Papers

The motion of atoms in programmable optical tweezer arrays offers many new opportunities for neutral atom quantum science. These include inter- and intra-site atom motion for resource-efficient implementations of fermionic and bosonic modes, respectively, as well as tweezer transport for efficient compilation of arbitrary circuits. However, the exploitation of atomic motion for all three purposes and others is limited by the inertia of the atoms. We present a comprehensive architectural blueprint for the use of fermionic metastable helium-3 ($^3$He$^*$) atoms – the lightest trappable atomic species – in programmable optical tweezer arrays. This includes a concrete analysis of atomic structure considerations as well as Rydberg-mediated interactions. We show that inter-tweezer hopping of $^3$He$^*$ atoms can be $\gtrsim3\times$ faster than previous demonstrations with lithium-6. We also demonstrate a new toolbox for encoding and manipulating qubits directly in the tweezer trap potential, uniquely enabled by the light mass of $^3$He$^*$. Finally, we provide several examples of new opportunities for fermionic quantum simulation and computation that leverage the transport and inter-tweezer hopping of $^3$He$^*$ atom arrays. These tools present new methods to improve the resource efficiency of neutral atom quantum science that may also enable quantum simulations of lattice gauge theories and quantum chemistry outside the Born-Oppenheimer approximation

We identify steerable exponentially localized in-gap mode in a quasiperiodic non-Hermitian Aubry-André-Harper chain with a spatially fluctuating, zero-mean imaginary gauge field. Under open boundary conditions, the system is exactly related to the Hermitian AAH model by a nonunitary gauge transformation: the OBC spectrum and Lyapunov exponents are unchanged, while eigenstates acquire a gauge-dependent envelope. In a parameter region with spectrally isolated in-gap boundary modes, we find two exponentially localized in-gap modes with sharply different responses to the imaginary gauge field. One remains boundary pinned, but the other is gauge-steerable: it stays exponentially localized while its probability maximum shifts as the gauge field is changed, with its eigenenergy unchanged. We further show that weak on-site gain, applied at a single site chosen once and then kept fixed, can dynamically prepare this steerable mode from a generic bulk wave packet. Changing the gauge field then yields exponentially localized states at different locations.

Magnetic skyrmions are localized magnetic structures that retain their shape and stability over time, thanks to their topological nature. Recent theoretical and experimental progress has laid the groundwork for understanding magnetic skyrmions characterized by negligible net magnetization and ultrafast dynamics. Notably, skyrmions emerging in materials with altermagnetism, a novel magnetic phase featuring lifted Kramers degeneracy-have remained unreported until now. In this study, we demonstrate that BiFeO3, a multiferroic renowned for its strong coupling between ferroelectricity and magnetism, can transit from a spin cycloid to a Neel-type skyrmion under antidamping spin-orbit torque at room temperature. Strikingly, the altermagnetic spin splitting within BiFeO3 skyrmion can be reversed through the application of an electric field, revealed via the Circular photogalvanic effect. This quasiparticle, which possesses a neutral topological charge, holds substantial promise for diverse applications-most notably, enabling the development of unconventional computing systems with low power consumption and magnetoelectric controllability.

The M8.8 Kamchatka earthquake on July 29, 2025 was one of the largest in the first quarter of the 21st century. It deserves a thorough analysis including the preparation process. A smaller M7.4 earthquake occurred on July 20 with its epicenter within the confidence ellipse for the July 29 event. The aftershock sequence of the July 20 earthquake and the evolution of seismicity within the Kamchatka Peninsula region during 10 days period before the July 29 event may provide important information on the earthquake preparation and initiation processes. The CTBTO's International Monitoring System is one of the most sensitive global seismic networks comprising high-resolution array stations with enhanced sensitivity relative to three-component stations at the same locations. The International Data Centre of the CTBTO processes IMS data automatically and interactively to create a Reviewed Event Bulletin (REB), which serves as a source of information for the International Seismological Centre. Waveform cross-correlation (WCC) allows for additional detection capabilities to the IMS data and IDC processing when repeated seismicity is analyzed. The aftershock sequence of the July 20 earthquake is recovered using the WCC-based detection and phase association techniques as applied to the IMS data in order to accurately describe the spatio-temporal evolution of seismic process just before the July 29 event. With the reduced detection threshold, smaller events are found in the zones where the REB has no located sources. This finding opens up the possibility for a more detailed study of seismic and mechanical processes before the July 29 mainshock.

