Papers

We predict a class of bound states in the continuum (BICs) in non-subwavelength periodic metasurfaces – Rayleigh BICs – that emerge precisely at Rayleigh anomalies, where diffraction channels open. In contrast to conventional symmetry-protected and accidental BICs, which are typically engineered in the subwavelength regime with only a few radiation channels, Rayleigh BICs remain nonradiating far beyond this limit, even when multiple diffraction channels are open. Their formation originates from the interplay between collective lattice resonances, Rayleigh anomalies, and anapole states of the constituent metaatoms. We show that Rayleigh BICs are characterized by an unusual cubic scaling of the quality factor in reciprocal space, ($Q \propto 1/k^3$), an asymptotic behavior that is not characteristic of either symmetry-protected or accidental BICs. Our results establish a constructive route for engineering nonradiating states in metasurfaces beyond the subwavelength regime.

Electromagnetic waves are intrinsically vectorial and require description via polarization, unlike scalar fields such as acoustic pressure or electronic wavefunctions. In three dimensions, the transversality constraint further prevents any globally smooth transverse-polarization frame at the $\Gamma$ point, which would apparently rule out a simple scalar band structure for three-dimensional (3D) photonic crystals. We show here that site-adapted $p$-orbitals can realize scalar-wave dispersion: the induced band representation is isomorphic to the scalar elementary band representation up to a one-dimensional character twist, so the symmetry-enforced degeneracies and compatibility relations are the same. We demonstrate this mechanism experimentally in 3D photonic meta-crystals, where the local $p$-orbital axes adapt from site to site according to symmetry. In contrast to a fixed-polarization reduction (e.g., in 2D), our construction preserves site-polarization textures while simultaneously supporting a scalar network with one amplitude per site. Thus, it offers a pathway from vectorial photonic degrees of freedom to scalar band engineering, keeping polarization as an active design knob.

Molecular passivation has become central to reducing photovoltage losses in metal-halide perovskite solar cells, but its electronic action is still often inferred from device-level metrics rather than directly resolved at the nanoscale. Here, we use amplitude-modulated Kelvin probe force microscopy to examine how [3-(2-aminoethylamino)propyl]trimethoxysilane (AEAPTMS) modifies the surface potential and photovoltage dynamics of mixed-cation, mixed-halide perovskite thin films. AEAPTMS homogenises the dark contact potential difference (CPD), narrowing its distribution from ~45.7 to ~14.6 mV without obvious morphological changes. Under illumination, passivated films show a larger steady-state surface photovoltage (SPV) and faster stabilisation, with the SPV increasing from ~345 to ~417 mV and the stabilisation time constant decreasing from ~840 to ~470 s. Wavelength-dependent SPV further indicates reduced sub-bandgap electronic disorder. By separating grain-boundary and grain-interior contributions, we show that AEAPTMS suppresses grain-boundary potential barriers, linking amino-silane passivation to a more homogeneous and stable carrier landscape.

A liquid drop falling into a deep pool can create a vortex ring at the right impact conditions. Such drop-formed vortex rings are of importance in nature and technology and the dynamics of rings created by single and synchronised double drop impacts have been extensively studied. In practice, two neighbouring drops rarely impact a liquid surface exactly at the same time, yet the interaction of two unsynchronised vortex rings have not been studied. Here, we have performed experiments with two water drops impacting a water pool at varying time differences $\Delta t$. By using particle image velocimetry, we have quantified the time-evolution of the resulting vortex rings. We find four distinct categories of vortex ring evolution depending on $\Delta t$. At $\Delta t<0.5$ ms, fully symmetric merging of the vortex rings occur. An unsynchronisation larger than this drastically influences the collision and merging, which either becomes asymmetric and incomplete ($0.5 < \Delta t<7$ ms) or does not happen at all ($\Delta t \geq 7$ ms). At $7 \leq \Delta t<80$ ms, the creation of the second vortex ring is impaired, whereas at $\Delta t\geq 80$ ms, the first impact no longer affects the formation of the second ring and eventually the two rings evolve without influencing each other. We show that these different regimes can be explained by the capillary waves created by the first droplet. Our results demonstrate the importance of the time difference between drop impacts in the creation and subsequent interaction of two adjacent drop-formed vortex rings, which is important for achieving uniform and controlled mixing in high-throughput applications.

