Papers

In the northern hemisphere, river subjects the right bank to the pressure generated by the Coriolis force, which will increase the erosion of the river on the right bank. On the other hand, the Coriolis force also causes the sediments in the water to move to the right bank, which will increase the sediment deposition on the right bank of the river. Therefore, for rivers with low sediment content, Coriolis force will increase the erosion of river water on the right bank; for rivers with high sediment content, Coriolis force will increase the sedimentation of sediment on the right bank. It is noted that the Lanzhou section of the Yellow River has siltation of sands and pebbles to the right (south) bank. It is believed that this is caused by the Coriolis force moving the sands and pebbles to the right bank.

We introduce an optimized protocol of fracture pattern classification using an artificial neural network to identify the solvent involved in the desiccation cracking process of starch-liquid slurries, even after it has been completely evaporated. For this purpose, image analysis techniques were used to characterize patterns obtained from drying suspensions using single solvents (water, ethanol, acetone) and two-component solvents (water-ethanol mixtures at different concentrations). Frequency histograms were generated based on nine morphological features, taking into account their size, shape, geometry and orientational ordering. Subsequently, we used these histograms as input data into artificial neural network variants to determine the set of features that lead to the higher accuracy in solvent identification. We obtained an average accuracy of $96(\pm 1)\%$ considering all solvents in the analysis. The highest accuracy was obtained with sets of features that include the crack area distribution. The proposed protocol can help to determine the combination of features that optimize pattern recognition in other fields of science and engineering.

We propose a sharp and conservative 3D numerical method for simulating moving contact lines on complex geometries, developed within a coupled geometric Volume-of-Fluid (VOF) and embedded boundary framework. The first major contribution is a modified VOF advection and reconstruction scheme specifically designed for mixed cells containing liquid, gas, and solid phases. This formulation ensures strict local mass conservation in the presence of arbitrarily shaped embedded boundaries. To overcome the severe time-step limitation caused by small cut cells, a redistribution advection strategy is introduced, which completely removes the CFL constraint while preserving both local and global volume conservation. The second key contribution is a novel 3D contact angle imposition technique built upon the height function framework. By incorporating a pre-fitting paraboloid procedure, the method achieves robust curvature estimation and accurate enforcement of contact angle conditions on irregular solid surfaces. In addition, contact angle hysteresis is modeled to capture more realistic wetting dynamics. A series of challenging benchmark tests have been conducted to demonstrate the accuracy, robustness, and superiority of the proposed method compared with existing sharp-interface approaches. This study, for the first time, establishes a fully geometric and conservative VOF-based scheme capable of accurately resolving contact line dynamics on arbitrarily complex 3D surfaces.

Kossin et al. (2020) report a rising ratio of satellite observations of major C3-C5 storms relative to all C1-C5 storms from 1979 to 2017. Decomposing their R = N(C3+)/N(C1+) statistic into per-category shares shows that their trend was driven primarily by fewer C1 rather than more C3-C5 observations. From the first half to the second half of their sample period, their per-year C1 observations fell by 17%. However, extending the record through 2023 greatly changes the picture. Although the relative decline in C1 observations persists, C3 and C4 observations now increase, too. The signal about the intensification of storms now becomes genuine in the extended sample, in that it is driven no longer only by fewer weak but now also by more strong tropical cyclone observations.

We provide a pedagogical review of the Schwinger effect, i.e., the non-perturbative production of particle and anti-particle pairs from the vacuum by strong fields, as well as related strong-field phenomena. Beginning with an overview of the Schwinger effect in quantum electrodynamics, we discuss its extensions to quantum chromodynamics and its applications in nuclear physics, including high-$Z$ nuclei, string breaking, relativistic heavy-ion collisions, and the chiral anomaly.

We develop a hydrodynamic framework for the interactions and collective dynamics of force dipoles embedded in a compressible fluid membrane supported by a shallow viscous subphase. Starting from the generalized two-dimensional Stokes equations with shear, dilatational, and odd (Hall) viscosities, we derive an exact real-space Green tensor using Hankel transforms. The resulting tensor is characterized by three hydrodynamic screening scales associated with shear, compressional, and odd-viscous modes, and smoothly reduces to the standard limiting cases of incompressible membranes and compressible parity-symmetric membranes, while also capturing the chiral response generated by odd viscosity. Using this Green tensor we obtain the velocity and vorticity fields generated by a force dipole and formulate the dynamical system governing interacting dipoles. The analysis reveals several distinct dynamical regimes and identifies observables that isolate the antisymmetric odd-viscous contribution to dipole interactions, including transverse drift and chiral relative motion.

