Papers

Shadow bands are transient, rippling patterns of light and dark that may appear in moments before and after totality in a solar eclipse. Despite centuries of reports, their physical origin has remained unresolved. This preprint develops a geometric-optical solution in which the Sun's extended structure produces a celestial analogue of Young's double-slit experiment, generating an interference-like intensity pattern on the ground, modulated by Earth-atmosphere effects. The analysis combines solar limb geometry, atmospheric propagation effects, and a wave-based formulation that yields quantitative predictions for fringe width and spacing. The resulting model accounts for the principal observational features of shadow bands and clarifies why the phenomenon is both elusive and highly sensitive to viewing conditions.

Supergranular flows organize transport in the solar photosphere over spatial and temporal scales much larger than granulation. While coherent vortical motions have been identified using objective Lagrangian diagnostics such as the Lagrangian-averaged vorticity deviation (LAVD), rotational coherence captures only one aspect of coherent flow organization. Here we introduce finite-time rotationally coherent sets (FTRCS) by combining the inflated dynamic Laplacian (IDL), which identifies finite-time quasi-material coherent regions, with LAVD-based rotational diagnostics. The IDL extracts coherent structures with finite lifetimes, while LAVD identifies those exhibiting enhanced intrinsic rotation. Application to photospheric velocity fields shows that instantaneous vortical features do not necessarily correspond to finite-time rotationally coherent structures. The analysis also illustrates the effect of compressibility: coherent sets may form through persistent contraction associated with convergent transport, rather than through the persistence of rotating material regions. The combined IDL–LAVD approach separates finite-time transport coherence from intrinsic rotational organization in time-dependent flows.

Past and recent observations suggest that many planetary mass or dwarf planet objects may exist in the outer Solar System. Gravitational perturbations may occasionally bring some of them into the inner Solar System. The early, rare collision between the early Earth and a Mars sized body is generally invoked to explain the formation of the Moon. More probable than a direct impact, are grazing or near Earth flybys of similar objects. Such passages may have left strong tidal signatures: giant waves, large volcanic episodes, sea regressions, coherent meteor showers, and major climatic perturbations. These mechanisms could have contributed to several major biological mass extinctions over the past $600$ million years, as suggested by peculiar correlations in the geological record. Similar events may have occurred several times during the earlier history of Earth. Accretion of mini planets by largest planets and in particular by the Sun may also have occurred many more times over the last four billion years. Possibly producing additional temperature variations on planets and Earth.

We describe two self-replicating mechanisms of energy accumulation in the seismic focus, which modify the Gutenberg-Richter law in the region of the big earthquakes. The first mechanism acts for magnitudes smaller than a narrow region of large critical magnitudes; it slows down the energy accumulation and may produce precursors. The second mechanism acts above that region, and accelerates the energy accumulation; the precursors may be absent. Both mechanisms reduce the Gutenberg-Richter excedence distribution. On the left of the critical region the Gutenberg-Richter magnitude probability density is unchanged, while on the right the probability density is reduced. The procedure described in this paper introduces a critical-magnitude region (range) as an additional fitting parameter. The results may bear relevance upon the recent concepts of "self-arresting" and "dragon-king" earthquakes. The two self-replicating mechanisms may introduce a magnitude gap between the two types of big earthquakes, and two branches in the excedence law, in the vicinity of the critical region.

Quantum computing promises transformative advances across science and industry, yet the physical hardware that enables these computations remains invisible to the public: quantum processors operate inside sealed dilution refrigerators at temperatures near absolute zero, making direct observation impossible. This "imagination gap" between quantum computing's growing societal impact and the public's ability to visualize it represents a significant barrier to quantum literacy and workforce development. We present Quantum Cinema, an open-source, browser-based interactive application that closes this gap by transforming invisible quantum hardware into explorable, cinematic experiences using generative world models. Quantum Cinema guides users through a four-act narrative – from the foundational Nobel Prize-winning science of quantum entanglement, through curated video introductions to three major quantum computing architectures (trapped-ion, neutral-atom, and superconducting systems), into immersive three-dimensional generative worlds that make invisible quantum phenomena observable, and finally to interactive radar-chart comparisons grounded in real quantum device specifications. All three-dimensional environments are generated using WorldLabs' generative world model platform and are scientifically grounded in curated metrics from Amazon Web Services (AWS) Braket quantum hardware. Quantum Cinema requires no installation, no specialized hardware, and no quantum computing background. It is designed to serve two distinct communities: scholars and developers seeking to replicate or extend the platform, and educators, researchers, and science communicators seeking an intuitive tool for explaining quantum hardware to diverse audiences. This paper describes the system architecture, the generative world model pipeline, use cases for both communities, and directions for future work.

