Papers

Marcus–Hush theory describes electron transfer through reorganization energies, driving forces, and electronic coupling, but it does not by itself determine when an adiabatic model possesses a local Hamiltonian bottleneck. We study a minimal asymmetric two-degree-of-freedom lower-sheet Hamiltonian with an exactly separable harmonic transverse mode. For this conservative model, we establish a necessary-and-sufficient root count for the stationary points and recover the known cusp boundary for disappearance of the lower-sheet double well. We then interpret that boundary in Hamiltonian phase space: inside the cusp, the lower sheet has an index-one saddle and the associated local transition-state structures — an unstable periodic-orbit NHIM, its stable and unstable manifolds, and an attached dividing surface — exist; outside the cusp, this local saddle-mediated structure is absent. The result applies to this conservative adiabatic potential-energy Hamiltonian. It does not describe solvent free-energy dynamics, bath-induced mode coupling, or nonadiabatic transfer, and it does not predict Marcus rates for realistic condensed-phase electron-transfer systems.

Large detectors are often monitored at the channel level (drift time, collected charge, and hit maps), which validates hardware but not tracking performance. A wire-by-wire tracking efficiency diagnostic is presented for the Belle~II Central Drift Chamber~(CDC). The method is directly analogous to the extrapolation-based efficiency measurement standard in resistive-plate-chamber~(RPC) stacks developed for the India-based Neutrino Observatory~(INO). A reference track (helix) is extrapolated to each wire layer; the fraction of crossings that contain an associated hit defines the per-wire efficiency. Implemented in the Belle~II Data Quality Monitoring~(DQM) framework and validated on Monte Carlo simulation with controlled dead-wire conditions, the method reveals localised tracking failures that are invisible to conventional channel-level diagnostics. The resulting plots provide direct feedback for run selection, operations, and long-term ageing studies.

Single-layer molybdenum disulfide ($MoS_2$) possesses significant potential for nanoscale optoelectronics, but achieving high-intensity, long-term-stable photoluminescence (PL) emission remains a challenge. In this work, we demonstrate a remarkably robust, more than 8-fold maximum enhancement in the PL intensity of exfoliated and CVD-grown single-layer $MoS_2$ via a non-destructive ultraviolet (UV) laser treatment method. This substantial increase in radiative efficiency is accompanied by a trion-to-neutral exciton transition in the PL signal and a corresponding blue shift of the Raman $E_{2g}^1$ and $A_{1g}$ vibrational modes, signaling successful electron depletion (p-doping) and formation of Mo-O bonds, respectively. Furthermore, we demonstrate precise spatial control over PL properties by confining PL treatment exclusively to the UV laser-treated area. Crucially, the enhanced PL performance shows exceptional longevity; the CVD sample and the exfoliated sample remained stable for the entire monitoring period (72 and 32 days, respectively) under ambient conditions. We further investigated UV laser treatment in a controlled-environment chamber under argon, nitrogen, and oxygen atmospheres, distinguishing the influence of oxygen as the PL treatment agent. These findings establish a reliable pathway for the permanent treatment of single-layer $MoS_2$ PL properties, an essential step toward practical, high-performance nanophotonic devices.

Reliable early detection of lithium-ion battery degradation requires health indicators that are physically interpretable and computable from routine cycler telemetry without access to the degradation region. We introduce CausalHealth, a framework that applies causal graph discovery and $k$-nearest-neighbour transfer entropy to per-cycle voltage, current, temperature, and resistance time series, and organises twelve resulting anomaly scores into three signal-class bundles (Magnitude-shift, Predictive-residual, Complexity-entropy) – with Isolation Forest reported separately as it falls below the bundle reliability threshold – to characterise detection sensitivity across ten commissioning fractions (5–30\,%). The Magnitude-shift class achieves 100\,% detection across all seven tested cells spanning LFP (MIT–Stanford MATR) and LCO (NASA PCoE, CALCE CS2) chemistries, with a lead time of up to 402 cycles before conventional capacity-threshold failure on gradual-fade cells. A Reliability-Weighted Master Health Index (RWMHI) – a cross-bundle fusion of five high-reliability detectors weighted by inverse coefficient of variation – improves lead time by 15–52 cycles over the class median on long-lived cells while maintaining 100\,% detection. Validation against electrochemical impedance spectroscopy on an NMC prismatic cell provides independent physical grounding: transfer entropy $\mathrm{TE}(R \!\to\! V)$ correlates with charge-transfer resistance $R_{\mathrm{ct}}$ (pooled $r = +0.990$; temperature-controlled partial $r = +0.898$), and an Arrhenius analysis of both quantities yields an activation energy consistent with published NMC charge-transfer kinetics. These results are evaluated on seven cells across three benchmark datasets.

