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Time and angle-resolved time-of-flight electron spectroscopy for functional materials science
(2022)
Electron spectroscopy with the unprecedented transmission of angle-resolved time-of-flight detection, in combination with pulsed X-ray sources, brings new impetus to functional materials science.
We showcase recent developments towards chemical sensitivity from electron spectroscopy for chemical analysis and structural information from photoelectron diffraction using the phase transition properties of 1T-TaS2.
Our development platform is the SurfaceDynamics instrument located at the Femtoslicing facility at BESSY II, where femtosecond and picosecond X-ray pulses can be generated and extracted.
The scientific potential is put into perspective to the current rapidly developing pulsed X-ray source capabilities from Lasers and Free-Electron Lasers.
The diffusion process of water in swelling (expansive) soil often deviates from normal Fick diffusion and belongs to anomalous diffusion.
The process of water adsorption by swelling soil often changes with time, in which the microstructure evolves with time and the absorption rate changes along a fractal dimension gradient function.
Thus, based on the material coordinate theory, this paper proposes a variable order derivative fractal model to describe the cumulative adsorption of water in the expansive soil, and the variable order is time dependent linearly.
The cumulative adsorption is a power law function of the anomalous sorptivity, and patterns of the variable order.
The variable-order fractal derivative model is tested to describe the cumulative adsorption in chernozemic surface soil, Wunnamurra clay and sandy loam.
The results show that the fractal derivative model with linearly time dependent variable-order has much better accuracy than the fractal derivative model with a constant derivative order and the integer order model in the application cases.
The derivative order can be used to distinguish the evolution of the anomalous adsorption process. The variable-order fractal derivative model can serve as an alternative approach to describe water anomalous adsorption in swelling soil.
We have investigated the self-assembly of the graphene nanoribbon molecular precursor 10,10'-dibromo-9,9'-bianthryl (DBBA) on Au(111) with frequency modulation scanning force microscopy (FM-SFM) at room temperature combined with ab initio calculations.
For low molecular coverages, the molecules aggregate along the substrate herringbone reconstruction main directions while remaining mobile.
At intermediate coverage, two phases coexist, zigzag stripes of monomer chains and decorated herringbones. For high coverage, the molecules assemble in a dimer-striped phase.
The adsorption behaviour of DBBA molecules and their interactions are discussed and compared with the results from ab initio calculations.
Hybrid nanophotonic elements, fabricated by organic and inorganic materials, are going to be key components of modern devices.
Coupled systems of photoemitters with a plasmonic waveguide serve the demand for nanoscopic frequency converters.
However, processes like the degradation of the photoemitters via photobleaching occur and need to be monitored and controlled, to realize future successful devices.
We introduce a hybrid perylene-diimide / silver nanowire as plasmon frequency converter. A versatile method is presented to monitor and analyze the bleaching process. It is based on a time series of photoluminescence images, during the operation of a single converter.
An analytical model is applied on the data and unveils that the photobleaching rate is constant and independent of the operation of the plasmon converter.
The printability of artificial defects inside the additively manufactured laser powder bed fusion (LPBF) 316L stainless steel is investigated.
The printing parameters of the LPBF process are optimized to produce artificial defects with reproducible sizes at desired positions while minimizing redundant porosity. The smallest obtained artificial defect is 90 mu m in diameter.
The accuracy of the geometry of the printed defect depends on both the height and the diameter in the input model.
The effect of artificial defects on the very-high-cycle fatigue (VHCF) behavior of LPBF 316L stainless steel is also studied. The specimens printed with artificial defects in the center are tested under VHCF using an ultrasonic machine.
Crack initiation is accompanied by the formation of a fine granular area (FGA), typical of VHCF. Despite the presence of relatively large artificial defects, FGA formation is observed around accidental natural printing defects closer to the surface, which can still be considered as internal. The causes for this occurrence are discussed.
As society paves its way towards device miniaturization and precision medicine, microscale actuation and transport become increasingly prominent research fields with high impact in both technological and clinical contexts.
In order to accomplish movement of micron-sized objects towards specific target sites, active biohybrid transport systems, such as motile living cells that act as smart biochemically powered microcarriers, have been suggested as an alternative to synthetic microrobots.
Inspired by the motility of leukocytes, we propose the amoeboid crawling of eukaryotic cells as a promising mechanism for transport of micron-sized cargoes and present an in-depth study of this type of composite active matter.
Its transport properties result from the interactions of an active element (cell) and a passive one (cargo) and reveal an optimal cargo size that enhances the locomotion of the load-carrying cells, even exceeding their motility in the absence of cargo.
The experimental findings are rationalized in terms of a biohybrid active particle model that describes the emergent cell-cargo dynamics and enables us to derive the long-time diffusive transport of amoeboid microcarriers.
As amoeboid locomotion is commonly observed for mammalian cells such as leukocytes, our results lay the foundations for the study of transport performance of other medically relevant cell types and for extending our findings to more advanced transport tasks in complex environments, such as tissues.
In this paper, we propose a revised fractional Brownian motion run with a nonlinear clock (fBm-nlc) model and utilize it to illustrate the microscopic mechanism analysis of the fractal derivative diffusion model with variable coefficient (VC-FDM).
The power-law mean squared displacement (MSD) links the fBm-nlc model and the VC-FDM via the two-parameter power law clock and the Hurst exponent is 0.5.
