Papers

Magnetometry with nitrogen-vacancy (NV) centers in diamond has shown great promise in recent years. In particular, absorption-based magnetometry techniques, employing a cavity to enhance the absorption length, can improve the contrast and sensitivity compared to conventional techniques based on reading out the NV$^-$ triplet fluorescence. The absorption techniques rely on magnetic-field-dependent absorption at the NV$^-$ singlet zero phonon line at 1042$\,$nm and its phonon sideband. In a cavity-enhanced spectroscopy approach, we study pump-laser- and microwave-induced cavity signal changes at room temperature over a spectral range of 680-1050$\,$nm. Through normalization, we eliminate the cavity-enhancement effect and provide quasi-single-pass values for the absorption and optically detected magnetic resonance (ODMR) contrast. The highest contrast is found at 1042$\,$nm, but multiple points of high contrast are found at the peaks of the phonon sideband. Additionally, cavity-enhanced ODMR contrasts in the range of 50-80$\,\%$ are presented. We further measure the broadband singlet absorption cross section at room temperature with a novel method through microwave-induced signal changes. This method is insensitive to pump-laser-induced signal changes by other defects and quantifies the room-temperature absorption strength of the singlet transition and its entire phonon sideband. We determine the absorption cross section at 1042$\,$nm to be $\sigma^{\,\bigstar}_{1042}=(0.89\pm0.14)\cdot 10^{-21}\,\text{m}^2$ or $\sigma^{\,\blacktriangle}_{1042}=(2.9\pm0.5)\cdot 10^{-21}\,\text{m}^2$. depending on the employed 532$\,$nm NV$^-$ absorption cross section.

Here, we investigate the motion of a thin circular quantum vortex filament near the infinite planar surface. The fluid surrounding this surface moves with a non-zero velocity $\bf{v}$, which is parallel to the surface. We study the specific features of this quantum system and show that they are quite suitable for the boundary layer theory. The developed model allows us to calculate the vortex energy spectrum, $E = E({\bf p})$, where ${\bf p}$ is the total momentum of a vortex ring. We have demonstrated that this function has complex non-trivial dependence on the velocity $\bf{v}$. It is stated that the inverse effective mass of a vortex under consideration is of a tensorial nature. In certain quantum states, the system shows the possibility of both negative and positive effective mass existing. This study employs a novel quantization method for classical closed vortex filaments, developed by the author earlier.

The commercialization of next-generation technologies, including optical interconnects, quantum computing, AR/VR, and medical diagnostics, requires a low-loss photonic platform offering compact, multifunctional systems in the visible and near-infrared range. Although silicon nitride (SiN) is an excellent material due to its ultra-low loss and broad transparency window, integrating active components such as light sources, modulators and photodetectors from diverse material platforms in a scalable, reliable way remains challenging. Micro-transfer printing is an emerging wafer-scale heterogeneous integration technology that can be implemented as a back-end post-processing step without disrupting the primary in-line fabrication process. In this work, we present a dual LPCVD SiN layer platform fabricated in a 200 mm CMOS pilot line, that incorporates micro-transfer printing modules, allowing the integration of active components on well defined recesses. A hydrogenated amorphous silicon layer is also available to increase the versatility of the platform allowing for evanescently-coupled III-V lasers as well as other passive functionality in the near-infrared region. We report full wafer-scale measurements showing low optical SiN losses of 4 dB/cm and 0.23 dB/cm at a wavelength of 488 nm and 940 nm respectively. In addition, a transition loss of only 0.35 dB is obtained from the SiN to the a-Si:H layer, in good agreement with simulated values. Finally, to showcase more advanced functionality, GaAs-based gain sections are micro-transfer printed on several dies, achieving consistent die-to-die lasing at 970 nm with on-chip optical powers of approximately 1 mW. These results showcase the potential of the integrated photonics platform towards unlocking a wide range of new applications in the sub-1-$\mu$m spectral region.

