In this note we consider a two-dimensional semi-discrete dislocation energy and propose a simple and physically motivated construction for the grain boundary between two crystal grains with a small orientation difference. In the case of a general Bravais lattice, the energy of this construction matches the logarithmic scaling predicted by Read and Shockley.

Football fans frequently exhibit pronounced emotional and physiological reactions during high-stakes matches. However, the temporal dynamics of this football fever are rarely modeled as a latent process. Using intensive longitudinal data from Arminia Bielefeld supporters who wore smartwatches during the 2025 German Football Association (DFB) Cup final, we investigate how football fever unfolds. The devices recorded heart rate, stress level, and related indicators in short intervals, allowing us to construct a latent variable for football fever and model its dynamics. We specify a time-dependent structural equation model with latent growth components and autoregressive effects to capture both overall trends and short-term carry-over effects in fans' physiological responses. Results are aggregated across multiple imputations of missing measurements. Model fit is evaluated using adjustments for the high data dimensionality. The results show that football fever follows a V-shaped trajectory: high at kick-off, followed by a steady decline until the renewed arousal in the second half, with substantial between-fan heterogeneity in both baseline level and temporal dynamics. Our findings demonstrate that football fever can be adequately represented as a latent variable using structural equation modeling and reflected by wearable technology data. This highlights the importance of accounting for temporal dependence when studying dynamic emotional phenomena, e. g., in sports spectatorship.

We present an explicit quantum circuit construction for Hamiltonian simulation of a first-order velocity--stress formulation of the three-dimensional elastic wave equation in homogeneous isotropic media. Previous studies have shown how elastic wave equations can be cast into forms amenable to Hamiltonian simulation, but they typically rely on black box Hamiltonian access assumptions, making gate complexity estimation difficult. Starting from the first-order velocity--stress formulation, we discretize the system by finite differences, transform it into Schrödinger form, and exploit the separation between the component register and the spatial register to decompose the Hamiltonian into structured tensor product terms. This yields explicit implementations of first-order and second-order Trotter formulas for the resulting time evolution operator. We derive corresponding error bounds and constant sensitive qubit and CNOT complexity estimates in terms of the discretization parameter, simulation time, target accuracy, and material parameters. Numerical experiments validate the proposed framework through comparisons with the exact time evolution and reconstructed physical fields.

We develop an operator-theoretic framework for the Convergent Born Series (CBS) method applied to the Lippmann--Schwinger equation for high-frequency Helmholtz problems. In contrast to the Fourier-based analysis of Osnabrugge et al., our approach expresses the preconditioned Lippmann--Schwinger iteration entirely in terms of the resolvent of a self-adjoint background operator. This leads to a unitary Cayley-transform representation of the CBS iteration operator, from which we derive basis-independent bounds on its numerical range and a general convergence criterion valid on arbitrary bounded domains and for complex-valued wave numbers. Because the analysis does not rely on an explicit Green's function in the Fourier domain, the Cayley-transform framework extends naturally to a broader class of frequency-domain wave and diffusion equations whose fundamental solutions are not available in closed form. We further incorporate smoothly tapered complex-wavenumber absorbing layers that preserve the self-adjoint structure of the reference operator and enhance the contractivity of the iteration without modifying the differential operator. In addition to this theoretical generalization, we present a detailed numerical validation in which CBS solutions are benchmarked against PML-based finite-difference wavefield simulations. These experiments demonstrate that the operator-theoretic CBS formulation delivers accurate and stable results across a broad range of contrasts and frequencies, thereby significantly extending the applicability and theoretical foundation of the CBS method beyond previously analyzed settings.

Image transmission for vehicle-to-vehicle collaborative perception in autonomous driving faces challenges including limited on-board terminal resources, time-varying wireless channel fading, and poor robustness under low signal-to-noise (SNR) ratio. Traditional separate source-channel coding schemes suffer from the cliff effect, while existing semantic communication models are limited by large parameter sizes and weak digital compatibility. This paper proposes a lightweight, low-SNR-robust deep joint source-channel coding (JSCC) semantic communication system. First, structured pruning is implemented based on batch normalization layer scaling factors and L1 regularization, which significantly reduces model complexity while ensuring image reconstruction quality. Second, a uniform quantization and M-QAM modulation scheme adapted to JSCC features is designed, and a training-deployment separation strategy is adopted to address the non-differentiable quantization problem, enabling compatibility with existing digital communication systems. Simulation results on the Cityscapes dataset show that the pruned model maintains comparable performance and robustness to the original one, even with over half of its parameters removed. Notably, the proposed scheme exhibits significant advantages over conventional communication methods under low SNR conditions.