The MSD is verified by using the experimental points of the chloride ions diffusion in concrete.
When compared to the linear Brownian motion, the results show that the power law MSD of the fBm-nlc is much better in fitting the experimental points of chloride ions in concrete.
The fBm-nlc clearly interprets the VC-FDM and provides a microscopic strategy in characterizing different types of non-Fickian diffusion processes with more different nonlinear functions.
Leveraging large-deviation statistics to decipher the stochastic properties of measured trajectories
(2021)
Extensive time-series encoding the position of particles such as viruses, vesicles, or individualproteins are routinely garnered insingle-particle tracking experiments or supercomputing studies.They contain vital clues on how viruses spread or drugs may be delivered in biological cells.Similar time-series are being recorded of stock values in financial markets and of climate data.Such time-series are most typically evaluated in terms of time-averaged mean-squareddisplacements (TAMSDs), which remain random variables for finite measurement times. Theirstatistical properties are different for differentphysical stochastic processes, thus allowing us toextract valuable information on the stochastic process itself. To exploit the full potential of thestatistical information encoded in measured time-series we here propose an easy-to-implementand computationally inexpensive new methodology, based on deviations of the TAMSD from itsensemble average counterpart. Specifically, we use the upper bound of these deviations forBrownian motion (BM) to check the applicability of this approach to simulated and real data sets.By comparing the probability of deviations fordifferent data sets, we demonstrate how thetheoretical bound for BM reveals additional information about observed stochastic processes. Weapply the large-deviation method to data sets of tracer beads tracked in aqueous solution, tracerbeads measured in mucin hydrogels, and of geographic surface temperature anomalies. Ouranalysis shows how the large-deviation properties can be efficiently used as a simple yet effectiveroutine test to reject the BM hypothesis and unveil relevant information on statistical propertiessuch as ergodicity breaking and short-time correlations.
Partial synchronous states appear between full synchrony and asynchrony and exhibit many interesting properties. Most frequently, these states are studied within the framework of phase approximation. The latter is used ubiquitously to analyze coupled oscillatory systems. Typically, the phase dynamics description is obtained in the weak coupling limit, i.e., in the first-order in the coupling strength. The extension beyond the first-order represents an unsolved problem and is an active area of research. In this paper, three partially synchronous states are investigated and presented in order of increasing complexity. First, the usage of the phase response curve for the description of macroscopic oscillators is analyzed. To achieve this, the response of the mean-field oscillations in a model of all-to-all coupled limit-cycle oscillators to pulse stimulation is measured. The next part treats a two-group Kuramoto model, where the interaction of one attractive and one repulsive group results in an interesting solitary state, situated between full synchrony and self-consistent partial synchrony. In the last part, the phase dynamics of a relatively simple system of three Stuart-Landau oscillators are extended beyond the weak coupling limit. The resulting model contains triplet terms in the high-order phase approximation, though the structural connections are only pairwise. Finally, the scaling of the new terms with the coupling is analyzed.
Global quantum thermometry
(2021)
A paradigm shift in quantum thermometry is proposed. To date, thermometry has relied on local estimation, which is useful to reduce statistical fluctuations once the temperature is very well known. In order to estimate temperatures in cases where few measurement data or no substantial prior knowledge are available, we build instead a method for global quantum thermometry. Based on scaling arguments, a mean logarithmic error is shown here to be the correct figure of merit for thermometry. Its full minimization provides an operational and optimal rule to postprocess measurements into a temperature reading, and it establishes a global precision limit. We apply these results to the simulated outcomes of measurements on a spin gas, finding that the local approach can lead to biased temperature estimates in cases where the global estimator converges to the true temperature. The global framework thus enables a reliable approach to data analysis in thermometry experiments.
The study of exoplanet atmospheres showed large diversity compared to the planets in our Solar system. Especially Jupiter-type exoplanets orbiting their host star in close orbits, the so-called hot and ultra-hot Jupiters, have been studied in detail due to their enhanced atmospheric signature. Due to their tidally locked status, the temperature difference between the day- and nightside triggers atmospheric winds that can lead to various fingerprints in the observations. Spatially resolved absorption lines during transit such as sodium (Na) could be a good tracer for such winds. Different works resolved the Na absorption lines on different exoplanets which show different line widths. Assuming that this could be attributed to such zonal jet streams, this work models the effect of such winds on synthetic absorption lines. For this, transiting Jupiter-type planets with rotational velocities similar to hot and ultra-hot Jupiter are considered. The investigation shows that high wind velocities could reproduce the broadening of Na-line profiles inferred in different high-resolution transit observations. There is a tendency that the broadening values decrease for planets with lower equilibrium temperature. This could be explained by atmospheric drag induced by the ionization of alkali lines that slow down the zonal jet streams, favouring their existence on hot Jupiter rather than ultra-hot Jupiter.
