Papers

Next-generation particle accelerators demand advanced beam-diagnostic capabilities to ensure high performance, operational reliability, and sustainable machine operation. Increasing beam intensities and stored energies make the precise characterization of transverse profiles, phase-space distributions, and halos often five orders of magnitude below the core but with significant environmental impact essential for loss mitigation and machine protection. Traditional analysis methods struggle with the heterogeneous, noisy, and non-Gaussian data produced under realistic operating conditions. This work presents a novel tool based on an unsupervised deep-convolutional neural-network framework that significantly enhances image denoising and restoration for emittance measurements. The method reconstructs beam-halo structures with unprecedented resolution, detecting signals at radii beyond seven standard deviations and particle densities below 10 -4 of the total beam intensity. Despite very low signal-to-noise ratios and small, non-annotated datasets, the approach preserves fine structures and reveals halo features previously unobserved at pilot installations. Built on a U-Net architecture with tailored early-stopping strategies and physics-informed metrics, the framework operates entirely on CPUs and requires minimal computational resources. The results demonstrate the potential of unsupervised deep learning as an enabling technology for high-dynamic-range beam diagnostics and motivate further development of systematic benchmarking and physics-informed learning strategies.

We consider the diffraction of time-harmonic plane waves by a periodic structure, governed by the Helmholtz equation. Bound states in the continuum (BICs) are quasi-periodic fields that remain $L^{2}$-bounded over one period and occur at frequencies embedded in the continuous spectrum. Perturbations that break a BIC can lead to ultra-strong resonances, enabling various applications in photonics. Employing the implicit function theorem, we demonstrate how a simple BIC continuously deforms into a propagating field as system parameters vary in a neighborhood, with the frequency adjusting accordingly. In this setting, the incident coefficients of the field persist as an eigenvector of the scattering matrix with a fixed eigenvalue. By introducing a mapping $\mathcal{P}$ from the parameters to these coefficients, the zeros of $\mathcal{P}$ correspond precisely to BICs. When such a zero is isolated and the dimensions of the domain and codomain coincide, the BIC can be related to the mapping degree of $\mathcal{P}$ in a small neighborhood. This perspective clarifies the phase singularity associated with BICs and provides a general topological interpretation of their local robustness with respect to the given parameters. Moreover, it yields a practical numerical criterion for detecting and verifying BICs via computation of the mapping degree of $\mathcal{P}$.

Soliton-similariton fiber lasers have demonstrated exceptional operational stability, maintaining continuous mode-locking for weeks despite large intracavity spectral and temporal breathing. We present the first stability study of this laser, rigorously establishing that the anomalous dispersion segment that supports the soliton is the cause of this robustness. Specifically, we perform linear stability analysis of the laser employing a Jacobian-based eigenvalue decomposition and show that the eigenvalues lie within the unit circle, leading to a positive stability margin, which is indicative of the robustness of the laser against small perturbations. Furthermore, the stability margin is observed to increase with the length of the anomalous fiber segment, clearly establishing its role in pulse stabilization. Critically, integrated pulse timing jitter and relative intensity noise as obtained from quantum noise-limited laser simulations are shown to be anti-correlated to the stability margin, further validating the results of the Jacobian analysis and establishing an unequivocal link between the reported noise performance of the soliton-similariton laser to the underlying pulse stabilization mechanism mediated by the anomalous segment. The direct link of the linear stability analysis to the underlying nonlinear physics of the laser, together with its significantly lower computational overhead, establishes it as a highly effective predictive framework for assessing laser noise performance, enabling novel approaches for designing quantum noise-limited ultrafast sources.

Single photon emitters (SPEs) are promising building blocks for practical devices in quantum technologies. Traditionally, these systems are excited using off-resonant visible light through their phonon transitions, yet this process remains poorly understood. Here, we explore the interaction of mid-infrared (MIR) excitation on the properties of SPEs in hexagonal boron nitride. Notably, we present a reversible, non-destructive method to enhance emission from blue SPEs using MIR co-excitation. By resonantly driving defect-localized in-plane infrared-active optical phonon modes near 7.3 um, the MIR field modulates carrier dynamics through a phonon-assisted recombination. This unique feature, not observed previously for defects in solids, is a promising reservoir in a growing toolkit to modulate quantum emitters at room temperature for their use in practical quantum technologies.

