Papers

Disordered stealthy hyperuniform materials combine liquid-like statistical isotropy with crystal-like homogeneity, suppressed density fluctuations at large length scales, bounded holes, and an isotropic structure factor that vanishes for a finite range of wavevectors. This combination yields unusual physical properties, including optical transparency, effective delocalization, ultrafast spreadability, optimal conductivity, and complete isotropic photonic bandgaps. Gyromorphs, point patterns whose structure factor includes rings of Bragg-like peaks arranged with discrete $G$-fold rotational symmetry, were recently introduced as counterexamples: disordered media that can somehow achieve the same physical properties, in some cases with higher performance, without stealthiness or hyperuniformity. In this paper, we resolve the puzzle of how gyromorphs fit consistently with the stealthy hyperuniform studies. We first show that gyromorphs are actually hyperuniform and, in the large-$G$ limit where they become nearly isotropic, belong to the weakest form of hyperuniformity, known as Class III. Thus, gyromorphs should have comparatively degraded physical properties compared to stealthy hyperuniform media, which belong to the strongest form of hyperuniformity, known as Class I. We verify this expectation using the rigorous spectral Green's matrix method for the calculation of the density of states (DOS) and Purcell factors in large arrays of electric dipoles. We find that gyromorphs display size-dependent pseudogaps richly populated by localized states rather than smooth band gaps like those found for highly stealthy hyperuniform materials or in deterministic structures such as Vogel spiral and triangular lattices. Furthermore, we predict similar disorder-induced degradation relative to stealthy hyperuniformity with regard to transparency, spreadability and diffusion properties.

It is often asserted that quantum states for same-type particles must be symmetrized due to “label redundancy,” i.e. the assumption that the permutations of labels in direct-product states do not reflect any real physical distinction and thus their permutations constitute an “exchange degeneracy”. This assumption is directly challenged by the case of scattering of same-type particles such as electrons, which involves two physically distinct scattering channels effectively corresponding to permutation of the labels. I discuss this counterexample with critical attention to an extant portrayal in the literature that omits pertinent physical content. I further note ways in which the assumption that symmetrization must be universally imposed is not supported by actual calculations of particle interactions, nor by seemingly viable particle states based on preparations and outcomes.

Techniques from glass art and fabrication provide a controllable physical platform for studying tissue mechanics in simple organisms. Here, we use glass-based physical models to investigate tissue deformation in the marine organism Trichoplax adhaerens. Previous studies have shown that the epithelial tissues in T. adhaerens undergo large deformations and form fracture holes under mechanical loading, exhibiting a ductile-to-brittle transition at fast loading rates. To model these behaviors in a tunable and experimentally accessible system, glass is shaped into tissue-like monolayers in a glass studio, heated to its specific process temperature, and subjected to controlled stretching. Rapid cooling arrests the deformed configurations, providing snapshots of tissue-like strain states under load. Under lateral and radial stretching, we quantify changes in the area and eccentricity of individual "cells" in the glass models, and found that eccentricity increases after stretching. We further use tensegrity-based models to quantify deformations in the cellular geometry of the glass tissues, enabling direct comparison between experiments and simulations. The model captures the principal experimental deformation patterns, but underestimates the magnitude of the observed eccentricity changes. Our results demonstrate that glass-based physical models provide an experimentally accessible platform for studying tissue-scale deformation and mechanical behavior, while supporting interdisciplinary approaches that connect methods in the arts and sciences.

Waveform cross-correlation (WCC) applied to data from seismic arrays allows for the reduction of the detection threshold by approximately an order of magnitude. When applied to the data of the IMS, the smallest WCC detected events were by at least one magnitude unit lower than those reported by the IDC and revealed that the pattern of low-magnitude activity prior to the July 29, 2025, earthquake was similar to that prior to the May 24, 2013, Sea of Okhotsk earthquake. The consistent increase in the number of events with magnitudes approaching the corner value of the Kamchatka recurrence curve can likely be used as a precursory indicator of a mega-earthquake preparation. The WCC-based events are characterized by detections with a signal-to-noise ratio below the IDC detection threshold and are often not visible to analysts. This makes the statistical significance of the WCC event hypotheses uncertain due to the absence of a random noise reference and the potential side-sensitivity of the IMS arrays. Both problems are addressed. Random noise is used to calculate a WCC bulletin. This exercise shows a negligibly low number of WCC events and confirms the statistical significance of the WCC-based events. The side-sensitivity is modelled using the March 11, 2011, Tohoku earthquake. When master events (MEs) within the Kamchatka region are used in the WCC processing, a large number of false events are generated. When MEs from the Tohoku zone are added, all false events disappear since the Tohoku MEs win the conflict resolution process. When the random noise is scaled to a small fraction of the maximum amplitude within the processed interval, the WCC detection is enhanced with more detections and WCC-based events created. This is an effect similar to noise whitening, which makes the matched filter detector more sensitive and closer to its optimal performance under stochastic noise conditions.