In the semiclassical limit (h) over bar -> 0, we analyze a class of self-adjoint Schrodinger operators H-(h) over bar = (h) over bar L-2 + (h) over barW + V center dot id(E) acting on sections of a vector bundle E over an oriented Riemannian manifold M where L is a Laplace type operator, W is an endomorphism field and the potential energy V has non-degenerate minima at a finite number of points m(1),... m(r) is an element of M, called potential wells. Using quasimodes of WKB-type near m(j) for eigenfunctions associated with the low lying eigenvalues of H-(h) over bar, we analyze the tunneling effect, i.e. the splitting between low lying eigenvalues, which e.g. arises in certain symmetric configurations. Technically, we treat the coupling between different potential wells by an interaction matrix and we consider the case of a single minimal geodesic (with respect to the associated Agmon metric) connecting two potential wells and the case of a submanifold of minimal geodesics of dimension l + 1. This dimension l determines the polynomial prefactor for exponentially small eigenvalue splitting.
The Rarita-Schwinger operator is the twisted Dirac operator restricted to 3/2-spinors. Rarita-Schwinger fields are solutions of this operator which are in addition divergence-free. This is an overdetermined problem and solutions are rare; it is even more unexpected for there to be large dimensional spaces of solutions. In this paper we prove the existence of a sequence of compact manifolds in any given dimension greater than or equal to 4 for which the dimension of the space of Rarita-Schwinger fields tends to infinity. These manifolds are either simply connected Kahler-Einstein spin with negative Einstein constant, or products of such spaces with flat tori. Moreover, we construct Calabi-Yau manifolds of even complex dimension with more linearly independent Rarita-Schwinger fields than flat tori of the same dimension.
Human migration is often studied using gravity models. These models, however, have known limitations, including analytic inconsistencies and a dependence on empirical data to calibrate multiple parameters for the region of interest. Overcoming these limitations, the radiation model has been proposed as an alternative, universal approach to predicting different forms of human mobility, but has not been adopted for studying migration. Here we show, using data on within-country migration from the USA and Mexico, that the radiation model systematically underpredicts long-range moves, while the traditional gravity model performs well for large distances. The universal opportunity model, an extension of the radiation model, shows an improved fit of long-range moves compared to the original radiation model, but at the cost of introducing two additional parameters. We propose a more parsimonious extension of the radiation model that introduces a single parameter. We demonstrate that it fits the data over the full distance spectrum and also-unlike the universal opportunity model-preserves the analytical property of the original radiation model of being equivalent to a gravity model in the limit of a uniform population distribution.
We present a supervised learning method to learn the propagator map of a dynamical system from partial and noisy observations. In our computationally cheap and easy-to-implement framework, a neural network consisting of random feature maps is trained sequentially by incoming observations within a data assimilation procedure. By employing Takens's embedding theorem, the network is trained on delay coordinates. We show that the combination of random feature maps and data assimilation, called RAFDA, outperforms standard random feature maps for which the dynamics is learned using batch data.
We use quantum chemical cluster models together with constrained density STM Ph CI functional theory (DFT) and ab initio molecular dynamics (AIMD) for open system to simulate tip and rationalize nonlocal scanning tunneling microscope (STM) manipulation experiments for Philh ci chlorobenzene (PhCl) on a Si(111)-7 X 7 surface. We consider three different processes, namely, the electron-induced dissociation of the carbon-chlorine bond for physisorbed PhCl molecules at low temperatures and the electron- or hole-induced desorption of chemisorbed PhCl at 300 K. All processes can be induced nonlocally, i.e., up to several nanometers (nm) away from the injection site, in STM experiments. We rationalize and explain the experimental findings regarding the STM-induced dissociation using constrained DFT. The coupling of STM-induced ion resonances to nuclear degrees of freedom is simulated with AIMD using the Gadzuk averaging approach for open systems. From this data, we predict a 4 fs lifetime for the cationic resonance. For the anion model, desorption could not be observed. In addition, the same cluster models are used for transition-state theory calculations, which are compared to and validated against time-lapse STM experiments.
'Complex systems are information processors' is a statement that is frequently made. Here we argue for the distinction between information processing-in the sense of encoding and transmitting a symbolic representation-and the formation of correlations (pattern formation/self-organisation). The study of both uses tools from information theory, but the purpose is very different in each case: explaining the mechanisms and understanding the purpose or function in the first case, versus data analysis and correlation extraction in the latter. We give examples of both and discuss some open questions. The distinction helps focus research efforts on the relevant questions in each case.
We provide an overview of the tools and techniques of resurgence theory used in the Borel-ecalle resummation method, which we then apply to the massless Wess-Zumino model. Starting from already known results on the anomalous dimension of the Wess-Zumino model, we solve its renormalisation group equation for the two-point function in a space of formal series. We show that this solution is 1-Gevrey and that its Borel transform is resurgent. The Schwinger-Dyson equation of the model is then used to prove an asymptotic exponential bound for the Borel transformed two-point function on a star-shaped domain of a suitable ramified complex plane. This proves that the two-point function of the Wess-Zumino model is Borel-ecalle summable.
High-resolution observations of polar crown and high-latitude filaments are scarce. We present a unique sample of such filaments observed in high-resolution H alpha narrow-band filtergrams and broad-band images, which were obtained with a new fast camera system at the Vacuum Tower Telescope (VTT), Tenerife, Spain. The Chromospheric Telescope (ChroTel) provided full-disk context observations in H alpha, CaiiK, and Hei 10830 angstrom. The Helioseismic and Magnetic Imager (HMI) and the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO) provided line-of-sight magnetograms and ultraviolet (UV) 1700 angstrom filtergrams, respectively. We study filigree in the vicinity of polar crown and high-latitude filaments and relate their locations to magnetic concentrations at the filaments' footpoints. Bright points are a well studied phenomenon in the photosphere at low latitudes, but they were not yet studied in the quiet network close to the poles. We examine size, area, and eccentricity of bright points and find that their morphology is very similar to their counterparts at lower latitudes, but their sizes and areas are larger. Bright points at the footpoints of polar crown filaments are preferentially located at stronger magnetic flux concentrations, which are related to bright regions at the border of supergranules as observed in UV filtergrams. Examining the evolution of bright points on three consecutive days reveals that their amount increases while the filament decays, which indicates they impact the equilibrium of the cool plasma contained in filaments.