Magnetized plasmas with equilibrium density gradients support drift-wave turbulence, which is often regulated by self-generated zonal flows. In this work, we experimentally examine the effect of increasing the magnetic field on turbulence characteristics in a linear plasma device. As the magnetic field is increased from 600 to 1000 G, zonal flow is suppressed while the mean flow increases. Spectral analysis of density and potential fluctuations shows a redistribution of power from low-frequency (0.1-1 kHz) to high-frequency (1-300 kHz) components, along with an increase in the spectral slope and the ratio PHF/PLF. This change is linked to a reduction in Reynolds stress due to the loss of correlation between radial and poloidal velocity fluctuations, which possibly weakens the drive for zonal flow generation. Similar behavior is observed near the peak gradient region, also indicating its global nature. The present results suggest a transition from a zonal-flow-dominated regime to a state dominated by smaller-scale fluctuations, possibly influenced by mean flow shear. These findings highlight how the magnetic field redistributes spectral energy across frequency scales in drift-wave turbulent plasmas

Elastic wave propagation and energy exchange in passively deforming cylindrical nozzles are investigated through three-dimensional, two-way fluid-structure interaction simulations. Flexible nozzles with varying stiffness (Eh = 75 to 500 N/m, E is Young's modulus, h is thickness) are subjected to pulsatile jet inflow at low Reynolds number (Re ~ 4400). Increased flexibility reduces deformation-wave speed following MoensKorteweg scaling, prolonging the expansion phase. This delayed expansion enhances jet entrainment and elastic energy storage while suppressing early shear-layer roll-up and vortex formation. During contraction, released elastic energy increases jet acceleration and vortex formation. For the most flexible nozzle, primary vortex-ring circulation increases by 52%, vortex convection distance by 9%, and peak outlet kinetic energy flux 4.6-fold versus a rigid nozzle, resulting in a 62% increase in total hydrodynamic impulse. A reduced-order model represents the coupled response as a lumped store-and-release oscillator, derived as a single-mode projection of the inviscid one-dimensional wave equation and closed at the exit by two terms: (i) an inertial end correction that adds the external fluid column of length Le = R accelerating with the jet, and (ii) a vortex-radiation damping term, active only during ejection, determined by the discharged-jet momentum theorem. This damping reproduces the post-overshoot velocity decay undamped closures fail to capture. The model predicts the simulated resonance frequency within 6% and momentum impulse within 4% across Eh = 75 to 500 N/m, and recovers energy histories. Outlet kinetic energy flux is predicted within 6% for the three stiffer nozzles and 14% for the most compliant.

Oscillator Ising machines (OIMs) are often viewed as physical systems that perform gradient descent on an energy landscape encoding Ising solutions. Here, we show that this interpretation is not generic and breaks down in a broad class of oscillator implementations. We establish that gradient-flow dynamics require a harmonic-by-harmonic quadrature relation between the oscillator waveform and its phase response. Deviations from this condition, which we term harmonic misalignment, introduce even components in the pairwise interaction function, leading to non-conservative phase dynamics and precluding a gradient-flow description. We introduce a normalized metric for this non-gradient contribution and evaluate it across representative oscillator models relevant to OIMs. This metric reveals substantial non-gradient contributions in ring oscillators and across other hardware-realistic oscillator models. These findings identify harmonic misalignment as a fundamental mechanism for the breakdown of energy-based dynamics in OIMs and motivate nonequilibrium analysis and algorithms that explicitly account for and potentially exploit non-gradient behavior.

