Papers

Modeling count data is important in physics and other scientific disciplines, where measurements often involve discrete, non-negative quantities such as photon or neutrino detection events. Traditional parametric approaches can be trained to generate integer-count predictions but may struggle with capturing complex, non-linear dependencies often observed in the data. Gaussian process (GP) regression provides a robust non-parametric alternative to modeling continuous data; however, it cannot generate integer outputs. We propose the Poisson Log-Normal (PoLoN) process, a framework that employs GP to model Poisson log-rates. As in GP regression, our approach relies on the correlations between data points captured via GP kernel structure rather than explicit functional parameterizations. We demonstrate that the PoLoN predictive distribution is Poisson-LogNormal and provide an algorithm for optimizing kernel hyperparameters. Furthermore, we adapt the PoLoN approach to the problem of detecting weak localized signals superimposed on a smoothly varying background - a task of considerable interest in many areas of science and engineering. Our framework allows us to predict the strength, location and width of the detected signals. We evaluate PoLoN's performance using both synthetic and real-world datasets, including the open dataset from CERN which was used to detect the Higgs boson at the Large Hadron Collider. Our results indicate that the PoLoN process can be used as a non-parametric alternative for analyzing, predicting, and extracting signals from integer-valued data.

Understanding the physical computing mechanisms of individual network nodes is essential for scaling neuromorphic photonic architectures. This work proposes a compact passive nonlinear photonic core based on a Side-Coupled Integrated Spaced Sequence of Resonators (SCISSOR) made of three nominally equal microrings and investigate its computing capabilities. Its nonlinearities and internal feedback enable analogue, spiking, and bistable responses that are accessed by tuning the injection power and wavelength. Implemented as a single nonlinear node in a time-multiplexed reservoir computing, the SCISSOR achieves error-free classification on the Iris dataset and accuracies above 97% on the Sonar task, using both analogue and digital reservoir representations with 150 virtual nodes. In the digital scheme, spiking dynamics naturally generate sparse reservoir states, enabling efficient classification even with a single spike. Intriguingly, optimal operating points are at the boundaries where sharp transitions in dynamical complexity and/or output power occur. In these points, the SCISSOR supports high task-performance, opening novel strategies for future on-chip training. Spiking and thermal bistabilities also participate to enhance the computational performance at low injected powers below 4 mW. These results suggest optical coupled microring resonators as effective building blocks for future edge computing and neuromorphic photonic systems.

Sub-Neptunes with hydrogen-rich envelopes are expected to sustain long-lived magma oceans that continuously exchange volatiles with their overlying atmospheres. Capturing these interactions is key to understanding the chemical evolution and present-day diversity of sub-Neptunes, super-Earths, and terrestrial planets, particularly in light of new JWST observations and upcoming missions. Recent advances in both geochemistry and astrophysics now allow the integration of experimental constraints and thermodynamic models across melt, metal, and gas phases. Here we extend a global chemical equilibrium model to include non-ideal behavior in all three phases. Our framework combines fugacity corrections for gas species with activity coefficients for silicate and metal species, enabling a fully coupled description of volatile partitioning. We show that for planetary embryos (0.5 M$_\oplus$ at 2350 K), non-ideality introduces only modest corrections to atmosphere-magma ocean interface (AMOI) pressures, volatile inventories, and interior compositions. In contrast, for sub-Neptunes with higher temperatures ($\approx$ 3000 K) and pressures, non-ideal effects are more pronounced, though still modest in absolute terms$-$typically within 20% and at most a factor of two. Including activity and fugacity coefficients simultaneously increases the AMOI pressure, enhances water retention in the mantle and the envelope. Our results demonstrate that non-ideality must be treated globally: applying corrections to only one phase leads to incomplete or even misleading trends. These findings highlight the importance of self-consistent global thermodynamic treatments for interpreting atmospheric spectra and interior structures of sub-Neptunes and super-Earths.

