Papers

Rydberg-based two-qubit gate fidelities in neutral atom arrays are limited chiefly by laser intensity inhomogeneity and by detuning errors from frequency miscalibration, background-field drift, intermediate state light shift and Doppler shifts. Quantum optimal control can suppress the former, but no pulse can render a controlled-Z gate first-order insensitive to detuning. Here we show that this obstruction can be circumvented by designing Rydberg gate pulses with every leading-order detuning error relegated to single-qubit Z-rotations, which an echoed sequence removes. The resulting maximally-entangling ZZ gate has no leading-order response to arbitrary detunings on either atom, maintaining an infidelity below $10^{-3}$ within a much wider range of single-atom detunings than the time-optimal gates. We further show that a large fraction of residual error is dominated by population outside the computational subspace, which can be converted into heralded erasures. Our results significantly reduce the requirements on laser frequency stability and intensity homogeneity, field calibration and atomic temperature toward practical fault-tolerant quantum computing with neutral atoms.

We introduce a phase retrieval method based on harmonic field representations generated by intensity-only spatiotemporal modulation. A periodic amplitude angular modulation encodes phase information into temporal intensity harmonics, enabling wavefront reconstruction without interferometry, reference beams, or a calibrated phase modulator. We consider a disordered system that can be modeled as a phase plate and measure the intensity pattern in the far field for a rotating excitation pattern generated by a digital micromirror device (DMD). We extract the harmonic components of the spatiotemporal speckle and exploit a gradient-based optimization algorithm to retrieve both the optical phase in the plane of the camera corresponding to a plane-wave illumination and the effective phase plate that represents the disordered system. We demonstrate experimentally the accuracy of the approach in quantitatively estimating and compensating for phase distortion ranging from low-spatial-frequency aberrations to high-frequency distortions of a ground-glass diffuser. The proposed approach establishes a new route toward calibration-free phase retrieval using intensity-only measurements.

Computing density-functional response properties requires contracting derivatives of the exchange–correlation (xc) energy with perturbed densities on a grid. While the xc functional's derivatives have long been available to high orders from libraries such as Libxc, the surrounding contraction layer - the chain rule that combines them with the grid-based basis-function and density data into the total xc contribution - has instead been hand-derived and hand-coded in every program, for every functional family, spin case, and property. We present libxckernel, a library that automatically generates this layer by symbolic differentiation. The xc functional's ingredients are expressed as sesquilinear forms in the density matrix, so the xc energy can be differentiated to any order while the functional derivatives remain opaque. The basis functions and the orbital coefficients may both be complex. The chain rule then produces any xc matrix element: Fock matrices, orbital Hessians, and response terms of any order. Terms sharing a pattern are collapsed for efficiency. Extensible plugins emit the expressions as NumPy Einstein sums, compiled C kernels with C++/Fortran interfaces, or host-program specific source code. libxckernel is free and open-source software under the BSD-3-Clause license, enabling rapid implementation of functionality missing from many electronic structure programs. We demonstrate it by extending Psi4 with meta-generalized gradient approximation (mGGA) response kernels for orbital stability analysis and time-dependent density-functional theory (TD-DFT), GGA and mGGA analytic nuclear Hessians, and exact quadrature grid response, and by extending GPAW with mGGA and triplet TD-DFT kernels and gradient-corrected kernels for periodic dielectric response.

In this study, direct numerical simulations (DNS) are employed to investigate NOx formation in turbulent lean premixed hydrogen-air flames under engine-relevant conditions. Various turbulence intensities and molecular transport models are examined to isolate the individual impacts of turbulence intensity, Lewis number, and preferential diffusion on local and global NO production. Results show that global NO production is significantly enhanced in all of the turbulent cases, reaching approximately five times the value of the 1D steady flame at a mixture residence time of 0.1 ms. Increasing turbulence intensity is found to have three competing effects on NO formation: (1) it strengthens turbulence-instability interactions by inducing local super-adiabatic hot spots and elevating the concentrations of key flame radicals within the flame brush, thereby promoting the NO reaction rate locally; (2) it accelerates the turbulent flame speed, reducing the flame-brush residence time and thus suppressing NO production globally; and (3) it reduces post-flame temperature fluctuations, suppressing thermal NO enhancement in the post-flame zone. As a result, the global NO production is slightly lower at higher turbulence intensities among all the turbulent cases considered. Lewis number effects are identified as the primary mechanism driving thermodiffusive NO enhancement, with preferential diffusion playing a secondary role, as evidenced by the nearly identical mean profiles of the NO reaction rate between unity Lewis number turbulent flames and their 1D steady flame counterparts in both the progress variable space and the residence time space. Finally, an excellent correlation between the peak conditional mean NO reaction rate and the stretch factor is identified, and a conceptual model is proposed to improve the predictions of global NO production in practical engine simulations.