The Bekenstein–Hawking entropy $S = k_B A/4\lp^2$ contains a coefficient $1/4$ that has been calculated by many approaches to quantum gravity. We show that this factor arises from the causal geometry of any null boundary in a four-dimensional Lorentzian spacetime. A heuristic accessibility argument is supported by a purely geometric derivation using the canonical symplectic structure on the cotangent bundle and the causal splitting of the space of null rays. No gravitational field equations are invoked.

We study the dynamics of observables that are conserved under the Hamiltonian evolution of a closed quantum system, but cease to be conserved when the system is coupled to a Markovian environment and described by a Lindblad master equation. Starting from the adjoint Lindblad equation, we derive elementary expressions for the time derivatives of the expectation value and second moment of an observable $O$, with particular emphasis on the case $[H,O]=0$ but $\mathcal L^\dagger(O)\neq 0$. These formulae provide a direct assessment of how collapse operators break Hamiltonian conservation laws and generate fluctuations of formerly conserved quantities. The discussion is illustrated by analytic examples: one-qubit amplitude damping, a two-qubit excitation-number model, a momentum-diffusion model in which the mean is conserved while the variance grows, and the Jaynes-Cummings model. The latter also shows the complementary case of a reservoir coupled through a conserved quantity, where dephasing can occur without changing the statistics of that quantity. We finally comment on the relation between Lindblad source terms and idealized wave-function reduction models in which local conservation may hold only statistically.

Quantitative studies of gender in physics education have often used categorical gender identity measures, which are valuable for documenting broad inequities across gender groups but less suited for capturing variation within groups or for examining how students perceive and express their gender in particular contexts. Metrics targeting gender expression, such as gradational self- and reflected appraisal measures of femininity, masculinity, and androgyny, offer a complementary approach. Prior work using this approach in introductory physics identified substantial within-gender variation in students' appraisals and gender-patterned self-reflected appraisal discrepancies. Building on this work, the present study provides a cross-institutional replication by examining whether these patterns recur in a second institutional context. We examined students' self- and reflected appraisals of femininity, masculinity, and androgyny, self-reflected appraisal discrepancies, and associations between these discrepancies, sense of belonging, and gender stigma consciousness. Across institutional contexts, both studies showed substantial within-gender variation in all three appraisal dimensions and recurring directional discrepancy patterns. Higher gender stigma consciousness was consistently associated with the directional discrepancy patterns observed across institutions. Lower sense of belonging was consistently associated with negative femininity discrepancy across institutions and was also associated with positive masculinity discrepancy in the present study. These findings suggest that students' appraisals along gendered dimensions are both patterned and context-sensitive. More broadly, self-reflected appraisal discrepancy may offer a useful quantitative lens for examining students' perceptions of gender, with implications for understanding belonging and inclusion in physics learning environments.

Accurate NH3 pressure-broadening parameters are essential for reliable line-by-line simulations in atmospheric sensing, combustion diagnostics, and planetary/exoplanet studies. Current HITRAN NH3 self- and air-broadened half-widths rely largely on the Nemtchinov rotational correlation and database rules that clamp or assign default values beyond the validated range, limiting the representation of measured rotational trends, especially at high J”. Here, published NH3 self- and air-broadened Lorentz half-widths were compiled and reassessed to develop updated HITRAN-ready empirical correlations. The dataset includes 1317 self-broadened and 1231 air-broadened widths at, or reduced to, 296 K across multiple bands, branches, and rotational states. The analysis shows that linewidths are governed mainly by rotational dependence rather than branch, band, or vibration-inversion effects. Weighted, positivity-constrained third-degree polynomial fits were developed for gamma_self and gamma_air as functions of the branch-dependent index m and K”. The new correlations reduce the MAPE from 10.95% to 6.80% for air broadening and from 23.61% to 10.89% for self broadening relative to HITRAN2024. Comparisons with PNNL and pure-NH3 spectra further confirm improved absorption simulations, providing a physically constrained replacement for the current HITRAN NH3 broadening treatment.

