Papers

Chiral phonons are quantized vibrations where the atomic motion in a solid breaks improper rotation symmetries. In many cases, chiral phonons possess angular momenta and are therefore selective to circularly polarized light. Both fundamental and applied research efforts on chiral phonons have been gaining increasing attention owing to their importance in a variety of fields including spintronics, spin-selective chemical reactions, thermal transport, quantum information processing and biosensing, where the bi-directional spin-lattice coupling enabled by chiral phonons can be harnessed in new ways, and potentially lead to new functionalities. Thus far, the studies of chiral phonons across diverse materials platforms have evolved largely independently within these fields, but the experimental techniques are often interrelated. In this perspective, we present a detailed description, as well as advantages and disadvantages of the current approaches for experimentally measuring chiral phonons in chiral and achiral materials. We conclude with a discussion of new methods for measuring chiral phonons. Ultimately, this work seeks to offer an experimental guide for systematically investigating the properties of chiral phonons in various materials systems and applications.

Energetic-ion formation in a low-current hollow-cathode plume is investigated using experiments, self-consistent electrostatic particle-in-cell (PIC) simulation, and particle-resolved analysis. Retarding potential analyzer measurements show a substantial energetic-ion population over discharge currents of 0.8-3.5 A, while probe measurements reveal broadband plume fluctuations. Two-point phase-derived frequency-wavenumber measurements do not resolve a continuous ion-acoustic dispersion branch within the principal apparent-wavenumber interval. Because the inferred wavenumber is obtained from a cross-spectral phase defined modulo 2pi, the fluctuation diagnostics do not provide an unambiguous modal attribution for the energetic-ion population. A representative PIC plume, used as a qualitative kinetic reference, likewise develops broadband time-dependent electrostatic fluctuations together with a nonthermal energetic-ion population. Particle-resolved analysis shows that the energetic outflow is dominated by ions generated through ionization inside the plume, while source localization biases access to distinct trajectory and escape families. Matched field controls further show that time-averaged and frozen fields strongly suppress access to high-energy trajectories relative to the full time-dependent field over the analyzed interval. At the single-particle level, ion kinetic-energy gain is determined by electrostatic-field work accumulated along the actual trajectory, with different escape families exhibiting distinct radial and axial work contributions. These results establish a source-trajectory-field-work pathway for energetic-ion formation that can be identified without first assigning the fluctuating plume to a unique resolved plasma mode.

Significant wave height (SWH) retrieval from high-frequency (HF) radar typically relies on a weak second-order Doppler continuum that is sensitive to noise, interference, and spectral leakage. This letter presents a Windowed Envelope Statistics Estimator (WESE) that operates directly on beam-formed time-domain voltages. A second-order term obtained from a Neumann expansion of the rough-surface field equation motivates quadratic compensation of localized radar features. WESE extracts the mean, standard deviation, or variance from overlapping windows of the in-phase, quadrature, or envelope-magnitude sequence, followed by quadratic compensation, rank ordering, least-squares regression, and causal smoothing. Evaluation used 335 synchronized hourly observations from a 13.385 MHz, 12-element WERA system at Argentia, Newfoundland and Labrador. The optimal configuration used quadrature variance, a 16-sample window, 896 retained chronological samples, and 30-h smoothing, achieving an RMSE of 0.152 m and a Pearson correlation of 0.978. This represents RMSE reductions of 32.1% and 18.7% relative to previously reported linear and second-order compensated ordered-statistics models, respectively. The results demonstrate robust time-domain SWH estimation without explicit Doppler-spectrum construction.