In this work, we investigate the potassium excess absorption around 7699 Å of the exoplanets HD189733b and HD209458b. For this purpose, we used high-spectral resolution transit observations acquired with the 2 × 8.4 m Large Binocular Telescope (LBT) and the Potsdam Echelle Polarimetric and Spectroscopic Instrument (PEPSI). For a bandwidth of 0.8 Å, we present a detection >7σ with an absorption level of 0.18 per cent for HD189733b. Applying the same analysis to HD209458b, we can set 3σ upper limit of 0.09 per cent, even though we do not detect a K-excess absorption. The investigation suggests that the K feature is less present in the atmosphere of HD209458b than in the one of HD189733b. This comparison confirms previous claims that the atmospheres of these two planets must have fundamentally different properties.
With the advent of big data and data lakes, data are often integrated from multiple sources. Such integrated data are often of poor quality, due to inconsistencies, errors, and so forth. One way to check the quality of data is to infer functional dependencies (fds). However, in many modern applications it might be necessary to extract properties and relationships that are not captured through fds, due to the necessity to admit exceptions, or to consider similarity rather than equality of data values. Relaxed fds (rfds) have been introduced to meet these needs, but their discovery from data adds further complexity to an already complex problem, also due to the necessity of specifying similarity and validity thresholds. We propose Domino, a new discovery algorithm for rfds that exploits the concept of dominance in order to derive similarity thresholds of attribute values while inferring rfds. An experimental evaluation on real datasets demonstrates the discovery performance and the effectiveness of the proposed algorithm.
Data-driven prediction and physics-agnostic machine-learning methods have attracted increased interest in recent years achieving forecast horizons going well beyond those to be expected for chaotic dynamical systems. In a separate strand of research data-assimilation has been successfully used to optimally combine forecast models and their inherent uncertainty with incoming noisy observations. The key idea in our work here is to achieve increased forecast capabilities by judiciously combining machine-learning algorithms and data assimilation. We combine the physics-agnostic data -driven approach of random feature maps as a forecast model within an ensemble Kalman filter data assimilation procedure. The machine-learning model is learned sequentially by incorporating incoming noisy observations. We show that the obtained forecast model has remarkably good forecast skill while being computationally cheap once trained. Going beyond the task of forecasting, we show that our method can be used to generate reliable ensembles for probabilistic forecasting as well as to learn effective model closure in multi-scale systems. (C) 2021 Elsevier B.V. All rights reserved.
Fractional Brownian motion in superharmonic potentials and non-Boltzmann stationary distributions
(2021)
We study the stochastic motion of particles driven by long-range correlated fractional Gaussian noise (FGN) in a superharmonic external potential of the form U(x) proportional to x(2n) (n is an element of N). When the noise is considered to be external, the resulting overdamped motion is described by the non-Markovian Langevin equation for fractional Brownian motion. For this case we show the existence of long time, stationary probability density functions (PDFs) the shape of which strongly deviates from the naively expected Boltzmann PDF in the confining potential U(x). We analyse in detail the temporal approach to stationarity as well as the shape of the non-Boltzmann stationary PDF. A typical characteristic is that subdiffusive, antipersistent (with negative autocorrelation) motion tends to effect an accumulation of probability close to the origin as compared to the corresponding Boltzmann distribution while the opposite trend occurs for superdiffusive (persistent) motion. For this latter case this leads to distinct bimodal shapes of the PDF. This property is compared to a similar phenomenon observed for Markovian Levy flights in superharmonic potentials. We also demonstrate that the motion encoded in the fractional Langevin equation driven by FGN always relaxes to the Boltzmann distribution, as in this case the fluctuation-dissipation theorem is fulfilled.
A characterization of the essential spectrum of Schrodinger operators on infinite graphs is derived involving the concept of R-limits. This concept, which was introduced previously for operators on N and Z(d) as "right-limits," captures the behaviour of the operator at infinity. For graphs with sub-exponential growth rate, we show that each point in sigma(ss)(H) corresponds to a bounded generalized eigenfunction of a corresponding R-limit of H. If, additionally, the graph is of uniform sub-exponential growth, also the converse inclusion holds.
Remote synchronization implies that oscillators interacting not directly but via an additional unit (hub) adjust their frequencies and exhibit frequency locking while the hub remains asynchronous. In this paper, we analyze the mechanisms of remote synchrony in a small network of three coupled Stuart-Landau oscillators using recent results on higher-order phase reduction. We analytically demonstrate the role of two factors promoting remote synchrony. These factors are the nonisochronicity of oscillators and the coupling terms appearing in the secondorder phase approximation. We show a good correspondence between our theory and numerical results for small and moderate coupling strengths.