We propose a noninvasive SQUID-based polarimeter for the polarized proton beam in the Electron-Ion Collider (EIC) Hadron Storage Ring (HSR), exploiting the collective magnetic dipole moment of the bunches rather than scattering. The six-snake HSR lattice has synchronous-particle spin tune $\nu_s = 1/2$, placing the in-plane spin-precession signal at half the revolution frequency ($\sim$39 kHz), in the DC SQUID band. Three pickup channels (cosine-$\theta$ and sine-$\theta$ saddle loops for the transverse components, a coaxial axial gradiometer for the longitudinal one) reconstruct the full polarization vector $(P_x, P_y, P_z)$ in two complementary modes. Static mode, the default for continuous noninvasive monitoring, reads all three components: $P_y$ at the revolution frequency and the residual in-plane components at $\nu_s f_\mathrm{rev}$, bunch by bunch over an hours-long fill, including $P_z$, inaccessible to single-spin scattering polarimetry by parity conservation. Dynamic mode gives a precise polarization-magnitude measurement: a longitudinal kicker tips a small fraction of the polarization into the horizontal (ring) plane to produce a free-induction-decay (FID) signal, and many phase-locked tip-$\pi$-echo-restore cycles are summed coherently via a matched filter across all bunches, with $\mathcal{O}(\alpha^2/\pi^2) \sim 10^{-4}$ loss per cycle, negligible over a full $\delta P/P = 1\%$ measurement. For tipping angle $\alpha = 30$ mrad, polarization $P = 0.7$, and effective rms spin-tune spread $\sigma_{\nu_s}^\mathrm{eff} = 10^{-3}$ (coherence time $\sim$2 ms), the integration time to reach $\delta P/P = 1\%$ is about 18 s at injection and 5 min at flattop. The architecture extends to deuteron and $^3$He beams via species-specific spin-magnetic factors, with applications to storage-ring EDM searches.

Periodic micro-pillar lattices integrated on elastic substrates provide a promising plat-form for controlling elastic-wave propagation through localized resonant interactions. In this work, defect-engineered resonant transmission in periodic tungsten micro-pillar arrays deposited on silicon substrates is numerically investigated using finite-element simulations. Two-dimensional frequency-domain analyses were performed to evaluate the influence of one-, two- and three-pillar defects on elastic wave transmission characteristics. The results reveal strong defect-width-dependent transmission modulation together with the localized resonant elastic-wave redistribution within the periodic lattice. Full three-dimensional simulations further confirm the presence of defect-sensitive resonant localization and modified elastic-wave transport pathways. Floquet dispersion analysis of a periodic unit cell reveals multiple nearly flat resonant branches associated with low-group-velocity elastic-wave modes, indicating predominantly subwavelength locally resonant behavior. A comparative study between tungsten and copper resonators demonstrates enhanced resonant confinement in tung-sten-based structures due to their larger inertial contrast with the supporting sub-strate. The proposed defect-engineered micro-pillar lattices provide an effective approach for frequency-selective elastic-wave control and localized resonant wave ma-nipulation in elastic metamaterial systems.

Large and persistent differences in opioid prescribing across physicians and regions cannot be explained by patient characteristics or physician attributes alone. We developed a behavioral framework in which prescribing evolves through persistence, exposure to peers in professional networks, and heterogeneous responses to a common policy signal that varies with network centrality. Using nationwide Medicare Part D data from 2013 to 2020, covering more than two million physician-year observations, we tested three hypotheses implied by this framework. Physicians exposed to higher peer prescribing subsequently prescribe more; more central physicians reduce prescribing more following the introduction of the 2016 CDC guideline, with no evidence of differential pre-trends; and changes in peer prescribing are closely associated with changes in individual prescribing in the post-guideline period. By 2020, physicians at the 90th percentile of network centrality exhibited prescribing reductions 0.30 percentage points larger than those at the 10th percentile, with the gap widening steadily after the introduction of the CDC guideline. Together, these results indicate that opioid prescribing operates through professional networks, in which policy effects spread through connections and appear to be shaped by network position. This suggests that engaging highly connected physicians may help extend the reach of opioid stewardship programs. It also raises questions about how the burden and benefits of such targeting would be distributed across physicians and patients.