Drag reduction is achieved by a steady square-wave forcing of the spanwise wall velocity, based on the experiments in Knoop et al. (Phys. Rev. Fluids, 10, 2025). Particle tracking velocimetry data are analyzed for a non-actuated reference case and actuation at forcing amplitude $A^+ = 12$ ($+$ denotes viscous scaling) for three streamwise forcing wavelengths, which correspond to sub-optimal ($\Lambda_x^+ = 471$), near-optimal ($\Lambda_x^+ = 942$), and post-optimal ($\Lambda_x^+ = 1884$) drag reduction conditions. Conditionally averaged fields on large-scale bursts of turbulent kinetic energy show that forcing suppresses near-wall ejections across all cases, while outer-layer sweep suppression strengthens with $\Lambda_x^+$. Post-optimal forcing exhibits streamwise-periodic attenuation and recovery of turbulence. The recovery phenomenon is caused by an enhancement of very small scales, significantly smaller than those typically energetic in wall turbulence, and is linked to the emergence of small-scale bursting events. While these small-scale bursts are statistically insignificant in the non-actuated and sub-optimal cases, their frequency increases by a factor of four between the near-optimal and post-optimal cases. The small-scale bursts exhibit uniform signatures and intensities, hinting at the possible universality of the recovery phenomenon. A wavelet analysis shows that, in the post-optimal case, very small scales increase progressively in the streamwise direction in regions where the wall velocity remains constant, driving a cyclic pattern of small-scale re-energization and suppression consistent with earlier statistical analysis. This turbulence modulation mechanism is scale-selective: while small-scale structures emerge periodically, large-scale motions are more effectively suppressed as the forcing wavelength increases.

Organic scintillators have been used for decades to detect gamma rays or fast neutrons at low cost. Despite extensive efforts it is still difficult to combine stability, ruggedness, high light yield, and decent pulse-shape discrimination (PSD) in a single scintillator material. We took the unusual approach of embedding phosphors and wavelengths shifters in a solid polyurethane matrix, trying to combine the robustness of a common construction material with scintillating properties and PSD performance. The plastic scintillators resulting from years of research ultimately meet these intentions. Moreover, the production process is less demanding and less complex than that of conventional plastic scintillators. It allows to directly integrate light sensors or electronics into the scintillator. This opens the door for the construction of extremely compact and robust plastic detectors for the simultaneous detection of fast neutrons and gamma rays. This paper presents basic recipes and properties of scintillators based on this novel conception and discusses first applications in neutron imaging and personal radiation protection.

Three-dimensional particle-tracking velocimetry (3D-PTV) measurements were used to compute the spectral transport of the Reynolds-stress tensor. The experimental framework is validated for a zero-pressure-gradient (ZPG) turbulent boundary layer (TBL) at a friction Reynolds number $Re_\tau = 1020$, demonstrating that the dominant non-linear energy transfer mechanisms are adequately resolved to draw flow physics-based conclusions. For the streamwise Reynolds stress in the ZPG TBL, a component-wise decomposition of the non-linear transport term is considered for the first time, which reveals distinct energy transfer mechanisms associated with the spanwise and wall-normal advection. The same experimental framework was applied to a drag-reduced ($\approx 38\%$) TBL flow, achieved by imposing a steady streamwise-alternating spanwise wall velocity. This wall forcing causes a strong attenuation of non-linear energy transfer and its shift away from the wall. The energy transfer mechanisms remain qualitatively similar to those of the canonical ZPG TBL, suggesting that the existing mechanisms simply readjust to their new low-turbulent-energy state.

Generalised continuum theories couple the macroscopic deformation and the micro-/meso-scopic deformation of an underlying micro-structure. They can account for internal length-scale effects and higher-order mechanical loadings absent from classical Cauchy elasticity and has shown its efficiency in modelling metamaterials. This has led to a proliferation of higher-grade and higher-order models (e.g. strain-gradient, micromorphic, micro-polar) whose underlying kinematic reduction strategies, in particular to reduce the number of material parameters, are rarely identifiable from the free energy alone. It leaves two open issues: the lack of a systematic criterion for selecting an appropriate model, and a persistent ambiguity regarding the physical status of the local frames (”directors of matter”) used in their kinematic description. Are they physical quantities describing the change of state of the given micro-structure or arbitrary kinematic descriptors of its deformation\,? This work addresses both questions through a gauge-theoretic formulation of generalised continua in finite strains. While relying on tools and modelling choices consistent with the existing geometric literature on continuum mechanics, the present approach departs from it in its objectives, aiming at a unifying classification of available mechanical models rather than the description of a specific microstructural phenomenon such as defects. In this work, generalised configurations are defined as moving frames over classical configurations, and invariance with respect to the reference generalised configuration is shown to be a necessary and sufficient condition for a gauge invariance, recovering the micromorphic theory as the general-purpose theory of the deformation of arbitrary directors of matter. A systematic classification of first-order generalised media follows from structural group reduction, while strain-gradient continua are recovered through convected frames, and finally constrained media (e.g. couple-stress) are addressed.