We derive modified reflection coefficients for electromagnetic waves in the THz and far infrared range. The idea is based on hydrodynamic boundary conditions for metallic conduction electrons. The temperature-dependent part of the Casimir pressure between metal plates is evaluated. The results should shed light on the "thermal anomaly," where measurements deviate from the standard fluctuation electrodynamics for conducting metals.
Characterising stochastic motion in heterogeneous media driven by coloured non-Gaussian noise
(2021)
We study the stochastic motion of a test particle in a heterogeneous medium in terms of a position dependent diffusion coefficient mimicking measured deterministic diffusivity gradients in biological cells or the inherent heterogeneity of geophysical systems. Compared to previous studies we here investigate the effect of the interplay of anomalous diffusion effected by position dependent diffusion coefficients and coloured non-Gaussian noise. The latter is chosen to be distributed according to Tsallis' q-distribution, representing a popular example for a non-extensive statistic. We obtain the ensemble and time averaged mean squared displacements for this generalised process and establish its non-ergodic properties as well as analyse the non-Gaussian nature of the associated displacement distribution. We consider both non-stratified and stratified environments.
The non-equilibrium state of two oscillators with a mutual interaction and coupled to separate heat baths is discussed. Bosonic baths are considered, and an exact spectral representation for the elements of the covariance matrix is provided analytically. A wide class of spectral densities for the relevant bath modes is allowed for. The validity of the fluctuation-dissipation relation is established for global equilibrium (both baths at the same temperature) in the stationary state. Spectral measures of entanglement are suggested by comparing to the equilibrium spectrum of zero-point fluctuations. No rotating-wave approximation is applied, and anomalous heat transport from cold to hot bath, as reported in earlier work, is demonstrated not to occur.
We consider a system of two spins under a scanning tunneling microscope bias and derive its master equation. We find that the tunneling elements to the electronic contacts (tip and substrate) generate an exchange interaction between the spins as well as a Dzyaloshinskii-Moriya interaction in the presence of spin-orbit coupling. The tunnel current spectrum then shows additional lines compared to conventional spin-resonance experiments. When the spins have degenerate Larmor frequencies and equal tunneling amplitudes (without spin orbit), there is a dark state with a vanishing decay rate. The coupling to the electronic environment generates significant spin-spin entanglement via the dark state, even if the initial state is nonentangled.
Bifurcations in rotating spherical shell convection under the influence of differential rotation
(2021)
The bifurcations of thermal convection in a rotating spherical shell heated from the inner sphere and driven by the buoyancy of a central gravity field are studied numerically. This model of spherical Rayleigh-Benard convection describes large-scale convection in planets and in the outer zones of celestial bodies. In this work, the influence of an additionally imposed differential rotation of the inner sphere with respect to the outer one on the heat transfer and, more generally, on the whole bifurcation structure is investigated. In addition to numerical simulations, path-following techniques are applied in order to compute both stable and unstable solution branches. The dynamics and the heat transfer are essentially determined by a global bifurcation, which we have identified as a homoclinic bifurcation that consists of a collision of a stable modulated rotating with an unstable rotating wave.
I study deterministic dynamics of chiral active particles in two dimensions. Particles are considered as discs interacting with elastic repulsive forces. An ensemble of particles, started from random initial conditions, demonstrates chaotic collisions resulting in their normal diffusion. This chaos is transient, as rather abruptly a synchronous collisionless state establishes. The life time of chaos grows exponentially with the number of particles. External forcing (periodic or chaotic) is shown to facilitate the synchronization transition.
Spherical particles from shape-memory polymers (SMP) can be stretched to ellipsoids with high aspect ratio (AR) and temporarily stabilized. They can switch back to low AR upon thermal stimulation. Here, the creation of an alternative shape-switching capability of particles from low to high AR is introduced, where a SMP matrix from polyvinyl alcohol (PVA) is used to create crosslinked high AR particles and to program the embedded micrometer-sized particles from a second SMP (oligo(epsilon-caprolactone) micronetworks, MN) with a low switching temperature T-sw. This programming proceeds through shape-recovery of the PVA matrix, from which the MN are harvested by PVA matrix dissolution. The use of a dissolvable SMP matrix may be a general strategy to efficiently create systems with complex moving capabilities.
Master equations are a vital tool to model heat flow through nanoscale thermodynamic systems. Most practical devices are made up of interacting subsystems and are often modelled using either local master equations (LMEs) or global master equations (GMEs). While the limiting cases in which either the LME or the GME breaks down are well understood, there exists a 'grey area' in which both equations capture steady-state heat currents reliably but predict very different transient heat flows. In such cases, which one should we trust? Here we show that, when it comes to dynamics, the local approach can be more reliable than the global one for weakly interacting open quantum systems. This is due to the fact that the secular approximation, which underpins the GME, can destroy key dynamical features. To illustrate this, we consider a minimal transport setup and show that its LME displays exceptional points (EPs). These singularities have been observed in a superconducting-circuit realisation of the model [1]. However, in stark contrast to experimental evidence, no EPs appear within the global approach. We then show that the EPs are a feature built into the Redfield equation, which is more accurate than the LME and the GME. Finally, we show that the local approach emerges as the weak-interaction limit of the Redfield equation, and that it entirely avoids the secular approximation.