Despite extensive study of the liquid-gas phase transition, accurately determining the critical point and the critical exponents in fluid systems through direct simulation remains a challenge. We employ the eigen microstate theory (EMT) to investigate the liquid-gas continuous phase transition in the Lennard-Jones (LJ) fluid within the canonical ensemble. In EMT, the probability amplitudes of eigen microstates serve as the order parameter. Using finite-size scaling of probability amplitudes, we simultaneously determine the critical temperature, $T_c = 1.188(2)$, and critical density, $\rho_c = 0.320(4)$. Furturemore, we obtain critical exponents of the LJ fluid, $\beta = 0.32(2)$ and $\nu = 0.64(3)$, which demonstrate a great agreement with the Ising universality class. This method also reveals the mesoscopic structure of the emergent phase, characterizing the three-dimensional (3D) spatial configuration of the fluid in the critical region. This work also confirms the finite-size scaling behavior of the probability amplitudes of the eigen microstates in the critical region. The EMT provides a powerful tool for studying the critical phenomena of complex fluid system.

A sudden change in material properties creates a temporal interface and forces a propagating wave to change its frequency while preserving its wavenumber. In contrast to monoatomic lattices with a single frequency-wavenumber pair, polyatomic lattices support multiple frequencies for each wavenumber. To date, experimental observations are limited to topologically trivial monoatomic phononic systems. Here, we utilize analytical, numerical, and experimental methods to examine topologically non-trivial phononic lattices subject to temporal interfaces. In particular, we realize phononic lattices demonstrating single-frequency shift (i.e., mode conservation) and multi-frequency splitting (i.e., mode conversion) following a temporal interface. Accordingly, we generalize temporal analogues of Snell's law and Fresnel equations. Moreover, we utilize Bloch mode overlaps to obtain a phononic time lens and a classical analogue of dynamic quantum phase transitions for phonons. Such overlap determines the probability of mode conversion or conservation after a temporal interface and, more importantly, can carry hidden topological characteristics. Our methodology paves the way for the use of temporal interfaces in probing phonon band topology and the realization of advanced acoustic devices.

We examine the energy of a scalar field in its ground state within $q$-deformed Euclidean space. Specifically, we compute the total vacuum energy of the entire $q$-deformed Euclidean space, originating from the scalar field's ground-state energy. Our results show that, for a massless scalar field, the total vacuum energy vanishes. In contrast, when evaluating the average ground-state energy over finite, localized regions of the $q$-deformed Euclidean space, we find that the vacuum energy density can assume significant values.

A hidden variables (HVs) model is reported, which reproduces quantum predictions for Bell-Clauser-Horne-Shimony-Holt (Bell-CHSH) tests. The existence of such a model poses some limitations to quantum certifications that rely on Bell-CHSH inequality violations. The reported model does not prove wrong Bell's theorem. The latter assumes the factorability of the probability density $p_{AB}$, which rules the stochastic behavior of the HVs. The reported HVs model is based on an extended form of $p_{AB}$, which is suggested by Lebesgue's decomposition theorem for bounded functions. The considered $p_{AB}$ complies with locality and realism, and also with measurement independence, parameter independence and outcome independence.

Deformed $\mathfrak{g}_2$ exceptional applications are introduced via the Clifford algebra-parametrized formalism. Using the products between multivectors of $\cl_{0,7}$, the Clifford algebra over the metric vector space $\RR^{0,7}$, and octonions, resulting in an octonion, we generalize the exceptional Lie algebra $\mathfrak{g}_2$ applications, also associated with the transformation rules for bosonic and fermionic fields on the 7-sphere $S^7$. The emergence of $SU(3)$-like subalgebras within the exceptional Lie algebra $\mathfrak{g}_2$ provides an algebraic framework reminiscent of the $SU(3)$ gauge symmetry of QCD.