Quantum systems are invariably coupled to a surrounding environment. A common theoretical method to simplify the problem is to trace over the environment under a Markov approximation, which assumes that the environment holds no memory over the timescales that the system evolves under. In interacting many-body systems, it is often not trivial to extract which of the multiple collective timescales are relevant. We consider a time-delayed waveguide QED setup with a single excitation. By fixing the maximum propagation time and increasing the number of emitters, we show that, even for small delay times, collective effects are sufficient to cause non-Markovianity. The impact of memory is intrinsically state-dependent. For superradiant states, the relevant system timescale is the superradiant lifetime while the relevant bath timescale is the end-to-end delay time. For subradiant states, both timescales depend on the structure of the specific state. Our results demonstrate the importance of prudently making Markov approximations in quantum many-body systems, and highlight potential pitfalls to avoid in scaling up quantum devices to large system sizes.

Metasurface design increasingly requires fast models that can operate across structurally distinct device families, rather than retraining a separate surrogate for every geometry class. Conventional neural network surrogates often depend on fixed-dimensional descriptors, family-specific output formats, and repeated architecture tuning, which limits their scalability across heterogeneous meta-atoms. Here, we present a unified large language model (LLM) workflow for multi-family metasurface modeling and inverse-design. Geometries, design parameters, and optical response channels were converted into a shared instruction-following text format and used to fine-tune Gemma-2-9B across 8 metasurface families. Compared with single-family baselines, the joint model simultaneously predicted the optical responses of all metasurface families while reducing the MSE for each family by an average of 56.5%. The same representation was also used for inverse design. These results show that a shared sequence-based LLM interface can provide a practical route to cross-family metasurface design while reducing the need for task-specific surrogate architectures.

We consider the motion of a charged test particle confined to the round unit sphere in a uniform ambient magnetic field. We use an extension of Noether's theorem for systems with magnetic forces to reduce the problem to a quadrature. The rotation number of a trajectory, the azimuth it gains over one oscillation in latitude, is a complete elliptic integral of the third kind in Legendre form. A trajectory closes if and only if that advance is a rational multiple of a full turn. The criterion holds on every level set of the two first integrals. Then, we differentiate the rotation number with respect to the half-cyclotron frequency and sign that derivative on each of the two branches into which a level set divides. The rotation number sees the charge, the mass, the field and the speed through a single dimensionless ratio, that of the half-cyclotron frequency to the speed. A closed trajectory therefore fixes a value of that ratio. We say how many values carry a given rational winding. The poles are attainable on a single level set, where the motion reduces to a pendulum. The field has no flux through the sphere, so it is globally exact. We compute the Mañé strict critical value of the resulting exact magnetic flow. Above that value the closed trajectories are closed Reeb orbits of an explicit contact form.

While thermal runaway occurs across diverse physical disciplines, its presence in subwavelength phase-change photonics remains unexplored because existing thermo-optical models break down near sharp optical transitions. Here, we introduce an iterative multiphysics framework coupling full-wave electrodynamics with heat transfer, and we discover optically induced thermal runaway in vanadium dioxide (VO2) nanostructures. The runaway switching threshold depends on the illumination wavelength, ambient temperature, and underlying substrate, with external thermal biasing significantly reducing the optical intensity required for runaway ignition. Our results push forward the modeling of sharp photothermal transitions and provide essential design principles for active metasurfaces, neuromorphic photonic devices, and nanoscale thermal management.