Turbulence plays a central role in shaping the structure and dynamics of the interstellar medium (ISM), governing the star formation rate (SFR) and the initial mass function (IMF). A key consequence of turbulence is the generation of density fluctuations, which regulate the amount of dense gas available for star formation. Accurate measurements of the three-dimensional (3D) turbulent density dispersion are therefore essential for understanding molecular-cloud structure and star formation. However, observations typically provide only two-dimensional (2D) column densities and are often affected by measurement/detector noise. The Brunt method estimates the 3D density dispersion from 2D column-density maps, but it does not account for finite signal-to-noise ratio (SNR). Here, we extend the method to recover the 3D turbulent density dispersion from noise-contaminated observations. Using numerical simulations spanning a range of density perturbation amplitudes and noise types, we identify a characteristic noise wavenumber, k_noise, corresponding to the intersection of the signal and noise spectra. Restricting the Brunt reconstruction to wavenumbers below k_noise yields a denoised density-dispersion estimate that closely reproduces the noise-free result. We provide a practical prescription to determine k_noise directly from the measurement SNR and image resolution. Alternatively, if the noise spectrum is known, it can be subtracted directly from the observed spectrum, eliminating the need to estimate k_noise. The proposed correction recovers the noise-free density dispersion with errors of <~5% for SNR>=3 and <~15% for SNR>=1, enabling substantially more reliable estimates of turbulent density fluctuations from noisy column-density data.

In this Letter, we show how a suspension of light solid spheres settling through a polymer solution results in a chaotic and highly-intermittent state. By leveraging particle-resolved direct numerical simulations, we investigate the effect of increasing polymer relaxation time and Deborah number $De$ on viscoelastic sedimentation at a low density ratio $\rho_s/\rho_f=5$ and a low Galilei number $Ga=3.16$. Even at moderate $De$, the spheres form gravity-aligned clusters and settle faster, while the polymer stresses energize the large scales of motion. The onset of elastic turbulence and intermittency is signaled by a $-4$ spectral scaling in the high-wavenumber range and by nonlinear high-order exponents of the velocity structure functions. These results indicate that viscoelastic effects induce pseudoturbulence in the presence of viscous-dominated sedimentation.

Magnesium ions are essential for RNA structure but difficult to model due to slow binding kinetics and experimental limitations. We present an enhanced-sampling strategy that accelerates Mg$^{2+}$ inner-shell binding by orders of magnitude, enabling quantitative exploration of ion-binding motifs in a large ribozyme. The method combines a barrier-flattening bias with Hamiltonian replica exchange to efficiently sample multiple equivalent binding sites, and builds on an approach that achieved top performance in the CASP16 blind assessment of RNA solvation structure. Using cryo-electron microscopy maps for validation, we introduce a local analysis framework that infers the population of individual binding motifs from their agreement with experimental density, enabling site-by-site validation. We find that insufficient sampling of inner-shell binding leads to significantly poorer agreement with experiment, whereas force fields predicting different inner/outer binding equilibria remain largely indistinguishable at the current experimental resolution. These results highlight the dominant role of sampling in modelling divalent ion binding and provide a general strategy for integrating simulations with experimental data in complex biomolecular systems.

Entanglement between two spatially separate matter particles can be generated via many means and often resides in the internal states of particles. Here, via Rydberg blockade in two spatially separate neutral atoms, we find that the photon recoil in Rydberg excitation can push one atom microns away provided the other atom exerts a state-dependent Rydberg-mediated blockade. When the atoms are recaptured by optical traps, a position-position entangled state between two spatially separate atoms can emerge. This realizes a Bell state of two atoms, where the entanglement exists in the position of each atom and the distance between the two possible locations of each atom can be in the hundred-micron regime.