Ecological communities are often characterized by many weak and few strong interspecific interactions, yet their quantitative structure, generative basis, and links to community-level properties remain poorly understood. Using two empirical datasets of plant–animal networks, we show that both trophic and mutualistic interaction strengths distribute skewed weak and Pareto-strong tails (SWAPS), as quantified by positive skewness and extreme value theory, respectively. We further find that interaction strengths are taxon-specific and largely constrained within taxa. In community assembly simulations based on a generalized Lotka–Volterra model, this taxonomic conservatism, together with multiple interaction types beyond trophic and mutualistic ones, is required for the emergence of SWAPS distribution. Notably, SWAPS distribution emerges not only at the species level but also across lineages, and its emergence accompanies increases in community diversity and complexity. Together, these results identify SWAPS distribution as a previously unrecognized interaction signature of ecological communities and provide a new perspective on the organization of community-level properties.

Time-resolved microscopy with the pump-probe protocol is one of the most important techniques for the investigation of dynamical processes at the nanoscale, thanks to the possibility of combining nanometric resolution imaging with sub-nanosecond temporal resolutions. Amongst the ensemble of time-resolved microscopy techniques, time-resolved scanning transmission X-ray microscopy has been, since its inception in 2006, extensively utilized for the study of magneto-dynamical processes. In this review, an overview of the concept and experimental implementations of the pump-probe protocol in time-resolved scanning transmission X-ray microscopy imaging will be presented together with some examples of recent applications of the technique. Possible future developments aimed at meeting the new opportunities and challenges offered by the upgrade of synchrotrons to diffraction limited lightsources will also be discussed.

Molten iron chlorides are central to emerging energy technologies, including electrochemical iron production and redox flow batteries. Optimizing their electrochemical performance and transport properties requires atomic-scale structural understanding, yet detailed data for molten FeCl2 and its differences from FeCl3 remain scarce. Here, we determined the structures of molten FeCl2 and FeCl3 using High Energy X-ray diffraction (HEXRD), Empirical Potential Structure Refinement (EPSR), and molecular dynamics (MD) simulations with machine learning interatomic potentials (MLIPs). HEXRD measurements provided structure factors and total radial distribution functions (RDFs), which were quantitatively reproduced through EPSR refinement directly constrained by experimental data. MD simulations using MACE foundation and fine-tuned models reproduced experimental structure factors as well as total and partial RDFs, capturing key structural differences between the melts. The models resolved the octahedral to tetrahedral coordination transition of Fe upon melting in FeCl3 and predicted a similar transition in FeCl2. Analysis of MD trajectories quantified coordination environments, bridging Cl populations, bond-angle distributions, and connectivity patterns, revealing distinct degrees of polymerization and local geometry. Polymer chain statistics further showed that, contrary to prior reports, both liquids predominantly consist of extended chains containing six or more Fe centers rather than discrete Fe2Cl6 units. Finally, diffusion coefficients of the two melts calculated from the MACE-MD simulations were compared. Together, these results establish atomic-scale structural benchmarks for molten FeCl2 and FeCl3 and demonstrate the reliability of MACE-based MLIPs for predictive modeling of high-temperature molten salts, while providing practical guidance for MLIP development in complex ionic liquids.

Additively manufactured (AM) alloys have heterogeneous microstructures with broad grain size distributions and highly anisotropic and/or non-convex grain shapes. AM components can have complex geometries and porosity which may affect the local microstructure. Currently there is no electron backscatter diffraction (EBSD)-based grain size measurement standard suitable for typical AM materials. An interlaboratory comparison study was conducted to find out what grain size metrics and summary statistics are currently used to describe average grain size. Participants were asked to measure and report the average grain size from the same EBSD map dataset. Detailed reports have been published in Reference [1]. Based on these results, we have tested and propose recommendations for a new standard for measuring average grain size in AM materials. The present work demonstrates the suitability and limitations of the proposal across several different Ni and Al AM components.