Exceptional points (EPs) are non-Hermitian spectral singularities where eigenvalues and eigenvectors coalesce. We propose a geometry-controlled route to EPs in orbital-angular-momentum (OAM) photonics. In an effective torsion-free helicoidal background, the twist supplies a signed, real chiral splitting between opposite-OAM modes, while openness, gain, loss, leakage, or channel coupling, supplies the non-Hermiticity. The EP is reached when the geometric detuning compensates for a residual mode splitting and the linewidth contrast meets the non-Hermitian balance condition; the twist rate is thus the control parameter, not the source of non-Hermiticity. We obtain the OAM slope both for a confined quantum problem and, in the paraxial regime, for a helically twisted guide, and embed the OAM doublet in a multimode mode-space model to show that the EP survives spectator modes. Eigenvalue coalescence, phase-rigidity collapse, linear EP tracking with residual detuning, and branch exchange under geometric encircling provide falsifiable signatures. An OAM-resolved input-output response maps these onto spectroscopy-level observables, including spectral maps and three-dimensional Riemann-surface visualizations. A device-level paraxial simulation of two distinct photonic platforms, one reciprocal and one asymmetric-coupling Wiersig-type platform, reproduces the predicted exceptional point and its linear geometric tracking.

IGR J17480-2446 is a low-mass X-ray binary, harboring an exceptional accreting pulsar (a neutron star) with an unusual spin frequency of 11 Hz and a very slow post-outburst crust cooling. The former may imply that it is observed at an early stage of recycling, while the latter was shown to indicate the presence in the outer crust of a low thermal conductivity layer, possibly made of glass. Here we argue that the glass layer formation is a natural result of accretion induced failure of pristine cold crystal crust. This allows us to determine the mass of the accreted material as $\Delta M \approx 2.4\times 10^{-6}~M_\odot$, confirming very early accretion stage for this neutron star. An analysis of spin and thermal state reveals a peculiar set of neutron star birth properties which is commonly associated with `recycled' neutron stars, i.e.\ those that have been experiencing prolonged periods of accretion from a companion. We speculate that such birth properties may represent the outcome of neutron star formation in an electron-capture supernova.

Large language models (LLMs) are increasingly deployed as planners and assistants in tasks with inherent spatial structure, such as navigation and route planning, yet they remain brittle in sequential spatial reasoning. We ask not merely whether LLMs fail at navigation but where in the spatial-cognition pipeline they get lost. We introduce a multi-scale diagnostic benchmark that decomposes maze navigation into three cognitive levels drawn from human spatial cognition: Fine (local passability), Meso (junction topology), and Macro (global goal direction). We evaluate three instruction-tuned chat LLMs (GPT-4o, DeepSeek-V3, Llama-3.3-70B) on 1,050 topology-annotated mazes spanning seven sizes (3x3 to 30x30) and three difficulty tiers. The benchmark is organized as three modules. (i) Input acquisition: among four input formats, structured coordinate text is the most navigable, far surpassing rendered images. (ii) Multi-scale representation: end-to-end one-shot navigation collapses to near zero by 10x10 for every model, yet the same models respond to isolated single-level probes (Fine, Meso, Macro) at 30-75% far beyond that size. A multi-hot first-error analysis localizes failures to Meso junction choices (59%) and Fine perception (39%), with global direction almost never at fault (1%). The barrier is therefore the cross-scale aggregation of individually available competences over a long sequential plan, not any single perceptual deficit. (iii) Hierarchical route planning: delegating per-step execution to a deterministic walker and querying the LLM only at junctions, with an explicit cell-type prompt, lifts GPT-4o success by up to 92 points at mid sizes, but the same scaling wall re-emerges by 30x30. We release the benchmark, mazes, and code as a reusable diagnostic instrument for spatial reasoning in LLMs, available at https://yuhanjiang415.github.io/lost-in-aggregation/.