When exposed to a contagion phenomenon, individuals may respond to the perceived risk of infection by adopting behavioral changes, aiming to reduce their exposure or their risk of infecting others. The social cost of such adaptive behaviors and their impact on the contagion dynamics have been investigated in pairwise networks, with binary interactions driving both contagion and risk perception. However, contagion and adaptive mechanisms can also be driven by group (higher-order) interactions. Here, we consider several adaptive behaviors triggered by awareness of risk perceived through higher-order and pairwise interactions, and we compare their impact on pairwise and higher-order contagion processes. By numerical simulations and a mean-field analytic approach, we show that adaptive behaviors driven by higher-order information are more effective in limiting the spread of a contagion, than similar mechanisms based on pairwise information. Meanwhile, they also entail a lower social cost, measured as the reduction of the intensity of interactions in the population. Indeed, adaptive mechanisms based on higher-order information lead to a heterogeneous risk perception within the population, producing a higher alert on nodes with large hyperdegree (i.e., participating in many groups), on their neighborhoods, and on large groups. This in turn prevents the spreading process to exploit the properties of these nodes and groups, which tend to drive and sustain the dynamics in the absence of adaptive behaviors.

Walking droplets are millimetric fluid drops that propel themselves across a vibrated liquid bath through interaction with their self-generated waves. They constitute classical active wave-particle entities and exhibit a range of hydrodynamic quantum analogs. We investigate an active soft-impact oscillator as a minimal model for a walking droplet moving within a piecewise-smooth external potential, analogous to classical mass-spring soft-impact oscillators and recently explored quantum soft-impact oscillators. Our active soft-impact oscillator model couples a non-smooth soft-impact force to the Lorenz-like dynamics arising from the wave-particle entity. Theoretical and numerical exploration of the full parameter space reveals a wide variety of nonlinear behaviors and bifurcations driven by impact and grazing events. These include grazing-induced and impact-induced transitions between periodic and chaotic motion, as well as grazing-mediated attractor switching and impact-free (invisible) attractor switching. The active soft-impact oscillator thus provides a versatile platform for probing nonlinear impact dynamics in active systems and exploring hydrodynamic quantum analogs in non-smooth potentials.

This is the third article in a series of three dealing with the exploitation of speckle for imaging purposes. In complex media, a fundamental limit is the multiple scattering phenomenon that completely blurs the imaging process in depth. Matrix imaging can provide a relevant framework for solving this problem. As it proved to be an adequate tool for probing reverberations in speckle [E. Giraudat et al., Part I], we will show how it can be used to tailor complex spatio-temporal focusing laws to monitor the interference between the multiply-reflected paths and the ballistic component of the wave-field. To do so, we extend the distortion matrix concept to the frequency domain. An iterative phase reversal process operated from the space-time Fourier space is then used to compensate for reverberations and optimize both the axial and transverse resolution of the confocal image. Here, we first present an experimental proof-of-concept consisting in imaging a tissue-mimicking phantom through a reverberating plate before outlining the potential and the limits of this strategy for transcranial ultrasound and beyond.

This is the first article in a series of three dealing with the exploitation of speckle for imaging purposes. Speckle is the complex interference wave-field produced by a random distribution of un-resolved scatterers. In this paper, we show how these scatterers can be used as virtual microphones to monitor the spatio-temporal propagation of a wave-packet inside the medium. To do so, the concept of matrix imaging is particularly useful. It consists in decoupling the location of the transmitted and received focal spots in a standard beamforming process. By scanning the wave-field with the output focal spot that then acts as a virtual transducer, one can image the spatio-temporal evolution of the wave-packet inside the medium. This unique observable will allow us to highlight the imperfections of the focusing process, in particular the defocus and reverberations induced by a strong aberrating layer. As a proof-of-concept, we will consider ultrasound experiments on tissue-mimicking phantoms. In the next two papers, we will show how this observable can be leveraged to compensate for these phenomena that hamper wave focusing and imaging in all fields of wave physics. Our method is indeed broadly applicable to different types of waves beyond ultrasound for which multi-element technology allows a reflection matrix to be measured.

