Papers

We develop a quantum model for the rotational dynamics of a freely floating levitated ferromagnetic gyroscope (LFG), emphasizing the interplay between intrinsic spin $\boldsymbol{S}$, mechanical angular momentum $\boldsymbol{L}$, and magnetic torque. The conserved total angular momentum projection along the $z$-directed magnetic field $\boldsymbol{B}$, $J_z=S_z+L_z$, is quantized, leading in the small-libration-amplitude limit to discrete precessional states $|m\rangle$ (eigenstates of $J_z$ with eigenvalues $J_z = m\hbar$) and librational harmonic oscillator states $|n\rangle$ ($n=0,1,2,\ldots$). The discreteness of the energies and dynamical variables is governed by the quantum precession scale $\Omega_Q=\hbar/I$, where $I$ is the moment of inertia of the LFG. We find that the phenomenon of LFG precession persists into high-field regimes where the magnitude of the rotational angular momentum associated with precession exceeds the total intrinsic spin. We analyze the complementary quantum limits of localized semiclassical LFG orientation wave packets and exact $J_z$-eigenstates $|m\rangle$, clarifying the relation between classical precession signals and the underlying quantized spin-rotor dynamics. We further show that radio-frequency fields can drive $\Delta m = \pm 1$ and $\Delta n = \pm 1$ transitions, enabling ladder spectroscopy, tilt-angle control, and sideband-like coupling between precession and libration. The coupled dynamics also exhibit branch-point magnetic resonances where precession and librational motion become strongly coupled. These results establish a framework for using LFGs not only as ultrasensitive torque and magnetic-field sensors, but also as controllable mesoscopic quantum systems. The techniques developed here may be applied to searches for exotic, beyond-the-standard model spin-dependent interactions, ultralight dark matter, and spin-gravity couplings.

During the gravitational collapse of a massive star into a regular black hole, a new form of matter must be produced in order to prevent the formation of a central singularity. Since such matter is not present in the initial stellar configuration, it must emerge dynamically during the collapse. This formation process is expected to be accompanied by a strong release of energy in the form of electromagnetic radiation, which may be observable. Here we investigate the gravitational collapse of baryonic matter into Dymnikova-Hayward-Bardeen regular black holes. We estimate the radiation density and the corresponding bolometric luminosity generated by the formation of the matter sector responsible for singularity avoidance. We show that such processes provide a possible mechanism for gamma-ray bursts. Moreover, compatibility with gamma-ray burst requires small regularization effects. As a result, the corresponding regular black holes differ weakly from the Schwarzschild black hole.

Despite the growing interest in two-dimensional (2D) MoSO systems, existing studies have exclusively focused on conventional Janus structures. In this work, we perform high-throughput first-principles calculations to explore novel stable 2D MoSO monolayers. Combined with random sampling strategy, graph theory and group theory, we successfully screen out three novel non-Janus 2D MoSO monolayers from 1325 candidate structures, namely Reversed 2H-MoSO, Hybrid 2H-MoSO, and Hybrid 1T'-MoSO. Compared with Janus MoSO monolayers, the non-Janus MoSO counterparts possess lower binding energies, varying from -4.38 to -4.51 eV/atom. A systematic combination of dynamic, thermodynamic, and mechanical stability analyses corroborates their excellent structural robustness. Ab initio molecular dynamics (AIMD) simulations confirm their superior thermal resistance, with the structures remaining stable at temperatures beyond 2000 K. Interestingly, unlike the semiconducting Janus MoSO, the Hybrid 1T'-MoSO monolayer exhibits distinct metallic characteristics. Furthermore, we found that strain and curvature can enable controlled phase transitions of MoSO among semiconducting, semimetallic, and metallic phases. More importantly, the Hybrid 1T'-MoSO exhibits favorable HER activity with a Gibbs free energy of -0.002 eV, rendering it a promising candidate for hydrogen evolution catalysis. This work not only expands the family of 2D MoSO materials but also provides a reliable strategy for discovering stable functional 2D materials via high-throughput computation.