The martian atmosphere hosts dynamical phenomena ranging from planet-encircling dust storms to mesoscale orographic clouds and nocturnal low-level jets. General circulation model show capability to simulate these phenomena, but is computationally expensive at resolution needed to resolve mesoscale features. While assimilation of satellite remote sensing observation enable forecasting capabilities using such models, observation record is often sparse, short and fragmented across instrument generators. These constraints motivate the development of a data-driven foundation model for the Martian atmosphere. Foundation models live in a complex design landscape. There is an interplay between the available data, the physics of the underlying processes and corresponding developments in AI. Even though the idea of a foundation model is to address multiple use cases in a data- and compute-efficient manner, it is important to have a clear picture what applications can sensibly addressed by a single model. The purpose of this paper is to elucidate this design landscape. We discuss available data ranging from atmospheric retrievals to reanalysis datasets as well as existing physical models. Moreover, we identify a wide range of candidate downstream applications. Finally, we consider relevant recent developments in artificial intelligence (AI) that can be leveraged in this context. Here, we put a particular emphasis on AI models for atmospheric physics, data-driven approaches to data assimilation as well as methods to work in a limited data setting.

The absolute value of the transition probability of the Rayleigh scattering is computed for the first time and applied to the scattering of solar light with molecules in the atmosphere and to the laser scattering with nanopartilces. The probability has a new contribution of unique properties from long-range correlations specific to the quantum mechanics. The magnitude is sufficient to resolve longstanding puzzle on diffusion lights in the sky and anomalous photon spectrum in laser experiments. The earth's albedo from the new calculations on Rayleigh scattering agrees with observations with satelites.

Deep subsurface access on Mars could enable sampling of ancient lacustrine deposits, volatile-rich horizons, and other geologic targets beyond the reach of current shallow drilling systems. This study evaluates a wireline pneumatic rotary-percussive drill concept that uses compressed atmospheric CO2 as both the actuation and transport fluid. The architecture combines a pneumatically driven hammer, magnetic flapper-valve, and incremental bit-indexing mechanism in a compact bottom-hole assembly for low-power deployment. We develop a reduced-order model of the hammer and chamber dynamics that captures coupled pressure, flow, and impact behavior during each strike. The model is compared with benchtop percussion experiments and used to interpret hammer velocity, displacement, strike timing, and impact energy. A modified testbed is then used to drill Martian rock simulants spanning weaker sandstone and stronger Saddleback basalt cases, linking drilling response to operating pressure and material properties. The experiments show repeatable percussive impacts and mechanical specific energy values from 74 to 360 MJ/m3, with lower values in weaker simulant and higher values in stronger basalt. The results indicate that the system is most effective in a percussion-dominant mode with bit geometry matched to available impact energy. Together, the architecture study, validated model, and drilling experiments support the wireline pneumatic drill as a candidate for low-power deep drilling on Mars, while identifying remaining work in robustness, cuttings removal, and full-system integration.

In dynamic flow fields, various animals exhibit remarkable odor search capabilities despite relying on stochastic detections. Interestingly, there exists an optimal time window for integrating these detections that maximizes search efficiency. To understand the underlying mechanism, we investigate the navigation performance of Reinforcement Learning (RL) agents in unsteady flows under varying memory lengths and flow conditions. Without any predefined models, the agents develop a flow-assisted casting strategy and adaptively adjust both the geometry of their search trajectories and the concentration threshold for initiating casting to maximize the success rate. The agent's average speed toward the odor source exhibits a non-monotonic dependence on memory length, which can be explained by the "sector-search" model.