Climate change is modifying the frequency and intensity of extreme hazards in a non-uniform spatial manner, increasing the risk of damage for existing physical systems. Vulnerability modeling based on vulnerability curves provides a quantitative link between hazard intensity and physical damage, supporting adaptation strategies. This paper proposes conceptual frameworks for vulnerability models of physical systems in the context of climate change, aimed at supporting vulnerability based adaptation. A theoretical use case illustrates the methodology: potential damage on power transmission towers facing wind gust hazards across France, modeled through vulnerability curves. Despite strong assumptions, this theoretical case study demonstrates how vulnerability models can guide adaptation by reducing intrinsic vulnerability, adapting the physical system to maintain acceptable damage levels under evolving climate extremes.

Betatron coupling near the difference resonance has been explored and adopted in several fourth-generation storage rings, yet its influence on high-order-mode-driven transverse coupled-bunch instabilities has not been systematically established. Using the Hefei Advanced Light Facility (HALF) as an example, we investigate this effect through theoretical analysis and macroparticle tracking simulations. The theoretical predictions agree well with macroparticle tracking simulations in both the weak- and strong-instability regimes, validating the description over the parameter ranges considered. For the vertical HOMs studied with HALF parameters, suitable betatron coupling effectively suppresses the instability, offering potential benefits for transverse stability control.

Discrete Forman-Ricci curvature is a quantity associated to each edge of a graph that describes its local geometry. It has proven to be a useful tool in network analysis in a variety of applications. Recent work by Roost et al.\ (2024) proposed the use of Markov bases to sample from the space of graphs with prescribed vertex degrees and curvatures. In the present work, we further develop the algebraic and combinatorial theory of these Markov bases. We show that the degree of an indispensable Markov move grows at least quadratically in the maximum degree of the graph. In light of this result, a compact description of all Markov basis elements seems unattainable at present. Instead, we find a lattice basis for this problem using only degree three Markov moves, which allows us to employ recently-developed reinforcement learning methods for finding Markov moves that can be applied to a specific graph.

We report a measurement of the optical frequency ratio between the $^2\mathrm{S}_{1/2}(F=0)$–${^2\mathrm{F}_{7/2}(F=3)}$ electric-octupole (E3) transition of $^{171}$Yb$^{+}$ and the $^1\mathrm{S}_0$–${^3\mathrm{P}_0}$ transition of $^{87}$Sr, $\nu_{\mathrm{Yb}^{+}}/\nu_\mathrm{Sr} = 1.495\,991\,618\,544\,900\,588\,1(65)$. Reaching a fractional uncertainty of $4.3 \times 10^{-18}$, this result improves upon the previous best by more than a factor of three and is among the few that meet the requirements for interspecies clock comparisons specified by the roadmap towards the redefinition of the SI second. The comparison is between a transportable optical lattice clock and a stationary single-ion clock. It spans a period of nearly two years, during which the transportable clock was intermittently operated off-campus. The ratio was reproducibly measured during four separate campaigns, which are consistent within their statistical uncertainties. The results demonstrate reproducible $10^{-18}$ level operation of the transportable clock and thus validate its application for chronometric geodesy and as a transfer standard for inter-institute clock comparisons, e.g., in the absence of optical fiber links.