Topologically polarized elasticity has been extensively studied in lower-dimensions, yet its three-dimensional (3D) counterpart remains largely unexplored. Here, we demonstrate omnidirectional topological elasticity in 3D structures that incorporate bending stiffness, which elevates zero-frequency topological mechanical states into finite-frequency phononic modes. These modes are localized at a single boundary, creating a pronounced stiffness contrast in both static and finite-frequency dynamic regimes. This three-dimensional structure exhibits highly polarized mechanical behavior across all spatial dimensions, establishing omnidirectional asymmetric topological elasticity. Experimental and numerical results confirm robust, asymmetric energy isolation, arising from the interplay between bulk topological polarization and boundary-localized surface modes. Our findings establish a paradigm for 3D metamaterials, with promising applications in vibration shielding and directional wave manipulation.

We present effective temperature (Teff) estimates of low-mass stars and T Tauri stars (TTS) candidate detections derived from automated spectroscopic measurements and low-complexity machine-learning models applied to the LAMOST DR10 V2 survey. Equivalent widths of key diagnostic spectral features, including the atomic lines Halpha, LiI 6708 AA and TiO/VO molecular bands, are automatically measured for all stars within 1 kpc observed by LAMOST. Using nine spectral features as inputs, we train a Gradient Boosting Machine tree-based regression model, calibrated with synthetic spectra from the PHOENIX library, to predict Teff over the range 2,500 - 5,100 K. We apply a logistic regression model to the principal components derived from the measured spectral features, enabling efficient identification of TTS candidates. Both models exhibit strong performance in validation tests. Finally, a Monte Carlo framework is employed to propagate input uncertainties and estimate Teff and its associated uncertainties for low-mass stars from 1,733,802 spectra and to identify 2,534 candidate TTS from 3,121 spectra.

As a fundamental arena for the development of his dynamics, Newton postulated the existence of absolute space, in which bodies innately possess absolute velocity. Despite this, Newton argued that, although real, absolute properties cannot be detected. Since then, the claim that absolute velocity would be undetectable in such a Newtonian universe has been generally accepted. Here, we show that standard arguments for such a claim, beginning with the one offered by Newton himself, beg the question. We conclude that there are no formal reasons to believe that absolute velocity would be undetectable in a Newtonian universe.

Kirigami turns stiff sheets into compliant, shape-morphing structures, but its reliance on periodic cut patterns comes at a cost: correlated panel rotations couple extension to shear, so stretching one axis drives a parasitic shear that cannot be suppressed, and also confine anisotropic stiffness to a narrow, discrete set of responses that cannot be tuned independently. Biological tissues overcome an analogous constraint through controlled disorder, such as graded fiber orientations in skin and hierarchical anisotropy in myocardium, achieving direction-dependent mechanics unavailable to regular architectures. Here, we show that engineered disorder is a design degree of freedom for kirigami, with stochastic kirigami accessing a continuous and far broader region of mechanical response than periodic patterns. This includes programmable anisotropy with near-complete elimination of extension-shear coupling. Because disordered patterns lack a simple parameterization, we navigate this design space with a geometry-aware graph neural network (GNN) that maps cut topology to the full nonlinear, bidirectional stress-strain response, coupled to a genetic algorithm that inverse-designs patterns reproducing target responses along two perpendicular axes. The GNN trains an order of magnitude faster and more accurately than image-based models. Fabricated elastomer samples reproduce the predicted nonlinear, anisotropic responses, closing the loop from design to physical component. By turning disorder into a variable to control directional stiffness, this work develops architected materials that stretch without parasitic shear, from soft actuators to tissue-interfacing devices matched to the anisotropy of living tissue.

A direct separation of the linearized Einstein equations in Kerr is presented. The trace of the perturbed metric is found to obey the spin-0 perturbation equation and so is irrelevant for the spin-2 perturbations. By combining the traceless condition, the Killing-Yano symmetry, a parity requirement, and the de Donder gauge condition, it has been found possible to reduce the linearized Einstein equations in Kerr to a manageable level, thereby enabling the direct separation of the equations and the derivation of a unique set of decoupled mode functions for the spin-2 perturbation of the Kerr black hole.