The transverse modal identity of a freely propagating optical beam is ordinarily fixed at the point of generation. We show that the conical angular spectrum of a Bessel beam establishes a one-to-one mapping between radial beam position and axial reconstruction distance. This mapping converts the radial aperture of a single static, phase-only spatial light modulator into a programmable longitudinal-mode register. By partitioning the modulator into independent annular regions, we encode discrete transverse modes at preselected axial positions. We demonstrate this principle with programmable ring-lattice fields of axially varying site number, and with passive transitions that sequence through Bessel, Bessel vortex beam, Hermite-Gaussian-Bessel, and Airy caustic modes within a single beam, without dynamic modulation or cascaded optical elements.

Memory systems can store vastly different amounts of information despite similar hardware constraints. Here, we show that superior spatial memory emerges from a discrete stiffening of hippocampal population geometry-a transition from disorganized to crystalline collective coding. Comparing food-caching chickadees to non-caching zebra finches, we found that the caching hippocampus maintains a topologically rigid, "crystalline" geometry with significantly higher geometric stability (Shesha 0.245 v 0.166) and nearly two-fold greater temporal coherence (Shesha 0.393 v 0.209), while the non-caching hippocampus resembles a disorganized "mist." This stability is actively constructed by synergistic circuit dynamics: excitatory neurons form the spatial scaffold while inhibitory populations contribute orthogonal decorrelation, a circuit motif in which excitatory and inhibitory populations occupy largely non-overlapping representational subspaces. A double dissociation with Valiant's Stable Memory Allocator, a model predicting that dedicated neuron ensembles underlie each memory, confirms this advantage reflects continuous topological organization rather than discrete neuron allocation: caching networks exhibit near-zero split-half allocation reliability despite their geometric superiority. Computational modeling across 10k configurations reveals topological rigidity as the mathematical prerequisite for scale: crystalline codes sustain high-fidelity readout beyond M=1k locations while mist codes fail below M=10, a >100-fold capacity advantage. This capacity requires a 169fold representational redundancy: a "geometric tax" stabilizing the manifold against biological noise. These results establish geometric stability as a candidate organizing principle of biological memory: evolution achieves high-capacity memory not by proliferating neurons, but by engineering the geometry of the neural code itself.

This work provides an overview of key historical developments in the formulation of the Second Law of Thermodynamics, focusing on the notorious challenge of “Maxwell's Demon”, a hypothetical creature who could presumably violate that law. It begins by recalling Maxwell's challenge and discussing the apparent loophole in the Second Law that appears to make such a violation possible. An alternative formulation of the Demon challenge by Szilard is considered, along with his attempted defeat of the Demon through reference to measurement. A similar effort by Brillouin is also analyzed. The proposal of Bennett to defeat the Demon through the requirement of memory erasure is critically discussed. Finally, it is proposed that the Second Law gains a firm foundation through neglected features of quantum theory. In particular, an application of the Heisenberg Uncertainty Principle is shown to decisively defeat the Demon, as well as to serve as justification for Landauer's Principle, albeit in terms distinct from the usual computational formulation.

The wide-bandgap semiconductor 4H-silicon carbide (4H-SiC) offers a compelling combination of radiation hardness, thermal stability, and high critical electric field for particle detection in harsh environments. To compensate for the comparatively low charge generation in SiC, the Low-Gain Avalanche Detector (LGAD) concept can be adopted to provide internal signal amplification. Building on three preceding generations of single-pad 4H-SiC LGAD prototypes fabricated by ion implantation, this work presents the design, fabrication, and initial characterization of segmented 4H-SiC LGAD devices – the first fabricated and characterized devices reported. Strip detectors with 80~$\mu$m pitch and pixel arrays with 55 and 110~$\mu$m pitch were produced using multiple inter-channel isolation strategies, including geometric separation and oxide-filled trenches. Two-photon absorption transient current technique (TPA-TCT) measurements performed at ELI ERIC demonstrate clear charge separation between adjacent strips with internal gain, confirming functional segmentation.