Computationally efficient models for multimodal traffic flows with inter-modal interactions are foundational for coordinated traffic management. However, such models are lacking in the current literature. This study introduces a multimodal link transmission model (M-LTM) accommodating both continuous road traffic and discrete tramway traffic at the network level. M-LTM builds on a link model that captures the inter-modal interactions through the moving bottleneck theory. We further develop node models describing the flow transfer, tram operations, and mode interactions at tram stops and intersections. Specifically, the tram dwell process and dwell-induced congestion of road traffic are simulated at the stop node, and the intersection node model can reproduce queue spillback and tram priority. Case studies are conducted on two synthetic one-node networks, a synthetic arterial network, and the real network of Dresden to demonstrate the predictive power and the applicability of the proposed model in network traffic analysis and management. The GEH statistics of road traffic are below 4, and the average tram arrival time absolute errors are less than 10 seconds.

Modeling the quantum dynamics of plasmonic excitations – collective oscillations of free electrons interacting with light – remains a significant theoretical challenge, particularly due to the need to accurately describe their quantum nature and the role of non-radiative decay channels. At the same time, a reliable theoretical framework is essential for advancing applications ranging from materials design to the development of new quantum optical platforms for quantum technologies. In this work, we address these challenges by introducing a Hermitian formalism based on the linear vibronic coupling (LVC) model for the description of plasmonic excitations in metallic nanostructures. This is parameterized through first-principles calculations – including but not limited to, the full DFT ground state with tight-binding excited states – and machine learning techniques using a newly implemented automated platform named Python Plasmonic Cavity (PyPC). The effectiveness of this workflow is demonstrated by successfully reproducing the experimental absorption spectra and vibronic broadening of plasmonic silver nanoparticles containing more than a hundred atoms. Additionally, the population dynamics of plasmonic states are investigated, showing that the LVC model accurately predicts ultrafast lifetimes for bright states and effectively captures the dynamics of dark states.

Exotic helium atoms act as unique atomic traps for heavy, negatively charged particles, protecting them from nuclear annihilation and nuclear capture on timescales long enough to enable high-precision laser spectroscopy. Such measurements serve as stringent tests of three-body quantum electrodynamics and offer a direct route to determining fundamental particle masses. Motivated by upcoming spectroscopic efforts targeting pionic ($\pi^{-\,4}\mathrm{He}^+$) and kaonic ($K^{-\,4}\mathrm{He}^+$) helium, we present a rigorous theoretical evaluation of the collisional and density effects governing these systems. Using an ab initio potential energy surface and coupled-channel quantum scattering calculations, we study the collisional stability of the candidate metastable states against inelastic quenching in a cryogenic helium buffer gas. Furthermore, we provide theoretical reference values for the pressure broadening and pressure shift coefficients of the targeted transitions. These results establish an essential benchmark for future experiments, paving the way for refined determinations of the pion and kaon masses.

Zn-metalloproteins play vital roles in numerous metabolic processes, making them high-value targets for structure-based drug design. To advance these efforts, it is useful to unravel the individual components of the intermolecular interaction energies (DE) that stabilize the Znbinding cavity, both in the absence and presence of bound protein ligands. Here, we utilize quantum chemistry (QC) to decompose DE into distinct physical contributions. The relative magnitudes of these components vary significantly depending on the coordination number (four to six) and the chemical nature ('hard' vs. 'soft') of the Zn-coordinating ligands. These high-level QC analyses serve to calibrate and validate polarizable molecular mechanics potentials, effectively extending the accurate description of electronic effects beyond the immediate Zn-binding cavity to enlarged recognition sites and, ultimately, entire protein systems over long molecular dynamics (MD) simulation timescales. Following a concise overview of our QC methodology, we present validation studies on complexes containing up to 300 atoms and discuss the prospects of applying this framework to large-scale simulations of Zn-metalloprotein-ligand complexes. Finally, the structural and energetic role of discrete, highly polarizable water molecules is highlighted.