Fluctuations in disordered matter play a central role in determining material properties and physical responses. Recent studies have identified an exotic class of systems known as structurally hyperuniform materials, in which large-scale density fluctuations are anomalously suppressed through special spatial organization of particles, phases, or microstructural features. Here we demonstrate that ordinary, structurally nonhyperuniform disordered materials can nevertheless support hyperuniform physical scalar, vector, and tensor fields such as charge, bound current, vorticity, defect density, and stress. We develop a general theoretical framework in which a physical field is generated from a more primitive parent field through a local physical operator. In Fourier space, the spectrum of the derived field is determined by the product of the parent-field spectrum and the Fourier symbol of the operator. When the operator embodies a local gauge-like constraint, its Fourier symbol possesses zeros at small wavenumber, eliminating the corresponding long-wavelength fluctuations. As a consequence, the derived field exhibits complete suppression of infinite-wavelength intensity fluctuations, irrespective of the large-scale disorder and nonhyperuniformity of the parent field. We demonstrate this mechanism in elastic, electrostatic, and magnetostatic settings, showing that operator-generated incompatibility, bound charge, and bound-current fields can become hyperuniform even when their parent eigenstrain, polarization, or magnetization fields remain conventionally disordered. These findings broaden the notion of hyperuniformity from a structural property of matter to a universal field phenomenon generated by local physical constraints.

Semi-analytic models of black-hole movies require both an emitting flow prescription and a time-dependent source variability. Existing prescriptions are often limited to either equatorial emission or time-independent sources. In this work we present a unified model for these two ingredients. First, we prescribe an off-equatorial, nongeodesic Kerr fluid rotation law by lifting an equatorial specific-angular-momentum profile to cylindrical surfaces, setting the polar component of the four-velocity to zero, normalizing the flow with the full Kerr metric at the spacetime point, and retaining the option to recover a geodesic-like plunging prescription when needed. Second, we use this velocity as the disk advection field in a four-dimensional inhomogeneous, anisotropic Matérn-like Gaussian random field. We provide a parametrized model for a torus-like disk and a central jet through a single composite correlation tensor. The resulting effective model is an implementation-ready prescription for time-dependent thick-disk and disk-jet emission for relativistic studies.

Nanophotonic platforms have multiple properties and features desirable for producing correlated photon pairs. In these platforms, spontaneous parametric down-conversion (SPDC) and spontaneous four-wave-mixing (SFWM) have been used to achieve photon pair production. By placing the nonlinear region in a resonant cavity, the source obtains an enhanced nonlinear interaction and naturally filters out photons by frequency according to the cavity linewidth. Among various platforms, X-cut thin-film lithium niobate (TFLN) stands out for its strong second-order optical nonlinearity ($\chi^{(2)}$) and access to a strong platform for modulating light. Although previously demonstrated, present sources are limited in their photon pair channel availability, limiting the potential of quantum applications in quantum information processing, communication, and sensing that can scale in robustness by having access to multiple photon pair channels. To this end, we demonstrate a photon pair source on X-cut TFLN with 80 measured photon pair channels spanning the C and L optical bands with a frequency spacing of 49.5 GHz between photons. We characterize the second-order correlation function and pair generation rate (PGR) of 80 channels, the highest number of channels demonstrated to date, and achieve a pair generation of 125.7 kHz / {\mu}W after accounting for the cavity's escape efficiency. We also demonstrate heralded single photon operation by calculating a heralded auto-correlation dip of 0.0544 $\pm$ 0.0054 with 2.2 mW of on-chip pump power. These findings demonstrate the promise of X-cut TFLN as a strong platform for quantum optical applications.

We develop a comprehensive formalism for magnon transport in ferromagnetic insulators driven by a temperature gradient. The formulas for magnon current and corresponding magnon noise are derived herein based on the spin Hamiltonian of a topological magnon insulator, which enables us to calculate the magnon Hall angle, to provide an explicit expression for the Fano factor, and to reaffirm the quantitative relations between magnon conductance and magnon noise. We find that the magnon current is not conserved in the presence of the Gilbert damping. Consequently, the reciprocal relation between the local and nonlocal noises, the Johnson-Nyquist formula between the conductance and the thermal noise, and the relation between the transmission coefficient and the shot noise are profoundly altered.