Robust single-vessel tracking from fixed coastal platforms is hindered by modality-specific degradations: cameras suffer from illumination and visual clutter, while LiDAR performance drops with range and intermittent returns. We present a particle-filter tracker that supports sequential measurement-level camera-LiDAR fusion and an information-gain (entropy-reduction) adaptive sensing policy that selects the most informative sensing modality at each fusion time bin. The approach is validated in a real maritime deployment at the Cyprus Marine and Maritime Institute Smart Marina Testbed (Ayia Napa Marina, Cyprus), using a shore-mounted 3D LiDAR and an elevated fixed camera to track a rigid inflatable boat with onboard GNSS ground truth. We compare LiDAR-only, camera-only, All sensors, and adaptive configurations. Results show LiDAR dominates near-field accuracy, the camera sustains longer-range coverage when LiDAR becomes unavailable, and the adaptive policy achieves a favorable accuracy-continuity trade-off by switching modalities based on information gain. The adaptive configuration therefore provides a practical sensor-selection baseline for resilient and resource-aware maritime surveillance.

Matter has two physical properties: Inertia and interaction. If we define the center of mass of an elementary particle in relation to its inertia, and a center of interaction in relation to its interactive properties, there are only two possibilities to describe this elementary particle: that both points are the same or that they are different. If they are the same, what we describe is the point particle model, while if we consider them to be different, what we obtain is the description of an elementary spinning particle. If the center of interaction or center of charge is moving at the speed of light, completely determines also the dynamics of the center of mass, and when quantizing this model satisfies Dirac's equation. We obtain the classical description of the spinning Dirac particle. The general analysis of the interaction Lagrangian, suggests a modification of the minimal coupling Lagrangian, for a possible classical description of the strong and weak interaction.

Efficient locomotion is important for the evolution of complex life, yet the physical principles selecting specific swimming strokes often remain entangled with biological constraints. In viscous fluids, the scallop theorem constrains the temporal organization of strokes, but no analogous principle is known for their spatial structure, leaving the prevalence of symmetric gaits across diverse organisms without a physical explanation. Here we show that spatial symmetry acts as an emergent organizing principle for efficiency in viscous fluids. By analysing deformable swimmers whose strokes are not constrained to any particular symmetry class, we identify a hydrodynamic duality: symmetric and anti-symmetric strokes are dynamically equivalent, yielding identical speeds and efficiencies, which we prove are optimal among all strokes. We validate this using numerical simulations of Stokes flow, demonstrating that these symmetry rules persist even in three-dimensional body plans. Our results suggest that the prevalence of symmetric and alternating gaits in nature reflects not merely a developmental constraint, but a physical optimality principle for locomotion in viscous environments, complementing developmental and neural constraints.

Excited atoms and molecules can utilize their excess energy to ionize a neighboring system by a process named interatomic and intermolecular Coulombic decay (ICD). ICD is ultrafast, in the femtosecond regime, and has many modes of appearance. Ample applications of ICD have been reported spanning a wide range of fields and it is expected to be ubiquitous in nature. Essentially all the investigations on ICD were for weakly bound systems, like clusters and fluids. We demonstrate that, unexpectedly, ICD can be efficiently active in atomic and molecular gases in spite of the very large distances between the units. We uncover the underlying mechanism, which differs from that prevailing in weakly bound systems. The dynamics of ICD in gases is analyzed. The results considerably broaden the impact of ICD and open the gateway to new kinds of applications.

Although commonly associated with limbless animals like snakes and fish, multi-legged organisms like centipedes also utilize undulatory locomotion. Whether these undulations are actively reinforced or resisted by the axial musculature remains an open question. We present a dynamical model of centipede locomotion that integrates leg-ground interactions, passive body mechanics, and active lateral musculature. By varying stepping rate, actuation, and body stiffness, we examine how locomotor strategies affect speed and an effective energetic efficiency. Coordination emerges only when body stiffness is tuned to stepping frequency: overly flexible bodies lose synchrony, while overly rigid ones move slowly and inefficiently. This leads to the prediction that centipedes utilize speed dependent active stiffness to maintain this coordination. Our results suggest that lateral muscles also have a speed dependent function, revealed by optimizing speed and an effective cost, that resists a phase lag between leg touchdowns and body curvature. Together, we find that centipedes actively modulate body mechanics to achieve rapid, efficient locomotion, highlighting how complex control can emerge from embodied physical properties rather than solely from neural computation.