Highly accurate stability boundary values for the ADER-DG method are obtained for arbitrary degrees $N$ of basis polynomials. In the linear case, stability is violated precisely when one of the matrix eigenvalues reaches $\lambda = -1$, regardless of the phase $\theta$. A rigorous mathematical framework for the stability is developed. The stability condition is significantly simplified, reducing it to the problem of calculating the roots of polynomials in the Courant number $\mathrm{CFL}$. The maximum of the Courant numbers $\mathrm{CFL}_{\rm max}(N)$ are calculated. These results are new and very convenient for practical use. A comparison of the obtained results with existing results reveals differences that may be significant for the selection of calculation parameters, especially for high degrees $N$. It is shown that widely used existing estimates $\mathrm{CFL}_{\rm max}(N) \propto 1/(2N+1)$ are overestimated. An interesting qualitative asymptotic $\mathrm{CFL}_{\rm max}(N) \propto 1/(N+1)^{2}$ is obtained. A rigorous direct proof of the approximation is presented. Approximation orders $p = N+1$ for arbitrary degrees $N$ are rigorously derived. A set of numerical experiments is carried out to apply the ADER-DG method to solving both a linear advection equation and an Euler system of equations. The results obtained in these calculations confirm the theoretical results well. In particular, an excess of the Courant number over the $\mathrm{CFL}_{\rm max}(N)$ by even 1% in the linear case immediately leads to significant instability of the numerical solution. The obtained estimates of the boundary Courant number in the nonlinear case are somewhat underestimated – by no more than 5%, which is due to the diffusivity and stability of the approximate Riemann solver. Empirical convergence orders are obtained, which are in good agreement with the theoretical results.

Hyperbolic media enable ultra-strong light-matter interactions through their extreme field localization and small mode volumes, but low-loss realizations are fundamentally limited to the mid-infrared, owing to the long lifetimes of optical phonons in high-quality crystals. Here we show that bright emitters operating at visible or near-infrared frequencies can be used to generate radiation in this regime by inducing mid-infrared population dynamics, thereby creating a source in the hyperbolic frequency band without a corresponding dipole transition. We demonstrate that even a source with vanishing dipole and higher multipole moments - strictly non-radiating in any isotropic medium - becomes radiatively active in a hyperbolic environment. This enables visible and near-infrared control of light-matter interactions in polaritonic hyperbolic materials, establishing a new low-loss solid-state quantum optics platform.

It has been known for decades that laser fusion can be, and often is plagued by the production of energetic electrons.produced either by a instability or by the production of energetic electrons, produced either by an instability or by the energetic tail of a Maxwellian distribution. Despite more than 25 years of a variety of efforts, there is still no generally accepted way to address this issue. This work hopes to advance the progress by developing a Fokker Planck model which is simple enough to be used at every time step of a rad-hydro simulation, and accurate enough to be useful. It makes several approximations, the main one being that the percentage of these energetic electrons is small. Recent experiments confirm this so far that this is the case for plasmas subject to a laser plasma instability. Hence energetic electons interact with the background plasma, but not with each other. This work makes no attempt to solve for the entire electron distribution function. It makes a variety of tohter approximations to solve the resulting Fokker Planck equation. This rather elngthy report both summarizes the author's work with the NRL group, and presents new advances since the termination of the NRL laser fusion project. An important tentative conclusion is that energetic electrons may not be such a big problem for laser fusion.

Dissipative Raman solitons in passive Kerr resonators have emerged as a promising route to broadband coherent frequency comb generation. Yet, their centre frequency has so far been mostly fixed near the Raman gain peak (13~THz downshifted from the pump centre frequency in silica-based fibres), constraining spectral coverage and compatibility with standard optical amplifiers. This limitation arises because the frequency shift of Raman solitons that fulfills phase-matching and group-velocity-matching conditions has to fall within the Raman gain band, leaving little room for spectral tuning when using a single conventional optical fibre. Here, we demonstrate that dispersion management of the fibre Fabry-Pérot resonator which allows us to directly shift the soliton centre frequency. By combining two fibres with complementary dispersion profiles, we tailor the resonator's average dispersion to satisfy the phase-matching conditions for soliton formation at a target frequency downshifted by 7.8~THz from a pulsed pump, which is well outside the conventional 13~THz Raman gain band. This allows us to optically amplify the dissipative Raman soliton with a commercial L-band erbium-doped fibre amplifier, and fully characterise its temporal profile via the frequency-resolved optical gating technique.