Phononic materials (PMs) with engineered resonances have been leveraged for fluid-structure interaction (FSI) with fluid flow instabilities, yielding beneficial outcomes such as transition delay, stabilized hypersonic boundary layers, and increased aerodynamic lift. Prior PM-FSI studies primarily identify spatio-temporal flow scales of interest and choose PM structural parameters producing structural dynamics conducive for FSI. However, a fully-coupled FSI system generally produces complex coupled dynamics that is not accurately captured by studying either physical system in isolation. In this context, our prior work established behavioral parameters that govern the coupled PM-FSI dynamics in a separated aerodynamic flow over a limited parameter range. Adopting this framework, this paper explores strongly-coupled high-fidelity PM-FSI simulations over a broader range of two behavioral parameters—truncation resonance frequency and displacement amplitude—to establish their quantitative (linear/cubic) relations to the coupled frequency, lift force, and circulation in the coupled system response. In addition, the results indicate the presence of distinct FSI regimes, depending on the proximity of the truncation resonance frequency or its sub-/super-harmonics to the vortex-shedding frequency. FSI dynamics ranging from multi-/single-frequency dynamics, downshifted coupling frequency due to fluid-added mass effects, generation of non-linear harmonics to convergence of FSI dynamics to the rigid plate case are observed. These results reiterate the importance of the PM frequency and amplitude in determining the coupled FSI dynamics, and the proposed quantitative relations provide a new pathway for designing PMs for aerodynamic flow control to achieve beneficial outcomes, e.g., lift force enhancement.

We propose a hybrid mirror design that places an embedded metasurface beneath a Bragg reflector, combining the low coating Brownian noise of metasurface mirrors with the low optical loss of conventional multilayer coatings. Unlike previous hybrid designs, which place the metasurface at the input surface, our design positions it below the Bragg stack, reducing the optical field incident on the loss-prone resonant layer. For a design operating at 1064 nm, we show that this reduces absorption from 24 ppm for a bare metasurface to 7 ppm for the hybrid. We introduce a general method for calculating the coating Brownian noise of hybrid metasurface-multilayer mirrors at arbitrary coupling strength, extending prior methods to coherently combine a beam-scale mean-field contribution with the periodic, sub-wavelength-scale response of the metasurface. Applying this to our design, we find a reduction in Brownian noise amplitude spectral density relative to an equivalent-reflectance Bragg mirror by a factor of 1.6. Finally, we show that this design has higher angular tolerance than a bare metasurface mirror, maintaining higher reflectance over an angular range of 1 degree. This work provides a practical path towards incorporating low-noise metasurface mirrors into precision optical cavities, while minimizing optical loss and angular sensitivity.

This proposal presents a concept design for a European high-energy heavy-ion facility dedicated to electronics radiation-effects testing, directly addressing the critical challenges of global beam time shortages and energy limitations in existing facilities. Aligned with the HORIZON-CL4-2026-SPACE-03-85 call under Horizon Europe's Cluster 4 (Digital, Industry, and Space), the facility will enhance European sovereignty in space technology by providing approximately 1,900 additional hours of heavy-ion beam time annually–a 50% increase in European capacity–and extending the accessible ion energy range up to 100 MeV/nucleon, significantly improving penetration capabilities for state-of-the-art electronics testing. The facility will leverage CERN's Low Energy Ion Ring (LEIR) synchrotron, integrating a dedicated extraction system, transfer line, and user experimental area. The project timeline includes a technical design study, followed by infrastructure and hardware production, installation, commissioning, and user operations. Funding will be secured through a collaborative framework involving CERN and the European Union, ensuring sustainable deployment and long-term operational success.

The apokamp discharge is an atmospheric-pressure plasma jet generated at the bending point of the discharge channel between high-voltage and floating-potential electrodes. The jet propagates perpendicularly to the interelectrode discharge channel without convection. In ambient air, the apokamp length reaches several centimeters, and the temperature of its tip is 100-250 {\deg}C. The typical apokamp propagation speed ranges from 100 to 220 km/s. The proposed time-dependent theoretical model explains the phenomenon. The discharge modeling confirms the tendencies observed in various experiments on the problem.