Dissipative equations admit distinct variational descriptions in the Bateman and Caldirola–Kanai (CK) formalisms. The classical correspondence between them is extended to a homogeneous canonical scalar field on a prescribed spatially flat Friedmann–Lemaître–Robertson–Walker (FLRW) background, where the expansion produces the time-dependent damping coefficient $3H(t)$. A multiplier action yields the Klein–Gordon equation and a complementary anti-damped equation containing the term $-3\dot{H}(t)\chi$. A first-order Bateman Lagrangian derived from the same multiplier action reproduces this physical–auxiliary pair for a general potential. Specializing to a free massive field gives the Bateman and doubled CK Lagrangians and Hamiltonians used in the canonical comparison. The factors $a^{3}(t)$ and $a^{-3}(t)$ generate the damped and anti-damped CK sectors, respectively. An explicit time-dependent canonical transformation, generated by a function linear in the Bateman momenta, maps the complete doubled CK system to the Bateman system. For this point transformation, the terms proportional to $\dot{H}(t)$ are required for Hamiltonian equivalence. In rotated variables, the Bateman scalar-field Hamiltonian takes the difference form $H_{B,\mathrm{SF}} = E_{u} - E_{v}$. It is conserved for constant $H$ and generally varies with time otherwise. For the power-law background $a(t) \propto t^{p}$, however, a correlated family at $p = 2/3$ has conserved $H_{B,\mathrm{SF}}$ despite the time dependence of $H(t)$. These results concern classical homogeneous fields on a prescribed FLRW background and exclude the gravitational phase space.

Successive personal best performances provide a natural measure of progression in an athlete's career. Classical record theory predicts a universal gap distribution, $P(g)\sim 1/g$, for independent and identically distributed (i.i.d.) sequences. However, sporting careers are shaped by learning, aging, changes in ability, and external influences that violate these assumptions. We investigate the statistics of inter-record gaps, defined as the number of innings between successive personal best scores, in cricket. Using career records of leading Test, ODI, and T20 players obtained from ESPN Cricinfo. We find that the empirical distributions are well described by truncated power law $P(g) \propto g^{-\alpha} e^{-\lambda g}$ with exponents in the range (0.799 $\leq \alpha \leq$ 0.843). Much of this deviation disappears when the temporal ordering of innings is destroyed, indicating that career evolution plays a key role in shaping record occurrence. Bootstrap-shuffled careers, which preserve individual score distributions and career lengths while removing temporal ordering, yield significantly larger exponents ($\alpha \approx 0.939\text{--}0.979$). These findings show that the progression of personal best performances retains information about the temporal organization of a player's career and cannot be fully explained by simple stochastic record processes. More generally, they illustrate how record statistics are altered in nonstationary and path-dependent systems.

We present an optimization procedure using machine learning (ML) libraries for optimization of electron beam transport for maximal bunch compression and optimal operation of a bunched-beam Superradiant FEL. This is exemplified for the parameters of the 6MeV ORGAD Accelerator at Ariel University that is driving a THz Superradiant waveguide FEL. For superradiant emission (proportionally to the number of electrons squared), the bunch duration ${\sigma}_t$ at the undulator should be shorter than the optical period (2${\pi}/{\omega}$) of the radiation. Also, the beam transport optimization must confine the transverse dimensions of the beam to enter the undulator waveguide. The variables of the ML Bayesian optimization are the RF parameters and the currents of the coils and quads along the beamline. The beam dimensions and duration are provided from full 3D GPT simulations that are automatically driven by the ML exploration and exploitation algorithms. Twenty-five simulation iterations sufficed to arrive to an optimal beam transport design.

Predicting drought risk is essential for anticipating impacts on water resources, agriculture, ecosystems, and climate adaptation planning. Yet drought forecasts remain uncertain because variability can substantially alter regional precipitation and evaporative demand. Treating this variability as unstructured noise ignores the fact that internal variability has spatial, seasonal, and temporal structure and thus contains information that can be used to improve drought forecasting. We propose a deep-learning-based forecasting framework for European drought prediction and extend it with an uncertainty-aware drought bound that explicitly incorporates internal forecast variability from a large climate model ensemble. This bound represents a physically plausible lower-tail trajectory of future drought conditions and marks how severe drought could plausibly become under an unfavourable realisation of internal variability, giving adaptation planning a conservative, risk-averse reference. We compare the proposed bound with a lower bound derived from reanalysis data only and show that our proposed ensemble-informed bound is better calibrated across most regions and seasons. This is specifically true during anomalously dry conditions, when historical reanalysis alone underestimates lower-tail drought risk. Our results show that internal variability should be treated as a forecast quantity in its own right. More broadly, large ensembles provide a practical way to transfer physically plausible climate variability into machine-learning drought forecasts, yielding risk-aware bounds that are more informative for drought assessment under shifting climate conditions.