We investigate the effect of rotor velocity induction on the distribution of particles impinging on rotor blades and model the delayed response of a particle to the rotor-induced velocity field. We consider as reference a wind turbine rotor and a small-scale propeller in axial flow conditions. We first show that the classical 2D modeling of the multi-phase flow can generate a systematic error with respect to the 3D solution. We consider two limiting cases: particles in equilibrium with the rotor-induced velocity field, where the carrier phase is computed using the section's aerodynamic velocity vector, and induction-independent particles, where the geometric velocity vector is used. The 3D solution differs from the two limiting cases when particles are in partial equilibrium with the induced velocity. We introduce an induction Stokes number $\mathit{Stk}_\text{ind}$ and identify a transition regime between the two limiting solutions for $0.1 \lesssim \mathit{Stk}_\text{ind} \lesssim 10$. Then, we present a simple 1D delay model to evaluate the induced component of the particle velocity at the rotor disk as a function $\mathit{Stk}_\text{ind}$. We validate the model by showing that it allows capturing the transition regime in 2D simulations. The model only requires knowledge of the aerodynamic and geometric velocity vectors, i.e., of the axial and tangential induction factors.

In response to the 2008 global financial crisis, Science Foundation Ireland (SFI), now Research Ireland, pivoted to research with potential socioeconomic impact. Given that the latter can encompass higher technology readiness levels, which typically correlates with lower academic impact, it is interesting to understand how academic impact holds up in SFI funded research. Here we decompose SFI Investigator Awards - arguably the most academic funding call - into $3,243$ constituent publications and field weighted citation impact (FWCI) values searchable in the SCOPUS database. Given that citation counts are skewed, we highlight the limitation of FWCI as a paper metric, which naively restricts one to comparisons of average FWCI ($\overline{\mathrm{FWCI}}$) in large samples. Neglecting publications with $\textrm{FWCI} < 0.1$ ($8.8\%$), SFI funded publications are well approximated by a lognormal distribution with $\mu = -0.0761^{+0.017}_{-0.0039}$ and $ \sigma = 0.933^{+0.011}_{-0.012}$ at $95 \%$ confidence level. This equates to an $\overline{\mathrm{FWCI}} = 1.433^{+0.029}_{-0.015}$ well above $\overline{\mathrm{FWCI}}=1$ internationally. Broken down by award, we correct $\overline{\mathrm{FWCI}}$ for small samples using simulations and find $\sim 67\%$ exceed median international academic interest, thus exhibiting a positive correlation between the potential for socioeconomic impact and academic interest.

Evidence-based education has become a central concept in science education, with meta-analyses often regarded as the gold standard for informing practice. This emphasis raises critical questions concerning the applicability, generalizability and transferability of research findings into classroom practice. It remains unclear both what kind of evidence education should be based on and whether science education research can provide the type of evidence required to guide decisions at different levels. This paper argues that theories play a crucial role in building bridges between research and practice. Drawing on literature from science education and the philosophy of science, we contrast the explanatory scope of meta-analyses with the predictive and integrative potential of theories, understood in a structuralist sense as systems of models with defined domains of applicability. We propose that science education research requires both fundamental and applied research, each contributing to theory development at different levels, ranging from local and context-specific models to more fundamental theoretical frameworks. Importantly, we argue that theories in science education should not be viewed merely as applications of psychological or pedagogical theories, but as fundamental theories in their own right. We conclude that the future development of science education research may benefit more from the systematic refinement and integration of theories than from the continued accumulation of isolated local findings, and we propose ways to support the development of such theories. A theory-guided understanding of evidence-based education can strengthen the scientific foundations of the field while simultaneously enhancing its practical relevance, thereby helping to narrow the long-standing theory-practice gap.