Halide segregation in metal halide perovskites limits their bandgap tunability and hinders their adoption in tandem solar cells and light emitting diodes. Here, we reveal the thermodynamic driving force behind halide segregation in mixed halide (Br-I) perovskites. By performing first-principles calculations on slab models with varying bromide and iodide distributions, we demonstrate that bromide ions preferentially occupy surface sites over bulk sites. Our simulations show that the segregation tendency is higher in MAPb(Br$_x$I$_{1-x}$)$_3$ (MA=methylammonium) compared to FA$_{0.8}$Cs$_{0.2}$Pb(Br$_x$I$_{1-x}$)$_3$, highlighting the role of the A-site cation. To quantify this effect, we establish a descriptor for halide segregation: the difference in defect formation energies of Br antisite defects between the bulk and the surface, which confirms the role of the A-site cation at equimolar Br-I concentration. Furthermore, we identify the localization of photo-generated holes near iodide ions, which triggers their oxidation and accelerates the formation of iodide vacancies, thereby promoting segregation. Overall, this work establishes defect thermodynamics as a framework for understanding halide segregation and provides a structural basis for designing stable mixed halide perovskites.

Digital holography is an interference-based imaging technique capable of recording both the amplitude and phase of an electromagnetic field. It can be obtained at the laser illumination wavelength, but also with second-harmonic generation, since the latter is produced in a coherent process. Here we describe the development of a harmonic holographic microscope for 3D single-shot mapping of second-harmonic emitters. The knowledge of the scattered field, in amplitude and phase, in a given plane, that of the camera, allows its reconstruction in any other plane using the angular spectrum representation of the optical fields, a process called 3D numerical back-propagation. In order to probe the polarization dependence of the sample nonlinear response, we implement polarization multiplexing, in which a Wollaston prism creates two off-axis reference beams with orthogonal polarizations and non-parallel propagation directions. Each reference only interferes with the corresponding polarization component in the sample SHG emission, thus providing two independent sets of interference fringes which are easily separated in the angular spectrum representation. From a single measurement, two second-harmonic fields corresponding to orthogonal polarizations can be back-propagated. In the particular case of collagen, the second-harmonic polarization state can reveal the orientation or disorder of molecules and fibers. We demonstrate the feasibility of the method by reconstructing the spatial distribution of the second-harmonic field generated by collagen fibers in a rat-tail tendon sample and show that polarization-multiplexed holography can provide single-shot 3D mapping of biophysical parameters such as the helical pitch angle of collagen molecules.

In this study, we present a comprehensive investigation of the structural, optical, and electrical properties of Bifidobacterium longum subsp. longum 35624 (BB35) thin films, and demonstrate their application as a novel relative humidity sensor. UV-Visible spectroscopy revealed that BB35 exhibits two distinct optical absorption regions, corresponding to direct band gaps of 2.1 \pm 0.05 eV and 2.8 \pm 0.05 eV, as confirmed by Tauc plot analysis, establishing BB35 as a genuine wide-bandgap semiconductor material. Photoluminescence measurements under 280 nm excitation exhibited a broad emission spectrum, which was deconvoluted into four Gaussian peaks centered at 434 nm (2.86 eV), 499 nm (2.48 eV), 543 nm (2.3 eV), and 620 nm (2.0 eV), indicating the presence of multiple radiative recombination centers characteristic of semiconducting materials. Electrical characterization revealed dispersive charge transport with current decay following a power-law I \propto t^{-\alpha} (\alpha \approx 0.3), suggesting Poole-Frenkel conduction mechanism typically observed in disordered organic semiconductors. The relative humidity (RH) sensing performance of BB35 films was evaluated using gold interdigital electrodes across 15-90% RH range. The sensor exhibited reversible response with sensitivity increasing linearly from 0.85 to 4.80 as RH increased from 15% to 90%. The devices demonstrated excellent stability over two months with less than 5% degradation in baseline current. These results establish BB35 thin films as a promising eco-friendly semiconducting material for humidity sensing applications and open new avenues for integrating biological materials into electronic and optoelectronic devices.