A novel experimental platform is developed to investigate the dynamics of inertial particles (micro-droplets) in air turbulence. The goal is to observe particle collision and coalescence in turbulent flows, focusing on its impact on the radial distribution function (RDF) and relative velocity statistics. The main tool is a three-dimensional Lagrangian particle tracking (LPT) system, designed for high-resolution measurements at sub-Kolmogorov scales. The system uses LED illumination with high-speed spinning-disk atomizers, enabling tracking of particles of approximately 10~$\mu$m and larger under controlled turbulence. A minimum resolvable particle separation of $r/\eta \approx 0.1$ is achieved. A central contribution is the identification and mitigation of three dominant sources of spurious particles: FMIS, IIS, and TIF. An angle-based geometric filtering criterion strongly suppresses FMIS artifacts on RDF. These procedures establish a validated workflow for reliable small-scale statistics. Using this framework, RDF and a normalized pseudo-collision rate are measured at near-contact separations for particles with Stokes numbers $St \approx 0.2$–$1.0$. Sub-Kolmogorov clustering increases with Stokes number, and near-contact statistics are consistent through the filtering strategy. This study extends LPT limits and provides a reliable methodology for investigating inertial-particle dynamics at previously inaccessible spatial scales.

The finite square potential well is a staple problem in introductory quantum mechanics. There is an extensive literature on the determination of the allowed energies, which requires the solution of a transcendental equation by numerical, graphical or approximate analytic methods. Here we investigate the less explored problem of a particle in a semi-infinite potential well. The energy eigenvalues, which are also determined by a transcendental equation, are found by a standard graphical method, and a simple rule that yields the number of stationary states is provided. Next a simplification of the aforementioned transcendental equation is attempted. During the process pitfalls are encountered and a purportedly simpler graphical treatment of the problem given in the solutions manual to a fine textbook is shown to be flawed. A more careful analysis brings forth the correct simplification, which is shown to be particularly suitable for finding highly accurate approximations to the energy levels. Finally, a class of exact solutions is produced, the associated normalized eigenfunctions are constructed and the probability of finding the particle inside the well is computed.

The characteristics of the nocturnal drainage wind flowing from the tributary Isarco Valley into the Bolzano basin, in the Italian Alps, during wintertime are investigated. Analyses are performed by combining measurements from an intensive field campaign and the output of four high-resolution numerical simulations, run with the Weather Research and Forecasting (WRF) model using different planetary boundary-layer (PBL) schemes. Two episodes are identified, based on the vertical temperature stratification in the basin and the evolution of the drainage flow at the valley exit. Numerical results show that the drainage flow behaves as a valley-exit wind, whose main structure at the exit of the valley is well captured by the model independently of the PBL scheme. However, the model struggles to correctly reproduce the temperature stratification in the basin, with better results when a PBL scheme including, among others, a prognostic equation for the temperature variance and a counter-gradient term is used. This has an impact on the simulation of the onset and duration of the valley-exit wind, which are sensitive to the temperature contrasts between the valley and the basin. Overall, the model is able to reproduce the different behavior of the drainage wind at the exit of the valley in the two case studies. It is found that the presence of a cold air pool in the basin favors an upward trajectory of the flow at the exit of the valley, resulting in unperturbed calm wind conditions in the lower levels. On the other hand, with weak temperature stratification, the drainage flow closely follows the topography, resulting in strong winds also near the surface.

Numerical simulations were conducted to investigate the influence of inlet Reynolds number on the isothermal flow field in a lab-scale swirl combustor while keeping a fixed inlet swirl number of 0.67. The combustor geometry and baseline conditions were adopted from Taamallah et al. [1]. Unlike the experimental setup, which used axial vane swirlers to generate rotation, this study imposed a velocity profile at the inlet to introduce swirl. The simulations employed the Reynolds averaged Navier Stokes (RANS) approach with the shear stress transport k omega turbulence model, using ANSYS Fluent 2024R2. A grid independence study was performed using meshes of approximately 0.4, 0.5, and 0.6 million elements. The turbulent kinetic energy varied by less than 2 percent between the 0.5M and 0.6M grids, confirming adequate mesh resolution. The solver was validated against experimental data from Taamallah et al. [1], showing good agreement in axial velocity distribution. The validated model was then used to simulate a higher Reynolds number of about 30000. Contours and centerline profiles of axial velocity were analyzed. An inner recirculation zone (IRZ), identified by negative axial velocity in the core, formed in both cases and plays a key role in flame stabilization. An outer recirculation zone (ORZ) was observed near the expansion plane. Increasing Reynolds number raised the peak forward axial velocity by about 46 percent and intensified reverse velocity at x = 0.10 m by nearly 68 percent, indicating stronger recirculation. However, the axial location of the IRZ remained nearly unchanged. These results suggest robust flame anchoring under varying inertial conditions. Reacting flow simulations are planned as future work.