Burning plasma is computationally challenging to simulate due to the multi-scale interactions between energetic particles (EPs), Alfven eigenmodes, and microinstabilities that drive turbulence. Many studies circumvent this difficulty by focusing on a single instability and making the corresponding simplifying assumptions. However, these approximations do not necessarily preserve the global instability spectrum, leading to conflicting results and inconsistencies. In this work, we identify the minimal set of assumptions needed to model a burning plasma self-consistently with the modes and species in the system. Using the global gyrokinetic code ORB5, to systematically evaluate the impact of commonly adopted assumptions on the plasma response. We find it is essential to include Shafranov shift and finite $\beta$ effects from all magnetically confined species. Otherwise, unphysical electromagnetic modes like internal kinks and kinetic ballooning modes (KBMs) appear to dominate the instability spectrum. The EP contribution to the Shafranov shift is particularly important, stabilizing both the toroidal ion temperature gradient (ITG) and toroidal Alfven eigenmode (TAE) at the longer wavelengths (low toroidal mode numbers). For TAEs, these effects significantly reduce the linear growth rate, which saturates instead of proportionally increasing with EP fraction. In the nonlinear regime ITG-driven heat and particle fluxes are unaffected by the Shafranov shift in self-consistent magnetic equilibria. While the the nonlinear saturation level of the TAE remains unchanged across all cases, unlike for the ITG case Shafranov shift does reduce the TAE-driven EP fluxes.

We describe a high-order ADER-DG solver for the compressible Euler equations within the ExaHyPE framework. The implementation combines a high-order ADER-DG polynomial representation, a local space-time DG predictor, adaptive mesh refinement, and an a posteriori subcell finite-volume limiter. We test the code on a deliberately mixed set of one- and two-dimensional problems: a strong-shock Sod-type problem, the Shu-Osher shock-entropy interaction, the Woodward-Colella blast wave, a contact-driven vortex sheet, and a shock-interface interaction. The one-dimensional cases recover the expected Euler wave patterns and show clear order-dependent gains in smooth and oscillatory regions. The two-dimensional cases probe a different part of the method, namely contact preservation, shear-driven roll-up, baroclinic vorticity deposition, and Richtmyer-Meshkov-type growth. In these tests the high-order update gives the expected resolution away from discontinuities, whereas the subcell limiter keeps the calculation stable near shocks and steep interfaces. The resulting code provides a reproducible ExaHyPE implementation for idealised inviscid, non-relativistic flows in which shocks, contacts, and multidimensional interfaces are the dominant features.

For the physically important case in which the viscosity coefficients depend on the density $\rho$ through a power law (i.e., $\rho^\delta$ with some exponent $\delta \in (\frac{1}{2},1)$), we establish the global well-posedness of regular solutions of the compressible Navier-Stokes equations for barotropic flow with large initial data of spherical symmetry in two and three spatial dimensions. The initial density considered here is positive everywhere but vanishes in the far field, ensuring that the resulting solutions satisfy the conservation laws of total mass and momentum. The most crucial step in our analysis is to obtain a uniform upper bound for the density, which is challenging due to the combined difficulties of degeneracy near the far-field vacuum, coordinate singularity at the origin, and nonlinearity of viscosity coefficients. Furthermore, the methodology developed here can also be applied to the corresponding problem in which the density remains strictly away from the vacuum.

Rarefied hypersonic bow shocks over blunt bodies inflate as the Knudsen number increases, but it remains unclear whether this inflation is a simple shift and broadening of one common shock layer or a multi-scale change of the macroscopic and internal-energy fields. We address this question using direct simulation Monte Carlo (DSMC) data for Mach-10 flow over a circular cylinder in argon and nitrogen over \(Kn_\infty \approx 0.01\)–\(1\), together with a Mach-number sweep at \(Kn_\infty=0.01\). At low rarefaction, a ray-based density-gradient ridge gives a reproducible bow-shock location and agrees with an independent schlieren-based shock-wave-detection method. As \(Kn_\infty\) increases, this ridge is replaced by a broad kinetic compression layer, so the high-Knudsen cases are analysed using profile-based standoff and thickness metrics rather than by imposing a visual shock line. The Knudsen- and Mach-number sweeps separate two mechanisms. At fixed \(M_\infty\), the continuum normal-shock density ratio provides a useful low-rarefaction reference compression scale, whereas the measured standoff growth is governed primarily by the kinetic mean free path; the effective density thickness shows an intermediate minimum before increasing in the diffuse regime. At fixed low \(Kn_\infty\), changing \(M_\infty\) mainly changes compression strength and curvature, preserving a coherent attached-layer structure. Density-registered profiles and shock-attached proper orthogonal decomposition (POD) show that, within the present maximum-density-gradient registration, density becomes nearly rank one, whereas Mach number and thermal variables retain independent modal content. Rarefied bow-shock inflation is therefore a coupled compression–relaxation process, not a single-scale rescaling of a continuum-like shock.