We present new relations derived from Noether's identity that reveal the compatibility between the components of the Hessian matrix of the Lagrangian, the infinitesimal symmetry transformation of the configuration variables and time, and a constant of motion. Using these relations, we develop two new methods to incorporate symmetry requirements directly into the inverse problem of mechanics, thereby restricting the set of acceptable Lagrangians. We accomplish this by combining these relations with Helmholtz's conditions, which allow us to construct Lagrangians whose actions exhibit specific symmetries from the outset. The theory is illustrated with one- and two-dimensional examples.

Dual-comb distance metrology combines sub-um precision with absolute distance measurement over meter-scale non-ambiguity ranges. The most common interferometric implementation requires sophisticated approaches to achieve continuous streaming due to the need for digitization at near-gigasample/s rates. Here, we exploit the naturally low data burden of two-photon dual-comb LiDAR to demonstrate continuously-streamed distance metrology at 11.5 kHz, reaching a precision of nearly 1 um in an averaging time of 10 ms. Using free-running 500 MHz Er,Yb:glass femtosecond lasers we achieve sampling rates >10 kHz, sufficient to demonstrate the capture of a four-minute audio track from the displacement of a loudspeaker-mounted mirror. The ability to perform high-speed yet low-data-burden distance metrology using unstabilized lasers presents exciting opportunities for diverse applications in industrial machine-tool control and calibration.

Coupling physics with machine learning models has shown great potential for solving fluid dynamics problems governed by partial differential equations. However, conventional methods, such as physics-informed neural networks, often suffer from slow convergence, unstable training, and limited generalization across different flow conditions. To overcome these challenges, this study proposes a novel meta-learning en- hanced physics-informed neural networks (Meta-PINNs) framework, which integrates a meta-optimization strategy into the training process. The approach allows the model to automatically adapt its learning process to varying physical regimes, thereby substantially improving both training efficiency and predictive robustness. The proposed Meta-PINNs model is evaluated on two representative flow problems: (1) unsteady flow around a circular cylinder at multiple inlet Reynolds numbers, and (2) steady turbulent flow within a compressor cascade passage at various angles of attack. In both cases, the extrapolation performance of the developed framework is comprehensively tested by predicting the flow fields at Reynolds numbers and angles of attack that are not included in the training set. The results demonstrate that Meta-PINNs achieve a 1-2 order-of-magnitude improvement in accuracy over vanilla physics-informed neural networks and standard neural networks, while reducing computational cost by up to 95.7 % and 92.1 %, respectively. It successfully captures the sequential patterns of key flow features such as pressure and velocity distributions under unseen conditions. Thus, the findings confirm that the Meta-PINNs framework offers a notable improvement in convergence and generalization over existing machine learning approaches, providing a promising pathway toward smart simulations of complex turbomachinery flows.

We identify a fundamentally new class of resonances in light scattering from a pair of point-like electric dipoles. These resonances arise from multiple scattering response and correspond to poles of the two-particle Green function. The realization of exact resonances requires violation of the optical theorem, which holds in equilibrium systems but can be violated under nonequilibrium conditions, without violating causality. As a concrete example, we show that a pumped two-level atom can realize the required polarizability and access the exact resonance regime. Our results for one electric and one magnetic dipole show how resonances can amplify a weak magnetic response of a single dipole to the incident field. In equilibrium systems, only approximate resonances with finite amplification are possible. Using the Drude model for metallic nanoparticles, we show that while equilibrium resonances enhance the scattering, they never exceed the optimal single-dipole response.