Sliding ferroelectrics built from stacked nonpolar monolayers enable out-of-plane polarization and unconventional switching via interlayer sliding, yet the microscopic sliding dynamics remain unclear. Using machine-learning molecular dynamics, we reveal spontaneous thermally driven interlayer sliding in ferroelectric MoS2 moiré superlattices, with relative velocities on the order of 1 m/s at 300 K. Instead of rigid translation of the entire bilayer, the motion appears as a global drift of the moiré pattern. Such thermally driven sliding is inconsistent with the meV/atom-scale rigid-sliding barrier. In contrast, when constrained relaxation is allowed, the sliding proceeds along an almost barrierless pathway that directly reproduces the global drift of the moiré pattern. Furthermore, sulfur vacancies trigger a sliding-to-pinning transition, with about 0.1% S vacancies already sufficient to convert the long-range sliding into localized oscillations. Notably, these phenomena are not restricted to small twist angles, but arise generically in twisting-induced multidomain structures. These results reveal that the sliding process is governed by a domain-wall-mediated collective reconstruction pathway with an ultralow barrier, rather than rigid layer translation, deepening the understanding of microscopic dynamics in moiré superlattices and sliding ferroelectrics.

Many real-world graphs have degree distributions that are well approximated by a power-law, and the corresponding scaling parameter $α$ provides a compact summary of that structure which is useful for graph analysis and system optimization. When graphs contain sensitive relationship data, $α$ must be estimated without revealing information about individual edges. This paper studies power-law exponent estimation under edge differential privacy. Instead of first releasing a noisy degree distribution and then fitting a power-law model, we propose privatizing only the low-dimensional sufficient statistics needed to estimate $α$, thereby avoiding the high distortion introduced by traditional approaches. Using these released statistics, we support both discrete approximation and likelihood-based numerical optimization for efficient parameter estimation. We develop edge-DP algorithms for both centralized and local DP models, compare degree release and log-statistic release in the local setting, and evaluate the resulting methods on various graph datasets across multiple privacy budgets and tail-cutoff settings.

Disorder in moire superlattices simultaneously degrades flat-band localization and induces Anderson localization, yet how these two regimes interact has remained unclear. Here, we introduce a combined framework linking localization-length scaling with differential probability density analysis to map localization transitions in partially disordered one-dimensional silicon moire lattices. It is found that flat bands confined within the interband gap keep their strong localization even as disorder grows. In contrast, flat bands intersecting dispersive bands exhibit rich behaviors: the low-frequency branch undergoes an inverse Anderson transition, while the high-frequency branch supports coexisting flat-band and Anderson localization at strong disorder. Our results deliver the direct evidence of competing localization mechanisms in disordered moire systems and offer guiding principles for engineering robust, nonideal moire photonic devices.

Skyrmions are particle-like topological textures that hold great promise for low-power electronics and wave-based functionalities. Yet their utility is hindered by the lack of robust and controllable transport. Here, we show that band topology can be harnessed to overcome this limitation. We experimentally realize an acoustic quantum skyrmion--valley Hall effect in a surface phononic crystal via engineered spin--orbit--momentum interaction. Skyrmions emerge as valley-locked topological edge states, robustly propagating along designed domain walls. Crucially, the skyrmion transport exhibits concurrent orbital angular momentum (OAM)--valley locking and spin--texture locking, enabling controllable propagation through selective excitation. Our results establish a direct correspondence between real-space and momentum-space topology, providing a general strategy for robust, controllable skyrmion transport.