Transition interface sampling (TIS) and replica exchange TIS (RETIS) are powerful methods for computing rates of rare events inaccessible to straightforward molecular dynamics (MD) simulations. Path reweighting extends their output, enabling the evaluation of diverse thermodynamic and kinetic quantities, including reaction prediction metrics, activation barriers, committor functions, and free energies. The recently developed Infinity-RETIS algorithm boosts parallel efficiency through asynchronous replica exchanges in the infinite-swap limit, eliminating the wall-time bottlenecks of conventional RETIS. This approach introduces fractional samples and biased sampling distributions, requiring a generalized path reweighting framework, for which we derive expressions demonstrating how exact dynamic and thermodynamic variables can be computed. We then focus on a special class of free energy surfaces defined by history-dependent conditions, whose values are influenced by kinetic factors such as particle mass and friction, unlike standard unconditional free energy surfaces. Even with suboptimal reaction coordinates, these conditional free energies can reveal kinetically relevant barriers that may be misrepresented by standard unconditional free energies, thereby providing a rigorous and versatile tool for characterizing complex molecular transitions.

First, we describe vacuum brazing and vacuum soldering. Then, we demonstrate how vacuum assists in reducing specific metal oxides, significantly enhancing the wetting of the braze material. Examples of metal-to-metal brazing and soldering are provided. The brazing of large accelerating cavities, specifically Radio Frequency Quadrupoles (RFQ), is then explained in more detail to present a comprehensive procedure tailored for high-precision, large-scale assemblies. Finally, we discuss the process of brazing ceramics using both techniques: with metallisation and with active brazing alloy.

The Borgnakke-Larsen model, widely used in rarefied flow predictions, serves as the mainstream energy-exchange kernel for polyatomic gases. However, it lacks integrability and does not guarantee detailed balance, limiting theoretical foundations for near-continuum relaxation mechanisms, transport coefficients, and relaxation model equations. In this work, we adopt the Pullin equation, which possesses an integrable collision kernel and satisfies detailed balance, to analyze near-continuum relaxation. Considering only translational and rotational degrees, we obtain explicit analytical expressions for the relaxation rates of macroscopic variables including stress, temperatures, and heat fluxes by approximating the distribution function in mixed Hermite and Laguerre spaces. Based on the same elementary moments, we derive transport coefficients via Chapman-Enskog expansion, rigorously confirming a long-standing speculation that thermal conductivity depends on the degree of thermal non-equilibrium; under equilibrium, the results reduce to those of Mason and Monchick. Using the correct relaxation rates, we propose a novel Rykov-type relaxation model that captures the coupled relaxation of translational and rotational heat fluxes, a mechanism ignored in the widely used Rykov equation. The model is validated against benchmark test cases.

By using a neural network that takes momentum distributions of photoelectrons produced in strong-field ionization as input, we retrieve the time-dependent bond length of a dissociating one-dimensional H$_{2}^{+}$ molecule. The photoelectron momentum distributions are calculated from the direct numerical solution of the non-Born-Oppenheimer time-dependent Schrödinger equation. We simulate two setups: first, molecules prepared in the first excited electronic state, second, a pump-probe scheme starting from the ground state. We show that in both schemes a neural network trained on momentum distributions calculated for frozen nuclei retrieves the time-dependent bond length with an absolute error of $0.2$-$0.4$ a.u. We find that a neural network, when applied to photoelectron momentum distributions obtained within the pump-probe scheme, can be used for the retrieval of the equilibrium internuclear distance and ground-state population. This opens new perspectives for extracting electronic properties of molecules from electron momentum distributions using deep learning.