Spectral control of closely spaced excitonic transitions is central to valleytronic photonics, nanoscale light sources, and wavelength-encoded sensing. In monolayer molybdenum disulfide (MoS2), the A and B excitons are separated by only tens of meV, making selective excitonic emission control both fundamentally important and technologically challenging. Here, we numerically investigate plasmon-enhanced excitonic emission from monolayer MoS2 coupled to vertically oriented hollow gold nanocylindrical cavities through a dielectric spacer. Finite-difference time-domain simulations combined with a photoluminescence-rate framework enable separate evaluation of excitation enhancement, radiative decay modification, nonradiative quenching, and excitonic charge generation. By tuning the cavity aspect ratio, the localized surface plasmon resonance is selectively aligned with either the A- or B-exciton transition, while the spacer thickness and refractive index regulate near-field coupling and the local density of optical states. Under optimized conditions, the excitation rate is enhanced by up to 4.34-fold and the radiative decay rate by more than 40-fold, yielding photoluminescence enhancements of 143.85 and 87.27 for the A and B excitons, respectively. The cavity also redistributes the relative excitonic peak intensities, producing exciton-selective peak ratios up to 2.4 times higher than those of bare MoS2. These results establish hollow plasmonic nanocavities as geometry-tunable platforms for exciton-selective emission and charge-generation control in atomically thin semiconductors.

The chiral plasma instability (CPI) has been invoked as a possible mechanism for generating primordial magnetic fields in the universe and ultrastrong fields in neutron stars. We investigate chiral dynamos where the chirality imbalance is pumped by a source on a timescale $t_0$ and show that the CPI rate $\gamma$ is limited to $\gamma_0/(1+{\cal Q}^2)$, where ${\cal Q}= (\gamma_0 t_0)^{1/3}$ and $\gamma_0$ corresponds to models with instantaneously created chirality imbalance $(t_0=0)$. We then find that chiral flipping with rate $\Gamma_{\mathrm f}$ hinders the chiral dynamo if $\Gamma_{\mathrm f} >\gamma_0/(1+{\cal Q}^2)$ and completely suppresses it if $\Gamma_{\mathrm f} >\gamma_0/(1+{\cal Q}^{3/2})$. Realistic $t_0$ typically give ${\cal Q}\gg 1$, which makes the dynamo greatly vulnerable to suppression by chiral flipping. The suppression is strong in protoneutron stars and may be (barely) avoided near the electroweak transition in the early universe.

Machine learning (ML) can represent processes unresolved in coarse-resolution Earth system models (ESMs) by learning from high-resolution climate data. Such ML parameterization approaches have been primarily tested in idealized setups where they have focused on deep convection. It remains largely unexplored whether these approaches could be used in a more targeted fashion to learn vertical fluxes resulting from midlatitude mesoscale processes, such as slantwise convection and frontal dynamics in extratropical cyclones, which are not well represented in ESMs. To address this, we employ a variable-resolution CESM2 simulation with a refined area over the North Atlantic (14-km grid refinement) that resolves such midlatitude mesoscale processes. We train an artificial neural network to predict vertical profiles of mesoscale moisture, heat, and momentum fluxes from the perspective of a coarse-resolution (111-km grid) model. Our results show that a large number of features are required to achieve reasonable model performance when data come from the midlatitudes of real-geography atmospheric simulations, especially when coarse-grained vertical velocities, which we show are not representative of vertical velocities in a coarse-resolution model, are excluded as inputs. Feature importance analysis reveals the importance of vertically non-local information in temperature, moisture, and the meridional wind. We suggest that these non-local relationships capture the influence of cold air outbreaks and fronts on mesoscale fluxes. Our results demonstrate the importance of vertically non-local processes, clarify the regime-dependent predictability of mesoscale fluxes, and identify variables most informative for their parameterization, providing guidance for improving ESMs with ML and advancing our understanding of multi-scale interactions in the midlatitudes.

We report the first realization of a fractional topological phase in a fully unitary, noninteracting discrete-time quantum walk implemented on finite cyclic graphs. Using a single-coin split-step cyclic quantum walk (SCSS-CQW), we uncover topological phenomena that are inaccessible within conventional cyclic quantum-walk dynamics. The protocol enables controlled engineering of quasienergy spectra, flat bands, and topological phase transitions through the step-dependency parameter and coin-rotation angle. We show that cyclic graphs with even and odd numbers of sites exhibit qualitatively different band structures, while rotational flat bands arise exclusively in $4n$-site cycles; a general analytic condition for their emergence is derived. The SCSS-CQW produces fractional winding numbers $\pm \frac{1}{2}$ (Zak phases $\pm \frac{\pi}{2}$), in sharp contrast with the integer invariants in standard cyclic quantum walks. These fractional invariants lead to an unconventional bulk-boundary correspondence and support protected {zero energy} edge states beyond the usual integer topological classification. In the step-dependent protocol, transitions between distinct fractional winding sectors generate robust edge modes pinned at zero quasienergy. Numerical simulations show that these states remain stable in the presence of both dynamic and static coin disorder as well as phase-preserving perturbations, while survival-probability analysis demonstrates their long-time persistence. Requiring only a constant number of detectors independent of the evolution time and fewer operators, the proposed scheme offers a minimal-resource and experimentally accessible platform for realizing fractional topology, flat bands, and protected zero energy edge states in small-scale synthetic quantum systems.