Organic mixed ionic electronic conductors (OMIECs) are a promising class of polymer materials for applications spanning neuromorphic computation to energy efficient electronics and bioelectronics. Despite being highly tunable, the relationship between structural features and key performance properties such as charge carrier mobility is poorly understood. Scanning nanodiffraction in the transmission electron microscope (TEM) is a powerful probe for elucidating this structure-property relationship, but produces large, noisy datasets that are difficult to interpret because polymer reflections exhibit several distinct morphologies. To address the complexity, we trained a machine learning (ML) model to detect these polymer diffraction peaks and their intensities from synthetic data. Compared to correlative peak detection algorithms, the conventional method for analyzing nanobeam 4D scanning transmission electron microscopy (4DSTEM) data, we show that the ML model is significantly faster and outperforms correlative algorithms in almost all cases, opening up the possibility of near-live visualization of 4DSTEM experiments.

Single-photon emission in two-dimensional single-layer WSe2 is attractive for the on-demand generation of quantum states of light. The electronic states that are responsible for single-photon generation preferentially form in regions of localized tensile strain, enabling deterministic positioning and strain engineering. Nanoindentation of single-layer WSe2 yields controlled and reproducible deformations that generate the localized strain needed to activate the single-photon-emitting states. However, using nanoindentation both for investigating structure-property relationships and for manufacturing quantum light sources based on WSe2 is hindered by key questions on the structural integrity of the indented 2D material, the resulting strain generated, and the sub-micron location of the emitters. In this work, we study the structure of indented single-layer WSe2 using a fabrication process that inverts the indents into protruding pillars that can be probed using electron microscopy. We explicitly identify strain relaxation of the indented single-layer WSe2 due to tearing and confirm that single-photon-emitting states still form in these systems, likely at the extremities of the tear. For indents that are confirmed to be intact (i.e., not torn), we assess the ability to strain engineer the single-photon emitters. While strain does not strongly affect the emission energy or the brightness, we find that increased strain reduces the spatial density of emitters. This trend indicates that an optimal amount of strain is needed for emitter formation and/or the emitters preferentially form on the periphery of the indent. Our investigation provides insight into the most relevant structure-property relationships for using strain to engineer quantum light sources in single-layer WSe2 and other 2D semiconductors.

Signal dissipation in large-scale neural networks can lead to information loss and ultimately to computational failures, necessitating local signal amplification at neuron - synapse connections. In biological nervous systems, axons are responsible for local signal amplification. Translating axon functionality into hardware, i.e., the ability to amplify and transmit signals without loss, is non-trivial because emulating the human brain implies building networks composed of ~10 billion interconnected neurons, each requiring a dedicated compact and scalable amplifier. Here, we demonstrate signal amplification in simple two-terminal devices made of a metal-insulator transition material. By operating the devices on the verge of the phase transition and taking advantage of negative differential resistance, we achieve robust signal amplification up to a factor of ~11.5. We also demonstrate the amplification of spiking sequences generated by a real neuristor, opening new exciting opportunities for the direct integration of artificial neurons and axons. The amplification can be controlled by easily adjustable experimental parameters, including DC bias, AC excitation, series resistance, and temperature. We further propose a model that predicts the gain using readily observable transport characteristics. Our results establish a framework for developing and optimizing axon-like amplification functionalities in nonlinear electronic materials.

We solve the two models for Glauber dynamics and in equilibrium, both in the presence and absence of the external magnetic field on a complete graph. We compare the steady state of the Glauber dynamics with equilibrium and find that for low values of variance $R^2$ of the Gaussian random field, the steady state of the Glauber dynamics depends on the initial state. Beyond a critical value $R_{c}$ the equilibrium and non equilibrium steady states coincide. The variance $R$ in random field models behaves similar to the temperature. The location of both the continuous and first order transitions can be obtained exactly for the Glauber dynamics steady state. The frustration is introduced by considering repulsive bi-quadratic interaction for Blume-Emery-Griffiths model. We also consider repulsive bi-quadratic interaction and show that $R_c$ can become zero depending on the value of the crystal field. Interestingly, we also find that even when a system has $R_c=0$ at the start of quasi-static evolution with Glauber dynamics, with increasing $R$, in some regime of the couplings, the model undergoes a crossover to a random field Ising model universality with $R_c$ changing from $0$ to $\sqrt{\frac{2}{\pi}}$. In the presence of uniform magnetic field, regions of first order transition exhibit hysteresis under Glauber dynamics. These models exhibit rectangular, hexagonal, parallelogram, wasp-waisted, and double hysteresis loops. We derive the shapes of hysteresis loops analytically and also the equation for the coercive field. We show that while the area under the hysteresis loop depends on $R$, the shape is determined by the behavior of the models at $R=0$. In particular, in the case of Blume-Emery-Griffiths model the hysteresis plots have regions of continuous and first order transitions both, resulting in a rich phase diagram that depends non-trivially on the initial state.