Plasma discharge devices have recently emerged as compact and versatile tools for particle beam manipulation. Building upon the Active Plasma Lens (APL) and its curved extension, the Active Plasma Bending (ABP), this work introduces the concept of the Plasma Discharge Undulator (PDU). In a PDU, a high-current discharge within a capillary generates an azimuthal magnetic field providing strong linear focusing ($O(1)$ (kT/m)), while a controlled and periodical spatial modulation of the discharge axis acts as a geometric driving term. The resulting beam dynamics can be modeled as a forced harmonic oscillator, yielding a well-defined oscillation at wavelength $\lambda_{\mathrm{PDU}}$, distinct from the natural betatron wavelength $\lambda_\beta$ related to APL focusing. Proper injection conditions result in the suppression of collective betatron oscillations, significantly reducing the intrinsic undulator strength spread typical of conventional plasma undulators, while allowing for matched beam transport thanks to APL strong focusing. Analytical models for particle trajectories and radiation emission are developed, and the one-dimensional requirements for free-electron laser (FEL) emission are evaluated, providing scaling relations and feasibility criteria for FEL operation in the proposed scheme. Theoretical estimates and multi-particle simulations indicate that the PDU can operate in the short-period regime ($\lambda_{\mathrm{PDU}} = $ mm-cm) with tunable undulator strength $K_{\mathrm{PDU}}$, supporting narrow-band radiation emission. The PDU thus provides a pathway toward miniaturized, tunable, fully-plasma-based light sources with enhanced control over focusing and spectral properties.

This paper presents an experimental framework for inducing and tuning vibration bandgaps in digitally controlled mechatronic metamaterials. A slender-beam structure instrumented with collocated piezoelectric sensor-actuator pairs distributed periodically along the length is used as the host medium, with decentralized second-order low-pass resonant filter with negative position feedback controllers implemented in real time on an FPGA platform. Unlike conventional approaches that assess bandgap formation through tip displacement, this study relies on bending strain minimization of piezoelectric sensors as the principal indicator of control-induced bandgaps. This reflects more accurately the moment-based phase cancellation dynamics similar to resonator behavior. We derive analytical expressions for transmissibility in an n x n decentralized feedback architecture and verify them experimentally using a 7 x 7 unit-cell configuration. The findings show that resonant controllers with negative feedback applied at the unit-cell level can be systematically tuned through controller gain and damping to open targeted low-frequency bandgaps and significantly improve vibration attenuation. By shifting the focus to localized dynamics, this work deepens the understanding of how control-induced bandgaps emerge and demonstrates a scalable pathway for designing programmable mechatronic metamaterials based on unconventional resonator behavior.

The bystander effect is a social psychological phenomenon in which individuals are less likely to help a person potentially in need if there are others present. Sociologists and psychologists have proposed multiple plausible reasons for the bystander effect, from situational ambiguity and social contagion to diffusion of responsibility and mutual denial. We build a new model of an individual's decision to intervene in a bystander situation based on these social psychological hypotheses, along with ideas borrowed from prospect theory. This model shows, for the first time, that the bystander effect emerges from social risk perception among non-coordinating individuals in ambiguous bystander situations. Expanding upon this static model, we explore the effect of social learning, where individuals update their perceived risk of intervening after experiencing or witnessing the social repercussions of previous interventions. A novel result of this model is that social learning exacerbates the bystander effect. We validate these models using a new database of 42 experimental and observational studies across a wide range of bystander situations, demonstrating a straightforward and generalizable explanation for the observed phenomenon, which may suggest effective interventions tailored to specific bystander situations.

Skyrmions, topologically stable field configurations, have recently emerged in classical optics as structured light for high-density data applications. Achieving controllable on-chip generation of single-photon skyrmions, while being highly desirable for quantum information technologies, remains challenging due to the nanoscale confinement of quantum emitters (QEs). Here we demonstrate a metasurface-integrated quantum emitter (metaQE) platform enabling room-temperature on-chip generation of single-photon skyrmions. Near-field coupling between QEs and propitiously designed surface arrays of meta-atoms mediates spin-orbit interaction, transforming nanoscale-localized dipole emission into free-propagating topologically structured photonic modes. By exploiting this approach for structuring quantum emission from different color centers in nanodiamonds, we realize diverse skyrmionic states, including high-order anti-skyrmions and skyrmionium, and thereby demonstrate its universality across QEs. Our work establishes a unified framework for on-chip structured quantum light sources, offering versatile control of high-dimensional topological states, such as skyrmions, and advancing scalable quantum photonic technologies.