Reinforcement-learning quadrotor controllers are usually trained under simplified wind models, yet the impact of wind-field fidelity, as opposed to magnitude, on policy robustness remains unquantified. This paper compares five disturbance-fidelity levels, from wind-free flight and discrete 1-cosine gusts through statistical turbulence and synthetic coherent structures to large-eddy-simulation fields of the atmospheric boundary layer, in a full cross-fidelity train test evaluation of proximal policy optimization (PPO) agents, with cascaded PID and geometric SE(3) controllers as training-free references, over a 0-12 m/s wind sweep. Before any controller comparison is made, all disturbance data are validated: every synthetic generator is checked quantitatively against its analytical or certification-standard reference, and the large-eddy-simulation fields against the imposed log law. On a racing-class quadrotor in hover, the train test matrix is remarkably flat, and the cheapest structured training wind, which is discrete-gust domain randomization, ranks first in every test column, a ranking replicated on a wind-sensitive 27 g platform; a once-tuned geometric controller brackets the learned PPO policies at zero crash rate. Mechanism diagnostics show that control authority, not wind realism, bounds robustness, so wind-fidelity investment should scale with platform wind sensitivity.

The use of the shifted inverse Hamiltonian in the Lanczos algorithm is examined. We present a perturbative inverse and demonstrate that the Krylov subspace formed from it is better suited to approximating the ground state wavefunction compared with the Hamiltonian itself. We further demonstrate that the perturbative inverse provides an adequately accurate approximation to the inverse Hamiltonian at second order. Naturally, the quality of the results depend on the quality of the initial guess, here we use the Hartree-Fock, CISD, MP-PT1, and EN-PT1 wavefunctions. Lastly, we examine the scaling of the method where we find that accurate results can be found for similar cost as PT5.

Granular slip forecasting can conflate material state, loading progress, and the geometry of event-centered sampling. We separated these contributions in slowly sheared two-dimensional frictional disks using a compact neural score of stress, pressure, coordination, non-affine motion, and force-network observables. The model was developed on 36 trajectories and frozen efore testing on 18 new trajectories under two nested stress-drop definitions. Inspection of held-out results revealed post-event sampling asymmetry; recovery-aware analyses are therefore descriptive. With trajectories weighted equally, the compact score ranked near-slip windows above both prevalence and within-trajectory circular-phase controls under both definitions (representative average precision 0.310 versus prevalence 0.173; phase-null upper bound 0.257). Loading-history coordinates ranked more strongly, reaching 0.534 for causal elapsed strain. The recovery-aware rule retained 78.4% of activity-gated events and preferentially selected longer preceding intervals; ranking by time since the previous catalogued event remained compatible with a count-conditioned geometry null. Compact observables thus contain temporally aligned slip information, but stronger loading-history baselines and window-geometry sensitivity bound that evidence. These startup data do not isolate a state-specific short-horizon precursor beyond loading history or support a renewal interpretation of elapsed-strain ranking.

We propose the use of an a priori localization method based on separating the molecule into fragments to generate a wavefunction suitable for post Hartree-Fock methods. A quasi-Newton approach utilizing Thouless rotation is developed to optimize the strictly localized molecular orbitals(sLMO). We discuss the properties of the sLMO-HF wavefunction and compare it to the tail deleted a posteriori localization methods that are usually done in preparation of post Hartree-Fock methods. We then discuss the effects of choosing different fragmentation patterns and basis sets.

The High-Granularity Dual-Readout Calorimeter (HG-DREAM) designed for FCC-ee aims to achieve unprecedented energy resolution through fine three-dimensional shower imaging, simultaneous measurement of Cherenkov and scintillation signals, and machine learning capabilities. A key enabling technology is longitudinal segmentation via timing measurements, where multiple energy deposits along optical fibers are distinguished by the arrival times of Cherenkov photons. We present quantized one-dimensional convolutional neural networks that predict pulse locations directly from 80-sample, 16 ns waveforms digitized at 200 ps, and evaluate their implementation in front-end electronics. Three architectures, a compact baseline and two variants using dilation and stride to reach the $\sim$ 20-sample receptive field set by the SiPM pulse width, achieve ROC AUC above 0.95 with four to eight filters per layer. Fixed-point quantization to a $<$16,8$>$ baseline costs less than $10^{-3}$ in AUC relative to the floating-point reference. Applied to pairwise deposits, the smallest model separates two pulses with better than 95% probability at longitudinal separations of 20 cm and above. Synthesized at 400 MHz, this model uses 9663 LUT on a Xilinx XCVU13P FPGA and occupies $\sim$ 18500 $\mu$$m^2$ in TSMC 28 nm CMOS with reconfigurable weights. Assuming a triggered readout architecture for FCC-ee, the $\sim$ 500 kHz Z-pole trigger rate will be the most stringent throughput requirement across all FCC-ee operating modes. The ASIC implementation of the model sustains 4.8 MHz, exceeding the 0.5 MHz requirement by an order of magnitude, while the reconfigurable-weight FPGA implementation fails to do so. Sustaining the 40 MHz FCC-ee Z-pole bunch-crossing frequency in the triggerless architecture is not feasible with the models developed and the hardware targeted in this work.