We present a message passing formalism to study the age-targeted robustness of networks that have evolved under the addition and deletion of vertices. We show that in the growing regime removing the oldest vertices fragments the network far sooner than random failure, while the oldest core is far more robust under targeted removal of the young. At a balanced turnover of vertices the attack value vanishes identically and we prove that the giant component is invariant under arbitrary age-targeting.

Black-hole hair can affect boundary mixed-state entanglement through local stress-energy and through topological information invisible to the classical metric. We separate these channels for a Nielsen–Olesen vortex on a nonrotating BTZ black hole. A superselection theorem shows that Shannon sector entropy cancels from the Markov gap, while standard $U(1)$ symmetry-resolved reflected entropy in a thermal $U(1)_k$ CFT is equipartitioned at leading order, excluding a universal $\log|n|$ term in the imbalance-resolved gap. We therefore define a Wilson-threaded reflected moment in a probe $U(1)_k$ Chern–Simons completion coupled to the compact vortex-flux class. In a reflected-replica sector with linking number $\nu$, its normalised phase is $2\pi\kappa pn\nu/k$, where $\kappa\in\mathbb Z$ is the mixed topological coupling; for $\gcd(\kappa\nu,k)=1$, a discrete Fourier transform reconstructs $n\bmod k$. The RT connectivity transition switches the specified linked contour on or off, whereas the independent scale $\ell_\star r_+/L^2=1.128378\ldots$ determines the direction of the vortex-induced shift of that transition. The charged-moment modulus and the ordinary Markov gap remain geometric observables and are computed from a horizon-anchored Einstein-Abelian-Higgs solution with a complete first-variation kernel including the motion of the entanglement-wedge cross-section endpoints. This phase and modulus separation distinguishes topological hair from gravitational dressing without assigning an unsupported winding-dependent entropy.

Microscopic motors are commonly monitored through a single mechanical coordinate, whereas the chemical, conformational, or rotational cycles that sustain their motion remain unresolved. Mechanical stall is defined by the vanishing of the mean observed velocity; this scalar condition, however, does not generally imply thermodynamic reversibility. We analyze an overdamped Brownian motor in which one observed coordinate is coupled to several internal phases through a single shared interaction potential. Because the transmitted force and the reaction torques derive from the same energy, the resulting rank-one reciprocal structure yields an exact pointwise identity between the observed and hidden probability currents. This identity provides an exact expression for the entropy production at stall for an arbitrary periodic interaction. In particular, a positive current-square dissipation in the mechanical channel, defined from the full stationary state through the coupling-coordinate-resolved local velocity, determines together with the stall load the collective hidden current projected onto the coupling direction. The stationary one-coordinate marginal current nevertheless vanishes identically at stall; consequently, the stationary marginal density and mean displacement current do not determine this dissipation. Hidden currents orthogonal to the coupling direction dissipate without affecting the observed motion and generate an irreducible contribution that cannot be inferred from the rank-one mechanical channel.