We report a comparison of two photonic techniques for single-molecule sensing: fluorescence nanoscopy and optoplasmonic sensing. As the test system, oligonucleotides with and without fluorescent labels are transiently hybridized to complementary "docking" strands attached to gold nanorods. Comparing the measured single-molecule kinetics helps to examine the influence of the fluorescent labels as well as factors arising from different sensing geometries. Our results demonstrate that DNA dissociation is not significantly altered by the fluorescent labels and that DNA association is affected by geometric factors in the two techniques. These findings open the door to exploiting plasmonic sensing and fluorescence nanoscopy in a complementary fashion, which will aid in building more powerful sensors and uncovering the intricate effects that influence the behavior of single molecules.
We analyze historical data of stock-market prices for multiple financial indices using the concept of delay-time averaging for the financial time series (FTS). The region of validity of our recent theoretical predictions [Cherstvy A G et al 2017 New J. Phys. 19 063045] for the standard and delayed time-averaged mean-squared 'displacements' (TAMSDs) of the historical FTS is extended to all lag times. As the first novel element, we perform extensive computer simulations of the stochastic differential equation describing geometric Brownian motion (GBM) which demonstrate a quantitative agreement with the analytical long-term price-evolution predictions in terms of the delayed TAMSD (for all stock-market indices in crisis-free times). Secondly, we present a robust procedure of determination of the model parameters of GBM via fitting the features of the price-evolution dynamics in the FTS for stocks and cryptocurrencies. The employed concept of single-trajectory-based time averaging can serve as a predictive tool (proxy) for a mathematically based assessment and rationalization of probabilistic trends in the evolution of stock-market prices.
We study the probability density function (PDF) of the first-reaction times between a diffusive ligand and a membrane-bound, immobile imperfect target region in a restricted 'onion-shell' geometry bounded by two nested membranes of arbitrary shapes. For such a setting, encountered in diverse molecular signal transduction pathways or in the narrow escape problem with additional steric constraints, we derive an exact spectral form of the PDF, as well as present its approximate form calculated by help of the so-called self-consistent approximation. For a particular case when the nested domains are concentric spheres, we get a fully explicit form of the approximated PDF, assess the accuracy of this approximation, and discuss various facets of the obtained distributions. Our results can be straightforwardly applied to describe the PDF of the terminal reaction event in multi-stage signal transduction processes.
We study the first passage dynamics for a diffusing particle experiencing a spatially varying diffusion coefficient while driven by correlated additive Gaussian white noise and multiplicative coloured non-Gaussian noise. We consider three functional forms for position dependence of the diffusion coefficient: power-law, exponential, and logarithmic. The coloured non-Gaussian noise is distributed according to Tsallis' q-distribution. Tracks of the non-Markovian systems are numerically simulated by using the fourth-order Runge-Kutta algorithm and the first passage times (FPTs) are recorded. The FPT density is determined along with the mean FPT (MFPT). Effects of the noise intensity and self-correlation of the multiplicative noise, the intensity of the additive noise, the cross-correlation strength, and the non-extensivity parameter on the MFPT are discussed.
The electron-phonon scattering is one of the main microscopic mechanisms responsible for the spin-flip in the transient state of ultrafast demagnetization. Here, we present an experimental determination of the temperature-dependent electron-phonon scattering rate in Gd. Using a static x-ray emission spectroscopy method, where the reduction of the decay peak intensities when increasing the temperature is quantified, we measure independently the electron-phonon scattering rate for the 5d and the 4f electrons. We deduce the temperature dependence of scattering for the 5d electrons, while no effect on the phonon population is observed for the 4f electrons. Our results suggest that the ultrafast magnetization dynamics in Gd is triggered by the spin-flip in the 5d electrons. We also evidence the existence of a temperature threshold, above which spin-flip scattering of the 5d electrons takes place. We deduce that during the transient state of ultrafast demagnetization, the exchange energy between 5d electrons has to be overcome before the microscopic electron-phonon scattering process can occur.
How different microscopic mechanisms of ultrafast spin dynamics coexist and interplay is not only relevant for the development of spintronics but also for the thorough description of physical systems out-of-equilibrium. In pure crystalline ferromagnets, one of the main microscopic mechanism of spin relaxation is the electron-phonon (el-ph) driven spin-flip, or Elliott-Yafet, scattering. Unexpectedly, recent experiments with ferro- and ferrimagnetic alloys have shown different dynamics for the different sublattices. These distinct sublattice dynamics are contradictory to the Elliott-Yafet scenario. In order to rationalize this discrepancy, it has been proposed that the intra- and intersublattice exchange interaction energies must be considered in the microscopic demagnetization mechanism, too. Here, using a temperature-dependent x-ray emission spectroscopy (XES) method, we address experimentally the element specific el-ph angular momentum transfer rates, responsible for the spin-flips in the respective (sub)lattices of Fe20Ni80, Fe50Ni50 and pure nickel single crystals. We establish how the deduced rate evolution with the temperature is linked to the exchange coupling constants reported for different alloy stoichiometries and how sublattice exchange energies threshold the related el-ph spin-flip channels. Thus, these results evidence that the Elliott-Yafet spin-flip scattering, thresholded by sublattice exchange energies, is the relevant microscopic process to describe sublattice dynamics in alloys and elemental magnetic systems.