Tunable optical delay lines that simultaneously offer nanosecond-scale delay, broadband operation, low dispersion, and compact footprint remain challenging to realize with conventional integrated photonic platforms. Here we demonstrate a mechanically reconfigurable slow-light delay line based on a surface nanoscale axial photonics (SNAP) microresonator dynamically induced by controlled bending of a silica optical fiber. A localized nanoscale cutoff-wavelength dip, introduced by CO2-laser annealing, provides a reflective boundary, while fiber bending generates a smooth axial potential whose shape is continuously tunable via loop curvature. By adjusting the bending radius, the induced SNAP microresonator evolves from a nearly linear to an approximately semiparabolic axial profile, enabling a controlled transition from dispersive to nearly dispersionless delay. Using a transverse microfiber coupler operated at the impedance-matching condition, we experimentally demonstrate continuous delay tuning from 2 ns to 0.5 ns within a 10 GHz bandwidth in an approximately 2 mm long fiber segment, with insertion loss below 6 dB. The results confirm that mechanically induced SNAP microresonators provide a compact, robust, and reconfigurable platform for dispersion-engineered optical delay lines, with direct relevance to photonic beamforming, frequency-comb stabilization, and neuromorphic photonic signal processing.

Hyperbolic phonon polaritons (HPPs) in hexagonal boron nitride (hBN) confine mid-infrared light to deep-subwavelength scales and may offer a powerful route to strong light-matter interactions. Generation and control of HPPs are typically accessed using classical near-field probes, which limits experiments at the quantum level.A complementary frontier in hBN research focuses on color centers: bright, stable, atomically localized emitters that have rapidly emerged as a promising platform for solid-state quantum optics. Here we establish a key connection between these two directions by developing a cavity-QED framework in which a single hBN color center serves as a quantum source of HPPs. We quantify the emitter-HPP interaction and analyze two generation schemes. The first is spontaneous emission into the phonon sideband, which can produce single-HPP events and, in ultrathin slabs, becomes single-mode with an enhanced decay rate. The second is a stimulated Raman process that provides frequency selectivity, tunable conversion rate, and narrowband excitation. This drive launches spatially confined, ray-like HPPs that propagate over micrometer distances. We also outline a two-emitter correlation measurement that can directly test the single-polariton character of these emissions. By connecting color-center quantum optics with hyperbolic polaritonics, our approach enables quantum emitters to act as on-chip quantum sources and controls for HPPs, while HPPs provide long-range channels that couple spatially separated emitters. Together, these capabilities point to a new direction for mid-infrared photonic experiments that unite strong coupling, spectral selectivity, and spatial reach within a single material system.

This paper studies the use of optical lattice clock (OLC) detector networks for detecting the stochastic gravitational-wave background (SGWB). Starting from the cross-correlation formalism for two OLC detectors, we analyze how the detector geometry influences the overlap reduction function (ORF) and systematically search for configuration transformations that preserve the modulus of the ORF. We identify an equivalent transformation in which the emitting and receiving ends of both OLC links are exchanged, while the modulus of the ORF remains invariant. We then numerically compare the ORFs of isosceles trapezoidal configurations with different separations and included angles. Based on these results, we design a feasible four-spacecraft orbital configuration and evaluate its strain sensitivity and noise energy-density spectrum in comparison with LISA, Taiji, and TianQin.

A large field of view of an optical system is needed for many applications, and optical systems with high magnification often suffer from a limited field of view due to the limited size of the camera sensor. This study proposes a novel technique for engineering the field of view of an optical system without compromising the magnification. In the proposed method, an object response pattern is recorded on a camera by introducing a coded phase mask (CPM) in the imaging system. The coded phase mask is a multiplexing of N distinct scattering phases, where N-1 represents the number of isolated object areas to be brought within the field of view. Each scattering phase yields a point spread function of a unique sparse dot pattern on the camera. With the introduction of a coded phase mask, the objects' images are brought within the region of the camera sensor, which, without the CPM, would have remained outside the inherent field of view of the system. To reconstruct the original object plane with N objects at their respective locations, the zero-padded object response pattern is deconvolved with the system's zero-padded and shifted point spread function. A simulation study followed by experimental results for N = 2 and N = 3 is presented in this article.