Modern particles physics experiments have demonstrated an increasing need for fast, high-fidelity detector simulation as detector components have improved and subsequent computational requirements approach the limits of available resources. Recently, deep generative models have emerged as a promising alternative to traditional Monte-Carlo methods, with recent works drawing inspiration from large language models (LLMs) and self-supervised next-token prediction methods. In this work, we present an application of a GPT-style autoregressive transformer as a fast surrogate model for the calorimeter inside the CLAS12 experiment at the Thomas Jefferson National Accelerator Facility. The model is conditioned on incident momentum and generates realistic detector hits autoregressively across all nine calorimeter layers as sequences of strip, ADC, and TDC tokens. We demonstrate that the model faithfully reproduces hit multiplicity, spatial distributions, energy deposits, and the energy-momentum response of the electromagnetic calorimeter. The generator achieves inference rates exceeding 700 events per second on a single GPU, providing a substantial speedup over traditional Geant4-based simulations while maintaining physics fidelity essential for high-luminosity experimental programs.

Cathode lithiation occupies a chemical regime of tightly localized orbitals, narrow bandwidths, and strong electron-lattice coupling. The defining electrochemical observables (open-circuit voltage and differential capacity) are open-system, reservoir-equilibration quantities that closed-Hamiltonian quantum simulation cannot produce, set by exchange with electron, Li$^+$, and phonon baths. We present a fault-tolerant quantum algorithm that recovers them through a unitary chain-mapped Caldeira-Leggett embedding, rendering the baths Trotterizable. The resulting fourth-order Trotter step has a T-gate count polynomial in system size, validating its open-system dynamics against hierarchical equations of motion (HEOM) at strong coupling and the Lindblad limit at weak coupling. For single-carrier olivine LiFePO$_4$, a single voltage anchor on an otherwise DFT-fixed Hamiltonian places the differential-capacity peak within the $\pm5$ mV reproducibility of the experimental plateau. For multi-carrier spinel LiMn$_2$O$_4$, whose $1{:}1$ Mn$^{3+}$/Mn$^{4+}$ filling makes the inter-site Coulomb repulsion dynamically active, the same kernel yields a two-plateau voltage curve with a $125$ mV split, within $17\%$ of the observed $150$ mV. We deliver an end-to-end fault-tolerant resource estimate for such a multi-carrier, three-reservoir observable: $368$ logical qubits and $\sim3\times10^5$ T-gates per step, or $\sim1.7\times10^{12}$ T-gates for a full voltage curve (parallelizable over $\sim10^3$ trajectories), leaving the production-scale dynamical run as a milestone for future hardware. The same kernel reproduces macroscopic quantum coherence, two-band superconductivity, and the Mikheyev-Smirnov-Wolfenstein resonance without modification, placing dynamical battery chemistry and similar Hamiltonians within scope for fault-tolerant quantum simulation.

Interpreting machine-learning models has attracted increasing attention, particularly in the physical sciences, where one often seeks to understand the underlying mechanisms rather than merely make predictions. Multiple linear regression is often regarded as an interpretable alternative to more complex models, such as deep neural networks, because its predictions are expressed as explicit weighted sums of input features. However, when input features are strongly correlated, namely in the presence of multicollinearity, the learned weights can exhibit large dataset-to-dataset fluctuations and oscillatory behavior across physically similar features, making their interpretation difficult or even impossible. Although the instability of the weights under multicollinearity is well known in statistics, its consequences for physical interpretation, in particular its connection to oscillatory weights across physically similar features, have not been systematically clarified. Here, we theoretically discuss the mechanism behind this loss of interpretability by analyzing the eigenmodes of the feature correlation matrix. We show that small-eigenvalue modes associated with multicollinearity amplify fluctuations in the weights and generate oscillatory patterns that do not necessarily reflect meaningful contributions. We test this theoretical picture numerically on physics datasets and show that Ridge regularization suppresses these unstable modes, although the resulting weights must still be interpreted with caution. We further confirm the generality of our findings beyond physics by analyzing a diverse collection of publicly available datasets. Our results clarify why, in the presence of multicollinearity, physical interpretation can remain difficult even for linear regression models.