A central goal of quantum optimal control is to achieve high-fidelity and low-energy control pulses. When quantum optimal control methods optimize every point of a pulse discretized over small time steps independently this can yield high fidelity control but also results in broadband and energy-hungry waveforms. We extend MAGICARP, a shooting method inspired by Pontryagin's maximum principle on energy that generates an entire pulse from a small set of parameters, making it smooth and energy-efficient by construction, from driftless systems to closed systems with the constant drift Hamiltonian of two exchange-coupled spins in an external magnetic field. The optimization proceeds in stages: the dressed states of the drift Hamiltonian structure the target, an initial shooting optimization is performed in the rotating-wave frame, and an exact laboratory-frame refinement follows. Benchmarked against Krotov and GRAPE at matched gate infidelity, MAGICARP consistently achieves the lowest energy and a conserved pulse area, concentrates its spectral weight on the gate-relevant transitions, and is the most robust to fluctuations in the exchange coupling; GRAPE independently converges to essentially the same pulse while black-box Krotov meets the same error at an order-of-magnitude energy premium. This method-independence is what qualifies the bounded solver as a measurement instrument, and the central result follows: a large statistical survey of unselected optimization runs resolves a weak-driving quantum speed limit for two exchange-coupled electron spins: low-amplitude realizations of the two-qubit quantum Fourier transform cease to exist below a critical gate time, and the minimum control energy diverges on approach to this limit. The divergence obeys a simple two-parameter area–pole law, $E_2^{\mathrm{law}}(T)=A/T+B/(T-T^*)$.

The present research presents potentials and complementary potentials used in the one-dimensional nonlocal integral formulations. The pure stress and the pure strain nonlocal formulations were considered. While the potential used in the strain driven formulation is well known, the complementary potential has not yet been presented in the literature. The same applies to the stress driven formulation. The equivalent formulations are obtained by resorting to the Legendre transformation, and their equivalence is proved. It is also shown that these results can be used to postulate a novel potential, i.e. a kind of mixed stress-strain potential, which is, however, as ill-conditioned as the pure strain-driven formulation. Finally, an example is given that practically confirms that the stress-driven formulations resulting from the potential and the complementary potential are equivalent.

We study the problem of cooking the yolk and albumen of a hen's egg to their respective optimal temperatures of $T_Y^* = 65^\circ$C and $T_W^* = 85^\circ$C, subject to the requirement that neither temperature ever exceed its target at any time during cooking, since temporary overshoot still overcooks the egg even if the final reading is correct. We model the egg as a two-domain sphere with distinct thermal diffusivities, and take the Laplace transform of the heat equation in each domain, reducing the problem to a $3 \times 3$ linear system in the transform variable $s$ with hyperbolic-trigonometric solutions. The resulting transform is inverted numerically via Talbot's method and validated against a finite-difference solver. A single boiling phase cannot satisfy the no-overshoot requirement: the thin outer albumen heats far faster than the insulated yolk and necessarily overshoots $T_W^*$ before the yolk approaches $T_Y^*$. We show that a three-phase protocol resolves this: a sous-vide pre-soak at exactly $65^\circ$C (which cannot overshoot since the bath temperature equals the target), a short boil to bring the albumen toward $T_W^*$, and an ice-water bath that arrests the albumen's residual overshoot while residual heat continues raising the yolk to its target. Optimizing the phase durations gives $17.26$ minutes of sous-vide, $66$ seconds of boiling, and an ice bath, achieving both targets at $T^* \approx 20.67$ minutes with neither constraint violated at any time. This compares favorably with the periodic protocol of Di Lorenzo et al. (2025), which requires 32 minutes and misses both targets substantially.

Electrochromic devices (ECDs) offer a compelling route toward low-power, non-emissive optical modulators with nonvolatile states. However, their widespread implementation is hindered by limitations in operating voltage, switching speed, color tunability, and long-term stability. Mixed ionic-electronic conductors (MIECs) provide a promising alternative platform, enabling optical modulation through ion-driven redox and structural transformations. Oxygen-based MIECs offer enhanced durability, environmental robustness, and compatibility with oxide electronics and silicon photonics, yet remain largely underexplored for electrochromic and photonic applications. Here, we demonstrate structure-driven analog optical control in an ion-pumped SrFeO$_{3-\delta}$ thin-film device by undergoing reversible oxygen-driven phase transitions between brownmillerite and perovskite structures. Phase transition is accompanied by pronounced changes in its electronic structure and optical constants. By harnessing these ion-induced structural transformations and integrating an optically passive Al$_2$O$_3$ interference layer, we achieve continuous and reversible modulation of optical transmittance and color. These results provide a general framework for ion-driven analog photonic and electrochromic devices and highlight the potential of oxygen-based MIECs for next-generation ionochromic systems compatible with silicon-based photonic platforms.