Trions – Coulomb-bound three-particle excitations composed of two like-charge carriers and one oppositely charged carrier – are central quasiparticles in two-dimensional semiconductors. Reduced dielectric screening and quantum confinement strongly enhance their binding energies, making them robust and experimentally accessible. This review surveys theoretical and experimental advances in trion physics, emphasizing rigorous few-body approaches and the role of dielectric environment, anisotropy, and external electric and magnetic fields. We analyze computational methods for describing trions in two-dimensional configuration spaces and discuss how reduced dimensionality modifies their structure and stability. Connections to many-body phenomena, including screening, Landau-level mixing, and exciton–polaron crossover, are also highlighted.

Urban land cover doubled between 1985 and 2015, yet the spatial dynamics of urban form remain under-quantified, despite its importance for sustainability, infrastructure planning, and climate risk. Urban expansion is a non-equilibrium process shaped by interactions between population growth, infrastructure, institutions, and market failures – rendering static and equilibrium models inadequate. We review key challenges and modeling approaches, focusing on partial differential equation (PDE) frameworks. Borrowed from statistical physics, PDEs capture spatial heterogeneity, anisotropy, stochasticity, and feedbacks between land use and transport networks. Integrating economic and institutional factors remains a major challenge for policy relevance. We propose a research agenda that bridges remote sensing, urban economics, and complexity science to develop dynamic, empirically grounded models of urban expansion.

Thermal neutron total scattering experiments of light and heavy water were reproduced using the CSNS in-house Monte Carlo thermal neutron transport code, Prompt, with a focus on the instrumental detector response and the accurate derivation of thermal neutron scattering cross-sections. In this work, a data reduction method is developed to process both the measured and simulated detector events for estimating angular, wavelength distributions, as well as angular differential cross sections. The reduction results of simulations and experiments show a high degree of consistency. The prominent inelasticity signatures observed in the experiments can be accurately reproduced in simulations. We discuss the cause of the inelasticity effects, and demonstrate the elimination of such effects when the inelastic scattering process is taken into account in simulations. In addition, multiple scattering in samples is analysed and discussed.

The turbulent attractor of wall bounded flows is not a structureless strange set but contains a skeleton of dynamically distinct states connected by rare directed transitions whose geometry is reflected in the invariant measure of the phase space trajectory. We show that this skeleton can be recovered from wall measurements alone, namely wall pressure and wall shear stress, without physical labels or prior knowledge, provided that the data driven function library used to identify the dynamics respects the intrinsic geometry of the attractor rather than the variance hierarchy of the POD representation. Standard sparse identification approaches introduce two structural biases during library construction. First, the steep decay of POD spectra causes Euclidean distances in k means clustering to be dominated by leading modes, collapsing basis function centres into a low dimensional subspace and leaving transitional dynamics poorly represented. Second, turbulent trajectories slow near quasi invariant states, so uniform time sampling over represents these regions and under samples rapid transitions. Both biases are corrected by resampling the trajectory uniformly in arc length and replacing the Euclidean metric with a Mahalanobis metric derived from the local cluster covariance. A single sparse regression on this corrected library yields a reduced model. Applied to a minimal turbulent channel at low Reynolds number, unsupervised clustering reveals two phases of the near wall cycle: stable streak states and burst initiating instabilities corresponding to the coherent structure skeleton of the flow. The model reproduces the invariant measure, reaches the Lyapunov predictability horizon and provides a differentiable vector field on which invariant solutions can be located by Newton iteration.

