Papers

Harvesting – the periodic removal of individuals above or below a threshold trait value – reshapes heterogeneous populations without altering their underlying stochastic dynamics. We study how repeated harvesting events steer the evolution of probability densities for classes of stochastic processes exhibiting both normal and anomalous dynamics, as well as a prototypical predator-prey model. Removal of the upper portion of the density drives the system to a quasi-steady state when viewed at the “harvesting clock”. This state depends only on the harvesting threshold and frequency but not on the initial conditions. Removal of the lower portion of the density fixes its shape while generating a constant effective drift that exceeds that of the unharvested mean. Our results suggest the possibility of manipulating the dynamics of stochastic populations through external selection interventions.

The classical Gibbs-Duhem relation applies to quasi-static processes and neglects kinetic effects, leaving a fundamental gap between Gibbs thermodynamics and Newtonian mechanics. Here, we derive a generalized Gibbs-Duhem framework that incorporates kinetic contributions, thereby establishing a unified connection between classical thermodynamics and Newtonian mechanics. Based on this framework, we propose an alternative evolution equation governing density dynamics at fluid-fluid interfaces. In appropriate limiting cases, the resulting density evolution equation naturally recovers the definition of the speed of sound, Bernoulli's law, and the van der Waals equation of state (EOS).

Open questions in collisionless plasma dissipation can be addressed using space-based observations in different astrophysical environments, with implications for both astrophysical and laboratory plasma systems. We study a low-$\beta$, highly imbalanced, sub-Alfvénic stream observed by Parker Solar Probe (PSP) to identify and distinguish between signatures of stochastic heating (SH) and resonant heating (RH) by parallel ion cyclotron waves (ICWs). Prior work studying this stream (Bowen et al., 2025) showed that the SH rate, accounting for intermittency, matched the amplitude of the local energy transfer (LET) rate while the RH rate did not. This comparison relied on a number of assumptions regarding the nature of the diffusive process, and the calculation of the LET rate. We introduce a novel technique of inverting the proton guiding center equation to empirically measure velocity-space diffusion coefficients using three-dimensional proton velocity distribution functions (VDFs), from the ion electrostatic analyzer (SPANi) on PSP. Measured diffusion coefficients are used to determine phase-space heating rates, leading to a calculation of a fully kinetic heating rate independent of assumptions made in prior work. We show that scale-dependent analytic expressions for SH via non-coherent fluctuations match the empirical measurements from PSP data, provided that we account for intermittency in the heating calculation. In contrast, the derived heating rates for SH that accounts for the effects of the helicity barrier, and heating rates for RH via $\parallel$-ICWs do not peak in the same region of velocity-space as the empirical measurements, nor reach the required magnitude. Our approach provides novel methodology to uniquely identify and constrain heating processes in collisionless plasmas, and shows evidence of a Fokker-Planck like diffusive process in the near-Sun solar wind.

For a reversible system relaxing to equilibrium, the obvious fastest strategy is to lower all kinetic barriers (open all gates). We find that such intuition holds at three levels: the all-open-gate strategy achieves the highest local conductance, it maximizes the instantaneous speed of approach in every $f$-divergence, and it simultaneously maximizes all relaxation eigenvalues. Nevertheless, we show that a counter-intuitive finite-time optimum lies beyond this intuition and operates at a fourth level, invisible to all three: eigenvector rotation. Noncommutativity enables timed schedules to reproject residual amplitudes across relaxation modes, thereby achieving faster relaxation. Optimal schedules are bang–bang. In our illustrative example, the best-found schedule also employs counter-gating, transiently raising selected barriers, and reduces the terminal residual by a factor of $130$ relative to all-open, and by $7$ relative to the best static landscape. A no-go theorem shows that noncommutativity is necessary: commuting generators collapse every schedule to a static time-averaged landscape, worse than the intuitive static control. In the reverse problem, the dual schedule preserves nonequilibrium free energy far more effectively than intuitively keeping all barriers at maximum heights. Whether accelerating or delaying relaxation, barrier control performs no work on the reduced Markov system; it only re-times a fixed total dissipation budget.