An alternative explanation is presented for recent reports that attribute sustained chemiluminescence (CL) and electrochemiluminescence (ECL) from electrogenerated microbubbles on steel or copper electrodes in aqueous luminol solutions (over 2-30 V range) to the spontaneous formation of hydroxyl radicals at the gas-water interface. Our experiments with a broad set of electrodes, viz., steel, copper, aluminium, and platinum, reveal that while microbubbles can be electrogenerated on all electrodes, CL is exhibited by steel and Cu only and not by Al and Pt. These observations establish that the gas-water interface of microbubbles is not the site for hydroxyl radical generation (else CL would be recorded in all cases). Complementary quantification of H2O2 in these experiments reveals its electrode dependence as follows: Al > Cu > Steel > Pt. This establishes that depending on the electrode, H2O2 forms first, and in some cases, hydroxyl radicals are observed (i.e., where CL/ECL is seen). Experiments with NMR and EPR spectroscopy revealed that: (i) H2O2 formation occurs only when O2 is present in water; and (ii) while steel and copper generate hydroxyl radicals through 1-electron reduction of H2O2, Al does not promote one-electron reduction of H2O2 to generate hydroxyl radicals, and Pt preferentially promotes disproportionation of H2O2 to H2O and O2. In fact, we demonstrate that H2O2 and hydroxyl radicals can be observed at specific metal-water interfaces even without microbubbles, confirming that the solid surface is the reactive site. Therefore, this work affords electrode-based predictions of whether or not electrogenerated microbubbles would yield CL in luminol solutions and calls into question the notion of spontaneous formation of hydroxyl radicals at gas-water interfaces.

Accurate prediction of crystal properties remains a key challenge in computational materials science. While graph neural networks (GNNs) such as CGCNN, MEGNet, ALIGNN, and SchNet have shown strong performance, they primarily represent crystals at the atomic level and implicitly learn local chemical environments through message passing. However, many material properties are governed by coordination polyhedra, the fundamental structural units formed by atoms and their neighboring atoms. To address this limitation, we propose the Coordination Polyhedron Graph Network (CPGN), a multi-scale GNN that jointly learns atomic, bond, and coordination-polyhedron representations. CPGN constructs three coupled graphs: an atom graph encoding elemental and bonding information, a line graph capturing angular interactions, and a coordination polyhedron graph describing Voronoi-derived local environments through corner-, edge-, and face-sharing relationships. Physically meaningful geometric descriptors are incorporated for each polyhedron, while an interleaved message-passing mechanism with bidirectional cross-attention enables effective information exchange across structural levels. Extensive evaluations on the Materials Project, JARVIS-DFT, and QM9 benchmark datasets demonstrate that CPGN outperforms existing state-of-the-art GNN models. It achieves a formation-energy MAE of 0.060 eV/atom and a band-gap MAE of 0.292 eV on the Materials Project, while providing competitive multi-property prediction on JARVIS-DFT and superior HOMO prediction on QM9. The results highlight that explicit modeling of coordination polyhedra improves crystal representation learning and enables accurate, physically interpretable prediction of material properties.

We present various discretisation techniques that mark a departure from the classical algorithms of numerical analysis, in the aim of preserving the physical behaviour of the solutions to the differential systems we are discretising, even for discretisation steps that are not very small. These techniques are inspired by the principles laid down by Mickens and are close to those proposed by Hirota and Kahan. Detailed applications of these methods are presented for the logistic equation and for the Lotka-Volterra system. We discuss the importance of preserving positivity whenever the latter is an expected property of the solution and give a practical rule for achieving this. Possible problems arising from the discretisations we propose are also discussed. A section is devoted to discretisations of integrable systems aimed at preserving integrability. Finally we conclude this review with a discussion of the possible relevance of a discrete space-time.

Acemoglu and Robinson (2024 Nobel laureates in Economics) trace national histories in The Narrow Corridor as paths through a two-dimensional (state power, society power) space but plot none: quantifying the two axes at each moment is the labor-intensive, judgment-laden task that has kept the framework qualitative. We ask whether large language models (LLMs) can operationalize it. We introduce a reproducible, provider-agnostic pipeline that scores a country period by period using chain-of-thought (events first, then score) and in-context anchoring on prior periods, against an explicit rubric with schema-validated output. As a proof of concept we produce a twelve-country trajectory atlas (Iran, France, the United Kingdom, the United States, China, Chile, Colombia, the Democratic Republic of the Congo, Lebanon, Zambia, Somalia, and India), chosen to place at least two countries in each of the book's four Leviathan types, and compare four models. We assess the scores for consistency with an expert index (V-Dem) and for inter-model agreement, reading agreement as concurrent consistency rather than accuracy, since such indices likely appear in the models' training data, and discuss conceptually how the biases of an LLM annotator and a human expert differ. Code, prompts, runs, and an interactive gallery of the animated trajectories are released.