X-ray free-electron laser (XFEL) facilities require progressive compression of electron bunches as they are accelerated from an injector to the undulators. This is necessary to achieve the peak currents required for efficient lasing, without compromising transverse brightness. In the present generation of XFELs, high peak currents are achieved by means of a sequence of four-dipole bunch compression chicanes. It is well known that these systems are not ideal in that they allow projected emittance dilution at the percent level, and they exhibit amplification of microbunching, which typically must be controlled through the otherwise unwanted addition of slice energy spread by use of a laser heater. Both emittance dilution and microbunching are mediated through coherent synchrotron radiation that occurs within a bunch compression chicane. In this paper we introduce a new option for bunch compressors, that of full arc compression, and compare it to the standard four-dipole chicane and to a recently proposed variant, the five-dipole CSR mitigating chicane. It is shown that the arc compressor and the five-dipole chicane are able to give greatly improved XFEL performance compared to the standard four-dipole chicane, both in soft and hard X-ray regimes. This is demonstrated in the context of two proposed XFELs, SXL at MAX-IV, Sweden, and UK-XFEL. It is further shown that the optimal choice of compression option depends on the particular FEL scheme. This means that a simultaneous multi-FEL facility, such as UK-XFEL, must implement both arc and five-dipole methods and must be able to select between them on a bunch-by-bunch basis scheme. This means that a simultaneous multi-FEL facility, such as UK-XFEL, must implement both arc and five-dipole methods and must be able to select between them on a bunch-by-bunch basis.

This presentation discusses potential signals of Lorentz violation that could be observed in atomic and molecular spectroscopy experiments. It provides a general overview of the nonrelativistic effective SME coefficients that have been constrained, as well as the prospects for placing first-time bounds on those that remain unconstrained. Additionally, it highlights the importance of considering transitions involving atomic or molecular states with high angular momentum in tests of Lorentz symmetry.

Event horizon-scale observations of low-luminosity black hole accretion flows favor magnetically arrested disks, characterized by dynamically important magnetic fields ($\beta\lesssim1$, where $\beta$ is the ratio of plasma thermal pressure to magnetic pressure) and a two-temperature transrelativistic plasma. Motivated by plasma conditions in the synchrotron-emitting regions of these models, we perform 2D particle-in-cell simulations of electron-ion plasmas with a realistic mass ratio, subject to continuous compression perpendicular to the mean magnetic field $\boldsymbol{B}_0$. Conservation of particle magnetic moments drives pressure anisotropy $P_{\perp}>P_{\parallel}$, triggering anisotropy-driven instabilities. For ion plasma beta $\beta_{i0}=0.5$ and ion temperature $k_{\text{B}}T_{i0}/m_i c^2=0.05$, the ion pressure anisotropy is regulated by the ion cyclotron instability, while the mirror mode influences the late-time electron anisotropy. Both species develop nonthermal components at high energies, consistent with stochastic acceleration by cyclotron-scale fluctuations. We characterize how the onset and time evolution of the plasma instabilities, as well as the resulting ion and electron anisotropies and energy spectra, vary with $\beta_{i0}$, $k_{\text{B}}T_{i0}/m_i c^2$, electron-to-ion temperature ratio $T_{e0}/T_{i0}$, and the compression rate. Increasing the thermal energy toward relativistic values raises the anisotropy thresholds for all instabilities observed in our simulations, allowing larger anisotropies to develop. For $T_{e0}/T_{i0}<1$, as expected in collisionless two-temperature accretion flows, the growth of mirror and whistler instabilities is delayed or suppressed, leading to increasingly adiabatic evolution of the electrons. Our findings can be used to inform global fluid models of black hole accretion.

A knife-edge is recognized as a critical component of the schlieren imaging system. This knife-edge serves as a cutoff element, which is required to achieve high sensitivity in the schlieren imaging setup. This article describes a method for totally removing the knife-edge from a normal schlieren imaging system while maintaining the same sensitivity. In this approach, the camera lens's internal aperture acts like the cutoff element making an external knife-edge redundant. This method simplifies the schlieren setup and also reduces the setup cost due to the reduced number of optical or optomechanical elements. We show flow visualization data that clearly demonstrate that schlieren contrast can be obtained by employing a lens's internal aperture as the cutoff.