Quantum light sources capable of generating single photons are fundamental building blocks for photonic quantum technologies. In the ongoing search for an ideal quantum emitter, inorganic halide perovskite nanocrystals have emerged as a promising source of single photons. Their unique optical response, with an unmatched ease of synthetic tunability, stands out amongst the competing platforms. However, their stochastic dispersion in solution challenges the deterministic and stable integration of individual emitters with photonic structures that is required for practical technologies. Notably, resolution and material compatibility constraints make conventional top-down fabrication processes insufficient for such heterogeneous integration. Here, we report direct writing of perovskite quantum dots (QDs) with individual-emitter resolution. By inducing a nanoscale-confined formation volume using a thermal scanning probe method, we achieve site-selective synthesis down to a single atomic-scale QD with spectral tunability and < 25 nm spatial control. As a result, we demonstrate high-yield arrays of CsPbI3 single-photon emitters with narrow linewidths and high single-photon purity up to 98% at room temperature, performance consistent with that of their state-of-the-art colloidal counterparts. Through such deterministic control, we uniquely realize the precise, on-demand coupling of these emitters to photonic cavities, as evidenced by a measured enhancement in the spontaneous emission rate. This represents a key advancement toward addressing the longstanding integration obstacles of these materials. Overall, by combining the atomic-scale tunability of chemical synthesis with the spatial control of additive manufacturing, our work opens new emitter engineering strategies to realize the untapped potential of colloidal materials for next-generation quantum technologies.

Estimating ocean heat content (OHC) with reliable uncertainties is critical for understanding and monitoring the evolution of Earth's climate, as the ocean has stored most of the energy accumulated in the climate system due to Earth Energy Imbalance. Here, we use Argo profiling float data from 2004-2022 to map OHC. As fewer Argo observations are available deeper in the water column, previous studies have partitioned the ocean into at least two pressure layers and mapped each separately, which complicates the estimation of uncertainties when the maps are summed to get the total OHC. In this work, we consider the case of two pressure layers and propose an improved mapping and uncertainty quantification method using bivariate locally stationary Gaussian processes and conditional simulations to map the two sections jointly while accounting for the correlation between them. We find that modeling this correlation results in improved OHC anomaly mapping and up to a 15 percent reduction of global OHC anomaly uncertainties in comparison to mapping the two layers separately without accounting for their dependence. These estimated uncertainties are essential to analyze the statistical significance of OHC anomalies on both regional and global scales, which we demonstrate using several climatological case studies.

Which properties of a quantum many-body system are operationally accessible is a central question underlying spectroscopy, thermodynamics, and quantum information science. Conventional response theory answers this question within a system-only paradigm: one perturbs and measures the matter itself, obtaining susceptibility built from causally ordered nested commutators. Here we show that coherently controlled quantum probes, when measured at the end, define a strictly larger operational learning framework beyond that accessible from response theory. We establish this through a quantum-circuit description that unifies spectroscopy, probe microscopy, and probe-based quantum technologies within a common operational framework, from which we develop quantum protocols for learning many-body properties from probe readout only. This advantage arises because the reduced dynamics of quantum probes generically encode anti-commutator and mixed-order correlators of the target; therefore, measurements on the probe provide access to fluctuations, non-equilibrium structure, and entanglement entropy that are in general not accessible through response functions or a single probe alone. Moreover, we demonstrate that entangled probes can access many-body properties such as von Neumann entropy. We prove that the required probe resources scale with the complexity of the target correlations rather than with the size of the many-body system. Quantum probes are therefore not merely more sensitive sensors but provide a new way to learn many-body properties distinct from those of tomography or quantum simulation.