Simulation-based inference (SBI) for parameter estimation is vulnerable to model misspecification: neural summaries and density estimators trained on a specific forward model typically fail when applied to data drawn from another model, or from real observations, and no training simulator can capture the full observational pipeline of a real measurement exactly. We show that a self-supervised Vision Transformer (ViT), pretrained label-free on a fast approximate simulator, produces transferable data summaries that generalize across simulators. Without retraining, it can be reused as a frozen encoder to infer astrophysical parameters from a completely different simulator that resolves the radiative transfer explicitly, on which it has never seen either data or parameters. As a concrete use case in 21cm cosmology, SKATR, a ViT pretrained with a Joint Embedding Predictive Architecture (JEPA), serves as a foundation model for reionization inference from upcoming SKA measurements: SKATR is pretrained once on 67k low-cost, noiseless semi-numerical 21cmFAST lightcones, then frozen and applied to hydrodynamical Loreli II lightcones, where a lightweight conditional flow matching head infers five astrophysical parameters; the encoder is never shown Loreli data, its parameters, or any noise. In our comparison, SKATR yields the most precise and best-calibrated posteriors across all five parameters, matching the accuracy of the fully-supervised in-domain baseline while requiring 2.6x fewer radiative-transfer simulations. Under realistic SKA AA* noise, only SKATR remains simultaneously accurate, informative, and calibrated, outperforming even a supervised baseline retrained from scratch on noisy data. Self-supervised pretraining on computationally efficient semi-numerical simulations is therefore a viable route to calibrated, simulator- and noise-agnostic reionization inference for the SKA-era.

Many variational principles for acoustics have appeared in the literature, often introduced in an ad hoc manner by picking and choosing terms in a Lagrangian density to yield a desired governing partial differential equation. In this chapter, we show that such guesswork is unnecessary, as the governing equations of acoustics can be derived systematically from the primitive Lagrangians of classical continuum mechanics. Furthermore, we note that using Eulerian coordinates is not the only way to derive variational principles in acoustics. To this end, we review the construction of an action in the Lagrangian frame for compressible nondissipative fluids. We explore the consequences of material relabeling symmetry and the associated pseudomomentum balance, together with the boundary and jump conditions it implies. Via perturbation expansions, we show how to recover the equations of linear acoustics from each variational principle, the material frame yielding in addition the second-order acoustic energy balance. We show how weakly nonlinear approximations with variational structure emerge in each frame, in both cases for a general barotropic fluid, with the nonlinearity carried by the fluid's parameter $B/A$ and the perfect-gas results recovered as a special case.

Background: Diffusing alpha-emitters Radiation Therapy ("Alpha DaRT") enables the treatment of solid tumors using alpha particles. In Alpha DaRT, the tumor dose distribution is mainly dictated by the diffusion of the decay products of $^{224}$Ra. Due to the inherently different mechanism of dose delivery of the Alpha-DaRT source compared to sources emitting only electrons or photons, the conventional formalism of TG-43 cannot be directly applied to Alpha DaRT. Purpose: To adapt the TG-43 formalism to be used with the Alpha-DaRT model, with the specific aim of allowing commercial treatment-planning software packages to be used for Alpha-DaRT treatment planning. Methods: The effective dose rate is defined, along with an activity conversion factor. These, together with a numerical calculation that solves the model equations, allow implementing the Alpha-DaRT model predictions into the TG-43 formalism. Results: An example of calculated $F(r, \theta)$ and $g_L(r)$ tables is presented for an Alpha-DaRT treatment scenario, with the model parameters representing preclinical data on squamous cell carcinoma. Conclusions: Commercial software can be used for Alpha-DaRT treatment planning. However, the generated $F(r, \theta)$ and $g_L(r)$ tables depend on tissue parameters, as well as treatment duration, and so these tables should be generated on a case-by-case basis.

