrmions is possible without changing the external field. These results enable further investigations to optimise the magnetic layer to maximise the energy gap between the formation and annihilation barrier. As a result, unwanted switching due to small laser fluctuations can be avoided and fully deterministic optical switching can be achieved.
We review an approach for reconstructing oscillatory networks’ undirected and directed connectivity from data. The technique relies on inferring the phase dynamics model. The central assumption is that we observe the outputs of all network nodes. We distinguish between two cases. In the first one, the observed signals represent smooth oscillations, while in the second one, the data are pulse-like and can be viewed as point processes. For the first case, we discuss estimating the true phase from a scalar signal, exploiting the protophase-to-phase transformation. With the phases at hand, pairwise and triplet synchronization indices can characterize the undirected connectivity. Next, we demonstrate how to infer the general form of the coupling functions for two or three oscillators and how to use these functions to quantify the directional links. We proceed with a different treatment of networks with more than three nodes. We discuss the difference between the structural and effective phase connectivity that emerges due to high-order terms in the coupling functions. For the second case of point-process data, we use the instants of spikes to infer the phase dynamics model in the Winfree form directly. This way, we obtain the network’s coupling matrix in the first approximation in the coupling strength.
Inferring oscillator's phase and amplitude response from a scalar signal exploiting test stimulation
(2022)
The phase sensitivity curve or phase response curve (PRC) quantifies the oscillator's reaction to stimulation at a specific phase and is a primary characteristic of a self-sustained oscillatory unit.
Knowledge of this curve yields a phase dynamics description of the oscillator for arbitrary weak forcing. Similar, though much less studied characteristic, is the amplitude response that can be defined either using an ad hoc approach to amplitude estimation or via the isostable variables.
Here, we discuss the problem of the phase and amplitude response inference from observations using test stimulation. Although PRC determination for noise-free neuronal-like oscillators perturbed by narrow pulses is a well-known task, the general case remains a challenging problem. Even more challenging is the inference of the amplitude response. This characteristic is crucial, e.g. for controlling the amplitude of the collective mode in a network of interacting units-a task relevant to neuroscience. Here, we compare the performance of different techniques suitable for inferring the phase and amplitude response, particularly with application to macroscopic oscillators. We suggest improvements to these techniques, e.g. demonstrating how to obtain the PRC in case of stimuli of arbitrary shape. Our main result is a novel technique denoted by IPID-1, based on the direct reconstruction of the Winfree equation and the analogous first-order equation for isostable dynamics. The technique works for signals with or without well-pronounced marker events and pulses of arbitrary shape; in particular, we consider charge-balanced pulses typical in neuroscience applications. Moreover, this technique is superior for noisy and high-dimensional systems. Additionally, we describe an error measure that can be computed solely from data and complements any inference technique.
Abstract
In recent years, feedforward neural networks (NNs) have been successfully applied to reconstruct global plasmasphere dynamics in the equatorial plane. These neural network‐based models capture the large‐scale dynamics of the plasmasphere, such as plume formation and erosion of the plasmasphere on the nightside. However, their performance depends strongly on the availability of training data. When the data coverage is limited or non‐existent, as occurs during geomagnetic storms, the performance of NNs significantly decreases, as networks inherently cannot learn from the limited number of examples. This limitation can be overcome by employing physics‐based modeling during strong geomagnetic storms. Physics‐based models show a stable performance during periods of disturbed geomagnetic activity if they are correctly initialized and configured. In this study, we illustrate how to combine the neural network‐ and physics‐based models of the plasmasphere in an optimal way by using data assimilation. The proposed approach utilizes advantages of both neural network‐ and physics‐based modeling and produces global plasma density reconstructions for both quiet and disturbed geomagnetic activity, including extreme geomagnetic storms. We validate the models quantitatively by comparing their output to the in‐situ density measurements from RBSP‐A for an 18‐month out‐of‐sample period from June 30, 2016 to January 01, 2018 and computing performance metrics. To validate the global density reconstructions qualitatively, we compare them to the IMAGE EUV images of the He+ particle distribution in the Earth's plasmasphere for a number of events in the past, including the Halloween storm in 2003.