In this paper, we first derive the compressible Navier-Stokes/Landau-Lifshitz-Gilbert (NS-LLG) model for magnetoelastic materials via the energetic variational approach (EnVarA). It is important to emphasize that the manner in which the evolution of magnetoelastic materials is influenced by the fluid motion--specifically through the deformation gradient--determines the kinematics of the magnetization and consequently leads to distinct governing equations. Subsequently, we establish the local-in-time existence of solutions to the compressible NS-LLG system under finite initial energy. Finally, near the constant equilibrium for magnetoelasticity in the absence of an external magnetic field, we reformulate the evolutionary model, which allows an additional dissipative term to be identified from the elastic stress. Based on this reformulation, we justify the global well-posedness of the evolutionary magnetoelasticity system with zero external magnetic field, provided the initial data are sufficiently small. In particular, when the magnetic field $M$ vanishes, this model reduces to the viscoelastic model. Our results significantly relax the previous initial data requirements, only assume the most basic structural condition $ρ_{0} \operatorname{det} F_{0} = 1$.

We study the existence of asymptotically $Z$-stable (a.Z stable) bundles over polycyclic surfaces. Our choice of polynomial central charge is related to the existence of solutions of the deformed Hermitian--Yang--Mills equations, with vanishing $B$-field, in the large-volume limit. The main result is a technique to construct rank $3$, strictly a.Z-stable bundles as extensions of a line bundle by a $μ$-stable bundle of rank $2$. In particular, this leads to new examples of strictly a.Z-stable bundles over $\mathbb{P}^2$, the product $\mathbb{P}^1\times \mathbb{P}^1$, and the blow-up $\mathrm{Bl}_q\mathbb{P}^2$. We also present an analogue of the Hoppe criterion for the a.Z-stability of vector bundles of rank $2$, which may be of independent interest.

We present the beam pattern measurement of the Tianlai Cylinder Pathfinder Array. As it is a pure drift-scan instrument, we exploit the North-South motion of the Sun to demonstrate that the primary beam is factorizable. Leveraging this property, we decompose the primary beam into independent East-West (E-W) and North-South (N-S) components. Using the Sun as a calibration source, we obtain the E-W beam profiles at various elevations, applying normalization to eliminate the effects of solar activity. Subsequently, we simulate the observed signals using a sky map model to derive the best-fit N-S beam. The results of this work are consistent with previous expectations.

Modern ransomware exhibits polymorphic and evasive behaviors by frequently modifying execution patterns to evade detection. This dynamic nature disrupts feature spaces and limits the effectiveness of static or predefined models. To address this challenge, we propose TL-RL-FusionNet, a reinforcement learning (RL)-guided hybrid framework that integrates frozen dual transfer learning (TL) backbones as feature extractors with a lightweight residual multilayer perceptron (MLP) classifier. The RL agent supervises training by adaptively reweighting samples in response to variations in observable ransomware behavior. Through reward and penalty signals, the agent prioritizes complex cases such as stealthy or polymorphic ransomware employing obfuscation, while down-weighting trivial samples including benign applications with simple file I/O operations or easily classified ransomware. This adaptive mechanism enables the model to dynamically refine its strategy, improving resilience against evolving threats while maintaining strong classification performance. The framework utilizes dynamic behavioral features such as file system activity, registry changes, network traffic, API calls, and anti-analysis checks, extracted from sandbox-generated JSON reports. These features are transformed into RGB images and processed using frozen EfficientNetB0 and InceptionV3 models to capture rich feature representations efficiently. Final classification is performed by a lightweight residual MLP guided by an RL (Q-learning) agent. Experiments on a balanced dataset of 1,000 samples (500 ransomware, 500 benign) show that TL-RL-FusionNet achieves 99.1% accuracy, 98.6% precision, 99.6% recall, and 99.74% AUC, outperforming non-RL baselines by up to 2.5% in accuracy and 3.1% in recall. Efficiency analysis shows 55% lower training time and 59% reduced RAM usage, demonstrating suitability for real-world deployment.

The identity map of an Einstein manifold is a critical point of both the classical energy functional and the conformal-bienergy functional. In this paper, we investigate the conformal-biharmonic stability of the identity map of compact Einstein manifolds of dimension at least four and with nonnegative scalar curvature, and we compare it with the harmonic stability, when the identity map is considered as a harmonic map. Somewhat surprisingly, we show that the conformal-biharmonic index coincides with the harmonic index, with a single notable exception: the four-dimensional Euclidean sphere. In this case, the identity map is unstable with respect to the energy functional, as shown independently by Mazet and Smith, whereas it is stable with respect to the conformal-bienergy functional.