Moiré theory is a revolutionary alternative arising from solid-state physics that can be extended to gravity, forming a framework called Moiré gravity. The idea behind it is that Einsteinian gravity has a validity limit and must be extended to Moiré gravity, in which the Friedmann equation changes and a new scalar field emerges. In this vein, in this paper, we propose an analytic solution for the Moiré scalar field coupled with the modified Friedmann equation, studying the viability and constraining the value for the main parameter of the scalar field and cosmology in general, through the use of datasets that contain cosmic chronometers, type Ia supernovae, intermediate-luminosity quasars, and hydrogen II galaxies. Our results allow for an accelerated phase with two peaks, but also predict an extremely decelerated stage, with $q(z=0)=15.376^{+6.403}_{-4.692}$ when the characteristic parameter of the theory is $\jmath=0.677^{+0.001}_{-0.002}$, in contrast to other models that decelerate at $z=0$.

Medium-range weather forecasting underpins operational and planning decisions across the energy industry. Developing competitive weather models was once the domain of national meteorological centers, but recent advances in machine-learned weather prediction (MLWP) have opened the field to industry. We present Aries, a SwinTransformer-based MLWP model developed at InCommodities. Aries is trained on ERA5 reanalysis data at 0.25\textdegree{} resolution, predicting 74 prognostic and 11 diagnostic atmospheric variables. We evaluate the model on 2025 ECMWF Analysis initializations, ensuring a recent and strictly out-of-sample test period for all models compared. On 10-metre wind speed, Aries outperforms both ECMWF HRES and AIFS in terms of RMSE for lead times up to four days, while on 2-metre temperature it achieves RMSE on par with AIFS operational. These results demonstrate that proprietary development of competitive weather models is technically viable, supporting a broader set of forecasts available for operational and planning applications in the energy industry.

Fluorescence lifetime imaging (FLI) measures the temporal decay of fluorescence after excitation and provides quantitative information about a fluorophore's local environment and molecular interactions. Depending on the fluorophore and experimental design, lifetime can report changes associated with pH, oxygenation, cellular metabolism, and Forster resonance energy transfer. These properties make FLI useful across microscopy, biophysics, biomedical optics, and preclinical imaging, where the same type of molecular contrast can be studied across different biological scales. FLI measurements, however, are acquired with instruments that record fluorescence in different ways. Intensified charge-coupled device (ICCD) cameras, single-photon avalanche diode (SPAD) arrays, and time-correlated single-photon counting (TCSPC) systems differ in temporal sampling, data organization, detector noise, instrument response, and file format. Lifetime-estimation methods also make different assumptions about the recorded decay, while learning-based approaches require realistic training and validation data for which the underlying parameters are known. PyFLI is an open-source framework for FLI processing and standardized data simulation. It imports measurements from acquisition systems, simulates labeled data under configurable acquisition and noise conditions, and provides complementary approaches for parameter estimation. These include nonlinear least-squares fitting (NLSF), maximum-likelihood estimation (MLE), phasor analysis, rapid lifetime determination (RLD), Laguerre-based estimation, and optional Bayesian and deep-learning inference. CPU and GPU processing support image-scale analysis, while reconstruction, visualization, statistical analysis, and cross-software comparison provide tools for evaluating results. PyFLI includes compressed-sensing reconstruction for single-pixel hyperspectral FLI.