Purpose: Recent advances in metasurface photonics and manufacturing have enabled a nanophotonic surface coating to be applied to conventional scintillators, which has been shown to significantly improve light yield. However, the dosimetric properties of such coatings has not been established. We performed the first dosimetric characterization of a nanophotonic scintillator and explored clinical application to real-time in-vivo total body irradiation (TBI) dosimetry. Methods: A 4.5x1.5 cm cerium-doped yttrium aluminum garnet (YAG:Ce) scintillator, half patterned with the nanophotonic structure, half left unpatterned, enabled direct comparison between conventional and nanophotonic surfaces. The scintillator was placed in a 3D-printed light-tight box with an off-axis CMOS camera and irradiated with a clinical linear accelerator. Absolute dosimetry was done with dose-calibrated radiochromic film. For TBI, the scintillator was positioned on an anthropomorphic phantom in a TBI booth, with signal measured by both CMOS and consumer-grade phone cameras under different room lighting conditions. Results: The nanophotonic scintillator showed a 4.1x increase in signal and a 3.7x increase in contrast-to-noise ratio versus the conventional scintillator. Both scintillators exhibited dose-rate independence and linear dose response, with modest energy dependence. For TBI, the nanophotonic scintillator produced a clearly detectable signal with both CMOS and phone cameras, whereas the conventional scintillator signal was undetectable. Conclusions: Nanophotonic structures significantly enhance light output of conventional scintillators without impacting their dosimetric properties. Nanophotonic scintillators may enable real-time in-vivo TBI dosimetry. Future work should investigate this technology for improved dosimetry equipment and X-ray imaging detectors.

Super-heavy atoms ($Z > 100$) are usually studied in the context of the so-called “Quantum Electrodynamics of Strong Fields”. In this theory the problem of the singularity in the electron energy whenever $Z > 137$ is overcome. This is done by considering the finite size of the nucleus and leads to interesting phenomena, such as the spontaneous production of positrons. Here, we show that taking into account the contribution from the Anomalous Magnetic Dipole Moment of the electron (by means of an effective theory), within a point-nucleus model, is a sufficient condition to obtain regular wave functions and physically acceptable energy values for $Z > 137$.

We present a quantum-enhanced Markov chain Monte Carlo (QE-MCMC) method to sample turbulent acceleration vectors from a joint target distribution that depends on all three components and height to model the transport and dispersion of massless Lagrangian tracer particles in two turbulent shear flows. A homogeneous shear flow, characterized by a uniform shear rate S, is considered as the starting point. Secondly, a turbulent boundary layer, which forms in both halves of a plane turbulent channel flow at friction Reynolds number Re_tau = 1000, is considered, where the mean shear rate S(y) varies with distance from the wall y. In this hybrid quantum-classical method, the proposal distribution Q for the first of two Metropolis-Hastings sampling substeps is constructed by a parametric quantum circuit. The algorithm generates synthetic tracer particle tracks. The resulting scaling laws for tracer-particle pair dispersion, a central quantity to probe turbulent mixing from a Lagrangian perspective, agree with a stochastic transport model consisting of coupled Langevin equations and with the classical MCMC counterpart. Differently from the classical sampling method, QE-MCMC uses a tempered target distribution. Due to the height dependence of the tracer dynamics in turbulent channel flow, an effective height-weighted spectral gap between the first and second eigenvalue of the Markov-chain transition matrix is introduced. The latter is found to significantly exceed the one of classical MCMC when sampling from a multivariate distribution with cross-correlations at the highest qubit numbers and thus resolutions. Consequently, our results support the applicability of this one-shot algorithm as a generative Lagrangian quantum-computing module, possibly embedded in a complex fluid-flow problem. Our module is found to work reliably for a relatively small number of qubits per spatial dimension of Nq <= 6.