A physics-constrained Gaussian Process regression framework is developed for predicting shocked material states and their associated uncertainties along the Hugoniot curve using data from a small number of shockwave simulations. The proposed Gaussian process is constrained by the Rankine-Hugoniot jump conditions between the various shocked material states to construct a thermodynamically consistent covariance function. This leads to the formulation of an optimization problem over a small number of interpretable hyperparameters and enables the identification of regime transitions, from a leading elastic wave to trailing plastic and phase transformation waves. Shock Hugoniots are an important measure for understanding material behavior under extreme conditions, including for the development of equations of state and determining material properties such as the Hugoniot Elastic Limit, but they are costly to generate through large-scale molecular dynamics simulations or shock experiments. Under these constraints, the proposed methodology establishes Hugoniot curves from a limited number of molecular dynamics simulations. We consider silicon carbide as a representative material and Molecular Dynamics simulations are performed using a reverse ballistic approach. The framework reproduces the Hugoniot curve with satisfactory accuracy while also quantifying the uncertainty in the predictions using the Gaussian Process posterior. These uncertain Hugoniot predictions can then be used to calibrate equation of state models, estimate material properties, or inform future experimental and/or simulation campaigns.

Pneumatic conveying is used in many process industries to transport dry, granular, and powdered solids. The triboelectrification of particles during conveying causes particle agglomeration, spark discharges, and disruptions in particle flow, making particles move upstream against the fluid flow. The effect of frequency of particle injection on particle backflow is studied using CFD-DEM simulations. Conveying flow in a square-shaped duct with fluid frictional Reynold's number equal to 180, particle Stokes number equal to 8, and individual particle charge equal to 504 fC, is simulated with different particle injection frequencies. The proportion of particles moving upstream is found to increase as the delay period between injections increases, and the effect of the length of the injection period is minimal. Further, particles moving upstream are situated in low-drag zones at the corners of the duct where the electrostatic force dominates. In conclusion, the delay period between discontinuous injections plays a major role in particle backflow. The findings of the article are important for industrial processes with discontinuous injection of particles with a risk of particle accumulation within the conveying boundary.

In industrial plants, pneumatic conveying systems are often used to convey particles from one location to another. Surprisingly, in bench-scale experiments, clusters of particles sometimes flow backward or upstream in the conveying channel. In this paper, the effect of electrostatic charge and forces on particle back-flow was investigated. Different conveying conditions with varying particle charges were simulated using computational fluid dynamics (CFD), and the resulting flow patterns were compared with CFD simulations of uncharged particles. In a channel flow with periodic boundary conditions in the streamwise and spanwise directions, it was found that electrostatic forces drive particles into low-velocity regions but do not reverse their flow. When transporting particles through a finite-length duct, electrostatic forces cause particles to settle close to the duct's inlet. Finally, when particles were injected into the duct in a pulse, back-flow was observed once particles obtained a charge of 5.04 femto-coulombs or more. The electrostatic forces decelerated the particles at the tail of the pulse and ultimately reversed their direction, whereas the particles at the head of the pulse were accelerated. Thus, it was concluded that electrostatic forces can cause particle back-flow in pneumatic conveying systems if particles are fed discontinuously.

The study of global-in-time dynamics of vacuum is crucial for understanding viscous flows. In particular, physical vacuum, which ensures a finite, nontrivial pressure-induced acceleration in the normal direction on the moving boundary, naturally arises in the motion of gaseous stars and shallow water. The corresponding large-data problems for spherically symmetric flows remain open, due to the combined difficulties of coordinate singularity at the origin and degeneracy on the moving boundary. In this paper, we analyze the free boundary problem for the barotropic compressible Navier-Stokes equations with density-dependent viscosity coefficients (as in the shallow water equations) in two and three spatial dimensions. For a general class of spherically symmetric initial densities: $\rho_0^{\beta}\in H^3$ with $\beta\in (\frac{1}{3},\gamma-1]$ ($\gamma$: adiabatic exponent), vanishing on the moving boundary in the form of a distance function, we establish the global existence of the unique classical solution with large data. Moreover, our solution is classical up to the moving boundary, and the physical vacuum is allowed for the data under consideration here when $\beta=\gamma-1$. The key ingredient of our analysis is to obtain the uniform control over the first-order spatial derivatives of the flow map $\eta(t,r)$ in spherically symmetric Lagrangian coordinates, which is achieved by some novel density-weighted estimates and flow-map-weighted estimates for the solutions.

This chapter reexamines wave function realism (WFR) through the lens of phenomenology. We begin by situating WFR within the broader debate about the ontology of the quantum state and the temptation to "read off" metaphysics from mathematical formalism. Against this background, we turn to the London-Bauer interpretation (LBI), the most explicit attempt to interpret quantum mechanics through phenomenological categories. On this view, the measurement transition is not a physical discontinuity but a reflective articulation of objectivity, and the wave function formally encodes the horizonal structure of world-givenness. We develop this idea by reconfiguring the notion of realism itself: not as objectivist, but as correlational and transcendental. The resulting picture suggests that quantum mechanics, rather than depicting a world "minus observers," mathematically articulates the very correlation through which a world becomes manifest at all.