Resonant wave-particle interactions between externally launched helicon waves (also known as whistler waves) and runaway electrons (REs) have been demonstrated on the DIII-D tokamak. In this work we extend the initial results reported in Choudhury, H. et al. Phys. Rev. Lett. 136, 025101 (2026) by exploring the effects of antenna alignment with the edge magnetic field, toroidal wave propagation direction, and coupled power on RE scattering in the quiescent RE experimental scenario. Two distinct experimental configurations have been investigated: one in which the antenna aligns well with the edge background magnetic field, known as the ideal antenna configuration, and one with misalignment, known as the non-ideal case. Previously, it had been found that helicon power in the ideal antenna configuration prevented RE growth despite the normalized toroidal electric field remaining high enough to drive exponential RE growth in the absence of helicon power. In this paper, we show that scattering via the normal Doppler resonance (n=1) effectively limits the growth of the RE population in both the ideal and non-ideal antenna configurations, with evidence of a power threshold in the latter case. In contrast, launching waves that favour the anomalous Doppler resonance (n=-1) is observed to enhance rather than reduce the RE population. In addition, fast magnetic measurements reveal rising-tones in the 30-60 MHz range during helicon-off periods, which are not observed prior to helicon power. Finally, the challenges of using launched helicon waves to scatter post-disruption RE beams are discussed. Collisional damping and a large vacuum gap between the plasma and antenna on the outboard side present significant obstacles to helicon waves propagating into the plasma core.

Surface elasticity plays a crucial role in the mechanics of soft solids at the scale of micrometers and may become significant even at the scale of millimeters in exceptional cases. However, despite the efforts made for the identification of surface elastic parameters, accurately determining these values remains challenging due to the complex interplay with bulk elasticity and nonlinearity. To address this issue, a novel GA-based optimization framework is developed by employing an ANN-based surrogate forward model for efficient identification of surface parameters from the force-displacement response of a cylindrical specimen. The ANN is trained on force-displacement data of a soft cylindrical specimen, generated by nonlinear FE model predictions incorporating model elastic surfaces. The data used for training is generated for non-dimensional values of surface tension in the range of 0-5 and surface shear modulus in the range of 0-50. The accuracy and reliability of the trained ANN are established. The key novelty lies in replacing analytical forward models, which rely on idealized boundary conditions, with a data-driven surrogate trained on FE simulations under realistic constraints. The parameter identification is performed for a number of surface parameter sets using numerically generated force-displacement data as well as for noisy data obtained by adding 5% error in simulated data. The maximum error in identified values of parameters in all the cases is less than 8%. Repeatability and uncertainty analyses based on multiple noisy realizations further demonstrate the robustness of the approach, yielding narrow confidence intervals for the predicted parameters. The proposed framework provides a novel, efficient, and robust alternative to FE-based inverse identification of surface parameters, particularly for experimentally relevant boundary conditions.

The performance of advanced materials for extreme environments is underpinned by their microstructure, including the size and distribution of reinforcing phases. Chromium-based superalloys are a recently proposed alternative to conventional face-centred-cubic superalloys for high-temperature applications, such as Concentrated Solar Power, and their development requires efficient measurement of precipitate volume fraction and size distribution from electron microscopy images. Traditional fixed-threshold image processing is sensitive to background noise, generalises poorly across materials, and requires substantial manual measurement effort. To address these bottlenecks, this study proposes DT-SegNet, an end-to-end two-stage deep learning scheme based on YOLOv5 and SegFormer for object detection and segmentation in electron microscopy images. The approach combines the training efficiency of convolutional neural networks at the detection stage with the segmentation accuracy of a Vision Transformer. Numerical experiments show that DT-SegNet substantially outperforms state-of-the-art segmentation tools offered by Weka and ilastik across metrics including accuracy, precision, recall, and F1-score. The model provides a useful tool for alloy-development microstructure examinations and helps address the large datasets associated with high-throughput alloy development.