The Internet, a living cell, a circle of friends, a billion-dollar construction project: these systems share almost nothing – yet, drawn as networks, they look astonishingly alike. Each has a few giant hubs among a multitude of sparsely connected nodes, short paths between any two parts, dense local clustering, communities, and many redundant routes. For two decades such patterns have been credited to "preferential attachment," the rich getting richer – a rule that, taken literally, asks every newcomer to survey the whole network before it links. This book makes a simpler case, and defends it one mechanism at a time: the global regularities of real networks are not imposed from above but emerge from purely local rules, in which each new node acts only on a node it has reached and that node's immediate neighbours. A surfer following links, a friend introducing a friend, a gene copied with its connections – none consults the network as a whole, yet each builds, in the aggregate, the full and unmistakable signature of a real complex system. Written for the curious reader as much as the specialist, with the ideas told in plain language and the mathematics set aside in boxes that can be skipped, it shows how citation graphs, the web, social ties, protein interactions, and project schedules all grow themselves from the same handful of local rules – one local decision at a time.

We present a spectroscopic study of argon electroluminescence (EL) light in a gaseous time projection chamber (TPC). Using a compact detector equipped with photomultiplier tubes with different spectral sensitivities, we measure the light emission in two nominal wavelength regions, approximately [110, 160] nm and [160, 650] nm, at different gas pressures. In addition to the well-known 128 nm emission of the second continuum, significant emission is observed in the [160, 650] nm band, with a prompt, nanosecond-scale response indicating that photon production closely follows the transit of drifting electrons across the high-field EL region. In contrast, the [110, 160] nm emission displays a markedly slower time evolution, dominated by excimer formation and de-excitation dynamics, with the light output governed primarily by the long-lived triplet component of the argon second continuum emission. We demonstrate that the full VUV pulse shape can be reproduced by convolving the fast UV3 response with excimer formation and decay functions, providing a coherent phenomenological interpretation of the observed signals. Our results provide new insights into the spectral and temporal properties of argon electroluminescence and have direct implications for the design and optimization of next-generation rare-event detectors based on gaseous TPCs. Further studies are underway to characterize this emission more precisely and to investigate its potential for particle discrimination.

Achieving joint quantum-enhanced precision in multiparameter sensing requires both high sensitivity and measurement compatibility. These two aspects are characterized by the quantum Fisher information matrix (QFIM) and the Uhlmann curvature matrix (UCM), respectively, with weak compatibility corresponding to the vanishing of the relevant UCM elements. Here, we develop a symmetry-projection framework that classifies phase generators into subspace-preserving and subspace-changing sectors. For probe states confined to a symmetry subspace, symmetry projection imposes a common block-diagonal structure on the QFIM and UCM, rendering cross-sector parameters simultaneously free from information cross-talk and measurement incompatibility. When the subspace-changing generators act as scalars within the occupied subspace, the corresponding QFIM block reduces to four times the symmetrized covariance matrix, even for mixed probe states. For parity-protected collective $\mathrm{SU}(2)$ systems, this structure singles out the transverse anti-squeezed quadrature and the longitudinal mean-spin direction as natural optimal sensing axes. Applied to a dissipative one-axis twisting model, the dynamically generated probe state exhibits identically vanishing UCM elements for transverse–longitudinal parameter pairs, while maintaining nearly balanced, Heisenberg-scaled QFIM components over a broad transient window. Our work opens a route to symmetry-protected, weakly compatible multiparameter sensing in interacting quantum many-body systems.