This study investigates the interplay between relativistic effects and electron correlation effects on the first ionization energies of heavy atoms (Au through Rn, Z = 79-86). We perform two complementary analyses: (1) comparing relativistic corrections computed at both the Hartree-Fock (HF) and coupled cluster CCSD(T) levels to assess how correlation influences the magnitude of relativistic corrections, and (2) comparing correlation corrections computed within both non-relativistic and relativistic frameworks to determine how relativity influences the magnitude of correlation corrections. Our results reveal a striking non-linear relationship between these two effects. Specifically, the combined effect of relativity and correlation on ionization energy does not equal the sum of their individual contributions. This non-additivity indicates that relativistic and correlation effects are not independent; they interact in complex ways that depend on the atomic system. We find that for some atoms, the two effects enhance each other, while for others they partially cancel. Moreover, the order in which one may add "separate" effects also counts, in that adding "pure" relativistic effects to the remaining outcome (including correlation) would give a different result than when adding "pure" correlation effects to the remaining outcome (including relativity). These findings demonstrate that relativistic and correlation effects are inherently non-additive, reflecting the non-linearity of the quantum many-body problem. Accurate computational predictions of ionization energies in heavy-element systems thus require simultaneous treatment of both effects rather than treating them as independent contributions.

The present study investigates the linear stability of Riemann ellipsoids in both the inviscid limit and in the presence of weak viscosity. In the inviscid regime, we derive a generalised Poincare equation governing small fluid oscillations and construct a family of polynomial solutions that extends the classical results of Cartan to flows with a uniform strain field. This formulation provides an analytic dispersion relation for three-dimensional ellipsoidal disturbances and remains computationally efficient at arbitrary harmonic degree, in contrast to the virial tensor method or to short-wavelength (WKB) approximations. The viscous effects are incorporated through a boundary-layer analysis based on Prandtls theory, leading to first-order viscous corrections to the inviscid spectrum and allowing a systematic investigation of viscosity-driven instabilities. Stability diagrams are presented over the space of admissible Riemann ellipsoids, illustrating the roles of rotation, internal strain, and diffusion, with implications for rotating shear flows in geophysical and astrophysical contexts.

Nonlinear SU(1,1) quantum interferometers based on non-degenerate optical parametric down-conversion exhibit strong unbalanced group velocity dispersion (GVD). This feature is intrinsic to this type of interferometer as correlated photons of vastly different frequencies propagate through a dispersive nonlinear crystal; consequently, the dispersion arises from the source itself. The resulting GVD degrades the axial point-spread function (PSF) in optical coherence tomography (OCT) with undetected photons; and physical compensation is less straightforward, in particular for non-degenerate broadband regimes due to the limited number of suitable materials. In this contribution, we analyze dispersion in bulk nonlinear interferometry and describe its implications for OCT imaging. Aspects of hardware compensation are addressed, and a novel empirical numerical method of compensation is proposed. The approach is based on the extraction of the phase component directly from the time-domain modality (high precision linearized quantum Fourier transform infrared spectrometer) and its injection into the mid-IR spectral-domain OCT signals (central wavelength of around 3770 nm) before the Fourier transform. The proposed method is compared with an alternative numerical technique. The results demonstrate a 2.2-fold improvement in axial resolution and outperform the alternative correction method in overall imaging performance.

The Front-Tracking Method (FTM) is a promising approach for numerical solution of multiphase flows, considering a trade-off between accuracy and computational cost. The existing open-source open-access software for FTM is scarce, due to complexity of the coding and algorithms, and is limited to structured Cartesian grids or connectivity-free front mesh hybrid FTMs. To provide a pure FTM solver on general unstructured grids, the Ftc3D FTM code has been integrated into the OpenFOAM CFD software by implementing necessary front mesh to Eulerian grid communication and front nodes advection algorithms, applicable to unstructured grids and for both serial and parallel runs. The new FTM package, called cfdmfFTFoam, has been further equipped with a variety of FTM sub-algorithms, including the front volume correction, remeshing, surface tension computation, indicator function construction, etc. Assessments and validations of the new solver are provided against several standard multiphase flow benchmarks. It is anticipated that cfdmfFTFoam would facilitate future research on and algorithm improvement in the field of FTM.