A reduced mathematical model for the flow in an open cavity is presented. The reduction is based on the center manifold theory applied to a perturbation of the original system which allows for a codimension two bifurcation point. The model exhibits many of the key characteristics observed in the flow dynamics including unstable quasi-periodic edge states as well as switching of limit cycles with parameter variations. An explanation for the exchange of stabilities of the limit-cycles is presented based on the cross-coupling terms of the two amplitude equations.

The NUCLEUS experiment aims to detect coherent elastic neutrino-nucleus scattering of reactor antineutrinos using low-threshold, gram-scale cryogenic calorimeters. Similar to other low-threshold experiments, NUCLEUS observes a sharp rise in the event rate below a few hundred eV, referred to as the low energy excess (LEE), whose origin remains yet unidentified. Building on results from the NUCLEUS testing and commissioning at the Technical University of Munich and from previous characterization campaigns, we present a comprehensive study of the background rate measured with a sapphire detector equipped with two transition-edge sensors under various experimental conditions. We find no evidence for a dependence of the LEE rate on the particle background level, whereas the results indicate that slower cooling-down procedures lead to lower initial LEE rates. The behavior of the LEE rate during the same cooldown is comparable across the measurements and is best described by a power law with a common exponent across datasets of $(-0.59 \pm 0.06)$, when time is expressed from the moment the detector reaches the 4 K temperature. These findings provide valuable guidance for future LEE mitigation strategies in the NUCLEUS experiment.

Chaos theory is a branch of classical physics, founded in the 1960s-70s, that studies systems whose solutions are sensitively dependent on their initial conditions. For many, it is surprising that chaos theory arrived so late. However, through the work of Henri Poincaré, we know that much of the math of chaos was understood by some 70 years prior. Furthermore, through the writings of Poincaré's colleagues – Jacques Hadamard and Pierre Duhem – we also see a detailed understanding of the chaos found in his work. They also have explicit reasons of why the math of chaos was to be ignored. It was a strict form of empiricism – positivism – causing them to label chaos as “useless” and “meaningless” mathematics because it was thought to be ungrounded in experience. In this paper, I describe how the empiricist tenets of positivism exiled chaos from physics following Poincaré.

Realistic modeling of stellar spectra requires accurate radiative opacity coefficients. Owing to the fragmentary nature of existing data from rigorous quantum-mechanical calculations, photoionization coefficients based on the rigid-wavefunction approximation remain the only practical option for studies of magnetic white dwarfs. Although variants of this approach have been widely used in spectral analyses for decades, a complete and explicit treatment of degeneracy-level breaking has not previously been presented. In this work, we provide a comprehensive description of this procedure, including explicit expressions for the photoionization probability of individual bound-free transitions as functions of magnetic field strength and radiation polarization. We also evaluate the occupation numbers of bound states in a magnetized gas under ionization equilibrium, enabling the calculation of absolute photoionization opacities. Because high-lying atomic states are strongly perturbed by the magnetic field and ultimately dissolved, substantial modifications of the monochromatic absorption are found even for fields below 10 MG–a regime where fully rigorous quantum calculations are numerically demanding and have not yet been applied. Over a wide range of magnetic field strengths, pronounced dichroic features appear in the hydrogen continuum absorption.