Academic libraries hold ebook collections so large that no reader can inspect more than a negligible fraction of the catalogue. Assessment of those collections rests almost entirely on usage telemetry. A title that generates no recorded interaction is treated as a title nobody wanted. That inference is unavailable on the present evidence. We separate two constructs the literature conflates: retrievability, the probability that a system returns an item to a query that already specifies it, and encounterability, the probability that an item enters a reader's attention without prior title-level intent. Following a stated protocol over work published from 2018 onward, we find three things. Large zero-use populations are robustly documented. Usage depends heavily on the measuring instrument. And no standard library metric records an item impression. The consequence is an identification problem. Recorded non-use mixes non-exposure, unnoticed exposure, rejection, and off-channel use, and no study located under our protocol decomposes it. Recommender-system research already names this problem: there, feedback is missing not at random. We close with four measurement directions that would narrow the gap without closing it.

Urban food environments may reflect broader socioeconomic inequalities, but district-level evidence remains limited in Brazilian cities. This study examined whether indicators of food retail and street-market availability discriminate between levels of social vulnerability across the 96 districts of São Paulo. We conducted an exploratory cross-sectional ecological analysis integrating the São Paulo Social Vulnerability Index (IPVS), establishment records from the Relação Anual de Informações Sociais (RAIS), and street-market data from CAISAN. Census-sector information was aggregated at the district level. Twenty districts without an IPVS classification were excluded, resulting in 76 observations. The outcome distinguished districts classified as IPVS level 1 from those classified as levels 2–7. Predictors described the densities of healthy and unhealthy food establishments, the number of street markets, and the availability of establishments selling fresh or in natura food. Eight conventional machine-learning classifiers were evaluated using leave-one-out cross-validation. Reported mean F-scores ranged from 0.62 to 0.75, with XGBoost obtaining the highest value. In the Random Forest model, the densities of healthy and unhealthy food establishments jointly accounted for approximately 60% of the total impurity-based feature importance. These findings indicate that publicly available food-environment indicators contain information associated with the district-level distribution of social vulnerability. However, the small ecological sample, class imbalance, outcome binarization, and cross-sectional design limit predictive generalization and preclude causal or household-level interpretations.

I propose a simple and progressive way of designing and fabricating complex multilayered optics, even as we scale to large numbers of layers. The approach relies on successive layers of two-by-two blocks in which light only flows in the forward direction. It exploits a proposed trapezoidal architecture that can also support self-configuration in programmable structures, with the desired linear function or matrix set up using input vectors that correspond to the matrix rows, without any iteration other than successive single-parameter power maximizations. A key required component is a layer of 2 by 2 beamsplitters. The approach can support functions corresponding to a broad range of banded diagonal matrices. Example applications include a camera that also measures phase gradients and the direct convolution of a line of inputs with a kernel based on wavelets.

A bubble bursting from a drop of finite size (a hollow droplet) is the generic bursting event in a breaking wave, yet it has been studied almost exclusively at unbounded baths. We follow it from the puncture of the film to the spectrum of a spray, in axisymmetric simulations over liquid-to-gas volume ratios $\Lambda$ from $1/16$ to $512$ and Ohnesorge numbers from $0.005$ to $0.11$. Ejection ceases at $\mathit{Oh}_1=\mathit{Oh}_c(1+2\beta/\lambda)$, with $\beta\simeq0.83$ and $\lambda=(1+\Lambda)^{1/3}$: confinement extends ejection to bubbles too small to eject at a flat surface, and the distance $\delta=1-\mathit{Oh}/\mathit{Oh}_1$ to that boundary organizes everything that follows. The collapse, driven by capillary waves, is that of a gas thread pinching next to its mouth, whether the liquid shell is punctured once or twice. The ejected volume is $M_e=C\,\delta\,V_{\rm red}$, with $C\simeq0.013$ and $V_{\rm red}=V_{\rm gas}V_{\rm liq}/(V_{\rm gas}+V_{\rm liq})$ a reduced volume. Whatever the confinement, the first droplet is smallest at $\delta\simeq0.2$ in units of the viscocapillary length $\ell_\mu=\mu^2/(\rho\sigma)$ and at $\delta\simeq0.3$ in units of the bubble radius $R_0$, where the unbounded bath also places its optimum. The largest reaches a tenth of $R_0$. Between them the census is exponential, with a scale set by $R_0$ and no lower cut-off: the smallest droplet a simulation records is set by its resolution, not by $\ell_\mu$, which belongs to the pinch singularity rather than to the droplets. Mixed over bubble populations, the census gives spray spectra in closed form, whose shape measures the population. The bursting also produces hollow droplets, each a potential new generator.