In the present work, we study the two-component model of microtubules, the basic components of the eukaryotic cytoskeleton. We introduce a couple of estimations, which tremendously simplified the model. The paper is devoted to tangential oscillations of dimers, but we explain that the model can explain the radial oscillations as well. Finally, we study the stability of all solutions of differential equations, describing the dynamics of the microtubules.

Quantum holography with undetected photons (QHUP) enables the complex amplitude of infrared to be acquired beyond the sensitivity range of silicon based sensors, through induced coherence withoud induced emission. QHUP generally requires multiple phase-shifted holograms to retrieve the complex-amplitude distribution of an object, which limits measurement stability and temporal resolution. Although classical parallel phase-shifting holography provides a favorable balance between temporal and spatial resolution, it has not previously been implemented in QHUP because of the constraints imposed by photon distinguishability. In this study, we propose a quantum eraser-based geometric phase-shifting QHUP. By accurately erasing not only polarization distinguishability but also temporal distinguishability arising from differences in the optical paths, the complex-amplitude distribution of an object can be retrieved in a single shot using a silicon-based image sensor equipped with a polarization-filter array. This single-shot acquisition, combined with real-time processing, enables the observation of dynamic objects in the near-infrared spectral region. To the best of our knowledge, these experimental results constitute the first real-time acquisition of the complex-amplitude distribution of a near-infrared object using QHUP with a silicon-based image sensor equipped with a polarization-filter array. Furthermore, to enhance the reproducibility and applicability of this study, the experimental optical setup, bill of materials, and source code for real-time imaging have been made openly available. The ability to retrieve the complex-amplitude information carried by undetected photons in real time is expected to extend the applicability of QHUP to a wide range of fields, including spectroscopic imaging and semiconductor inspection.

This paper introduces the strategy of using an interposing layer to mitigate thermal-stress-induced fracturing of silicon sensors in ATLAS ITk Strip modules. This strategy involves a change in the module design in which layers of soft adhesive and a kapton separator, known as an interposer, are added to the module stack-up to decouple thermal stresses. This paper discusses the interposer design and its implementation in the ATLAS ITk Strip barrel, including material tests to validate the additional components, the development of new processes to integrate the new layers into the module assembly workflow, results from design validation and quality control testing of prototype interposed modules, and studies indicating that the new design significantly reduces the thermal stress experienced by the sensor. Tests of prototype support structures loaded with interposed modules have shown no sensor fractures in the relevant temperature range for operation in ATLAS, resulting in the adoption of the interposer strategy as the primary sensor cracking mitigation in the ATLAS ITk Strip barrel.

We expand the correlation-consistent effective core potentials (ccECPs) library by developing semi-local pseudopotentials and matching basis sets by heavy-elements from $5d$ (Hf, Os, Hg) and $6p$ (Tl, Po, At, Rn) blocks. In order to accurately capture scalar relativistic effects, spin-orbit coupling, and electron-electron correlation, we implement a tiered core-valence partitioning strategy across three distinct resolutions. This includes a small 60-core (Hf, Os, Hg) that explicitly correlates subvalence shells, a large 78-core definition for the main-group elements that rigorously accounts for core polarization and relaxation effects in sparse valence environments, and an intermediate 68-core partition for Hg and Tl. This 68-core architecture represents a unique development in the ccECP library, optimizing the balance between accuracy and computational efficiency in a manner unexplored for ligther elements. Optimized against relativistic all-electron CCSD(T) references, the ccECPs deliver outstanding atomic precision, achieving a global average atomic low-lying states deviation of just 0.045 eV. This accuracy translates directly to robust molecular transferability, systematically restricting dissociation energy discrepancies to under 0.03 eV, equilibrium bond lengths to within 0.005 Å. By enforcing a regularized, finite potential at the origin for enhanced numerical stability in stochastic quantum Monte Carlo methods, this library removes a critical methodological bottleneck for predictive many-body simulations of heavy-element systems and materials.