We present a perturbative framework for computing the dynamics of an electronic wave packet launched by an attosecond x-ray pulse in a neutral molecule. The x-ray pulse excites the molecule via both x-ray absorption and Impulsive Stimulated X-ray Raman Scattering (ISXRS), coherently populating both the core-excited states and valence-excited states. We describe the electronic structure within the Equation-of-Motion Coupled-Cluster framework, adopting a compact representation of the sum over states expression characterizing the second-order perturbative description of ISXRS. We study the coherent electronic dynamics in OCS and oxazole utilizing the time-dependent difference electron density, decomposing it in terms of its perturbative components. While the core-excited components dominate the initial stages of the dynamics, the valence-excited components dominate the electronic dynamics on a longer time scale. The pulse polarization controls the symmetry of the states included in the wave packet. We show how the spatial symmetry of the states plays a role in shaping the spatial properties of charge migration. The atom-specificity of the ISXRS process translates directly into the initial localization of the wave packet. This determines the starting point of charge migration, shaping its subsequent evolution.

Wave-obstacle diffraction is, par excellence, an example of transition to nonlinearity, generating turbulence and complexity in fluids. We present an idealized kinetic plasma regime capturing this ubiquitous interaction and its transition to phase-space turbulence. High-resolution Vlasov-Poisson simulations reveal that the interplay between electrostatic waves and density gaps at Debye and sub-Debye scales redistributes a strongly anisotropic energy cascade throughout the full phase space, unveiling the effect of inhomogeneities on structure formation and small-scale-directed turbulent flow.

Several studies have considered sandpile dynamics not over regular grids, but over networks. In this case, avalanches redistribute grains not between neighboring sites in a geometrical sense, but between connected sites, in a topological sense. However, depending on how nodes are connected, grains may never leave the system, preventing energy release. In this work, we study the simplest case, the BTW model in one and two dimensions, rewiring the nodes so that at every rewiring step, the energy release is always possible, and study avalanche statistics as a function of rewiring. In the 1D case, a transition is observed in the Gini coefficient of the load distribution per node at about 85% the number of possible rewirings, a transition which is not evident with other measures, such as the size distribution of avalanches or the mean distance between nodes in the network. In the 2D case, energy release follows a power law even when the grid is fully rewired, while the Gini coefficient, unlike the 1D case, decreases at a steady rate, with a smoother transition. The effect of network size N is studied, finding that there is a transition for the Gini coefficient at the thermodynamic limit N \to \infty for both the 1D and 2D cases, transition which is also observed in the betweenness centrality, but not in other topological measures. Finally, the dependence of the results with the load per rewiring iteration, and the avalanche threshold is studied.

Characterizing the complete wall-pressure spectrum in turbulent wall-bounded flows requires simultaneous access to the viscous-scale high-wavenumber content and the outer-layer low-wavenumber content – a requirement that neither short-domain direct numerical simulation (DNS) nor sparse experimental measurements alone can satisfy. We propose Patched Flow Matching (Patched FM), a generative framework that fuses these two complementary sources by learning a patch-local prior over inner-scaled wall-pressure statistics from short-domain DNS and assimilating sparse sensor measurements at inference time through training-free posterior sampling. The patch-additive decomposition of the flow matching vector field decouples the generative prior from the global domain size, enabling reconstruction on domains arbitrarily larger than the training configuration. By expressing the patch prior in inner-scaled coordinates, where high-wavenumber wall-pressure statistics are approximately Reynolds-number invariant, the framework extends to higher Reynolds numbers through hierarchical transfer learning with as few as $500$ short-domain snapshots ($2.5\%$ of the base training data) at a fraction of the scratch-training cost. Applied to compressible channel-flow DNS at $Re_\tau = 180$, $500$, and $1000$, Patched FM reconstructs full-resolution wall-pressure fields on a domain four times larger than the training configuration ($L_x^L = 16\pi\delta$ versus $L_x^S = 4\pi\delta$) from sensor coverage as low as $0.25\%$, recovering the low-wavenumber spectral content inaccessible to short-domain DNS with high fidelity in both streamwise and spanwise directions. Zero-shot generalization to unseen Reynolds numbers and ablation studies further confirm the role of inner scaling as a physical prerequisite for data-efficient Reynolds-number transfer.