After geomagnetic storms erode the plasmasphere, cold ionospheric plasma flows along magnetic field lines to refill the depleted flux tubes. Previous studies have suggested that refilling undergoes two stages characterized by their distinct refilling rates; however, not all observations or models exhibit this feature, and a recent analysis indicates that only a subset of refilling events display two clear stages. In this study, we show that the magnitude of the field-aligned electron temperature gradient and initial/boundary temperature regulate the durations of both the early and late stages. Performing multivariate regressions from the results of simulating early and late-time refilling demonstrated that the length of each stage uniquely depends on the temperature gradient and initial/boundary temperature. These results suggest that variations in the temperature profile may explain why some refilling events appear single-staged in observations.

We report on two deep XRISM observations of the central and northern regions of Hydra-A's X-ray atmosphere, covering the bubbles inflated by jets from the central galaxy's active galactic nucleus. We use spatial-spectral mixing, combining Chandra's high spatial resolution with XRISM's high spectral resolution, to investigate atmospheric kinematics. The velocity dispersion in the northern region, $\sigma_v = 140^{+30}_{-20}$ km s$^{-1}$, is comparable to that in the central region ($\sigma_v = 162 \pm 10$ km s$^{-1}$). We show that motion of the large-scale cocoon shock front could be responsible for the large dispersion toward the north. The dispersion in the northeast quarter of the central pointing, $\sigma_v = 260 \pm 50$ km s$^{-1}$, is among the highest measured. This region contains an X-ray-bright feature previously identified as metal-rich, possibly gas uplifted in the wake of previous-generation cavities. Dispersions in all other quarter regions are low ($\sigma_v \leq 180$ km s$^{-1}$) and consistent with previous XRISM results from other objects. The kinetic energy at the center is comparable to the enthalpies of the cavities, while in the north it is roughly an order of magnitude smaller. The jet thus drives gas motion efficiently at smaller scales ($r < 95$ kpc) and inefficiently at larger scales ($95-317$ kpc toward the north along the jet). A bulk flow toward our line of sight of $-100 \pm 30$ km s$^{-1}$ in the southwest quarter of the central pointing, measured with respect to the central galaxy, is also observed, possibly due to sloshing. No significant bulk motion was detected in any other region.

We introduce a novel discretization of the incompressible Euler equations based on their interpretation as geodesic equations on the Lie group of volume-preserving diffeomorphisms. It is well known that encoding diffeomorphisms and their infinitesimal generators through a discretized Koopman representation places a nonholonomic constraint on discrete velocities, for which there is no consensus on a variational treatment. We show that taking the vakonomic perspective, as opposed to the usual perspective of Lagrange–d'Alembert, yields discrete fluid trajectories that remain geodesics on a (sub-)Riemannian manifold. In particular, the resulting vakonomic dynamics are Lie–Poisson and their solutions admit a discrete relabeling symmetry, leading to machine-precision satisfaction of Casimir invariants along with a discrete analogue of Kelvin's Circulation Theorem. Using an efficient momentum map representation based on low-rank Clebsch variables, we show that these vakonomic fluids behave stably and consistently even at low grid resolutions, leading to increased robustness and physical realism in the long term.