In electron-only collisionless magnetic reconnection (MR), a regime of growing importance in turbulent space plasmas, electrons develop strongly non-Maxwellian distributions that invalidate conventional fluid closures based on assumptions of near local thermodynamic equilibrium. Using particle-in-cell (PIC) simulations, we identify the physical origin of the electron heat-flux: counter-streaming between electron sub-populations originating from opposite sides of the current sheet, with each sub-population remaining approximately adiabatic. This insight yields a novel fluid closure, which we implement in fluid simulations using two adiabatic electron fluids initialized on opposite sides of the current sheet. The fluid simulations capture the heat-flux, reconnecting current density, thermal pressure, and bulk flows as observed in PIC, within a reduced fluid description that conventional single-electron-fluid models fundamentally cannot reproduce. The closure is most accurate at low $\beta_{\text{Reconn.}}$ and $B_{\text{Guide}}/B_{\text{Reconn.}}$, regimes relevant to Earth's magnetotail, where it establishes counter-streaming as the physical origin of heat-flux in electron-only collisionless MR and enables its computationally efficient fluid modeling.

Tissue surfaces exhibit complex curvature during embryogenesis and oncogenesis. Evidence shows that cells can actively sense curvature to regulate behavior and fate, yet the underlying mechanism remains unclear. Here, we develop a vertex model for arbitrary curved surfaces and uncover spontaneous cell size patterning on ellipsoidal surfaces: cells in high-curvature regions are consistently larger than those in low-curvature regions. This non-uniformity arises from a mechanical competition encoded in Riemannian geometry: positive Gaussian curvature reduces the perimeter-to-area ratio of polygonal cells, relaxing cell-edge tension in high-curvature regions, which is compensated by area expansion to maintain global force balance. This area pattern is robust against variations in model parameters and matches observations in biological systems. The perimeter pattern, in contrast, is governed by competition between the intrinsic geometric tendency and the deformation required by force balance, and undergoes reversal beyond a critical shape index. Together, these findings establish self-organized spatial variations in cell size as a potential physical mechanism for curvature sensing.

Compressible physical fields are widely present in the real physical world, but current artificial intelligence lacks an understanding mechanism for the non-differentiable features in compressible physical fields. Addressing the limitations of existing deep learning architectures in handling global non-differentiable features, we propose the Inverse Low-Dimensional Manifold reconstruction framework (ILDM). This framework couples the Non-differentiable Approximation Function (NAF) for capturing non-differentiable features in compressible flows with the Smooth Fluid Reconstruction (SFR) module tailored for smooth fluid regions. Extensive evaluations across 1D and 2D benchmarks, including Riemann problems and double Mach reflection, demonstrate that ILDM significantly outperforms cPINN and R-adaptive DeepONet. Specifically, ILDM achieves superior localization of non-differentiable interfaces and maintains robust super-resolution performance even with low-resolution inputs, establishing a physically consistent and scalable paradigm for data-driven fluid dynamics.

We report an improved absolute frequency measurement of the $^{176}$Lu$^+\,(^{3}\mathrm{D}_1)$ optical frequency standard, evaluated via a remote link to the NRC-FCs2 caesium fountain primary frequency standard. Operating a single ion clock with 94.2% uptime over 10 days, and using an ambiguity-resolved precise point positioning (PPP-AR) link over the Global Positioning System, we determine an absolute frequency of $353\,638\,794\,073\,800.332(91)\,$Hz at a fractional uncertainty of $2.6 \times 10^{-16}$. This agrees with our previous result, which underpins the Comité international des poids et mesures recommended frequency value, and reduces the uncertainty by a factor of 3.6.

Mobile C-arm cone-beam computed tomography (CBCT) has been widely used for real-time intraoperative 3D imaging. However, current practice often mechanically applies the fan-beam CT criterion of "180{\deg} plus fan angle" in pursuit of "data completeness" in reconstruction. This review argues that, under the single circular trajectory of three-dimensional cone-beam geometry, complete data are mathematically unattainable; moreover, blindly increasing sampling may exacerbate the trade-off among intraoperative image quality (Q), imaging time (T), and radiation dose (D). Against this background, this review reframes the evaluation of intraoperative CBCT around "data sufficiency" rather than "data completeness." This perspective moves beyond the excessive pursuit of absolute mathematical and analytic accuracy, and instead emphasizes task-specific minimum image-quality thresholds required for clinical decision-making. By synthesizing evidence from multiple clinical scenarios, this review suggests that approximation errors can be acceptable when clinical decision-making requirements are satisfied, thereby achieving a Q-T-D balance.