The Mu2e experiment at Fermilab requires stable resonant slow extraction from the Delivery Ring, making reliable tune monitoring an important operational diagnostic. This work investigates BPM-based tune-candidate extraction using synchronized turn-by-turn position data distributed across multiple digitizers. Each spill contains approximately 50,000 turns from many BPMs in both transverse planes, enabling spectral analysis of tune-like structure. The analysis captures coherent spill snapshots, verifies synchronization using stream timestamps, and computes tune candidates in configurable horizontal and vertical tune bands. Rather than relying on a single BPM or fixed BPM list, it evaluates BPM quality on a spill-by-spill basis and selects small adaptive BPM ensembles. A multi- spill study shows that tune observability is distributed and dynamic rather than concentrated in one globally optimal BPM. Adaptive ensembles improve tune-candidate quality compared with single-BPM selections, with the clearest results in the vertical plane. The horizontal plane shows useful ranking structure but weaker visibility under present thresholds. Direct evaluation of fixed global BPM sets shows that static selections do not reproduce dynamic per-spill performance. These results motivate an adaptive BPM-ensemble approach for Delivery Ring tune analysis using selected BPM subsets, confidence metrics, and quality flags rather than a single preferred BPM or fixed BPM list.

We study the dynamics of collisions and near-collisions in the system of three point vortices in the plane. The dynamics is known to be completely integrable and can be reduced to the study of Hamiltonian systems on two-dimensional symplectic leaves. This still allows for interesting behavior of the solutions, various aspects of which have been investigated in a large body of work by many authors. Our focus will be on collisions and the possibility of their regularization through perturbations of suitable parameters of the system. We will use the reduced coordinate given by $\zeta=(z_2-z_1)/(z_3-z_1)$, where $z_1,z_2,z_3$ are the complex numbers representing the positions of the vortices. This choice seems very natural, although we have not come across it in the existing literature on the topic. Some of our results concerning the near-collision behavior appear to be new, and we also prove inequalities between critical energy values that we have not found in the literature. The calculations we do to analyze the collisions and near-collisions also reproduce various classical results that were previously obtained by other authors using different coordinates, and parts of the paper therefore have an expository character.

In this paper, the log-conformation reformulation of a Giesekus fluid near a planar stick-slip singularity is investigated analytically. In what is, to our knowledge, the first use of the log-conformation formulation beyond its numerical purpose, we present results that match the asymptotic stress analysis of Evans [JNNFM 222 (2015) 24-33] for the stick, slip, and core regions under the assumption of a given Newtonian velocity field. Furthermore, the logarithmic reformulation allows us to extend the existing asymptotic theory substantially, showing, e.g., that the determinant of the conformation tensor is asymptotically constant, as well as thoroughly characterizing the transition behavior between the boundary layers and the core region. Combining these results, we obtain a composite asymptotic solution of the log-conformation equation that is valid uniformly throughout a close neighborhood of the singularity.

This paper presents the design and test results of a CMOS current-based Digital to Analog Converter (DAC) that operates at cryogenic temperatures and that can be used to precisely control the amount of flux coupled to qubits or that can be used in the readout of superconducting circuits. The current pulse output can be controlled in terms of its amplitude, rise and fall slopes, via digital controls, and pulse width, via external triggers, while driving a superconducting circuit. The design has been implemented in a planar 90 nm CMOS process and test results closely match circuit predictions. The solution's wide degree of digital tunability affords potential application of the same device to many types of quantum circuits, beyond those discussed here. Due to the wide-ranging flexibility of digital CMOS control, we envision that this DAC design will enable the next generation of high-fidelity cryo-CMOS control architectures for superconducting qubits.