Coastal areas are highly diverse, ecologically rich, regions of key socio-economic activity, and are particularly sensitive to sea-level change. Over most of the 20th century, global mean sea level has risen mainly due to warming and subsequent expansion of the upper ocean layers as well as the melting of glaciers and ice caps. Over the last three decades, increased mass loss of the Greenland and Antarctic ice sheets has also started to contribute significantly to contemporary sea-level rise. The future mass loss of the two ice sheets, which combined represent a sea-level rise potential of similar to 65 m, constitutes the main source of uncertainty in long-term (centennial to millennial) sea-level rise projections. Improved knowledge of the magnitude and rate of future sea-level change is therefore of utmost importance. Moreover, sea level does not change uniformly across the globe and can differ greatly at both regional and local scales. The most appropriate and feasible sea level mitigation and adaptation measures in coastal regions strongly depend on local land use and associated risk aversion. Here, we advocate that addressing the problem of future sea-level rise and its impacts requires (i) bringing together a transdisciplinary scientific community, from climate and cryospheric scientists to coastal impact specialists, and (ii) interacting closely and iteratively with users and local stakeholders to co-design and co-build coastal climate services, including addressing the high-end risks.
Mathematical modelling and statistical inference provide a framework to evaluate different non-pharmaceutical and pharmaceutical interventions for the control of epidemics that has been widely used during the COVID-19 pandemic. In this paper, lessons learned from this and previous epidemics are used to highlight the challenges for future pandemic control. We consider the availability and use of data, as well as the need for correct parameterisation and calibration for different model frameworks. We discuss challenges that arise in describing and distinguishing between different interventions, within different modelling structures, and allowing both within and between host dynamics. We also highlight challenges in modelling the health economic and political aspects of interventions. Given the diversity of these challenges, a broad variety of interdisciplinary expertise is needed to address them, combining mathematical knowledge with biological and social insights, and including health economics and communication skills. Addressing these challenges for the future requires strong cross disciplinary collaboration together with close communication between scientists and policy makers.
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.
The study of exoplanets and especially their atmospheres can reveal key insights on their evolution by identifying specific atmospheric species. For such atmospheric investigations, high-resolution transmission spectroscopy has shown great success, especially for Jupiter-type planets. Towards the atmospheric characterization of smaller planets, the super-Earth exoplanet 55 Cnc e is one of the most promising terrestrial exoplanets studied to date. Here, we present a high-resolution spectroscopic transit observation of this planet, acquired with the PEPSI instrument at the Large Binocular Telescope. Assuming the presence of Earth-like crust species on the surface of 55 Cnc e, from which a possible silicate-vapor atmosphere could have originated, we search in its transmission spectrum for absorption of various atomic and ionized species such as Fe , Fe (+), Ca , Ca (+), Mg, and K , among others. Not finding absorption for any of the investigated species, we are able to set absorption limits with a median value of 1.9 x R-P. In conclusion, we do not find evidence of a widely extended silicate envelope on this super-Earth reaching several planetary radii.
Forests play a key role in a bio-based economy by providing renewable materials, mitigating climate change, and accommodating biodiversity. However, forests experience massive increases in stresses in their ecological and socioeconomic environments, threatening forest ecosystem services supply. Alleviating those stresses is hampered by conflicting and disconnected governance arrangements, competing interests and claims, and rapid changes in technology and social demands. Identifying which stresses threaten forest ecosystem services supply and which factors hamper their alleviation requires stakeholders' perceptions. Stakeholder-oriented stress tests for the supply of forest ecosystem services are therefore necessary but are not yet available. This perspective presents a roadmap to develop a stress test tailored to multiple stakeholders' needs and demands across spatial scales. We provide the Cascade and Resilience Rosetta, with accompanying performance- and resilience indicators, as tools to facilitate development of the stress test. The application of the stress test will facilitate the transition toward a bio-based economy in which healthy and diverse forests provide sustainable and resilient ecosystem services.