There is a need to develop quantitative, high-resolution hydrogen gas (H2) permeation techniques to provide a better understanding of hydrogen-material interactions. This study aims to develop and validate a high-sensitivity H2 permeation system, which is then leveraged to systematically quantify the influence of surface condition and key testing variables (surface oxides, residual gas impurities, pressure, and temperature) on hydrogen permeation. A gas permeation system capable of operating at pressures up to 50 bar and temperatures up to 250 C was developed, incorporating high-sensitivity mass spectrometric detection and controlled surface preparation protocols. Permeation transients were analysed in a model material (annealed pure Fe) to determine hydrogen diffusivity and permeability under systematically varied surface states, oxygen contents, pressures and temperatures. Surface oxides are shown to play a dominant role in controlling hydrogen permeation at room temperature. The presence of oxide layers can severely hinder or completely suppress hydrogen uptake, with measurable permeation requiring oxide removal via pickling and Pd coating on both surfaces, or activation through hydrogen-assisted reduction at elevated temperature. Residual oxygen present prior to hydrogen exposure further reduces permeability by modifying surface boundary conditions, indicating strongly surface-controlled kinetics. Under optimised surface conditions, hydrogen transport follows bulk diffusion-controlled behaviour, with steady-state flux obeying Sieverts' law at 25 C (1-5 bar) and diffusivity and permeability exhibiting Arrhenius behaviour between 25 and 150 C at 5 bar, indicating bulk diffusion-controlled transport. The developed system resolves hydrogen fluxes as low as 1.98x10-9 mol(m2 s) and provides a robust platform for investigating surface, mechanical and environmental effects on H2 permeation.

In this work, we investigate the impact of fusion-born alpha particles on core turbulence and transport in the ARC tokamak fusion power plant using linear and nonlinear gyrokinetic CGYRO simulations. A significant reduction in ion-scale turbulent heat and particle fluxes is observed in the inner core (r/a $\leq$ 0.5), which is associated with multiscale interactions between fast ion-destabilized modes, zonal flows, and the background turbulence. A nonlinear upshift in the ITG critical gradient is observed in the simulations with fast alphas compared to those with artificially thermalized alphas. The turbulence reduction is found to scale beneficially with alpha particle density and plasma $\beta_e$, and the radial extent of the turbulence suppression is limited to the volume containing a significant density of fast particles. The suitability of local gyrokinetics and potential impacts of fast ion effects on fusion performance are discussed.

The properties of candidate particles for solar radiation management (SRM) through stratospheric aerosol injection (SAI) should comply with safety, controllability, and functionality requirements. Following the proposal in arXiv:2604.02283 of safety and controllability requirements, we define here a set of functionality requirements on the particles' properties – optical properties, stratospheric residence time, scalable manufacturing compatibility, and aerial dispersion compatibility – that, if met, ensure the feasibility of practical implementation, providing reflection of $\sim1$% of the solar flux. We then present design principles and fabrication methods for sub-micron solid particles that may enable satisfying the combined requirements. These requirements do not identify a unique solution, but favor sub-micron particles with tightly controlled size distributions and stable properties over their stratospheric lifetime, and motivate a composite design where the bulk core composition is selected primarily for optimal radiative properties and the outer shell surface is engineered to control atmospheric chemistry and aging, and enhance aerial dispersion compatibility. We present two specific particle designs that are viable for meeting the coupled requirements: amorphous silica spheres and calcium-carbonate cores surrounded by spherical silica shells (both with appropriate surface treatment). The former is at an advanced stage of experimental verification (described in detail in a companion paper) of meeting all requirements, provides a practical platform for surface engineering, and will enable reaching a substantial fraction of $\sim\!1$% solar flux reflection. The latter is under development and will enable reaching $>1$% reflection.

We demonstrate a practical and sensitive low-field approach to magnetic resonance imaging (MRI) of $\mu$L-scale samples using an optically pumped magnetometer (OPM). Using a simple setup where a commercial OPM is placed directly adjacent to a sample, without intermediary signal-pickup coils, we perform one- and two-dimensional imaging with a >1 cm field of view and sub-mm Fourier-limited resolution at 10 $\mu$T, near Earth's field. This enables (i) high-throughput, low-field MRI of fluidic and tissue samples, and (ii) a quantitative benchmark of the sensitive volume surrounding the OPM.