This study introduces a systematic and optimised methodology for designing Linear Variable Differential Transformer (LVDT) sensors and Voice Coil (VC) actuators, tailored for high-precision applications such as gravitational wave detectors and particle accelerators. Unlike prior studies, which focus primarily on industrial-grade LVDT design frameworks or isolated parameter studies, this work addresses the specific challenges of achieving both enhanced sensor response and actuation force within strict geometric and thermal constraints. Using a custom-developed simulation pipeline based on Finite Element Method Magnetics (FEMM), we evaluate the influence of key design parameters such as coil dimensions, radial gaps, and coil wire diameter on performance metrics such as response and linearity. The novelty of this work lies in its systematic exploration of design trade-offs, such as maximising performance while minimising heat dissipation, and its applicability to high-precision environments. In this work, particular emphasis is placed on the combination of the LVDT and VC functionalities in one unified sensor-and-actuator system designed for gravitational wave detectors. In addition, the methodology and simulation results are validated with experimental measurements of an optimised design, demonstrating a 2.8-fold increase in LVDT response and a 2.5-fold increase in VC actuation force compared to the initial configuration while preserving LVDT linearity and VC force stability. This work represents a significant advance over existing methodologies by offering a structured, scalable design process.

This study investigates the influence of aerofoil shape optimisation on blade aerodynamic performance under curvilinear and unsteady kinematics characteristic of vertical-axis turbines and cycloidal propellers. Using a cyclorotor in hover as a representative configuration, aerofoil optimisation was performed using two-dimensional unsteady Reynolds-averaged Navier-Stokes simulations coupled with Kriging. The optimised design was subsequently experimentally assessed through force measurements and flow-field characterisation using particle image velocimetry. Performance was enhanced through the suppression of leading-edge vortex separation during the primary thrust peak. This finding also reveals a governing constraint: the effectiveness of aerofoil optimisation depends on dynamic stall severity. Under light dynamic stall, geometric modification promotes vortex attachment and improves aerodynamic loading. Under deep dynamic stall, flow separation dominates the blade aerodynamics, and aerofoil shape modification cannot suppress leading-edge vortex shedding. The stall severity is regulated by rotor solidity through its influence on the induced throughflow-to-blade-speed ratio and the resulting effective incidence. Aerofoil optimisation is therefore viable primarily in high-solidity configurations that operate within a moderated stall regime. These findings establish a physics-based condition for aerofoil optimisation in curvilinear dynamic stall environments.

Nonlinear photon upconversion processes driven by diverse forms of structured light are receiving increasing attention. In harmonic and high-order harmonic generation (HG and HHG) with Laguerre-Gauss (LG) beams, linear scaling the driver topological charge (TC) with the harmonic order is equivalent to driver orbital angular momentum (OAM) per photon scaling, and constitutes a proof of OAM conservation. However, with generic driving fields, such as non-LG vortices or spatiotemporal optical vortices, TC and OAM per photon may scale or not in a process in which the OAM is conserved. We find the physical magnitude that scales with generality when the OAM, either longitudinal or transverse, or its intrinsic part, is conserved. This new rule allows for the wealth of phenomena observed in HHG that are unintelligible from the rigid LG rule.

At moderate levels of convective driving, simulations of dynamos in spherical shells often separate into two broad dipolar regimes characterised either by their relative magnetic field strength (weak/strong) or by their dominant force balance. These regimes can tend smoothly from one to the other but can also be bistable, a phenomenon which occurs particularly at low magnetic diffusivity. Nonlinear simulations of the geodynamo cannot be performed at realistic parameters and hence it is important to ensure that the (strong-field) branch, appropriate for Earth's core, is tracked as a distinguished limit is established towards a suitable parameterisation from the simulations that we can perform. In order to understand the transition to strong-field dynamos, and better understand the mechanisms that occur in both branches, we report on a series of magnetoconvection simulations: models in which an external magnetic field modifies the dynamically-generated dynamo. Our primary input parameters are the magnetic diffusivity, imposed magnetic field strength, and the convective forcing; as these vary, we show how the morphology of the flow can change gradually, as modifications of an existing mode or continuous variations in force composition, and also abruptly, when onset modes become unstable to secondary instabilities and are replaced either by newly-dominant modes, a vacillating regime, or highly nonlinear configurations of the flow. The loss of equatorial symmetry is also investigated, as this typically coincides with the weak-to-strong transition, and we discuss why an anti-symmetric instability emerges inside the tangent cylinder along with its implications for the geodynamo.

The widespread use of non-SI quantities and units, together with improper and misleading terminology, generates confusion in the domain of phase and amplitude noise. We discuss such physical quantities, units and terms with the purpose of stimulating a discussion between labs, and to agree for the full adoption of the International System of Units (SI) and clear, unambiguous terminology.