Paleo-detectors are a proposed approach to the direct detection of dark matter (DM) based on the observation of DM-induced nuclear recoils. Rather than relying on large detector masses required for conventional detectors, paleo-detectors exploit extremely long integration times, using small samples of naturally occurring minerals that have resided deep underground and accumulated damage tracks over geological timescales of order a gigayear. In this contribution, we review recent theoretical predictions for the sensitivity of paleo-detectors to WIMP-nucleus interactions within the framework of a Non-Relativistic Effective Field Theory (NREFT). We discuss both elastic and inelastic scattering processes and consider isoscalar couplings, taking into account backgrounds from neutrinos and radiogenic sources. We present projected sensitivities of paleo-detectors for different readout and exposure scenarios and compare the reach of paleo-detectors to that of conventional direct-detection experiments. For DM masses in the range $1\ \mathrm{GeV}/c^2$-$10\ \mathrm{GeV}/c^2$, paleo-detectors are expected to achieve sensitivities exceeding those of conventional experiments for WIMP-nucleus interactions mediated by all NREFT operators, with only a weak dependence on the read-out scenario or target mineral. For larger DM masses, $10\ \mathrm{GeV}/c^2$-$5\ \mathrm{TeV}/c^2$, paleo-detectors are projected to attain sensitivities comparable to or surpassing conventional experiments for interactions mediated by several NREFT operators, depending on the specific read-out scenario and choice of target mineral.

We draw on 't Hooft's seminal formulation of the holographic principle to analyse the methodological and conceptual role of information in quantum gravity. We argue that, in 't Hooft's work and in later developments, information functions as a substantive guiding principle. We distinguish three aspects of this role: First, holographic bounds on the amount of information that can be stored in a region function as theory selection criteria that constrain viable quantum gravity theories. Second, holography functions as a principle of theoretical equivalence: the bulk and boundary theories must describe the same physical content, even though 't Hooft privileges a more fundamental, lower-dimensional, and potentially deterministic boundary description. Third, the distribution and encoding of information connect 't Hooft's proposals to contemporary work on bulk reconstruction, holographic quantum error correction, and ER=EPR, where emergent spacetime structure is tied to patterns of entanglement and redundancy. On the basis of these three roles, we argue that purely epistemic or Shannon-style conceptions of information are inadequate in this context: we instead outline a distinction between what we call maximal and intermediate conceptions that aim to capture the methodological and interpretative roles of information in holographic quantum gravity. We therefore suggest that, in the context of holography and quantum gravity, a more systematic philosophical treatment of the role of information as an interpretation-guiding principle would be desirable.

Macroscopic hydrogen transport codes model material interfaces with local thermodynamic equilibrium (LTE), imposing continuity of chemical potential as a per-species constraint. Three assumptions hide in that condition: fast interfacial equilibration, a single exchange pathway between the two sides, and a carrier species known in advance on each side. The literature scrutinises the first, but the other two are the more consequential failures, and neither survives at a metal/molten-salt interface. We replace the constraint with reversible reaction channels at the interface that obey mass action, with detailed balance fixing each ratio of rate constants from the thermodynamic data that already parameterise LTE, and we implement the framework in festim. LTE is recovered as the fast-kinetics limit of a single channel, in both its Sieverts/Sieverts and its Sieverts/Henry form, so the framework generalises LTE and does not compete with it. A Damköhler number delimits validity within a channel, a branching ratio between channels. In a representative nickel/FLiBe system, hydrogen partitions kinetically between molecular and fluoride carriers. The apparent interfacial law then drifts between Sieverts and Henry with loading and salt redox state, and an LTE condition underestimates the steady permeating flux. The measured pressure exponent is set by the branching ratio, not by any fixed property of the salt; a redox sweep at fixed temperature should continuously shift it between 0.5 and 1. With two isotopes, two metal-side species feed five salt-side carriers, and a per-species LTE condition is ill-posed.