Dynamical phase transitions in open quantum systems govern how non-equilibrium states relax toward a stationary state. We study these transitions experimentally using a discrete-time photonic quantum walk on a three-node graph. A tunable synthetic gauge flux and calibrated dephasing allow us to control time-reversal symmetry and the detailed balance properties of the effective Markovian dynamics. With detailed balance, we observe a first-order dynamical phase transition marked by a crossing of real Liouvillian eigenvalues. When detailed balance is broken, we observe a second-order dynamical phase transition at an exceptional point where eigenvalues and eigenvectors coalesce. By progressively reducing the dephasing strength, we track the crossover toward the quantum-coherent regime and determine that the transitions persist down to a finite threshold. Our results link Liouvillian spectral topology to relaxation criticality and demonstrate a controllable platform for engineered dissipative dynamics.

We develop a localised wavelet formulation of multifractal random walk unwrapping based on the local multiplicative modulation freezing. The framework is motivated by the observation that finite-support wavelet localisation may induce approximate local factorisation of multiplicatively modulated stochastic fields, allowing the modulation component to become effectively frozen within sufficiently localised probing domains. Within this regime, logarithmic wavelet amplitudes admit an approximate additive decomposition linking local wavelet statistics directly to the underlying modulation field. This viewpoint reformulates covariance-based MRW unwrapping as a localised multiscale operator problem in which wavelet coefficients act as finite-support probes of multiplicative organisation. The validity of the approximation depends explicitly on support geometry, scale-dependent overlap, and residual multiscale mixing generated by internal modulation variability. We show that these effects naturally produce finite-scale deviations from ideal logarithmic covariance scaling and lead to structured covariance distortions whose form depends on the interaction between the modulation field and the geometry of the wavelet representation. In the resulting framework, localisation itself becomes the operational mechanism enabling multiscale probing of local stochastic organisation. Numerical investigations using orthonormal wavelet decompositions support the proposed interpretation and demonstrate the emergence of scale-dependent freezing regimes, residual covariance mixing, and finite-support breakdown effects consistent with the theory. The proposed framework suggests a broader connection between wavelet localisation, local regularity organisation, and finite-support multiscale stochastic operators. Wavelet localisation becomes an operational mechanism for probing localised multiscale structure.

Biofouling – the occupation of microplastic (MP) surfaces by marine microbes – alters particles' buoyancy and transport, yet its effect on the global distribution of MPs has not been well quantified. We present the first three-dimensional global Eulerian model to fully couple MP transport with biofouling, by augmenting the concentration field with an extra dimension representing the biomass attachment density on MP surfaces. This approach embeds time-dependent particle properties directly into the Eulerian concentration field, overcoming a fundamental challenge of tracking property evolution in grid-based models. Idealized simulations show that biofouling significantly reshapes the vertical distribution of MPs when two conditions are met: the particles must be sufficiently buoyant when they are clean to remain near the sea surface, and the local plankton growth rate must exceed the decay rate. In three-dimensional global simulations, biofouling substantially alters the distribution of large MPs ($\gtrsim 10$ $\mu$m): biofouled particles are transported below the mixed layer to 500 m depth, and the subtropical surface garbage patches become more dispersed with reduced peak concentrations. This dispersion is due to a subsurface transport route, where biofouled particles sink into layers with reversed current and are carried outward from the gyre centers before regaining buoyancy. Small particles ($\lesssim 1$ $\mu$m) remain unaffected as they stay effectively neutrally buoyant even when biofouled. A comparison with a global trawler dataset shows that incorporating biofouling reduces the fraction of outlying model-observation data points from 25% to 13%, demonstrating a meaningful improvement in model skill.

Specific heat treatments applied to superconducting radiofrequency (SRF) cavities, such as nitrogen infusion or Mid T baking, aim to improve the quality factor (Q0) at medium accelerating fields (10 to 20 MV/m). These treatments reduce the BCS surface resistance by tuning the mean free path of niobium over a few hundred nanometers, either by diffusing oxygen from the native oxide layer or by diffusing nitrogen after the dissolution of the oxide layer. However, these treatments preclude the usual chemical polishing, as it would reverse the beneficial effects of the heat treatments, making the cavities highly sensitive to surface contamination. In particular, the formation of niobium carbides, which can mask the expected benefits, strongly depends on the annealing conditions, surface preparation, and the materials history. Several hypotheses are considered regard-ing the origin of carbon: vacuum contamination, surface pollution, or internal migration from the niobium itself, potentially enriched with carbon during previous chemi-cal treatments (BCP, EP). This work aims to identify the primary source of carbon responsible for niobium carbide growth, using techniques such as X Ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), and secondary ion mass spectrometry (SIMS). The study will also help pinpoint the key influencing parameters, thereby contributing to a better understanding of and potential mitigation strategies for their impact on SRF cavity performance.