Synthetic-population tools increasingly run every individual as an independent large language model (LLM) agent. Using real survey microdata, we show that this paradigm has a basic failure mode, and we set a distribution-first corrective against it, all measured with a deterministic, construct-validated verifier on non-WEIRD (Turkey-first) data. First, N independent LLM agents grounded on 2,414 real World Values Survey respondents fail to reproduce the population's response distribution: they pile onto a modal default (four scenarios x five seeds: concentration 0.36->0.69, entropy 1.46->0.77, 85% collapse, TVD=0.44), and the collapse is a predictable function of scenario structure (r=0.55 with a single-answer structure). Second, Verbalized Sampling (VS) fixes the field's chronic under-dispersion without training in three model families (fidelity +7 to +10; significant on Qwen, p=0.002, d=6.2), yet the same move universally overshoots into over-dispersion (SD-ratio 0.4-0.56 -> 1.26-1.37), a structural property of VS. Third, survey fidelity transfers only weakly to agentic behavior: in a single-model, single-domain booking task, a persona is dominated by a cheapest-default (~80%) that income modulates but does not override (comfort choice 0%->7%->32% across income bands). Fourth, a placebo-controlled memorization attack and an election backtest show VS keeps aggregate strength while subgroup and individual claims are contaminated by recall and underdetermination. We close with the corrective: model the distribution once (VS) and assign it to grounded characters at O(1) cost, with a budget-aware router whose honest AUC is 0.805, not the tautological 1.0 of a code-derived oracle. The central contribution needs no realism claim: it measures the internal inconsistency of the independent-agent route and the conditions under which the distribution-first route calibrates.

Unsteady aerodynamic phenomena, such as gusts, turbulence, and fluid-structure interactions affect an aircraft during flight. For design, optimisation and certification, it is indispensable to quantify such unsteady aerodynamic effects. Industry-standard computational fluid dynamics methods, such as solving the unsteady Reynolds-averaged Navier-Stokes equations or the linearized frequency domain method, are either computationally expensive or restricted by assumptions like linearity. Once trained, machine learning methods are capable of computing non-linear relationships very fast, making them suitable as surrogate models. By autoregressively applying graph neural networks (GNNs), operating on a discretised spatial domain, spatio-temporal predictions can be made. However, autoregressive GNNs suffer from error accumulation leading to unstable rollouts over time. Here we show that combining GNNs with augmented Neural Ordinary Differential Equations yields temporally stable predictions of the surface forces on a pitching airfoil. We found that our approach, called GNODE, based on Graph Neural Ordinary Differential Equations, provides temporally more stable, spatially smoother, and overall more accurate results than an autoregressive GNN baseline. Tests are conducted on a dataset consisting of a simulations of a pitching airfoil, including transonic shocks, transient behaviour and dynamic non-linearities. Augmenting GNODEs with additional latent dimensions improves the expressivity and accuracy by capturing underlying history effects. The developed method demonstrates an approach that is suitable to model non-linear spatio-temporal systems with exogenous inputs.

The behavior of the polarization data on $\mu_p(G^p_E(t)/G^p_M(t))$ ratio, at the present day available up to $t=-8.5$ GeV$^2$, obtained in the Jefferson Lab experiments carried out by the Akhiezer-Rekalo polarization method, demonstrates a decreasing tendency, which indicates the possible existence of a zero of the proton electric form factor $G^p_E(t)$ in the finite spacelike momentum transfer squared value. However, recently appeared two papers, investigating these data, one of them also included all other existing data on the nucleon electromagnetic structure in the spacelike and timelike regions, where the existence of such zero was questioned. Nevertheless, the reinvestigations we provide in this paper by means of the Unitary and Analytic model of the nucleon electromagnetic form factors give arguments for the possible existence of such a zero.

We report observations of faint ($10^{-6}$), concentric, planet-wide rings in the polarized flux of sunlight that is reflected by Venus, obtained during a serendipitous, 36-minute run in 2010, with the highly sensitive Extreme Polarimeter (ExPo) on the William Herschel Telescope. The rings appear to be centered slightly downwind of the sub-solar point, are visible in different filters across the visible, and are not obvious in the simultaneous total flux observations. ExPo's dual-beam exchange and double-differencing design strongly suppresses first-order instrumental polarization, and we could not identify an instrumental cause of the observed pattern. Because ExPo was dismantled before the rings were identified in the data, this is the only set of observations of these rings. We are therefore careful in claiming the detection of a new atmospheric phenomenon on Venus. However, numerical radiative transfer simulations show that planet-wide rings in polarization can arise due to density variations of 5 to 10% in the gas above the clouds, consistent with a gravity wave. Our simulations also show that such density variations would not show up in total flux observations. By presenting our observations and numerical simulations, we hope to motivate new polarimetric observations of Venus that could confirm or refute the presence of such planet-wide waves.