We demonstrate that acoustic waves can induce controlled translation and rotation of macroscopic objects through small, but deliberate, detuning of the driving wave frequency. When an object is patterned with a suitably designed acoustic metasurface, small changes in the incident frequency $\omega \pm \delta \omega$ are converted into directional radiation forces and torques, enabling steerable motion even for objects much larger than the acoustic wavelength. We present the concept of a force-optimal metasurface topology and show that it enables fully reversible forces in real time: the object is moved in one direction for positively detuned incident frequency $\omega+\delta \omega$ and in the opposite direction for negatively detuned frequency $\omega-\delta \omega$, where $\omega=22.5 \textrm{ kHz}$ and $\delta \omega =2.5 \textrm{ kHz}$ for a proof of concept at inaudible frequencies. This mechanism is demonstrated experimentally at ultrasonic frequencies with 3D-printed metasurfaces. The proposed concept is scalable across frequencies and materials, offering a building block for realizing complex, remote-controlled, dynamical behaviors that can be programmed by reconfiguring material surface patterns.

Despite their widespread use, mesoscopic models for non-ideal fluids have rarely been systematically validated against microscopic simulations. In this work, molecular dynamics (MD) simulations of confined fluids are mapped onto a mesoscopic framework, enabling direct comparison with lattice Boltzmann (LBM) formulations. By analyzing the moments of the distribution function, we identify a force formulation that consistently reproduces the microscopic statistics and macroscopic force balance. The results show that a hybrid formulation combining pseudo-potential and free-energy approaches provides the most consistent description. These findings establish a direct link between microscopic particle dynamics and mesoscopic modeling, offering practical guidance for the development and selection of LBM models for non-ideal and multiphase flows.

Guided acoustic wave Brillouin scattering (GAWBS) is a major obstacle in fiber-based quantum and high-speed classical communication systems as well as in interferometry. The transverse phonons driving it modulate the light field in the fiber core, adding thermal noise to the signal. To this day, there is no known method to eliminate GAWBS from the fiber or to compensate its effects completely. In this letter, we present twisted photonic crystal fibers (t-PCF) as the first-ever fiber system allowing a complete removal of mixed torsional radial GAWBS in a Stokes basis. The torsional radial modes modulate the fiber asymmetrically in the transverse direction, resulting in linear birefringence. While pure phase modulation is added as common noise in the guided fiber modes and can be easily removed through self-referencing, linear birefringence induces polarization modulation, which cannot be counteracted. In t-PCFs, the transverse symmetry of the geometry translates to multiple symmetries in the acoustic and optical domains in the circular basis. This enables equal phase accumulation in certain orientations in the two optical modes. Through experiments and theory, we show that the GAWBS-induced phase can be compensated down to the quantum-noise limit by self-referencing in a symmetric interferometer with Stokes detection.

Some numerical simulations of very warm climates suggest that the Earth's atmosphere may undergo a transition to a state of equatorial superrotation, where the zonal-mean zonal wind in the tropics is westerly. However, major uncertainties remain about the circumstances under which such a transition could happen. A natural first step towards reducing these uncertainties is to better understand the dynamical processes involved in the transition in idealized setups. However, simple numerical experiments have reported very different responses to tropical diabatic heating in different models, with both a continuous and an abrupt transition to superotation. In this paper, we investigate the mechanisms controlling the nature of the transition. We show that in an idealized Held-Suarez framework, it is governed by both the meridional temperature gradient and the bottom friction coefficient. These two parameters control a competition between two feedback mechanisms: a positive tropical wave-jet mechanism, and a negative feedback mechanism related to absorption of extratropical waves near their critical latitudes in the tropics.

Discovering the fundamental dynamical rules that generate the main statistical features of human mobility is essential for understanding the mechanisms underlying such processes. A prominent example is the exploration and preferential return model and its generalizations, which successfully reproduce several empirical findings. Here, we exploit another observation: the endpoint distances of a trip from the trajectory's starting point are strongly correlated. We consider a movement process in which each user performs a sequence of trips to satisfy a set of demands, given a spatial distribution of suppliers on a two-dimensional lattice. In each trip, destinations are chosen with a probability that depends on the ratio of the initial and final distances from the user's origin (home). We show that even a single agent with uniformly distributed demands and suppliers qualitatively reproduces key empirical statistics, such as the power-law distribution of traveled distances. The results are also robust to introducing interactions between agents via queues and incorporating more realistic demand and supplier distributions.