A train of periodic optical pulses gives an optical frequency "comb" that acts as a precise ruler for light measurement due to its equally spaced frequencies. Today, such pulses last millionths of a billionth of a second (Femtoseconds/fs) and associated comb spans billions of frequencies (Terahertz), similar to a discretized rainbow ranging from ultraviolet to infrared light. This is the core technology in many optic-based applications like atomic clocks and secure communication. Despite its obvious value, these remain mostly confined to research labs for being complex, expensive, and power-hungry. One promising solution is to use laser mode-locking: a technique that forces a laser to emit short coherent pulses. While chip-size systems have already been demonstrated, this approach still lacks flexibility and performance in repetition rate and bandwidth simultaneously. This research proposal leverages the industrialization of integrated photonic chips to develop a first-ever all-integrated two-coloured pulsed source with durations of a few hundred fs. It will engineer a novel turn-key device that will 1) pioneer the demonstration of modelocked pulses at two separate central frequencies originating from the same laser, 2) fit on a fingertip, and 3) be compatible with generic foundry processes, and thus, mass-manufacturable. Sustained generation of such pulses is intricate with little knowledge about light-material interaction at this scale. The chip will emit two broadband combs using one control parameter. These combs will have synergetic comb properties and coupled through one gain medium. Thus, we will create a new ultra-broadband comb resulting in unprecedented phase correlation between the two sub-combs. Simultaneously, the device will be significantly smaller, lighter, cheaper, and more power-efficient than its free-space rivals, reducing the gap between lab and market.

Neural-network quantum states offer a flexible route to compact many-electron wave functions, but their practical accuracy depends strongly on how fermionic antisymmetry, electron correlation, and optimization noise are treated. Here we combine an antisymmetrized geminal power (AGP) determinant with feed-forward neural networks that replace conventional basis-set expansions in the geminal and in two Jastrow-factor constructions. The resulting basis-free Jastrow–AGP ansatz is optimized by variational Monte Carlo and is designed to separate two tasks: the AGP part defines the nodal surface, while the neural-network Jastrow factor recovers dynamical correlation at fixed nodes. This separation makes it possible to distinguish errors associated with dynamical correlation from those caused by static, multireference correlation. Applications to the hydrogen molecule and the rectangular hydrogen tetramer show sub-millihartree accuracy when the AGP nodes are adequate, and expose the residual nodal limitation near the large-radius square geometry of the hydrogen tetramer. These results clarify where neural-network building blocks can improve a compact geminal ansatz and where additional nodal flexibility is required.

Slope stability description through mechanical laws has important implication for Earth morphology understanding and risk assessment. Previous researches have showed that shear, tensile, and hybrid fractures can be observed experimentally and in the field, but their descriptions by a single equation is still an open debate. Fracture envelope able to describe contemporaneously these three fracture modes differ signif-icantly from the Mohr-Coulomb law. Despite the need to apply such a law at all scales, from the laboratory to the mountain range, the fracture criterion that characterizes all types of fractures is rarely used in geotechnical engineering and geological investiga-tions. In order to analyze the stability thresholds of large-scale relief, the current work examines the effects of considering the Griffith criterion with a variable rock traction instead of the Mohr-Coulomb law using a modelling approach. The difference esti-mated on maximum relief using these two different rupture criterions could be of the same order than the one caused by geological phenomena, such as with or without seismic activity, or from the one caused by the destabilization processes (tilting vs. landslide). When compared to the modified Griffith criterion, the Mohr-Coulomb law tends to overestimate the maximum escarpment height. The results are examined in relation to the Carrara marbles, which serve as a case study for the theoretical frame-work.