Mobilities and lifetimes of photogenerated charge carriers are core properties of photovoltaic materials and can both be characterized by contactless terahertz or microwave measurements. Here, the expertise from fifteen laboratories is combined to quantitatively model the current-voltage characteristics of a solar cell from such measurements. To this end, the impact of measurement conditions, alternate interpretations, and experimental inter-laboratory variations are discussed using a (Cs,FA,MA)Pb(I,Br)(3) halide perovskite thin-film as a case study. At 1 sun equivalent excitation, neither transport nor recombination is significantly affected by exciton formation or trapping. Terahertz, microwave, and photoluminescence transients for the neat material yield consistent effective lifetimes implying a resistance-free JV-curve with a potential power conversion efficiency of 24.6 %. For grainsizes above approximate to 20 nm, intra-grain charge transport is characterized by terahertz sum mobilities of approximate to 32 cm(2) V-1 s(-1). Drift-diffusion simulations indicate that these intra-grain mobilities can slightly reduce the fill factor of perovskite solar cells to 0.82, in accordance with the best-realized devices in the literature. Beyond perovskites, this work can guide a highly predictive characterization of any emerging semiconductor for photovoltaic or photoelectrochemical energy conversion. A best practice for the interpretation of terahertz and microwave measurements on photovoltaic materials is presented.
Interpreting high-energy, astrophysical phenomena, such as supernova explosions or neutron-star collisions, requires a robust understanding of matter at supranuclear densities. However, our knowledge about dense matter explored in the cores of neutron stars remains limited. Fortunately, dense matter is not probed only in astrophysical observations, but also in terrestrial heavy-ion collision experiments. Here we use Bayesian inference to combine data from astrophysical multi-messenger observations of neutron stars(1-9) and from heavy-ion collisions of gold nuclei at relativistic energies(10,11) with microscopic nuclear theory calculations(12-17) to improve our understanding of dense matter. We find that the inclusion of heavy-ion collision data indicates an increase in the pressure in dense matter relative to previous analyses, shifting neutron-star radii towards larger values, consistent with recent observations by the Neutron Star Interior Composition Explorer mission(5-8,18). Our findings show that constraints from heavy-ion collision experiments show a remarkable consistency with multi-messenger observations and provide complementary information on nuclear matter at intermediate densities. This work combines nuclear theory, nuclear experiment and astrophysical observations, and shows how joint analyses can shed light on the properties of neutron-rich supranuclear matter over the density range probed in neutron stars.
Random logic networks
(2021)
We investigate dynamical properties of a quantum generalization of classical reversible Boolean networks. The state of each node is encoded as a single qubit, and classical Boolean logic operations are supplemented by controlled bit-flip and Hadamard operations. We consider synchronous updating schemes in which each qubit is updated at each step based on stored values of the qubits from the previous step. We investigate the periodic or quasiperiodic behavior of quantum networks, and we analyze the propagation of single site perturbations through the quantum networks with input degree one. A nonclassical mechanism for perturbation propagation leads to substantially different evolution of the Hamming distance between the original and perturbed states.
We apply the concepts of relative dimensions and mutual singularities to characterize the fractal properties of overlapping attractor and repeller in chaotic dynamical systems. We consider one analytically solvable example (a generalized baker's map); two other examples, the Anosov-Mobius and the Chirikov-Mobius maps, which possess fractal attractor and repeller on a two-dimensional torus, are explored numerically. We demonstrate that although for these maps the stable and unstable directions are not orthogonal to each other, the relative Renyi and Kullback-Leibler dimensions as well as the mutual singularity spectra for the attractor and repeller can be well approximated under orthogonality assumption of two fractals.
The fundamental sensitivity limit of atomic force microscopy is strongly correlated to the thermal noise of cantilever oscillation. A method to suppress this unwanted noise is to reduce the bandwidth of the measurement, but this approach is limited by the speed of the measurement and the width of the cantilever resonance, commonly defined through the quality factor Q. However, it has been shown that optomechanical resonances in interferometers might affect cantilever oscillations resulting in an effective quality factor Q(eff). When the laser power is sufficiently increased cantilever oscillations might even reach the regime of self-oscillation. In this self-oscillation state, the noise of the system is partially determined by the interaction with laser light far from equilibrium. Here, we show and discuss how tuning of laser power leads to nonlinear optomechanical effects that can dramatically increase the effective quality factor of the cantilever leading to out-of-equilibrium noise. We model the effects using a fourth order nonlinearity of the damping coefficient. Published under an exclusive license by AIP Publishing.