This reply is also a friendly introduction to the impossibility of emergence of preferred structures from the Hamiltonian $\mathsf{H}$ and the unit vector $|\psi\rangle$ only. The obstructions to emergence are illustrated on the concrete construction of a tensor product structure (TPS) from Soulas et al., 2025 (arXiv:2512.07468v2). Soulas et al. offer their TPS as a counterexample to the proof from Stoica, 2022a (arXiv:2102.08620) that structures constructed only from $\mathsf{H}$ and $|\psi\rangle$ either contradict physical observations or can't describe them unambiguously. Soulas et al.'s construction of a unique TPS can't be both invariant and compatible with physical observations, so it can't be a counterexample. Its incompatibility becomes visible by examining how the relation between $|\psi(t)\rangle$ and the TPS, encoding the entanglement, changes in time. Therefore their TPS doesn't refute, but confirms (Stoica, 2022a). Besides this, since Soulas et al.'s method to construct preferred structures consists of choosing their invariants, by the same logic one could claim as well that the masses of elementary particles emerge uniquely just by fixing their values by hand. Soulas et al.'s construction is concrete and can illustrate the major obstructions for emergent structures, confirming them despite doing the best possible to avoid them. This makes it an excellent pedagogical tool to illustrate the trilemma, but also the relational and structural aspects of quantum theory and its symmetries.

Zonal jets (ZJ) are prominent coherent structures that spontaneously emerge from the background turbulent state in both stellar and planetary atmospheres. Although formation and maintenance of coherent jets from small scale hydrodynamic turbulence is well-documented, the mechanism underlying this phenomenon remains controversial. The dynamics of the Earth's polar jet and that of the quasi-biennial oscillation of the equatorial stratosphere have been analytically explained using the Statistical State Dynamics (SSD) framework applied to mid-latitude beta-plane and stratified turbulence of the equatorial equatorial,respectively (Farrell & Ioannou 2003). Extension of SSD to the shallow water equations of the equatorial beta-plane provided a corresponding theory for the dynamics of Jovian jets (Farrell & Ioannou 2009). However, the influence of Lorentz forces in the dynamics of a substantial subset of coherent structures observed in both planetary and stellar turbulence motivates the further extension of SSD analysis of coherent structure formation to magnetohydrodynamics (MHD) turbulence. In this work, we apply the SSD framework to shallow water MHD turbulence to study coherent structure dynamics in which both Reynolds and Maxwell stresses are involved. Perturbative and nonlinear equilibria SSD solutions reveal formation and statistical equilibration of zonal jet-toroidal field structure (ZJTFS) with both fixed point and time-dependent oscillation behavior with implications for understanding coherent structure formation in MHD turbulence including steady jets such as the solar super-rotation and time-dependent phenomena such as the 22 year old solar cycle.

The three-dimensional quasi-geostrophic equation is considered over a cylindrical domain with a multiply connected horizontal cross-section. Homogeneous Neumann boundary conditions, tantamount to homogeneous density fields, are imposed on the top and bottom surfaces, while no-flux boundary conditions combined with constant circulations are imposed on the lateral boundary loops. The global existence and uniqueness of a generalized solution is proven, provided that the initial potential vorticity (PV) field is essentially bounded. If the initial PV field is differentiable, then the solution is shown to satisfy the system in the classical sense.

The stability of two bubbles rising initially in-line through a viscous liquid is revisited using a global linear stability analysis formulated within an Arbitrary Lagrangian-Eulerian framework, complemented by fully resolved Embedded Boundary Method simulations. Whereas previous studies attributed the promoted in-line stability of oblate bubbles to a deformation-enhanced wake entrainment, the present analysis demonstrates that the dominant stabilizing mechanism arises instead from an inclination-induced rotational feedback generated as the trailing bubble experiences the asymmetric shear of the leading bubble's wake. This inclination-shear coupling, rather than deformation itself, governs the recovery of stability with increasing aspect ratio. Furthermore, the results reveal that the unstable drafting-kissing-tumbling mode originates from short-range, two-way coupling between the bubbles, whereas the asymmetric side-escape mode corresponds to a long-range, one-way interaction dominated by the trailing bubble response. In addition, a previously unreported oscillatory global mode emerges from the unsteady recirculation linking the two bubbles, acting as a hydrodynamic spring whose effective stiffness and damping govern the oscillation frequency and growth rate. Together, these findings identify inclination-induced lift as the primary mechanism controlling the stability of rising bubble pairs and provide a unified framework for interpreting their stationary and oscillatory transitions across a broad range of inertial and deformable regimes.