Additive manufacturing using light is commonly constrained by serial voxel-by-voxel or layer-by-layer processing, which fundamentally limits fabrication speed and scalability. Here, we introduce a single-exposure holographic three-dimensional (3D) printing approach that synthesizes an entire volumetric dose distribution optically in one step. The method combines inverse-designed microstructured phase masks with photopolymer resins engineered for controlled optical absorption. By precisely tailoring the phase-mask topography, we generate arbitrary 3D light-intensity distributions within the resin, including intentionally encoded dark regions that define hollow internal features. Simultaneously, the resin formulation is designed to balance optical penetration with sufficient local energy deposition to achieve high-fidelity polymerization throughout the volume. Using this approach, millimeter-scale architectures comprising more than $10^{6}$ addressable voxels are fabricated in a single 7.5~s exposure, corresponding to a volumetric throughput of $\sim$1~mm$^{3}$/s ($>10^{5}$~voxels/s). The demonstrated performance is presently limited by resin kinetics and illumination geometry rather than by the phase-mask framework itself. Because the volumetric information capacity scales with the space–bandwidth product of the phase mask, this approach provides a clear pathway toward substantially higher throughput, enabling scalable fabrication of micro-optical components, biomedical scaffolds, and other precision-engineered mesoscale systems.

An elastic arch is an archetypal bistable system. Here, we combine elastica theory and photo-mechanical experiments to elucidate the mechanics of an active arch with a spatio-temporally varying preferred curvature $\overline \kappa(s)$. Our shallow-arch theory completely describes any such system via the decomposition of its $\overline \kappa(s)$ into Euler-buckling modes. Intuitively, if $\overline \kappa(s)$ overlaps with the fundamental mode, it snaps the arch up/down. Conversely, non-overlapping $\overline \kappa(s)$ drives a second-order transition to a higher-order shape. Furthermore, the form of $\overline \kappa(s)$ enables control over the instability's character; we find the forms for snapping with maximum energy release and at the lowest stimulation (both binary patterns) and design forms for symmetric and asymmetric switching pathways. Analogous control can also be achieved in boundary-driven instabilities of passive arches by fabricating them with suitable $\overline \kappa(s)$. We thus anticipate our results will improve switchable/snapping elements in MEMS, robotics, and mechanical meta-materials.

The current standard model of cosmology assumes that the majority of matter in the Universe is made of dark matter, and that the latter is fundamentally different from ordinary matter. Dark matter can in principle explain the rotation of galaxies, the gravitational lensing from galaxy clusters or the appearance of the cosmic microwave background, the oldest light in the Universe. But does dark matter really exist? Here, we review the history of this concept and its implications for the formation and evolution of galaxies. We also consider the questions that remain, the limitations of the model, and present alternative theories, in particular modifications to the gravitional law that would – perhaps – make it possible to do without it.

In frequency division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems, downlink channel state information (CSI) plays a crucial role in achieving high spectrum and energy efficiency. However, the CSI feedback overhead becomes a major bottleneck as the number of antennas increases. Although existing deep learning-based CSI compression methods have shown great potential, they still face limitations in capturing both local and global features of CSI, thereby limiting achievable compression efficiency. To address these issues, we propose TCLNet, a unified CSI compression framework that integrates a hybrid Transformer-CNN architecture for lossy compression with a hybrid language model (LM) and factorized model (FM) design for lossless compression. The lossy module jointly exploits local features and global context, while the lossless module adaptively switches between context-aware coding and parallel coding to optimize the rate-distortion-complexity (RDC) trade-off. Extensive experiments on both real-world and simulated datasets demonstrate that the proposed TCLNet outperforms existing approaches in terms of reconstruction accuracy and transmission efficiency, achieving up to a 5 dB performance gain across diverse scenarios. Moreover, we show that large language models (LLMs) can be leveraged as zero-shot CSI lossless compressors via carefully designed prompts.