We report the first direct frequency comparison between two multi-ion optical clocks based on the S$_{1/2}$ to D$_{5/2}$ transition in \Ca and \Sr ions. Using linear chains of up to nine \Ca ions and six \Sr ions, we demonstrate improved stability as a function of the number of ions that are contributing to the laser frequency stabilization servo. The measured joint fractional frequency stability of the two clocks reaches $1.37(12)\times 10^{-15}$ at one second, placing an upper bound on the same stability of one of the clocks at $9.6(8)\times 10^{-16}$ in one second. We measured the frequency ratio of the two clocks to be $R_{\text{Sr/Ca}}=1.082076536381896986(18)$, where the systematic uncertainty is primarily limited by the room temperature blackbody radiation. Our direct measurement represents an order of magnitude improvement compared to existing indirect frequency ratio measurements. Furthermore, by combining our results with recent absolute frequency measurements of the \Sr transition, referenced to a primary frequency standard, we refined the absolute frequency of the \Ca transition to $\nu_{\text{Ca}^+}=411042129776400.21(4)$ Hz, reducing its uncertainty by a factor of three. This study presents the first direct comparison between two multi-ion optical clocks, highlighting their significant potential for future applications in fundamental physics tests, geodesy, and precision metrology.

Infrared (IR)-transparent passive radiative cooling (PRC) enables non-contact thermal management by regulating radiative heat exchange without direct attachment to the cooling object. While asymmetric IR transmission at a specific incidence angle – typically normal incidence – is often emphasized, we show that such single-angle asymmetry is neither sufficient nor predictive of practical cooling performance. In this work, we demonstrate that effective non-contact PRC requires angularly distributed asymmetric IR transparency evaluated through hemispherical integration over emission directions, rather than asymmetry at a single incidence angle. To quantify this effect, an angle-resolved full-wave electromagnetic (EM) model with Bloch periodic boundary conditions and Floquet mode decomposition is employed to compute wavelength- and angle-dependent bidirectional reflection and transmission of periodic PRC structures. The resulting EM response is coupled to an energy-balance-based thermal model to predict the transient temperature evolution of the cooling object. By comparing models that account for the full angular distribution with normal-incidence-only approximations, we show that pronounced asymmetric transmission at normal incidence is generally not preserved at oblique angles. As a result, angular integration yields only marginal cooling or may even result in net heating, whereas normal-incidence-based models can substantially overestimate cooling performance. These results establish angularly distributed asymmetric transparency as a key EM design principle for IR-transparent PRC and wide-angle asymmetric metasurfaces.

A random number generator for the Kappa velocity distribution in particle simulations is proposed. Approximating the cumulative distribution function with the q-exponential function, an inverse transform procedure is constructed. The proposed method provides practically accurate results, in particular for k<4. It runs fast on graphics processing units (GPUs). The derivation, numerical validation, and relevance to GPU execution models are discussed.