One of the advantages of LTL over CTL is that the notion of a counterexample is easy to grasp, visualise and process: it is a trace that violates the property at hand. In this paper we propose a notion of evidence for CTL properties on explicit-state models -- which equally serves as witness for satisfied properties and counterexample for violated ones -- and how to visualise it, with the main aim of (human) comprehension. The main contribution consists of a formal model of evidence, a characterisation of minimal evidence per temporal operator, and a concrete, implemented proposal for its visualisation. This is the extended version of a paper published in SPIN 2026, containing the proofs of all results.

Heffter arrays are combinatorial structures used to construct orthogonal cyclic cycle decompositions and biembeddings of complete graphs onto surfaces. A Heffter array $H(m,n;h,k)$ is an $m \times n$ partially filled array with distinct nonzero entries from $\mathbb{Z}_{2nk+1}$ such that each row contains $h$ filled cells, each column contains $k$ filled cells, the elements in the filled cells form a half-set of $\mathbb{Z}_{2nk+1}$, and every row and column sums to zero modulo $2nk+1$. If these row and column sums equal zero over the integers, the structure is called an integer Heffter array. Furthermore, such an array is called globally simple if the partial sums of the entries in each row and column, evaluated in their natural order, are distinct modulo $2nk+1$. When $m=n$ and $h=k$, the array is square and denoted by $H(n;k)$. While the existence of globally simple square Heffter arrays has been established for several congruence classes, the cases where $k \equiv 1,2 \pmod{4}$ for $k > 10$ have remained an open problem [1]. In this work, we address this gap in the literature by explicitly constructing globally simple integer Heffter arrays $H(n;k)$ for the previously open cases where $k \equiv 1 \pmod{4}$ and $n \equiv 0,3 \pmod{4}$. Consequently, these constructions guarantee the existence of orthogonal cyclic $k$-cycle decompositions of the complete graph $K_{2nk+1}$ for these parameters. [1] J.H. Dinitz and A. Pasotti. A survey of Heffter arrays. In C.J. Colbourn, editor, New Advances in Designs, Codes and Cryptography, volume 86, pages 353-392. Springer Nature Switzerland, 2024.

We study a stochastic model of collective motion in which individuals update their orientation through pairwise aligning or anti-aligning copying interactions. We analyze both annealed dynamics, where interaction types are chosen probabilistically at each update, and quenched dynamics, where individuals are permanently assigned to aligning or anti-aligning subpopulations. Starting from the microscopic master equation on the circle, we derive an exact mesoscopic description via a Fourier-mode expansion and a systematic large $N$ expansion, obtaining closed Fokker-Planck equations and effective stochastic differential equations for the polarization. We show that competing alignment and anti-alignment suppress long-range polar order in the thermodynamic limit in both cases, while finite systems display nontrivial fluctuation-induced structure controlled by the interaction composition. Our results, validated by Gillespie simulations, establish an analytically tractable framework for collective dynamics characterized by competing copying rules and intrinsic noise.

We define and study the higher rank GKZ-fans of point configurations, where the rank one cases coincide with the usual GKZ-fans. A point in a higher rank GKZ-fan is then used to construct higher rank quasi-valuations to degenerate the toric variety associated to the point configuration flatly to a reduced union of toric varieties. Such a union encodes the polytopal subdivision arising from the point in the higher rank GKZ-fan.

Intrinsic Hall effects, such as the anomalous Hall effect, originate from the orbital quantum geometry of Bloch states. However, in layered materials, the combined action of out-of-plane electric and magnetic fields couples to layer polarization and orbital moment, generating a mixed layer-orbital quantum geometry in field-dressed Bloch states. We show that this geometry produces an intrinsic magnetoelectric Hall effect that is bilinear in the electric and magnetic fields. The response is scattering-time independent and can arise in nonmagnetic systems without spin-orbit coupling. Its origin lies in interband coherence involving layer polarization and orbital moment, leading to a finite, non-quantized Hall response that persists in the band gap. The Hall coefficient is odd under gate reversal and tracks layer polarization. A symmetry analysis identifies the classes of layered materials that host this effect. As a representative realization, we demonstrate the effect in rhombohedral pentalayer graphene, where the conductivity reaches values of order $0.05\,e^2/h$. These results establish mixed layer-orbital quantum geometry as a mechanism for intrinsic magnetoelectric Hall transport and a direct probe of layer-resolved quantum geometry in Bloch bands.