Steric hindrance of hydration and hydrogen bond enhancement by localized charges have been identified as key factors for the massive chemical differences between the hydroxypyridine/pyridone isomers in aqueous solution. While all isomers occur mainly in the hydroxypyridine form in the gas phase, they differ by more than 3 orders of magnitude both in their acidity and tautomeric equilibrium constants upon hydration. By monitoring the electronic and solvation structures as a function of the protonation state and the O- substitution position on the pyridine ring, the amplification of the isomeric differences in aqueous solution has been investigated. Near-edge X-ray absorption fine structure (NEXAFS) measurements at the N K-edge served as the probe of the chemical state. The combination of molecular dynamics simulations, complete active space self-consistent field (CASSCF), and time-dependent density functional theory (TD-DFT) spectral calculations contributes to unraveling the principles of tautomerism and acidity in multiple biochemical systems based on tautomerism.
Laser based powder bed fusion additive manufacturing offers the flexibility to incorporate standard and user-defined scan strategies in a layer or in between the layers for the customized fabrication of metallic components. In the present study, four different scan strategies and their impact on the development of microstructure, texture, and residual stresses in laser powder bed fusion additive manufacturing of a nickel-based superalloy Inconel 718 was investigated. Light microscopy, scanning electron microscopy combined with electron back-scatter diffraction, and neutron diffraction were used as the characterization tools. Strong textures with epitaxially grown columnar grains were observed along the build direction for the two individual scan strategies. Patterns depicting the respective scan strategies were visible in the build plane, which dictated the microstructure development in the other planes. An alternating strategy combining the individual strategies in the successive layers and a 67 degrees rotational strategy weakened the texture by forming finer micro-structural features. Von Mises equivalent stress plots revealed lower stress values and gradients, which translates as lower distortions for the alternating and rotational strategies. Overall results confirmed the scope for manipulating the microstructure, texture, and residual stresses during laser powder bed fusion additive manufacturing by effectively controlling the scan strategies.
We consider a sequential cascade of molecular first-reaction events towards a terminal reaction centre in which each reaction step is controlled by diffusive motion of the particles. The model studied here represents a typical reaction setting encountered in diverse molecular biology systems, in which, e.g. a signal transduction proceeds via a series of consecutive 'messengers': the first messenger has to find its respective immobile target site triggering a launch of the second messenger, the second messenger seeks its own target site and provokes a launch of the third messenger and so on, resembling a relay race in human competitions. For such a molecular relay race taking place in infinite one-, two- and three-dimensional systems, we find exact expressions for the probability density function of the time instant of the terminal reaction event, conditioned on preceding successful reaction events on an ordered array of target sites. The obtained expressions pertain to the most general conditions: number of intermediate stages and the corresponding diffusion coefficients, the sizes of the target sites, the distances between them, as well as their reactivities are arbitrary.
Hydrogels with a hierarchical structure were prepared from a new highly water-soluble crosslinker N,N,N',N'-tetramethyl-N,N'-bis(2-ethylmethacrylate)-propyl-1,3-diammonium dibromide and from the sulfobetaine monomer 2-(N-3-sulfopropyl-N,N-dimethyl ammonium)ethyl methacrylate. The free radical polymerization of the two compounds is rapid and yields near-transparent hydrogels with sizes up to 5 cm in diameter. Rheology shows a clear correlation between the monomer-to-crosslinker ratio and the storage and loss moduli of the hydrogels. Cryo-scanning electron microscopy, low-field nuclear magnetic resonance (NMR) spectroscopy, and small-angle X-ray scattering show that the gels have a hierarchical structure with features spanning the nanometer to the sub-millimeter scale. The NMR study is challenged by the marked inhomogeneity of the gels and the complex chemical structure of the sulfobetaine monomer. NMR spectroscopy shows how these complications can be addressed via a novel fitting approach that considers the mobility gradient along the side chain of methacrylate-based monomers.
Self-organized coherence-incoherence patterns, called chimera states, have first been reported in systems of Kuramoto oscillators. For coupled excitable units, similar patterns where coherent units are at rest are called bump states. Here, we study bumps in an array of active rotators coupled by nonlocal attraction and global repulsion. We demonstrate how they can emerge in a supercritical scenario from completely coherent Turing patterns: a single incoherent unit appears in a homoclinic bifurcation, undergoing subsequent transitions to quasiperiodic and chaotic behavior, which eventually transforms into extensive chaos with many incoherent units. We present different types of transitions and explain the formation of coherence-incoherence patterns according to the classical paradigm of short-range activation and long-range inhibition.
Various mathematical Black-Scholes-Merton-like models of option pricing employ the paradigmatic stochastic process of geometric Brownian motion (GBM). The innate property of such models and of real stock-market prices is the roughly exponential growth of prices with time [on average, in crisis-free times]. We here explore the ensemble- and time averages of a multiplicative-noise stochastic process with power-law-like time-dependent volatility, sigma(t) similar to t(alpha), named scaled GBM (SGBM). For SGBM, the mean-squared displacement (MSD) computed for an ensemble of statistically equivalent trajectories can grow faster than exponentially in time, while the time-averaged MSD (TAMSD)-based on a sliding-window averaging along a single trajectory-is always linear at short lag times Delta. The proportionality factor between these the two averages of the time series is Delta/T at short lag times, where T is the trajectory length, similarly to GBM. This discrepancy of the scaling relations and pronounced nonequivalence of the MSD and TAMSD at Delta/T << 1 is a manifestation of weak ergodicity breaking for standard GBM and for SGBM with s (t)-modulation, the main focus of our analysis. The analytical predictions for the MSD and mean TAMSD for SGBM are in quantitative agreement with the results of stochastic computer simulations.