In July 2026, Josh Kerr broke the 26-year-old mile world record, the latest in an unusual concentration of recent middle-distance records that has led to widespread speculation about the role of advancing shoe and other technologies. However, like almost every other recent record-breaking performance, Kerr's race featured a split-staggered start – an often overlooked, relatively novel start configuration that places a subset of athletes in a front group in the outside lanes, reducing the geometric burden associated with accelerating on tight turns while also avoiding the bulk of the extra distance associated with outside positioning in a traditional distance race. Here, these advantages are quantified using empirical lane-performance data, OMEGA measurements of realized race distance, video reconstruction, and a force-based model of curved running. Applying the resulting corrections to record-breaking performances from 2026, estimated advantages range from approximately 0.1 seconds to more than 1 second, depending on the event, race configuration, and model assumptions. Although small in absolute terms, these advantages demonstrate that start configuration represents a meaningful and previously overlooked source of performance advantage in modern middle-distance racing – large enough to make the difference between a world record and an otherwise great performance.

Coupled Cluster (CC) theory is one of the most popular correlated wavefunction methods, yet the steep computational cost scaling of CC truncated at higher rank limits its application. Modern Selected Configuration Interaction (SCI) methods successfully exploit the sparsity of ground-state wavefunctions in the determinant space, motivating an analogous approach with the exponential CC ansatz. In this work, we introduce Selected Coupled Cluster (SCC), an arbitrary-order sparse CC method that explicitly solves the CC residual equations within a compact amplitude space guided by an SCI wavefunction. SCC optimizes the CC amplitudes in the sparse amplitude space. Using a pilot Just-in-Time (JIT) compiled implementation, we benchmark SCC against SCI, SCI+PT2, standard rank-truncated dense CC (CCSD, CCSDT), and DMRG across various chemical systems. We demonstrate that SCC exhibits fast, monotonic convergence with the SCI variational threshold, outperforming SCI and surpassing SCI+PT2 in the tight-threshold regime. SCC also provides accurate energies for high-dimensional topologies, where DMRG typically converges slowly with bond dimension. SCC thus presents an efficient drop-in enhancement for modern SCI workflows.

Internal waves often propagate in the presence of currents. Internal waves and currents are widespread in the world's oceans. The equatorial internal waves and the equatorial undercurrent (EUC) are perhaps the most representative illustration of this phenomenon. The current profile in this study is a quadratic function of depth, which is in agreement with the known results of the EUC. With this assumption the integrable nonlinear Gardner's equation is derived as a model for the wave motion of the thermocline, separating the two layers of slightly different densities. In addition, we derive the generalised Gardner's equation in the case of variable bottom. We demonstrate that the coefficients of the equation are very sensitive with respect to the parameters of the EUC.

We investigate laminar mixing of a passive dye in an infinite, two-dimensional domain filled with a Newtonian fluid by simulating a cylindrical stirrer that rotates at constant speed along a circular path, stirring an initially quiescent fluid. The fluid is marked by a passive dye in the lower half of the domain, enabling a systematic analysis of dye-interface evolution and mixing dynamics. By varying the stirring Reynolds number within the laminar regime, we identify how transitions in flow topology govern mixing and distinguish three mixing regimes spanning diffusion-dominated and advective mixing. In the diffusion-dominated regime, mixing is characterized by the formation of a well-mixed central region and the development of a spiral dye pattern that evolves in an approximately self-similar manner. Advective mixing is marked by substantial deformation of the dye interface beyond the central region. We provide a mechanistic interpretation of advective mixing by relating mixing events to specific flow features: (i) direct interaction between the stirrer and the dye interface, and (ii) vortex shedding near the stirrer and away from the central region. Enhanced mixing occurs when vortical structures are able to escape the central region and transport scalar gradients nonlocally. When vortical activity remains confined near the stirrer's path, mixing per stirrer period exhibits only weak dependence on stirring speed despite increasing stirring intensity. Significant enhancement of mixing per period occurs only when escaping vortices introduce a new transport mechanism that carries scalar gradients far beyond the stirrer's path. Overall, we present a mechanistic link between flow topology and mixing by identifying the transport mechanisms through which flow features govern scalar evolution, providing a bridge between the kinematics of mixing and the underlying fluid dynamics.