Variational multiscale (VMS) methods offer a robust framework for handling under-resolved flow scales without resorting to problem-specific turbulence models. Here, we propose and assess a dynamic, term-by-term VMS stabilized formulation for simulating incompressible flows from laminar to turbulent regimes. The method is embedded in an incremental pressure-correction fractional-step framework and employs a minimal set of stabilization terms, yielding a unified discretization that (i) allows equal-order velocity–pressure interpolation and (ii) provides robust control of convection-dominated dynamics in complex three-dimensional settings. Orthogonal projections are a key ingredient and ensure that the non-residual, term-by-term structure induces dissipation through dynamic subscales suitable for turbulent simulations. The methodology is validated on large-scale external-aerodynamics configurations, including the Ahmed body at Re $ = 7.68\times 10^{5}$ for multiple slant angles, using unstructured tetrahedral meshes ranging from 3 to 40 million elements. Applicability is further demonstrated on a realistic Formula~1 configuration at $U_\infty=56~\mathrm{m/s}$ (201.6~km/h), corresponding to Re $ \approx 10^{6}$. The results show that the proposed stabilized pressure-segregated formulation remains robust at scale and captures key separated-flow features and coherent wake organization. Pointwise velocity and pressure spectra provide an a posteriori consistency indicator, exhibiting finite frequency ranges compatible with inertial-subrange reference slopes in the resolved band and supporting dissipation control in under-resolved regimes within a unified stabilized finite element framework.

Estimating the depth of a monoharmonic sound source at a fixed range using a vertical linear array (VLA) is challenging in the absence of seabed environmental parameters, and relevant research remains scarce. The orthogonality constrained modal search based depth estimation (OCMS-D) method is proposed in this paper, which enables the estimation of the depth of a monoharmonic source at a fixed range using a VLA under unknown seabed parameters. Using the sparsity of propagating normal modes and the orthogonality of mode depth functions, OCMS-D estimates the normal mode parameters under a fixed source-array distance at first. The estimated normal mode parameters are then used to estimate the source depth. To ensure the precision of the source depth estimation, the method utilizes information on both the amplitude distribution and the sign (positive/negative) patterns of the estimated mode depth functions at the inferred source depth. Numerical simulations evaluate the performance of OCMS-D under different conditions. The effectiveness of OCMS-D is also verified by the Yellow Sea experiment and the SWellEx-96 experiment. In the Yellow Sea experiment, the depth estimation absolute errors by OCMS-D with a 4-second time window are less than 2.4 m. And the depth estimation absolute errors in the SWellEx-96 experiment with a 10-second time window are less than 5.4 m for the shallow source and less than 10.8 m for the deep source.

In this lecture we discuss the intensity limitations in hadron LINACs. First, we will detail what are the two main meanings of intensity limitations as they differ substantially between high power LINACs and high brightness LINACs. Then we will illustrate in detail the building blocks of hadron linacs focusing on the beam dynamics. We will conclude with few examples of intensity limitations and their mitigations.

We present a comparative analysis of Wikipedia and Grokipedia to examine how generative mediation alters content selection, textual rewriting, narrative structure, and evaluative framing in encyclopedic content. We model page inclusion in Grokipedia as a function of Wikipedia page popularity, density of reference, and recent editorial activity. Inclusion is non-uniform: pages with higher visibility and greater editorial conflict in Wikipedia are more likely to appear in Grokipedia. For included pages, we distinguish between verbatim reproduction and generative rewriting. Rewriting is more frequent for pages with higher reference density and recent controversy, while highly popular pages are more often reproduced without modification. We compare editing activity across the two platforms and estimate page complexity using a fitness-complexity framework to assess whether generative mediation alters patterns of editorial participation. To assess narrative organization, we construct actor-relation networks from article texts using abstract meaning representation. Across multiple topical domains, including U.S. politics, geopolitics, and conspiracy-related narratives, narrative structure remains largely consistent between the two sources. Analysis of lead sections shows broadly correlated framing, with localized shifts in laudatory and conflict-oriented language for some topics in Grokipedia. Overall, generative systems preserve the main structural organization of encyclopedic content, while affecting how content is selected, rewritten, and framed.

A proof of principle experiment of Three-dimensional spiral beam injection scheme has been carried out. This injection scheme requires a strongly x-y coupled beam to meet magnetic field distribution through solenoid magnet fringe field. In this paper, we introduce outline of experimental setup, results of x-y coupling adjustment with DC electron beam of 80 keV. The results of this experiment will be evaluated and improvements for actual operation will be discussed.