We performed numerical simulations with the Kuramoto model and experiments with oscillatory nickel electrodissolution to explore the dynamical features of the transients from random initial conditions to a fully synchronized (one-cluster) state. The numerical simulations revealed that certain networks (e.g., globally coupled or dense Erdos-Renyi random networks) showed relatively simple behavior with monotonic increase of the Kuramoto order parameter from the random initial condition to the fully synchronized state and that the transient times exhibited a unimodal distribution. However, some modular networks with bridge elements were identified which exhibited non-monotonic variation of the order parameter with local maximum and/or minimum. In these networks, the histogram of the transients times became bimodal and the mean transient time scaled well with inverse of the magnitude of the second largest eigenvalue of the network Laplacian matrix. The non-monotonic transients increase the relative standard deviations from about 0.3 to 0.5, i.e., the transient times became more diverse. The non-monotonic transients are related to generation of phase patterns where the modules are synchronized but approximately anti-phase to each other. The predictions of the numerical simulations were demonstrated in a population of coupled oscillatory electrochemical reactions in global, modular, and irregular tree networks. The findings clarify the role of network structure in generation of complex transients that can, for example, play a role in intermittent desynchronization of the circadian clock due to external cues or in deep brain stimulations where long transients are required after a desynchronization stimulus.
Moving spiral wave chimeras
(2021)
We consider a two-dimensional array of heterogeneous nonlocally coupled phase oscillators on a flat torus and study the bound states of two counter-rotating spiral chimeras, shortly two-core spiral chimeras, observed in this system. In contrast to other known spiral chimeras with motionless incoherent cores, the two-core spiral chimeras typically show a drift motion. Due to this drift, their incoherent cores become spatially modulated and develop specific fingerprint patterns of varying synchrony levels. In the continuum limit of infinitely many oscillators, the two-core spiral chimeras can be studied using the Ott-Antonsen equation. Numerical analysis of this equation allows us to reveal the stability region of different spiral chimeras, which we group into three main classes-symmetric, asymmetric, and meandering spiral chimeras.
Generalized (non-Markovian) diffusion equations with different memory kernels and subordination schemes based on random time change in the Brownian diffusion process are popular mathematical tools for description of a variety of non-Fickian diffusion processes in physics, biology, and earth sciences. Some of such processes (notably, the fluid limits of continuous time random walks) allow for either kind of description, but other ones do not. In the present work we discuss the conditions under which a generalized diffusion equation does correspond to a subordination scheme, and the conditions under which a subordination scheme does possess the corresponding generalized diffusion equation. Moreover, we discuss examples of random processes for which only one, or both kinds of description are applicable.
We investigate whether the dust content of the circum-galactic medium (CGM) depends on the location of the quasar sightline with respect to the galaxy major-axis using 13 galaxy-Mg II absorber pairs (9-81 kpc distance) from the MusE GAs FLOw and Wind (MEGAFLOW) survey at 0.4 < z < 1.4. The dust content of the CGM is obtained from [Zn/Fe] using ultraviolet and visual echelle spectrograph data. When a direct measurement of [Zn/Fe] is unavailable, we estimate the dust depletion from a method that consists in solving for the depletion from multiple singly ionized ions (e.g. Mn II, Cr II, and Zn II) since each ion depletes on dust grains at different rates. We find a positive correlation between the azimuthal angle and [Zn/Fe] with a Pearson's gamma = 0.70 +/- 0.14. The sightlines along the major axis show [Zn/Fe] < 0.5, whereas the [Zn/Fe] is > 0.8 along the minor axis. These results suggest that the CGM along the minor axis is on average more metal enriched (by approximate to 1 dex) than the gas located along the major axis of galaxies provided that dust depletion is a proxy for metallicity. This anisotropic distribution is consistent with recent results on outflow and accretion in hydro-dynamical simulations.
Additive manufacturing (AM) of metals and in particular laser powder bed fusion (LPBF) enables a degree of freedom in design unparalleled by conventional subtractive methods. To ensure that the designed precision is matched by the produced LPBF parts, a full understanding of the interaction between the laser and the feedstock powder is needed. It has been shown that the laser also melts subjacent layers of material underneath. This effect plays a key role when designing small cavities or overhanging structures, because, in these cases, the material underneath is feed-stock powder. In this study, we quantify the extension of the melt pool during laser illumination of powder layers and the defect spatial distribution in a cylindrical specimen. During the LPBF process, several layers were intentionally not exposed to the laser beam at various locations, while the build process was monitored by thermography and optical tomography. The cylinder was finally scanned by X-ray computed tomography (XCT). To correlate the positions of the unmolten layers in the part, a staircase was manufactured around the cylinder for easier registration. The results show that healing among layers occurs if a scan strategy is applied, where the orientation of the hatches is changed for each subsequent layer. They also show that small pores and surface roughness of solidified material below a thick layer of unmolten material (>200 mu m) serve as seeding points for larger voids. The orientation of the first two layers fully exposed after a thick layer of unmolten powder shapes the orientation of these voids, created by a lack of fusion.