Topology optimization (TO) has been widely adopted in engineering design; however, it is prone to being trapped in local optima, particularly in strongly nonlinear problems. Sensitivity-free data-driven topology design (DDTD) offers a promising alternative. Nevertheless, existing DDTD-based methods still depend heavily on prior information or sensitivity-based TO methods for initialization, limiting their generality and independence in engineering applications. In this study, an efficient DDTD-based framework capable of being driven from low information-entropy initial datasets is proposed while improving computational efficiency. To reduce the dependence on high information-entropy initial datasets, a mesh-independent mutation module is introduced as a supplementary source of geometric features, enabling stable exploration under low information-entropy initialization. To alleviate the computational bottleneck in DDTD, where all candidate structures require numerical evaluations, a non-AI-based rapid identification algorithm is developed to efficiently identify potential high-performance structures, thereby significantly reducing the number of expensive high-fidelity simulations. The framework generates material distributions on body-fitted meshes to maintain consistency between numerical simulations and physical manufacturing. A signed distance field-based minimum length constraint is further incorporated to ensure reliable mesh generation. Numerical experiments on strongly nonlinear stress-related problems, together with comparisons with sensitivity-based TO methods, demonstrate the effectiveness of the proposed method. In microfluidic reactor and shell design problems involving non-differentiable constraints, the proposed method successfully addresses scenarios that remain challenging for both sensitivity-based TO and conventional DDTD-based methods.

Optical klystrons provide an efficient mechanism for enhancing coherent radiation through laser-induced microbunching and dispersive amplification. In the terahertz (THz) regime and at low beam energy, however, the radiation wavelength becomes comparable to the characteristic wavelengths of longitudinal space-charge (LSC) and coherent synchrotron radiation (CSR) driven microbunching. In this work, we analyze the impact of electron-beam microbunching on the spectral amplitude and phase of a seeded optical klystron operating in the THz regime. Using a phase-space formalism, incoherent energy modulations generated by collective effects are shown to enter the bunching spectrum as a stochastic longitudinal phase, producing local wavenumber jitter and spectral broadening. An explicit connection between the microbunching-induced energy modulation and LSC/CSR gain is established for low-energy beams, demonstrating that the overlap between collective-effect wavelengths and the optical-klystron radiation wavelength leads to strong spectral phase distortion. These effects impose fundamental constraints on the achievable harmonic bunching and spectral purity and stability of THz optical klystrons and must be considered in the design and optimization of next-generation low-energy THz FEL facilities.

Ion transport through narrow channels is described by the coupled Poisson–Nernst–Planck–Stokes equations (PNPS) on a continuum scale. However, direct numerical simulations in two or three dimensions of boundary value problems for small aspect ratio geometries, a crucial characteristic of nanopores, can quickly become computationally intensive and thus limit the insights into the underlying mechanisms that control electrokinetic phenomena. Taking advantage of the small aspect ratio, we derive a systematic asymptotic reduction of the PNPS system. In contrast to existing one-dimensional reductions, which assume a Debye length much smaller than the channel radius, our analysis identifies a distinguished asymptotic regime in which the Debye length is allowed to be comparable to the channel width. Our approach has a significantly larger range of validity and contains existing approximations such as the Helmholtz–Smoluchowski approximation as limiting cases. The derived asymptotic model extends also to a generalized PNPS system, where finite-size constraints and solvation effects are taken into account and thus applies to other well-known models such as the Bikerman–Freise model. Using our asymptotic model we demonstrate that the ion current can undergo a number of different flow transitions and in particular predict that positively charged ions can be pushed against their electrostatic gradient. Furthermore, we show how finite-size effects can influence the ion current and enhance ion selectivity. Finally, we revisit case studies of protein-based channels from the literature to illustrate the predictive potential of our asymptotic model.

A conceptual design study of a Transverse Deflecting Structure (TDS) for longitudinal beam diagnostics at the DALI accelerator facility is presented. The TDS provides a time-dependent transverse kick to the electron bunch, enabling direct measurement of the longitudinal bunch profile and reconstruction of the longitudinal phase space when combined with a dispersive spectrometer section. The report reviews the physical principles of RF deflecting cavities, including the transverse kick mechanism, temporal-to-spatial mapping, and the relationship between beam optics and achievable temporal resolution. Engineering considerations such as RF frequency choice, cavity design, wakefield effects, timing synchronization, and mechanical stability are also discussed.