Reynolds-averaged Navier-Stokes (RANS) turbulence models are known to perform poorly in predicting the dynamics of Rayleigh-Taylor mixing when turbulence is not fully developed, particularly during the transition from an initially perturbed interface. In this work, we investigate the use of data-driven strategies to enhance a simple $k$-$\varepsilon$-$b$ model for this transitional regime. The turbulence model is first embedded within a surrogate physics-informed neural network (PINN), enabling the calibration of coefficients that account for parametric errors and the identification of corrective terms representing structural errors associated with missing physical processes. The learned corrections are then re-expressed onto the model state variables and relevant flow indicators, leading to explicit analytical modifications of the closure. The resulting fully interpretable corrected model is assessed against an extensive database of direct numerical simulations (DNS) of Rayleigh-Taylor flows. This framework enables improved predictions of the mixing-layer growth during the transition to turbulence.

Salt-finger plume forests in a finite layer can differ in strength and in the route by which interfacial activity becomes vertically connected. We use direct three-dimensional simulations to test whether such a route is a short-lived realization-specific transient or a persistent route family under an added mean-shear perturbation. The baseline route atlas holds density ratio, diffusivity ratio, Prandtl number, interface thickness, roughness amplitude, domain, and resolution fixed while varying the imposed interfacial roughness spectrum. Low-mode roughness forms a broad connecting endpoint, high-annulus roughness forms a localized route-memory endpoint, and mixed roughness forms a delayed scale-transfer route. A second mixed realization preserves continuous active-width, spectral, and transport measures after \(t=45\), with mean absolute differences of \(3.1\%\) in \(w\)-active width, \(1.6\%\) in salinity-active width, \(2.8\%\) in broad spectral fraction, and \(3.6\%\) in salt flux, while shifting the binary scalar-contact label. We then impose an initial tanh mean shear on the mixed route. The full-resolution shear case reaches \(t=60\) and preserves finite-depth reach: first velocity contact occurs at \(t=57.75\), first salinity contact occurs at \(t=59.5\), and both times match the unsheared mixed reference. The spectral branch is redistributed. At \(t=60\), the broad fraction is \(1.116\) times the mixed value, the intermediate fraction is \(0.530\) times the mixed value, and the short-wave fraction is \(1.278\) times the mixed value. In this finite-depth configuration, route survival means preserved reach and contact timing with a changed spectral pathway.

We present first near-simultaneous observations of large-scale spatial response of the Martian H Lyman-{\alpha} and atomic oxygen dayglow emissions (O(3S) 130.4 nm and O(5S) 135.6 nm) during May 2024 interplanetary coronal mass ejection (ICME). Using coordinated near-simultaneous observations from MAVEN/Imaging Ultraviolet Spectrograph (IUVS) and the EMM/Emirates Mars Ultraviolet Spectrometer (EMUS), we have identified pronounced enhancements in all three emissions relative to quiet-time conditions. Interestingly, coordinated IUVS limb and EMUS disk observations reveal that ICME-driven response extends vertically through the thermosphere and horizontally across broad ranges of latitude, longitude, local-time, and solar zenith angle. Concurrent enhancement of hydrogen and oxygen emissions indicates the simultaneous contribution of proton and electron-driven excitation mechanisms during ICME. These findings reveal a novel planetary-scale response of the Martian dayglow. By highlighting the critical role of energetic-particle precipitation in amplifying this global response, our work carries crucial implications for understanding Martian thermospheric response during intense solar transients.