Existing super-resolution microscopy is often constrained by inherent trade-offs between resolution, acquisition speed, phototoxicity, and hardware complexity. Computational post-processing approaches offer a promising alternative, but they typically suffer from linearity distortion, high computational cost, reliance on pre-training data, or reconstruction artifacts. Here, we present Source Localization (SoLo), a novel single-frame super-resolution algorithm for fluorescence imaging without these limitations. Built on the principle of inferring fluorescent source positions via sampling-detection strategy, SoLo achieves non-iterative, parallelizable computation, enabling real-time live-cell imaging with high spatiotemporal resolution. The intensity linearity preservation of SoLo makes it compatible with quantitative analysis such as calcium imaging and fluorescence resonance energy transfer. We further extended this framework to 3D-SoLo for volumetric imaging and nonlinear SoLo (NL-SoLo) for high-density fluorescence fluctuation imaging. With its ease of parameter tuning and compatibility with existing imaging systems, SoLo offers an accessible solution for ordinary labs, enabling diverse biomedical imaging applications.

In this paper we design a switching control law for the Ćuk converter in the continuous conduction mode using piecewise linear Lyapunov functions. These Lyapunov functions can be constructed using different number of state variables affecting the system's performance. In the paper, some representative simulations covering construction of different piecewise Lyapunov functions, are provided.

Circuits' and in particular DC/DC converters' switching behavior is analyzed in this paper using the equivalent control modeling of the dynamic systems' sliding mode regime. As a representative example and also being one of the most complex circuits among DC/DC converters, the Ćuk converter is chosen. It is shown how the converter's behavior in the steady state regime can be studied and analyzed by the linear matrix inequalities based stability conditions for linear dynamic systems with nonlinear sector bounded perturbations. The maximization of the nonlinear sector bound provides a limit for applying the linear ripple approximation in the converter operation analysis. Furthermore, our approach is validated by providing simulation results for two different switching surfaces of practical interest.

We investigate the interplay between lepton flavor violation (LFV) and leptogenesis in the minimal scotogenic model, comparing high-scale hierarchical leptogenesis and low-scale resonant leptogenesis within a unified Casas--Ibarra framework. Since the same Yukawa couplings simultaneously govern radiative neutrino mass generation, charged LFV processes, and the CP asymmetry required for baryogenesis, strong phenomenological correlations arise. We show that high-scale leptogenesis remains naturally viable due to the effective decoupling between LFV and baryogenesis, while low-scale resonant leptogenesis is strongly constrained by the MEG bound on $μ\rightarrow eγ$. Nevertheless, we identify a narrow but nonvanishing resonant window where successful baryogenesis, controlled washout, and LFV safety coexist simultaneously. In particular, we obtain fully allowed benchmark points characterized by quasi-degenerate heavy fermions, resonantly enhanced CP asymmetry, and suppressed flavor violation through Casas--Ibarra phase alignment.

This invited paper proposes and discusses several Bayesian attempts at nonparametric and semiparametric density estimation. The main categories of these ideas are as follows: 1) Build a nonparametric prior around a given parametric model. We look at cases where the nonparametric part of the construction is a Dirichlet process or relatives thereof. (2) Express the density as an additive expansion of orthogonal basis functions, and place priors on the coefficients. Here attention is given to a certain robust Hermite expansion around the normal distribution. Multiplicative expansions are also considered. (3) Express the unknown density as locally being of a certain parametric form, then construct suitable local likelihood functions to express information content, and place local priors on the local parameters.