This paper describes the setup and the results of the direct on-wafer measurements of a FET noise parameters obtained with a source-pull method at temperatures down to T=4K and in the 5-12 GHz frequency range. The setup consists of a cryostat with wafer probes, two reflectometers, a programmable impedance generator, wideband isolators and bias tees and low noise preamplifier, all cooled to cryogenic temperatures, allowing to perform a full vector error-corrected wafer-level measurements of the discrete transistors and amplifier dies. The setup and its calibration procedure are designed in a such way that allows simultaneous calibration, S-parameters, noise parameters and I-V curve measurements of several FETs all in one cooldown. Using the described setup we perform first measurements of 14nm FinFETs and also measure noise parameters of an LNA based on these FETs. Resulting noise temperature values are compared against those obtained using independent and alternative measurement techniques.

We consider neutral-current parity-violating interactions in an atom mediated by the exchange of a neutrino-antineutrino pair. We explicitly account for the nuclear finite size encoded in the nuclear form factor. Based on its general properties, we derive an effective neutrino-mediated potential and determine its properties at short and long distances. We demonstrate that, once the form factor properties are correctly accounted for, the range of such an effective potential corresponds to the nuclear radius, removing any sensitivity to shorter-distance contributions. This potential changes sign over the atom's volume, so that the correction to the effective nuclear weak charge induced by this interaction is tiny and does not alter the interpretation of atomic parity violation experiments.

The function of the zebras striped coat has been discussed since Darwin and Wallace. Increasing amount of comparative and experimental evidence supports the hypothesis that the stripes mainly serve as protection against visually orienting biting Diptera, in particular tabanids (horse flies), glossinids (tsetse flies), and culicids (mosquitoes). The proposed ways this protection works include polarotactic disruption and silhouette break-up, as well as motion based illusions in motion based detectors of the insect visual system. In this work a complementary purely optical mechanism is presented to explain why the zebra's stripe pattern provides a measurable advantage in warding off biting flies. We have quantified the optical illusion caused by the interaction between the zebra's striped coat and the fly's compound eye with a linear, shift-invariant Fourier model based on published optical data of the diurnal Culicidae. The model predicts that, within an approach range of about 1-5 m, the interaction of the stripe pattern with the ommatidial sampling produces parasitic spatial frequencies that are absent from the physical stimulus. These frequencies fall within the range most important for host fixation and controlling their landing. A post-retinal motion-detector shows that these parasitic frequencies create misleading motion signals. The magnitude of this parasitic energy predicts the specific loss of the radial-expansion (looming) cue that gates landing, linking the optical disturbance quantitatively to the motion computation that controls the fly's final approach. By rigorously modeling visual processes and quantifying disturbances, this study makes a decisive contribution to clarifying the role of zebra stripes in defense against biting flies.

The Taishan Antineutrino Observatory (TAO) is a near-site experiment for the Jiangmen Underground Neutrino Observatory (JUNO). Its primary goal is to provide a precise reference reactor antineutrino energy spectrum, thereby eliminating the model dependence in reactor neutrino spectrum predictions and enhancing the sensitivity of the neutrino mass ordering measurement. To ensure accurate data acquisition and safe operation of the TAO experiment, a low-temperature monitoring and alarm system has been developed. Built on the Experimental Physics and Industrial Control System (EPICS) framework, the system employs PT100 platinum resistance thermometers embedded in the detector to monitor the temperature of the liquid scintillator. Real-time temperature data are acquired, enabling comprehensive thermal monitoring. The alarm program adopts a trigger-based mechanism with multi-level thresholds, providing instant alerts to operators when the temperature deviates from the safe range. The system has been operating stably for six months, accumulating over one thousand alarm records, and has proven effective in ensuring the safe and stable operation of the experiment.