Granger causality (GC), a popular statistical method for the inference of directional influences between time series measured from a complex network, is sensitive to high-order (non-pairwise) interactions which fundamentally shape the collective network dynamics. This work introduces Partial Decomposition of Granger Causality (PDGC), a tool eliciting redundant and synergistic causal interactions in the pattern of information flow between the subsystems of physiological networks. The tool exploits the framework of partial information decomposition to dissect the multivariate GC from a set of driver random processes to a target process into unique effects carried exclusively by each driver, redundant effects carried identically by more drivers, and synergistic effects carried jointly by some drivers but not by any of them individually. Computation is based on multivariate state-space models expanded in the frequency domain to assess PDGC both in specific bands of physiological interest and in the time domain after whole-band integration. The validation on benchmark simulations demonstrates that the measures of unique, redundant, and synergistic GC reflect the underlying causal mechanisms and are computationally reliable. The application to arterial pressure, respiration, cerebral blood velocity and heart period variability reveals striking differences in the response to postural stress of patients prone to neurally-mediated syncope compared to healthy controls. The extraction of high-order causality patterns from the spectral GC favors dissecting the mechanisms of causal influence underlying multivariate interactions among oscillatory processes in many data-driven applications of network science.

Based on Dou Huashu's energy gradient theory, this paper focuses on the weak singularity of the incompressible Navier-Stokes (NS) equations in steady, fully developed flows. When the gradient of total mechanical energy is perpendicular to the streamline (i.e., $ u_j \frac{\partial E}{\partial x_j} = 0 $), substituting this critical condition into the NS equations with no-slip boundary conditions leads to the viscous term $ \nu \to 0 $. To rigorously analyze the regularity of the solution, Sobolev space $ H_0^1(\Omega) $ is introduced for energy estimation. The results show that the velocity field loses $ H^1 $-regularity, and the NS equations degenerate into Euler equations, which admit discontinuous weak solutions. Thus, the position where the mechanical energy gradient is perpendicular to the streamline becomes a weak singularity of the NS equations.

Understanding the nuances of nonlinear pulse propagation in optical fibers has led to several impactful applications across domains like optical communications, sensing and biophotonics. A key aspect in this regard is the use of appropriate optimization strategies for attaining requisite performance parameters. In this paper, we present the Taguchi method as a viable tool for optimizing nonlinear pulse propagation in optical fibers. We show that its use of the orthogonal arrays leads to rapid convergences to the desired pulse parameters, with even faster convergences obtained by favouring exploitation over exploration. We demonstrate the application of the method using two well-known problems from the field - the guiding center soliton, and soliton order conservation in dispersion decreasing fibers - which serve to underscore its salient features and also its potential for solution discovery across nonlinear pulse propagation problems.

Most spherical viruses exhibit icosahedral symmetry, yet the growth of viral shells remains poorly understood due to the short lifetimes and broad size distribution of assembly intermediates. Classical nucleation theory has been widely applied to describe this process, but it treats the boundary of a growing shell as rigid and structureless. Here, we extend classical nucleation theory by incorporating thermal fluctuations of the capsid rim using both discrete and continuum descriptions. Allowing the rim of a partially formed capsid to undergo small geometric undulations, we show that these fluctuations generate an entropic contribution that renormalizes the effective line tension. As a result, rim fluctuations can either promote or hinder capsid closure, depending on the subunit-subunit binding free energy, temperature, and fluctuation amplitude. We find that fluctuations generally lower the nucleation barrier when the binding free energy is below a threshold value, while for sufficiently strong binding, they can instead raise the barrier by stabilizing incomplete capsids through a finite-size entropy penalty associated with rim closure. By moving beyond the idealized capillarity approximation, our results provide a controlled extension of classical nucleation theory that clarifies how boundary fluctuations influence capsid nucleation and growth.

Local material inhomogeneities can strongly influence magnetization dynamics and macroscopic magnetic properties, yet detecting such defects from magnetic imaging data remains challenging when thermal fluctuations and experimental noise obscure static contrast. Here, we investigate defect detection in strongly fluctuating magnetization regimes where signatures of inhomogeneities largely average out in time-resolved measurements. Using finite-temperature micromagnetic simulations with randomly distributed defects and material parameters representative of \ce{Ni80Fe20}, we compute per-pixel temporal mean, temporal standard deviation, and latent entropy and use them as inputs for U-Net-based semantic segmentation models. We find that the most effective descriptor depends on the noise level and, importantly, that robust detection requires training data that reflect the expected noise statistics. These results provide practical guidance for designing noise-robust defect-detection workflows in magnetic imaging.