Efficient terahertz (THz) generation with high field amplitude and pulse energy is studied through the interaction of a single-color long-wavelength infrared (LWIR) laser pulse with gaseous targets. Particle-In-Cell (PIC) simulations are performed to investigate the underlying mechanism and analyze the properties of the emitted THz radiation. The results reveal that THz pulses are generated via photon deceleration of the LWIR laser, driven by enhanced electron density accumulation at the pulse front in the self-modulated wakefield regime. The influence of key parameters, including target density, laser intensity, and propagation length, on nonlinear laser modulation and the resulting THz generation efficiency is analyzed. Important scalings governing the laser-to-THz energy conversion efficiency are identified from PIC simulations and validated through theoretical analysis. The study demonstrates a laser-to-THz energy conversion efficiency of approximately $4\%$, significantly exceeding previously reported values. The field amplitude of the emitted THz pulses is found to be on the order of 100 GV/m, with a pulse energy of approximately 50 mJ for the laser parameters considered in this work. The findings of this study provide valuable insights for the development of next-generation high-energy THz sources.

Magnetohydrodynamical (MHD) simulations of isothermal compressible turbulence report that the density distribution is well described by a lognormal with a variance proportional to the flow's Mach number. The distribution of magnetic field strength also has a lognormal component, but includes long, power-law-like tails. In this work, we use semi-analytical arguments to predict the distributions of density and magnetic field strength in compressible turbulent flows. Specifically, in the Lagrangian description of the continuity and the induction equations, we model the velocity gradients of the turbulent flow as a simple random process, essentially turning these equations into stochastic differential equations. Integrating them leads to a lognormal distribution for the density field and the strength of the magnetic field. The power-law tails in the magnetic field PDF appear when we introduce intermittent shocks due to sampling rare events. Gradually increasing the frequency of these events, essentially going closer to a continuous process, leads to lognormal-like distributions again. The asymmetry is connected to the relative abundance of slow and fast shocks. An overabundance of fast MHD shocks produces a high-value tail, while the contrary produces low-value tails. We propose that the appearance of power-law tails along lognormals in turbulent flows is the signature of the co-existence of continuous, diffusion-like propagation combined with localized, intermittent events.

Continuum descriptions of epithelial tissue mechanics can replace expensive individual-based simulations with tractable macroscopic models, yet the link between cell-scale forces and tissue-scale transport remains poorly understood. We show that dimensionality controls this link: long-time mechanical relaxation rates reveal generalized porous-media-type nonlinear transport phenomena, $D(\rho)\propto\rho^\gamma$. Exponents in nonlinear diffusivities are fixed by microscopic mechanics and dimensionality, providing a novel physical mechanism for emergent macroscopic transport phenomena.

Biochemical traveling waves transmit signals across cells and tissues, but the thermodynamic cost of reliable propagation remains unclear. We develop a stochastic thermodynamic framework for reaction–diffusion systems with stable traveling waves and show that diffusion of the wave position is bounded by the dissipation specifically associated with propagation. The bound follows by projecting noisy field dynamics onto the adjoint translational mode, which maps the wave position to an effective biased random walk. Its tightness is controlled by the non-self-adjoint part of the linearized dynamics, with finite wave speed and antisymmetric reaction dynamics generically producing deviations from equality. For excitable trigger waves in a FitzHugh–Nagumo model, we show that the slow inhibitor dominates the propagation cost, yielding a trade-off among wave speed, inhibitor amplitude, and dissipation. We test these predictions in stochastic simulations of a microscopic Belousov–Zhabotinsky reaction–diffusion system and find consistent signatures in mitotic trigger-wave experiments in Xenopus egg extracts. The same relation further imposes an annihilation-limited bound on the reliable signaling rate of wave trains.

Magnetic fields generated by the Rayleigh-Taylor instability were measured in laser-accelerated planar foils using ultrafast proton radiography. Thin plastic foils were irradiated with $\sim$4-kJ, 2.5-ns laser pulses focused to an intensity of $\sim$10$^{14}$ W$/$cm$^{2}$ on the OMEGA EP Laser System. Target modulations were seeded by laser nonuniformities and amplified during target acceleration by the Rayleigh-Taylor instability. The experimental data show the hydrodynamic evolution of the target and MG-level magnetic fields generated in the broken foil. The experimental data are in good agreement with predictions from 2-D magnetohydrodynamic simulations.