Vortex light, a unique optical field that carries orbital angular momentum (OAM), has attracted considerable attention in recent years. In this paper, we present a detailed theoretical analysis of OAM transfer from the input field to the generated signal field in a four-level double-Lambda system via the four-wave mixing (FWM) process, showing that their OAMs follow a specific algebraic relationship. We identify the optimal conditions for efficient vortex light transmission, analyze the influence of detuning on transmission efficiency and phase distortion, and specifically examine the scenario where the control field carries OAM the latter being essential for a complete characterization of OAM conservation in the FWM process, while all three aspects have been largely overlooked in the existing literature. Furthermore, we investigated the tunability of the group velocity between the probe and signal fields by modulating the Rabi frequencies of the two control fields and the relative phase between the probe and signal fields during the FWM process. We demonstrate that the conversion between matched vortex slow and fast light can be realized an effect that has not been widely explored in dual-Lambda-type systems. These results may hold promise for applications in quantum information storage and processing, quantum computing, and ultrasensitive detection.

Programmable photonic integrated circuits (PPICs) offer a versatile platform for implementing diverse optical functions on a generic hardware mesh. However, the scalability of PPICs faces critical power consumption barriers. Therefore, we propose a novel non-volatile PPIC architecture utilizing MEMS with mechanical latching, enabling stable passive operation without any power connection once configured. To ensure practical applicability, we present a system-level solution including both this hardware innovation and an accompanying automatic error-resilient configuration algorithm. The algorithm compensates for the lack of continuous tunability inherent in the non-volatile hardware design, thereby enabling such new operational paradigm without compromising performance, and also ensuring robustness against fabrication errors. Functional simulations were performed to validate the proposed scheme by configuring five distinct functionalities of varying complexity, including a Mach-Zehnder interferometer (MZI), a MZI lattice filter, a ring resonator (ORR), a double ORR ring-loaded MZI, and a triple ORR coupled resonator waveguide filter. The results demonstrate that our non-volatile scheme achieves performance equivalent to conventional PPICs. Robustness analysis was also conducted, and the results demonstrated that our scheme exhibits strong robustness against various fabrication errors. Furthermore, we explored the trade-off between the hardware design complexity of such non-volatile scheme and its performance. This study establishes a viable pathway to a new generation of power-connection-free PPICs, providing a practical and scalable solution for future photonic systems.

We report a comprehensive experimental study of spontaneous Brillouin scattering in a few-mode optical fiber, resolving both forward and backward scattering processes for intra- and inter-modal interactions. Using heterodyne detection, Stokes and anti-Stokes components without external acoustic excitation are observed and quantitatively extracted Brillouin shifts, linewidths, and gain coefficients. Forward scattering is mediated by guided torsional-radial acoustic modes with frequencies ranging from MHz to GHz, while backward scattering involves longitudinal core-guided modes at frequencies of tens of GHz. These results provide calibrated benchmarks for Brillouin interactions in few-mode fibers, offering insights relevant to phonon-based quantum applications and mode-selective optomechanics.

Machine learning-based flow field prediction is emerging as a promising alternative to traditional Computational Fluid Dynamics, offering significant computational efficiency advantage. In this work, we propose the Geometry-Parameterized Dual-Encoder Physics-Informed Neural Network (GP-DE-PINN) with a dual-encoder architecture for effective prediction of unsteady flow fields around parameterized geometries. This framework integrates a geometric parameter encoder to map low-dimensional shape parameters to high-dimensional latent features, coupled with a spatiotemporal coordinate encoder, and is trained under the Navier-Stokes equation constraints. Using 2D unsteady flow past petal-shaped cylinders as an example, we evaluate the model's reconstruction performance, generalization capability, and hyperparameter sensitivity. Results demonstrate that the GP-DE-PINN significantly outperforms the PINN with direct geometric input in flow field reconstruction, accurately capturing vortex shedding structures and pressure evolution, while exhibiting superior generalization accuracy on unseen geometric configurations. Furthermore, sensitivity analyses regarding geometric sampling and network width reveal the model's robustness to these hyperparameter variations. These findings illustrate that the proposed framework can serve as a robust and promising framework for predicting unsteady flows around complex geometric obstacles.