Large solar energetic particle (SEP) events are thought to originate from the shocks driven by fast coronal mass ejections (CMEs) and thus generally accompanied by type II radio bursts. However, a significant proportion of type II radio bursts is not accompanied by SEP events. To study the relationship between SEPs and type II radio bursts and the associated physical mechanisms, we statistically analyze 43 SEP halo-CMEs and 131 non-SEP halo-CMEs observed from 2010 to 2024, and check the related properties of type II radio bursts and solar source region. We find nearly all SEP events and approximately two-thirds of non-SEP events are accompanied by type II radio bursts. Type II radio bursts associated with SEP events usually have longer duration and lower ending frequencies. The starting frequency exhibits a clear source region dependence, being highest for ''single active region (AR)'', intermediate for ''multiple ARs'', and lowest for ''outside of ARs''. Furthermore, the spectra of both protons and electrons exhibit a similar softening trend in the three types of source regions. Joint analysis of spectra and type II radio bursts reveals that the proton spectra index has a good anti-correlation with the starting frequency of the type II radio bursts. Our statistical results have important implications for the mechanisms behind SEP acceleration

Based on a suitable basis system for the quark-gluon vertex' transverse tensor structures and on carefully chosen kinematical variables, the transverse part of the quark-gluon vertex in quenched QCD in the Landau gauge is obtained from a system of Dyson-Schwinger equations. We demonstrate by analysing this solution that the angular dependence of these transverse quark-gluon vertex form factors is seemingly weak. We nevertheless argue that this does not imply a planar degeneracy for this vertex because even this mild dependence cannot be neglected when aiming for reasonably precise results for derived quantities. Last but not least, for a self-consistently coupled systems of 3PI Dyson-Schwinger equations for the quark propagator and the quark-gluon vertex we confirm that the core ingredient to dynamical chiral symmetry breaking is the dynamically generated tensor coupling of glue to quarks which itself is only possible because of chiral symmetry breaking. Furthermore, we find (i) a relation in between the calculated chirality violating vertex form factors; (ii) that the quark propagator is identical within numerical errors when obtained either from a decoupling solution or the scaling solution for the Yang-Mills propagators and vertex functions; and (iii) that the resulting quark propagator is consistent with possessing poles only on the real time-like half-axis. Furthermore, we provide high-precision fits for the form factors based on sometimes astonishingly simple model functions.

This article proposes a Model Reference Adaptive Control (MRAC) strategy to achieve fixed-time convergence of parameter estimation and tracking errors for unknown linear time-invariant systems, without relying on the persistence of excitation condition. Instead, it employs a less restrictive initial/interval excitation condition on the regressor matrix, enhancing practicality and ease of implementation in real-world scenarios. Our primary contribution is a novel parameter update law within the indirect MRAC framework, ensuring that parameter estimates converge within a fixed time, once the initial/interval excitation condition is met. This approach simplifies the practical requirements for adaptive control while guaranteeing robust performance against parameter uncertainty and external disturbances. Simulation results provide a comparison with the current literature to validate the effectiveness of this approach.

The subject of our discussion is the theory of differential equations as set out in two classical Euler's textbooks "Institutiones Calculi Differentialis" and "Institutiones Calculi Integralis".

Accurate crystal structure prediction (CSP) requires accounting for finite-temperature and nuclear quantum effects, yet first-principles evaluation of the free energy surface (FES) remains prohibitive for high-throughput searches. We observe that the self-consistent harmonic approximation (SCHA) FES, as a function of nuclear centroid positions, shares the same mathematical structure as a potential-energy surface and can therefore be directly learned by a deep neural network potential. The resulting deep free energy (DF) model, constructed via a two-level concurrent-learning workflow, evaluates free energies, forces, and stresses in a single forward pass. Applied to the La-Sc-H system at 200 GPa and 300 K, DF-based CSP reproduces the stability of the experimentally observed LaH10 and LaSc2H24, and discovers an unreported thermodynamically stable clathrate hydride: P4/mmm LaScH8. Benchmarked on the LaH10 system, the DF model achieves a 1.72*10^6-fold cost reduction relative to DFT-level SSCHA. The DF framework provides a scalable route for incorporating finite-temperature and nuclear quantum effects into high-throughput crystal structure prediction.

We investigate the quantum properties of gravitational waves (GWs) generated by a classical energy-momentum tensor. Treating the GW field as a quantum field coupled to a classical source, we evaluate the expectation value of the GW operator. We demonstrate that this expectation value exactly reproduces the classical retarded solution. Furthermore, we show that the mean and variance of the number of emitted gravitons are equal. This suggests that the graviton emission is a Poisson process, as expected for a coherent state. We establish a quantitative criterion for the validity of the classical wave description. By applying this criterion, we find that the classical approximation is remarkably accurate for astrophysical sources, but laboratory-scale systems may reside in a regime where the discrete nature of graviton emission becomes significant.