A volatile droplet gently deposited on a superheated substrate can sit on a thin film of its own vapour, which prevents contact between the drop and surface. This phenomenon is called the Leidenfrost effect. In this paper, through direct numerical simulations, we analyse characteristics of Leidenfrost water droplets with a single computational model over four decades of droplet radius, stitching together previous works in the limit of large and small droplets. Using the model, we show that the ambient humidity, an underappreciated factor in the Leidenfrost system, in combination with the flow in the drop has a significant impact on the geometry and drying kinetics. Our results imply the inadequacies of commonly made assumptions of a pure vapour phase and an isothermal droplet. When modelling large Leidenfrost droplets with an axisymmetric model, large discrepancies between experiments and the computational results occur. Through azimuthal stability analysis, we show that this is due to the unrealistic constraint of axisymmetry. This finding is supported by 3D simulations of a simplified model. Finally, some hypotheses are explored to account for the remaining discrepancies with experimental data.

Foam scraping exhibits a dynamic transition between a slip state, in which the foam moves beneath a plate, and a scraping state, in which the foam is expelled from the confined region. Although this transition has been associated with the propagation of local T1 rearrangements, the physical parameter controlling their propagation remains unclear. Here, we investigate the dependence of the critical scraping velocity on the liquid fraction, bulk viscosity, and surfactant system. For all examined conditions, the critical capillary number follows $\mathrm{Ca}_c\propto\phi^{-1}$, apart from a solution-dependent prefactor. We propose a local fluid–structure-coupling model in which viscous work transmitted through the Plateau-border network competes with the effective energetic cost required for one T1 event to trigger the next. The observed scaling implies an effective energetic cost governed by the Laplace pressure and is consistent with a small local compressive component of the bubble deformation. These results identify local coupling between interstitial flow and bubble deformation as a mechanism controlling the macroscopic slip–scraping transition.

I derive the impedance response of an ideal electrolyte containing an arbitrary number of mobile ionic species between blocking planar electrodes, described by the Poisson–Nernst–Planck equations. By transforming the linearized equations to a charge–salt basis, the response is written in terms of a multi-component diffusion–migration matrix and its eigenvalues/eigenvectors. When all diffusivities are equal, the charge mode decouples from the neutral concentration subspace and the classical binary-electrolyte result is recovered. In contrast, unequal diffusivities couple charge relaxation to one or more neutral composition modes. For a ternary electrolyte with two cations and one anion, this coupling produces additional diffusive features and broadens the crossover between resistive and capacitive regimes. The results found in this paper provide a minimal continuum explanation for why mixed electrolytes can display impedance spectra that cannot be interpreted as a simple binary electrolyte with an averaged diffusion coefficient.

We introduce a validation process that harnesses engineered many-body relaxation to control and calibrate quantum hardware. On two independently developed neutral-atom processors, we realize the many-body quantum Mpemba effect in an open system for the first time. Initial-state engineering creates fast and slow relaxation pathways: the fast pathway opens access to unreachable mixed-state physics before hardware noise obscures the target dynamics, whereas the slow pathway amplifies hidden imperfections in preparation and control. Computational-basis measurements directly and independently benchmark dynamical reliability, revealing each processor's actual operating window as a many-body simulator. The processors are thus judged by the very dynamics they are built to reproduce. Complementary responses disentangle control errors and drive an adaptive, time-resolved scheme that supplies hardware developers directly actionable corrections, enhancing faithful reproduction of the target dynamics. These results establish many-body relaxation as a transferable validation and calibration tool for programmable quantum processors.

The high-extinction cross-polarization measurement of a paraxial laser beam results in a Hermite-Gaussian ($\text{HG}_{11}$)-like four-lobes with a dark-centered cross pattern. The azimuthally spin-separated mode pattern is understood to result from the spin-orbit interaction of light. The perfect dark region at the beam center, due to extreme cross-polarization extinction (EXE), is used here to accurately determine the on-axis residual polarization of the laser beam and, using it, the residual elliptical birefringence of optical crystals. By propagating the laser beam through uniaxial optical crystals with their optic axis cut either parallel or perpendicular to the beam propagation direction and performing the EXE measurement, we demonstrate a simple approach to precisely quantify the residual elliptical birefringence of crystals, which are otherwise assumed to be absent, to a high degree of extinction of 1 part in $10^{-8}$. The experimental results are interpreted using Jones-matrix-based calculations for a paraxial laser beam and upon its propagation through the optical crystals. The high sensitivity and high accuracy of the EXE technique make it well-suited for measuring and characterizing anisotropy and its dispersion of monolayers, ultrathin films, and 2D materials.