Melting is omnipresent in nature and technology, with applications ranging from metallurgy, biology, food science, and latent thermal energy storage to oceanography, geophysics, and climate science, and occurring on all scales from sub-millimeter to global scales. The key objective is to understand the rate at which an object melts as a function of its size and of the ambient conditions. To achieve this it is important to be able to extrapolate from small scale experiments and observations to large or even global scales. This is done by scaling laws. However, these are only meaningful if there is no transition from one scaling relation to another one. Here we show, however, that for both fixed and freely-advected melting objects immersed in a turbulent flow a melting transition does exist, namely from slow melting at the small scales to fast melting at the large scales. We do so by controlled melting experiments and corresponding direct numerical simulations, covering four orders of magnitude in scale. The transition corresponds to the transition from a laminar-type boundary layer around the melting object to a turbulent-type boundary layer, i.e., from so-called classical turbulence to ultimate turbulence, with its enhanced transport properties. Our results thus provide a quantitative understanding of the flow physics of the melting process and thereby enable a better extrapolation and prediction of melt rates on large scales such as relevant in geophysics, oceanography, and climate science.

Heterogeneous nucleation is the main path to ice formation on Earth. The ice nucleating ability of a certain substrate is mainly determined by both molecular interactions and the structural mismatch between the ice and the substrate lattices. We focus on the latter factor using molecular simulations of the mW model. Quantifying the effect of structural mismatch alone is challenging due to its coupling with molecular interactions. To disentangle both factors, we use a substrate composed of water molecules in such a way that any variation on the nucleation temperature can be exclusively ascribed to the structural mismatch. We find that a one per cent increase of structural mismatch leads to a decrease of approximately 4 K in the nucleation temperature. We also analyse the effect of the orientation of the substrate with respect to the liquid. The three main ice orientations (basal, primary prism and secondary prism) have a similar ice nucleating ability. We finally asses the effect of lattice flexibility by comparing substrates where molecules are immobile with others where a certain freedom to fluctuate around the lattice positions is allowed. Interestingly, we find that the latter type of substrate is more efficient in nucleating ice because it can adapt its structure to that of ice.

Predicting three-dimensional (3D) turbulent flows around bridge piers is a prerequisite for assessing local scour, a primary cause of infrastructure failure. While Computational Fluid Dynamics (CFD) captures complex flow features - such as horseshoe vortices - its high cost hinders real-time risk assessment. This study presents a physics-aware deep learning surrogate using a Body-Fitted Coordinate (BFC) system, BFC-UNet, designed to rapidly reconstruct 3D Reynolds-Averaged Navier-Stokes (RANS) solutions on curved domains. Unlike voxel-based Convolutional Neural Networks (CNNs) prone to staircase errors, the proposed architecture leverages a BFC system to predict the bed shear stress accurately. By transforming the physical O-grid into a canonical computational space, the model preserves the geometric integrity of the no-slip boundary. Trained on 2,304 simulations parameterized by inlet velocity and scour depth, BFC-UNet predicts velocity, pressure, and bed shear stress distributions with an R2 value of > 0.98. It infers a full 3D domain (200,000 cells) in just 8 milliseconds on a single Graphics Processing Unit (GPU) - achieving a speed-up of five orders of magnitude over the CFD solver. Crucially, the model captures the topological evolution of vortex structures, including wake expansion and diving flows. These findings position BFC-UNet as a promising foundation for real-time digital twins, bridging rigorous fluid mechanics with data-driven efficiency.

The classical theory of lift is confined to sharp edged airfoils. The search for a more general closure condition in potential flow remained elusive for over a century. Recently, a variational theory of lift, inspired by Gauss's principle of least constraint, was proposed as a remedy. The theory was shown to recover the Kutta condition as a special case for sharp-edged airfoils. However, recent criticism of the variational theory has asserted fundamental issues and discontinuities in its predictions. The present paper demonstrates that these assertions are incorrect and arise from inconsistencies with basic principles of analytical mechanics, the calculus of variations, and ideal-flow aerodynamics, as well as from misapplications of the variational theory itself. To resolve such misunderstandings, we review foundational concepts from analytical mechanics, including least action, Gauss's principle, and Hertz's principle; the definitions of impressed and constraint forces; and the distinction between actual work and virtual work. We then place these concepts in the context of incompressible fluid mechanics, utilizing the geometric interpretation of Helmholtz decomposition. In particular, we demonstrate that, for incompressible flows subject to the no-penetration boundary condition, the pressure force is orthogonal to the entire space of kinematically admissible flows and therefore performs no virtual work. The pressure force, thus, acts as the constraint force required to ensure the continuity constraint. From an aerodynamic perspective, we show that the classical and variational theories of lift, as well as any theory based on steady, irrotational motion, are necessarily reversible and therefore inapplicable to reversed-flow configurations.