As generative AI gains traction, researchers are investigating its potential to serve as proxies for humans. From undergoing cognitive psychology experiments to experiencing an epidemic, generative agents, agents powered by generative AI models, produce realistic human behavior when prompted. This study explores the sensitivity of these generative agents' behavior to prompt modifications and varied persona names of the agents. To assess this sensitivity, we use a generative agent epidemic model, wherein each agent is prompted daily on whether it wants to isolate or commingle with other agents. We found that using synonymous prompts results in negligible changes to the model's outcomes. However, minor variations in prompts, as well as contextual changes, do influence the model's results. Lastly, our data indicates that different persona names assigned to generative agents, specifically those imbued with personas, do not significantly impact epidemic outcomes.

The deployment of advanced, AI-enabled control algorithms in tokamak experiments requires robust integration with existing plasma control system (PCS) architectures and extensive pre-experimental validation. In this contribution, we describe the integration and testing of neural-network-emulated virtual circuits for plasma shape control within the MAST Upgrade (MAST-U) PCS environment. The neural network models predict the plasma shape using the plasma current, poloidal field coil currents, and plasma profile parameters. In this paper, we explain how they are deployed via a real-time C++ inference server that interfaces with the PCS, returning the shape prediction and its Jacobian, and how, from the latter, virtual circuit matrices and updated coil current requests are computed for real-time actuation. Emphasis is placed on the validation workflow and best practices adopted to ensure confidence in the proposed control framework prior to experimental deployment. This work demonstrates practical AI-based shape control components for fusion control systems, with direct relevance for upcoming MAST-U experiments and future devices.

We predict a new viscochiral regime of electronic transport in which spatially varying Hall viscosity selects vortical flow patterns. Although uniform Hall viscosity cannot alter incompressible bulk flow, its spatial gradient redistributes vorticity, amplifying vortices in one chamber while suppressing the vortex in the other. We further determine the underlying mechanism to be generic to recirculating flows and insensitive to the details of the device geometry. The paper maps the resulting phase diagram and shows that the regime is experimentally accessible in valley-polarized bilayer graphene.

Localized surface plasmons (LSPs) supported by metallic nanostructures exhibit a great tunability of their resonance frequencies and associated spatial field distributions. In particular, nanoscale gaps and sharp corners exhibit promising near-field enhancements for applications such as biochemical sensing and nanoantennas. In this work, we investigate the optical properties of bowtie nanowire dimers excited by linearly polarized light, including polarization orthogonal to the dimer axis. To distinguish dimer-separation-induced and monomer-shape-induced effects, we compare bowtie, circular-cylindrical dimer and triangular wires. We emphasize the advantages of a Bézier-type corner parametrization with tunable curvature and employ the discontinuous-Galerkin time-domain finite-element method for numerical calculations. This enables the identification of hybrid resonances and the systematic analysis of the role of geometrical parameters. For all investigated geometries, we compare the spatially local Drude model with the spatially nonlocal Halevi model. For the specific case of silver, we demonstrate quantitative curvature-dependent LSP line shifts arising from the longitudinal nonlocality captured by the Halevi model. For higher-order LSPs, this nonlocality gives rise to a sequence of resonances that may be exploited for light-harvesting applications. Furthermore, we investigate the field enhancement associated with LSP resonances and, motivated by the occurrence of both hot and cold spots, introduce geometry-dependent measures for assessing the ability of nanostructures to enhance nonlinear optical effects, such as through the optimal positioning of SERS-active molecules. To facilitate the simultaneous study these measures, we propose the use of suitable radar charts.

Large natural earthquakes are typically mediated by frictional pulse-like rupture, which features a finite slipping zone. Recently, a comprehensive two-dimensional theory of frictional slip pulses has been developed. It predicts that pulses are categorically unstable rupture modes, whose evolution is intrinsically slow. Unsteady pulses satisfy an equation of motion expressed in terms of discrete observables, which is inherently related to their steady-state counterparts. The theory also predicts a transition from decaying to slowly growing pulses. Here, we perform extensive lab earthquake experiments to test the theory. The experiments confirm the theoretical predictions for pulse-like lab earthquakes over a range of prestress levels, rupture nucleation conditions and small-scale fault roughness amplitudes. Specifically, the predicted time-dependent dynamics are tested in a plane defined by the evolving pulse size and peak slip rate, along with measurements of the dimensionless growth rate of pulses, demonstrating their intrinsically slow unsteady nature. The predicted transition between decaying and growing pulses is also experimentally demonstrated. These results constitute major progress in understanding a dominant earthquake rupture mode.