Metallenes have appealing properties, but stabilizing them in a monolayer phase poses challenges for their synthesis. A recent experiment showed that the van der Waals squeezing method can stabilize certain metallenes in a MoS2 sandwich. This pioneering work motivates systematic studies, but such studies are experimentally impractical, while first-principles modeling remains prohibitive. Here, armed with universal machine-learning interatomic potentials, we constructed 1620 metallene sandwich heterostructures containing 6 different sandwich layers and 45 metals. We performed phonon calculations, which revealed 1208 dynamically stable structures. We found that transition-metal dichalcogenides, particularly MoSe2, are highly effective in stabilizing metallenes. Specifically, buckled hexagonal and honeycomb crystal lattices exhibit the greatest stability. We further evaluated the thermal stability of selected heterostructures with density-functional theory molecular dynamics simulations at room temperature. By uncovering the physical and chemical factors governing the stabilization of metallenes, our results provide systematic insights to guide and accelerate synthesis for future applications.

The existence of an ideal MagnetoHydroDynamic (MHD) equilibrium does not guarantee its stability. Finite toroidal mode number (n) instabilities degrade performance in both tokamaks and stellarators and differentiable stability optimization tools to date have operated only in the infinite-n limit. We present AGNI (Analysis of Global Normal modes in Ideal MHD), a GPU-accelerated, automatically differentiable finite-n ideal MHD stability solver and optimizer. AGNI discretizes the ideal MHD energy principle pseudospectrally in real space using differentiation matrices and geometric coefficients from a DESC equilibrium, giving a variational eigenvalue problem for the plasma displacement, and efficiently finds the most unstable modes. Built on jax, AGNI yields reverse-mode gradients of the growth rate with respect to boundary-shape and profile parameters without re-solving the equilibrium. We benchmark AGNI against the initial-value code NIMSTELL for a modified Landreman-Bulle-Drevlak quasi-helically symmetric stellarator and a DSHAPE tokamak,recovering the dominant mode with agreement in terms of growth rate and eigenfunction structure, and verify the automatic differentiation gradients against central finite differences. We quantify CPU and GPU cost for eigenvalue and gradient evaluation, establish the finite-precision limit on resolving near-marginal eigenvalues, and present a numerical scheme to impose incompressibility, compatible with gradient-based optimization. AGNI will allow us to optimize tokamaks, stellarators, and mirrors against ideal MHD instabilities.

Gas-phase cluster growth by monomer addition is commonly modeled as an isothermal process. We develop a survival-limited framework in which association produces a thermally excited cluster that may dissociate before either cooling through bath-gas collisions or encountering the next monomer. A continuous-energy survival probability is first derived for an individual post-association thermal trajectory and is then marginalized over distributions of excitation energy, equilibrium energy, and monomer-arrival time using a trajectory functional. Molecular-dynamics simulations of water, silver, and gold clusters provide size-dependent caloric relationships and latent heats, while event-based Monte Carlo simulations independently test the survival formulation. Theory and Monte Carlo results agree closely. The ensemble-averaged survival probability exhibits strong and non-monotonic size dependence, with the largest thermal penalties generally occurring for the smallest clusters. Intermediate-size local maxima arise only when complete cluster-energy distributions are retained and result from competition between curvature-enhanced dissociation and the narrowing of the low-energy tail with increasing size. Surviving clusters are consequently drawn preferentially from the colder portion of the pre-collision energy distribution, and mean thermal trajectories can substantially underestimate population survival. To connect single-event survival to cumulative growth, we introduce a thermal forward-rate correction relative to an isothermal reference and incorporate it into a reversible birth–death model. Although the correction at each size may be moderate, its multiplicative accumulation can increase mean first-passage times by many orders of magnitude. The framework provides a general route for identifying post-collision stabilization as a control on gas-phase cluster growth.