Enantiomeric excess detection in a chiral molecular mixture is paramount because very often opposite enantiomers exhibit profound functional dissimilarities that play decisive roles in biochemical applications. Existing chiral sensing methods mostly rely on large operational sample volumes, hindering compatibility with integrated sensing schemes. Here, we propose a novel chiroptical sensing technique based on the inverse Faraday effect in a photonic micro-capillary filled with nl-volume chiral drug solution. We theoretically demonstrate that, upon excitation by intense laser light, an isotropic assembly of chiral drugs produces a static magnetisation, with amplitude and direction depending on the enantiomeric excess. In turn, by measuring the chirally-sensitive static magnetic field in the vicinity of the micro-tube one can retrieve the enantiomeric excess of the chiral drug solution. Our theoretical predictions unlock new opportunities for the development of innovative nanophotonic devices suitable for efficient chiroptical sensing with nl-volume sensitivity.

This study investigates the capability of linear modeling to characterize the transitional dynamics in an axisymmetric stenosis and attempts a low-order representation of the turbulent stresses. The transition to turbulence in stenotic flows generates wall shear stress fluctuations that strongly influence the progression of cardiovascular diseases and the risk of plaque rupture. A description of the linear mechanisms driving the forced dynamics at Reynolds number beyond transition is currently missing. Linear modeling of coherent structures is leveraged to identify the flow amplification mechanisms using the mean field from a LES at Re=4000. Global linear stability analysis reveals an unstable and sinuous stationary eigenmode that is known to destabilize the flow at lower Reynolds numbers through a weak Coanda-type wall attachment. At intermediate frequencies, resolvent analysis identifies a second amplification region within the shear-layer where the most amplified fluctuations are axisymmetric, in contrast to findings from studies at lower Reynolds numbers. The linear model is validated against SPOD. At intermediate frequencies, the optimal resolvent response mode demonstrates both high gain separation and strong alignment with the leading SPOD mode. The low-rank nature of the resolvent operator is leveraged to reconstruct the turbulent kinetic energy (TKE) and turbulent wall shear stress (tWSS) from the optimal response mode. In the immediate post-stenotic zone, axisymmetric fluctuations dominate the tWSS and exhibit low-rank dynamics. Our findings highlight that linear mechanisms effectively capture the complex post-stenotic dynamics. The successful reconstruction of turbulent quantities from mean flow data alone opens new predictive possibilities of key turbulent quantities.

Optical backflow in paraxial Gaussian beams is investigated within the Maxwell framework. Scalar potential representations are employed to identify conditions under which the longitudinal Poynting component becomes negative, showing that backflow is enabled by local suppression of the leading-order transverse field and the dominance of higher-order vectorial contributions. The spatial topology of backflow regions is shown to be governed by polarization through the number of independent local constraints on the transverse field. When the local polarization phase is free, as in the generic case of circular polarization, the leading-order field vanishes only at isolated points, giving rise to point-like backflow regions (extended curves may arise if an additional global phase constraint is imposed). In contrast, when the polarization phase is locally fixed, as for linear, radial, or azimuthal polarization, the suppression condition reduces to a single real constraint, resulting in extended backflow curves. Analytical Gaussian-polynomial solutions explicitly illustrate these effects. These results clarify the role of vectorial interference, establish a polarization-controlled backflow geometry, and provide a foundation for further studies of optical backflow in structured and nonparaxial beam configurations, as well as potential applications in optical manipulation and structured light design.