The ability to use single mode (SM) fibers for beam transport in optical interferometry offers practical advantages over conventional long vacuum pipes. One challenge facing fiber transport is maintaining constant differential path length in an environment where environmental thermal variations can lead to cm-level variations from day to night. We have fabricated three composite cables of length 470 m, each containing 4 copper wires and 3 SM fibers that operate at the astronomical H band (1500-1800 nm). Multiple fibers allow us to test performance of a circular core fiber (SMF28), a panda-style polarization-maintaining (PM) fiber, and a lastly a specialty dispersion-compensated PM fiber. We will present experimental results using precision electrical resistance measurements of the of a composite cable beam transport system. We find that the application of 1200 W over a 470 m cable causes the optical path difference in air to change by 75 mm (+/- 2 mm) and the resistance to change from 5.36 to 5.50 {\Omega}. Additionally, we show control of the dispersion of 470 m of fiber in a single polarization using white light interference fringes ({\lambda}c=1575 nm, {\Delta}{\lambda}=75 nm) using our method.

We demonstrate the use of proximity effect correction (PEC) in electron beam lithography (EBL) to improve the fabrication fidelity of dense photonic crystal structures. Monte Carlo simulations were employed to model electron scattering and determine the proximity function of the resist-substrate system. Based on this, a computational dose-modification scheme was implemented to compensate for nonuniform energy deposition during exposure. In addition, SEM-based image analysis was performed to quantitatively assess structural differences among uniformly exposed, manually dose-modified, and PEC-fabricated devices by comparing extracted geometries with the reference GDS design. The analysis revealed reduced dimensional deviation, improved spatial uniformity, and lower edge roughness in the PEC-corrected structures. These improvements resulted in a significantly enhanced optical quality factor in the fabricated photonic crystal cavities.

A robust finite-volume framework is presented for the simulation of compressible multiphase flows with surface tension across a wide range of Mach numbers. The method is based on a two-pressure, six-equation diffuse interface model incorporating viscous, gravitational, and capillary effects through the continuum surface force formulation. To consistently account for capillary-induced pressure jumps, an HLLC Riemann solver is developed using generalized Riemann invariant analysis, and the instantaneous pressure relaxation procedure is modified to preserve the Laplace pressure jump during phase equilibration. To overcome the excessive numerical diffusion of conventional approximate Riemann solvers in the low-Mach regime, a robust low-Mach correction is proposed by extending our previous formulation with a modified scaling strategy that remains stable in regions of strong pressure variation. The resulting method retains accuracy from nearly incompressible flows to compressible regimes while preserving the robustness of the six-equation formulation. The numerical framework is validated using a series of benchmark problems involving surface tension, viscosity, gravity, and compressibility. The results demonstrate accurate prediction of interface dynamics, capillary pressure, and low-Mach flow features, while significantly reducing numerical dissipation without compromising stability. The proposed methodology provides an efficient and reliable approach for the simulation of complex multiphase flows spanning a broad range of flow regimes.

We realize narrow-linewidth magneto-optical traps of $^{46}$Ti, $^{48}$Ti and $^{50}$Ti atoms based on a 1040 nm-wavelength transition, cooling atoms to a minimum temperature in one dimension of $T_z=990(20)$ nK and a three-dimensional temperature of $T_\mathrm{3D}=1.28(7)$ $\mu$K. Atoms are pre-cooled in a broad-line magneto-optical trap and then transferred with about 25% efficiency to the narrow-line trap. We operate the narrow-line trap in two stages over 85 ms. First, a single cooling beam, blue-detuned from the narrow-linewidth atomic resonance, optically pumps and traps the atoms on a two-dimensional surface where the Zeeman shift from the applied spherical quadrupole magnetic field brings the light nearly to resonance. Second, four additional beams, counter-propagating in the transverse directions, cool and compress the atoms in all dimensions. The high magnetic moment of the laser cooling state makes the dynamics of the narrow-line titanium trap similar to those of other magnetic atoms. We measure the lifetime of the excited state of the transition to be $\tau=8.2(9)$ $\mu$s, indicating a transition linewidth of $\gamma/2\pi =20(2)$ kHz, and also measure isotope shifts on the narrow-line transition. We use Stern-Gerlach separation on the ultracold Ti gas to measure the $m_J$-distribution in the narrow-line magneto-optical trap, finding over 98% of the atoms in the stretched spin state.