Molecular dynamics is used to study radiation cascades in solid C60 under ambient conditions. Simulations are performed for Primary Knock-On Atom (PKA) energies from 0.1 to 1 keV, and cascades are sampled over many PKA directions to collect statistics. Energies and forces are described using the Environment Dependent Interaction Potential for carbon paired with the Ziegler-Biersack-Littmark potential for short-range interactions, and cascade behaviour is characterized by tracking kinetic energy, hybridization and bond connectivity as a function of time. Compared to most materials, fullerite exhibits an unusual radiation response due to weak thermal transfer between C60 molecules leading to a thermalization phase lasting hundreds of picoseconds. The cascades damage the C60 molecules and link them together, and a linear relation is found between the number of cross-linked molecules and the number of new sp3 atoms. The threshold displacement energy computed is 18 eV, in agreement with experiments

Stimulated Brillouin scattering (SBS) microscopy enables label-free mapping of local viscoelastic properties, but frequency-domain implementations are often limited by uncertainty in the pump-probe frequency-difference axis. We demonstrate an RF-defined single-laser electro-optic-modulation SBS microscope in which the pump and probe are derived from the same optical carrier and their frequency difference is set by an electro-optically generated sideband. This architecture makes laser-frequency noise largely common mode and eliminates optical wavelength tuning during spectral scanning. It achieves Brillouin frequency shift and linewidth precisions of 0.07 MHz and 0.30 MHz, respectively. Comparison with a low-NA reference linewidth indicates a system-level spectral broadening of approximately 3.1 MHz, corresponding to an effective spectral resolution of approximately 3 MHz. Imaging of femtosecond-laser-modified chalcogenide glass resolves MHz-level Brillouin contrasts corresponding to 10^-4-level apparent longitudinal-modulus contrast. This work demonstrates the feasibility of transferring the frequency definition of SBS spectral scanning from optical wavelength tuning to RF-domain control, providing a new conceptual and technical basis for high-precision, high-spectral-fidelity Brillouin imaging.

In this work, a path integral Monte Carlo (PIMC) algorithm for fictitious identical particles (FIP) is proposed by introducing a $\xi$-ensemble and performing PIMC simulations on the resulting $\xi$-ensemble partition function. The PIMC algorithm with the $\xi$-ensemble allows us to obtain the thermodynamic properties of FIP for different $\xi$ values in a single simulation. Moreover, it also accelerates the simulation by improving the sampling efficiency, compared to the usual case where independent simulations are performed for each $\xi$ value, in the sense that the autocorrelation time of samples belonging to the same $\xi$ sector is decreased. Simulations of the uniform electron gas and uniform warm dense beryllium are performed to validate the improved algorithm and study the improvement in its sampling efficiency.

Magnetic fields generated by a current flowing through a U-shaped coil connecting two copper foils were measured using ultrafast proton radiography. Two $\sim$1.25 kJ, 1-ns laser pulses propagated through laser entrance holes in the front foil, and were focused to the back foil with an intensity of $\sim$3 $\times$ 10$^{16}$ W$/$cm$^{2}$. The intense laser-solid interaction induced a high voltage between the copper foils and generated a large current in the connecting coil. The proton data show $\sim$40-50 Tesla magnetic fields at the center of the coil $\sim$3-4 ns after laser irradiation. The experiments provide significant insight for future target designs that aim to develop a powerful source of external magnetic fields for various applications in high-energy-density science.

The problem of signal detection under an unknown background can be framed as one of inferring the weight of a mixture model with one misspecified component. Banerjee and Algeri (2026) show that, for this problem, the conservativeness of the inference is entirely determined by one single parameter, called the compensator. They demonstrate that, when the data are independent and identically distributed, an inferential approach based on the compensator circumvents the need to estimate the density of the misspecified component and the associated challenges. The main purpose of this manuscript is to broaden the scope of such an approach and extend it to the case in which, as is often encountered in modern experiments in physics and astronomy, the data consist of Poisson counts observed over a large number of bins.