Achieving high-lying vibrational states is essential for actively controlling molecular reactions. We demonstrate vibrational ladder climbing of CO adsorbed on Pt(111) within the plasmonic tip-substrate nanogap formed in a scanning tunneling microscope, detected via tip-enhanced sum-frequency generation (TE-SFG). As the infrared pulse energy increases, hot-band peaks appear sequentially up to the 3-4 transition, indicating the stepwise population of higher vibrational states. Numerical analysis using the optical Bloch equations captures the observed energy dependence of these features. These results demonstrate the capability of TE-SFG to probe vibrational ladder climbing in surface molecular systems and suggest a promising route toward accessing high-lying vibrational states and controlling vibrational excitation at the nanoscale.

Quantitative strain mapping using four-dimensional scanning transmission electron microscopy (4D-STEM) typically requires densely sampled scans that can damage beam-sensitive specimens. We develop a physics-informed neural network (PINN) for sparse 4D-STEM strain reconstruction that embeds elastic equilibrium and Saint-Venant compatibility in the training loss through automatic differentiation. The architecture combines a coordinate-based implicit representation, sine activations with stable second derivatives, frozen residual-scale normalization, an exponential physics-weight ramp, and residual-based adaptive collocation. We apply a sine-activated residual network to an experimental $180\times400$-pixel strain map of domain-structured PbGeSnSe$_{1.5}$Te$_{1.5}$. Across $1$-$75%$ sampling ($720$-$54{,}000$ probe positions), $R^2$ for $\varepsilon_{xx}$ reaches $0.80$ at $10%$ sampling and saturates near $0.86$ by $25%$; the chevron strain-band morphology is recovered from $10%$ of probe positions. At $10%$ sampling, the PINN reduces mean absolute error by approximately $26%$ relative to compressed sensing and $22%$ relative to Gaussian-process regression. An ablation against an equal-capacity data-only SIREN shows that the PDE prior improves accuracy at extreme sparsity and consistently improves physical self-consistency, but biases the reconstruction when data are abundant. Monte Carlo dropout and mean-field variational inference provide per-pixel epistemic uncertainty maps correlated with reconstruction error. With an appropriate constitutive model, the framework is adaptable to strain mapping across diverse material systems.

High-quality entangled states of photons underlie quantum information science (QIS) applications across communication, sensing, and computing. In many discrete-variable photonic QIS architectures, large application-ready states (e.g., cluster states, repeater graph states) are constructed via fusion measurements on small entangled seed states, of which Bell states are the fundamental example. The quality of seed-state generation therefore sets a baseline for application performance, making it crucial to understand this process under realistic error mechanisms, particularly in integrated photonics experiments. In this work, we analyze five heralded schemes for generating event-ready photonic Bell states, contrasting their heralding probabilities, fidelities, and error robustness. We develop a hierarchy of error models, progressing from an analytically tractable lumped-loss model to realistic heralded single-photon sources with multiphoton emission errors and finally to integrated frequency-bin implementations with architecture-dependent loss. Across these models, we find that schemes based on higher-order multiphoton interference provide superior fidelity robustness in low-loss implementations, while lower-photon-number schemes can be preferable when probabilistic sources or lossy beamsplitters dominate the resource cost. Our results provide design guidance for integrated discrete-variable quantum photonics, with particular relevance for frequency-bin architectures where active beamsplitter loss can determine the optimal resource-state-generation strategy.

The flow of moderately dense (n {\approx} 10^{11} cm^{-3}) hydrogen plasma with high electron temperature (T_{e} {\approx} 30 - 35 eV) and plasma potential (V_{p} {\approx} 100 V), expanding towards an expansion chamber (EC) from an ECR plasma source is investigated using Langmuir probes (LPs) and Ion Energy Analysers (IEAs). The LPs reveal presence of a second ionization zone (SIZ) a few centimetres from the ECR zone, indicating very short ionization mean paths, which are confirmed theoretically. The SIZ gives a density boost, produces a double layer, DL ({\Delta}V_{DL} {\approx} 106 - 40 V) and a warm electron population after the DL (n_{w}/n {\approx} 0.04 - 0.10, T_{w} {\approx} 40 - 60 eV). IEA measurements conducted at two sites (z_{1} {\approx} 5 cm, z_{2} {\approx} 10 cm) reveal ions with energies in the range {\approx} 65 - 8 eV at pressures {\approx} 1 - 8 mTorr. DL formation is explained in terms of the SIZ and warm electron generation is analysed in detail.