We present GW Explorer: A Beginner's Guide, an outreach curriculum designed to introduce high school students to gravitational-wave (GW) astrophysics through interactive Python Jupyter notebooks. Most existing GW resources target beginning audiences and advanced students, leaving a gap at the pre-college level that we directly address. The curriculum integrates foundational physics with hands-on computation implemented through both self-directed and workshop-based instructional formats. In the self-directed format, students completed the curriculum independently on cloud-based platforms such as Google Colab. During the workshop format, students worked through the same activities under the guidance of University of Nevada, Las Vegas graduate student mentors. Topics span gravity, spacetime, GW sources, interferometric detection, and data analysis. An implementation in local high school classrooms informed the content and pacing, and survey results demonstrate gains in conceptual understanding and coding confidence. GW Explorer offers a scalable, open-access framework for authentic astrophysics research in the high school classroom.

We study the electromagnetic radiation and wave-optical imaging of an oscillating electric dipole orbiting a Kerr black hole. We derive the effective 4-current associated with a pointlike oscillating electric dipole in curved spacetime, and use black hole perturbation theory to compute the resulting radiation field at future null infinity, from first principles. We then develop a wave-optical imaging framework for a moving electromagnetic source in curved spacetime. We obtain images of an orbiting electric dipole, displaying relativistic beaming, gravitational lensing, and Einstein rings. We study polarization-dependent scattering by comparing the images produced by spinning dipoles with opposite helicities, finding a displacement that roughly decreases with the inverse of the radiation frequency, as expected for a beyond-geometric-optics effect. Our results provide a first-principles benchmark for beyond-geometric-optics descriptions of electromagnetic radiation in Kerr spacetime.

We present a joint observational analysis confronting viable $f(R)$ modified gravity theories, specifically the Hu & Sawicki and Starobinsky models, with background and large-scale structure (LSS) data. Utilizing Monte-Carlo Markov chain (MCMC) sampling across datasets including baryon acoustic oscillations (BAO), type Ia supernovae (SNeIa), cosmic microwave background (CMB) distance priors, and linear growth measurements ($f\sigma_8$, $f$, $\sigma_8$), we place tight constraints on the model parameters governing deviations from General Relativity. For the full dataset combination, we obtain $\log_{10} b_\mathrm{HS} = -6.325_{-1.138}^{+1.216}$ for the Hu & Sawicki model and $b_\mathrm{S} = (0.8\pm61.0)\times10^{-4}$ for the Starobinsky model. Model comparison based on the Akaike Information Criterion indicates that these $f(R)$ extensions are statistically favored over flat $\Lambda\text{CDM}$ ($|\Delta\text{AIC}| \ge 3.99$) for the combined data. However, when considering the Bayesian Information Criterion, the evidence for support is significantly reduced. Furthermore, we construct two-dimensional phase-space diagrams in the $(\mu, \gamma)$ and $(\mu, \Sigma)$ planes across several redshifts, establishing a novel diagnostic null-test allowing us to probe for deviations from $\Lambda\text{CDM}$, corresponding to the fixed point $(1,1)$ in both planes, using LSS observables. Should future weak-lensing and galaxy surveys provide data points with $\mu-1<0$ and $\gamma-1>1$ or $\Sigma-1 < 0 $, then the aforementioned models could be directly ruled out.