Since the foundational studies in the late nineteenth century, fluid turbulence has stood as a profound, unsolved challenge in classical physics. Much of this enduring difficulty stems from non-equilibrium turbulence, where the lack of a unifying physical framework for macroscopic coherent structures has hampered predictive flow modeling. Here, we establish a foundational bridge between non-equilibrium statistical physics and turbulent coherent structures through the renormalized Navier-Stokes equations. We demonstrate that all forms of turbulent coherence are fundamentally universal thermodynamic responses mandated by macroscopic energy throughput imbalances. Depending on topological access to bifurcations, these formations manifest either as transient adjustments (analogous to Kubo's near-equilibrium fluctuations) or as autonomous, transformative states (mirroring Prigogine's far-from-equilibrium dissipative structures). By introducing a computable, effective thermodynamic order parameter ($\Pi$), this paradigm establishes a rigorous foundation for non-equilibrium theory, enabling unequivocal identification of necessary flow resolution in continuously driven, dissipative continuum systems.

Characterizing emission and decay time spectra in multi-component fluorescent media is essential for identifying intrinsic material properties and optimizing detectors. However, wavelength evolution from the secondary inner filter effect (IFE) distorts these observable spectra. While Monte Carlo (MC) ray-tracing can simulate this distortion, accumulating adequate tracking statistics requires long computation times, which hinders parameter optimization within high-dimensional spaces. This paper presents an analytical Markovian transport model based on spatiotemporal decoupling. A Laplace transform converts the multi-nested convolution integrals over continuous domains into a discrete Markov transition matrix, reducing the computational complexity from an exponential scale with respect to wavelength bins $N_{\lambda}$ and cascade order $n$, $\mathcal{O}(N_{\lambda}^n)$, to a linear scale, $\mathcal{O}(N_{\lambda} + n)$. The resulting algebraic solutions evaluate transient decay time spectra as a continuum superposition of Gamma wave packets and predict steady-state wavelength spectrum distortions driven by the IFE within a sub-second timescale. Validations across orthogonal and front-face spectrometer configurations show that the calculated spectra match MC simulations in lineshape. This model can serve as a fast forward engine to accelerate parameter space screening, provide early-stage detector design references, and act as a physics-constrained input for event vertex reconstruction algorithms.

Quantum random number generators, at the core of digital trust infrastructures, rely on quantum entropy sources (QESs) to produce randomness from physical processes. The quantum origin certification of a QES requires a physical model compatible with the measured signal of the device. Here, we study Quside Technologies' phase-diffusion QES consisting of a photonic integrated circuit (PIC) that uses the interference of two indium phosphide (InP) lasers operated in gain-switching by simultaneously modulating their pump currents from below to above the threshold. This produces intensity pulses in each laser that have random optical phases due to quantum spontaneous emission. The lasers' intensities interfere via heterodyning, and from the interference signal a random bit is obtained per modulation cycle. While this system offers high scalability and compactness, residual coupling between the two lasers can induce phase synchronization, thus reducing its extractable entropy. Through experiments and simulations of a physical model based on coupled stochastic rate equations, we quantify this effect and link laser coupling to phase synchronization. We further derive an analytical model for the probability distribution of the measured interference intensity, enabling direct extraction of the quantum phase difference distribution and laying the groundwork for the QES optimization.

Gas-focused liquid microjets – the flow-focusing sample delivery on which serial femtosecond crystallography depends – reach speeds several times the pressure-driven (Bernoulli) bound, unexplained by continuum, local-equilibrium models that do not resolve the rarefied, hypersonic expansion of the focusing gas. We resolve that expansion with a deterministic kinetic (Shakhov–BGK) solver and couple it to the slender liquid jet. The jet is shear-driven, not pressure-driven: the tangential stress of the hypersonic gas supplies nearly all of the axial momentum, accounting for the anomalous speed. The gas does not become ballistic behind the near field – its stress decays as a power law and it stays coupled – and its constitutive regime is set by a single rarefaction parameter $\delta=D/\ell_0$, the orifice diameter over the source mean free path, through the thermodynamic Deborah number $De_\theta\simeq K\!n\,M$ (Knudsen times Mach), whose $De_\theta=1$ surface maps where the Newtonian-gas closure fails: the small-$\delta$ vacuum corner where crystallography jets operate. The kinetically computed surface stress is the input for the fully non-Newtonian (viscoelastic-liquid) sequel.