We explore the movement of a thin, circular quantum vortex filament within an infinite cylindrical pipe. The fluid surrounding the vortex ring moves through the pipe at a non-zero velocity denoted by $v$. Our study examines the energy spectrum $E = E(p)$, where $p$ represents the total momentum of a vortex ring. We have demonstrated that the function $E(p)$ significantly depends on the velocity $v$. The discovered spectrum $E(p)$ reveals the existence of states with both negative and extremely large effective masses. We also explored the hypothesis regarding the existence of coupled vortex pairs possessing finite summary effective masses. Every pair consists of vortices that possess both positive and negative masses, with the magnitude of these masses being unrestricted. In our model, the criterion for the appearance of these states is based on comparing two numbers. The first is seen as a quantum counterpart to the Reynolds number, while the second represents its critical value for a flow with a single vortex. We also explore how this studied effect might contribute to the emergence of quantum turbulence. This study discusses a method for determining the critical Reynolds number in quantum turbulence, using the proposed model as a framework. Here, we use a new quantization technique for classical closed vortex filaments developed by the author earlier.

A theoretical and numerical study of optical forces acting on a Rayleigh particle in a paraxial Gaussian light beam exhibiting regions of optical backflow is presented. Within the dipole approximation, the total optical force is decomposed into gradient, scattering, and spin-curl terms. Vector fields satisfying the exact paraxial Maxwell equations are employed to describe the structured light configuration responsible for two distinct mechanisms leading to backward optical forces. The first originates from the local reversal of the Poynting vector, which induces a negative longitudinal momentum flux, while the second arises from the spin-dependent component of the force associated with the spatial variation of the optical spin density. Analytical expressions and numerical simulations confirm that both mechanisms can produce backward motion of a Rayleigh particle under appropriate beam conditions. These results provide a unified physical picture of backward-directed optical forces in Gaussian beams and open possibilities for particle manipulation in structured light fields.

The advent of large pretrained foundation models for computer vision has significantly improved the efficiency of visual data interpretation. The Segment Anything Model (SAM), in particular, offers powerful zero shot segmentation capabilities through prompt based interaction, thus making it a promising tool for seismic interpretation. However, most existing applications of SAM rely on fine tuning for specific geological targets, which requires extensive labeled data, incurs high computational cost, and often compromises the model's generalization capability. In this study, we introduce a principled framework for zero shot adaptation of foundation models to seismic data. The framework is built on two key components: (1) aligning seismic attributes and visualization choices (e.g., colormaps) with the geological target of interest, and (2) employing a hybrid prompting strategy that combines sparse user defined point prompts with dense mask prompts derived from SAM's internal feature activations. We systematically evaluate this framework across multiple geological targets, datasets, prompt configurations, and seismic attribute representations. Our results demonstrate that geologic target aware selection of seismic attributes and colormaps, combined with hybrid prompting, enhances the separability of geological features and improves boundary delineation and segmentation accuracy relative to point based prompting alone. Our findings show that, when these components are jointly applied, SAM can achieve competitive segmentation performance in a fully zero shot setting, thereby eliminating the need to retrain SAM for each geologic feature. This work establishes a practical and scalable pathway to leverage foundation models in seismic interpretation, reducing reliance on labeled data while preserving model generality.

The Zagros Orogenic Belt, formed by the Arabian-Eurasia collision, is a highly active collision zone hosting a large portion of Iran's seismicity. In this study, the IRSC catalog (2006-2024) was used to construct a homogeneous seismic dataset for the Zagros Belt. We analyzed the spatial and depth distribution of seismicity together with key parameters: b-value, fractal dimension (Dc-value), and differential stress (sigma1 - sigma3) to evaluate stress variations, fault clustering, and seismic hazard. The overall b-value of 0.81 +/- 0.01 indicates an elevated stress state, with persistently low b-value anomalies (0.4-0.7) systematically aligned along major fault zones (Mountain Front Fault, High Zagros Fault, and Main Zagros Reverse Fault). Cross-sectional analyses show that these low b-values (<0.6) are concentrated within the upper ~10 km of the crust, pointing to the shallow brittle layer as the primary zone of stress concentration. The correlation fractal dimension (Dc) ranges from 1.0 to 2.05, with high values (>=1.5) spatially coinciding with low b-value zones, reflecting intense deformation partitioning and structural complexity. This spatial complexity decreases with depth, where lower Dc-values show seismicity localizing onto simpler, discrete planes. Differential stress varies between 100 and 520 MPa (predominantly >=520 MPa) and is strongly anti-correlated with b-value, confirming that low b-values trace critically loaded fault segments. The spatial and depth convergence of these independent parameters confirms that seismic hazard is localized along shallow, highly stressed, and structurally complex fault segments capable of generating future moderate-to-large events. These findings highlight the need for targeted monitoring and hazard mitigation across the region.