Highly resolved computational fluid dynamics (CFD) simulations are essential for design but too expensive for dense design-space sampling. This chapter presents an AI-driven CFD workflow that combines scalar-response modeling and reduced-order dynamics using jet-in-cross-flow examples. A reacting hydrogen jet-in-cross-flow study is first used to train a multilayer perceptron (MLP) mapping injector spacing to unburnt hydrogen throughput, wall heat transfer, and bulk temperature concentration, with shape-preserving interpolation as a baseline. The CFD samples show a non-monotonic spacing response, and the MLP identifies an intermediate-to-wide favorable region near eight jet diameters. Leave-one-sample-out validation shows strong dependence on the predicted quantity: the bulk temperature concentration is robust, while heat transfer and unburnt hydrogen throughput are substantially harder to predict. Sparse Identification of Nonlinear Dynamics (SINDy) is then used as a reduced-order modeling framework for field-derived Reynolds-stress statistics. The parametric SINDy model provides compact field-level predictions at simulated and out-of-sample spacings, though its aggregate spacing-mean Reynolds-stress error is $6.7\%$ higher than the POD-basis reconstruction because of degradation at selected cases. The broader conclusion is that AI-driven CFD is not a single-model prescription: MLPs are effective for fast scalar responses, while POD–SINDy is better suited when transient reduced dynamics and field-derived statistics are central to the question.

Bright quantum emitters are key components for quantum communication systems. Radiative point defects in gallium nitride (GaN) are promising candidates for room-temperature single-photon emission, operating from the visible to the telecom O-band. Despite their potential, their integration into photonic structures has remained limited in the literature, with experimental photon extraction efficiencies far below simulated predictions. To identify the origin of this limitation, we investigate visible and near-infrared quantum emitters in GaN epilayers grown on $c$-plane sapphire substrates exhibiting narrow linewidths ($\sim$4 nm), high photon count rates ($ > $2 MHz), and strong antibunching, reaching $g^{(2)}(0)$ values as low as 0.06 at room temperature. We find that these emitters are located near the GaN/substrate interface, explaining their limited coupling to optical modes. Building on this observation, we show that the insertion of a thin low-temperature GaN interlayer enables the formation of quantum emitters at arbitrary depths with sub-60 nm accuracy, independent of the substrate. The intentionally introduced emitters retain optical properties comparable to naturally occurring ones, including narrow linewidths ($\sim$6 nm), saturation count rates exceeding 1.5 MHz, high Debye-Waller factors (0.69-0.98), and strong antibunching. The resulting epilayer fully coalesces within less than 250 nm ensuring compatibility with GaN-based cavity fabrication and enabling emitter placement within intrinsic regions of p-i-n diode architectures. These results mark a decisive step toward efficient emitter-cavity coupling, enabling the realization of cavity-enhanced quantum emission in GaN.

This work explores the sputtering of additively manufactured (AM) materials for use in gridded ion source applications. The first part of the paper uses 316L stainless steel as an example to demonstrate that additively manufactured material does not exhibit adverse sputtering behavior, such as higher sputter yield, compared with conventionally manufactured material. To this end, three additively manufactured 316L stainless steel samples were exposed to the beam of a KDC-40 electrostatic gridded ion source at three distinct energy levels of 400, 600, and 800 eV on each side of the sample for a duration of one hour. The samples were masked to create a distinct boundary between treated and untreated regions, identifiable using profilometry, and were biased to -18V for testing. Samples were then examined using a Bruker optical profilometer and further processed using the open-source software Gwyddion to evaluate the sputtering yield. The sputter yield varied in the range 0.2-2 atoms/ion for 400-800 eV ions and increased with ion energy. The measured sputtering yield was fairly consistent with predictions from analytical models developed in prior literature, while exhibiting some variations potentially due to added effects of increased temperature and oxide layers. The second part of the paper demonstrates feasibility of using an additively manufactured tungsten-rhenium grids in existing KDC-40 electrostatic gridded ion source.