A. A. Friedmann (04.06.1888 – 16.09.1925) proposed the first physical cosmological models in 1920s. Despite the fact that Friedmann's works were very famous soon after their publication, the study of dynamic models of the Universe in the USSR was actually banned in the 30s - 50s of the last century, and Soviet philosophers and propagandists wrote that models of the evolving Universe were invented by Lemaitre on the demand of the Roman Pope, because according to Soviet philosophers such the birth of the universe is very similar to the divine creation of the world described in the Bible. Thus, in the USSR, Friedman's works were in oblivion in since 1930s until 1960s.

Local flux-tube gyrokinetic simulations of ion-scale turbulence in tokamak plasmas at finite plasma beta are conducted to investigate the generation of zonal flows via turbulent stresses. A parameter scan in the safety factor $q$ and electron beta $\beta_e$ reveals a transition from low- to high-transport states when $\beta_{\mathrm{eff}} \equiv q^2\beta_e$ exceeds a certain critical value $C_{\mathrm{nl}}$. While the linear stability limits for kinetic and ideal ballooning modes also scale as $\beta_e \propto 1/q^2$, they lie above the observed transition, indicating that the effect is not due to linear instabilities but to nonlinear dynamics. At low $\beta_{\mathrm{eff}}$, Reynolds stress dominates and drives zonal flows. At higher values, Maxwell stress becomes comparable, suppressing zonal-flow formation and leading to divergent transport. This nonlinear-transition boundary is determined for both the Cyclone Base Case and a spherical tokamak (ST40) configuration, suggesting that the relation $\beta_{\mathrm{eff}} = C_{\mathrm{nl}}$ may have broader applicability, though $C_{\mathrm{nl}}$ appears to be configuration-dependent. For the Cyclone Base Case, the ratio of energy transfer rates into zonal flows due to Maxwell and Reynolds stresses is observed empirically to scale as $\beta_e$ for $\beta_e$ below a critical value $\beta_{e,\mathrm{sb}}$ (scaling breakdown). The value of $\beta_{e,\mathrm{sb}}$ is found to increase with decreasing aspect ratio, suggesting that the linear scaling remains valid over a wider range of $\beta_e$ for more compact magnetic equilibria. This low-$\beta_e$ scaling provides the basis for a practical method to predict the nonlinear-transition threshold with minimal reliance on highly electromagnetic nonlinear simulations.

Chiral molecules have attracted broad interdisciplinary interest for their ability to produce highly spin-polarized current. This phenomenon, known as the chiral-induced spin selectivity effect, holds great potential in the field of spintronics. Here, we propose to combine chiral molecules with altermagnets to construct highly efficient and tunable spin valves. Using the nonequilibrium Green's function method and the Landauer-Büttiker formula, we obtain the conductance and the magnetoresistance of a normal metal/chiral molecule/altermagnet spin valve. Our theoretical results reveal that the conductance of the spin valve can be effectively tuned by reorienting the Néel vector of the altermagnet, and the magnetoresistance of the spin valve increases with molecular length and altermagnetic anisotropy. Moreover, the magnetoresistance vanishes for achiral molecules or in the absence of molecular spin-orbit coupling. Our work paves the way for developing efficient, controllable, and stray-field-free spintronic devices.

A novel physical mechanism whereby sheared equilibrium flow enables temperature-gradient-driven turbulence is identified. Gyrokinetic simulations of ion-scale plasma turbulence show that imposed equilibrium $\vec{E}\times \vec{B}$ flow shear can destroy the self-generated zonal flows that regulate the turbulence. This results in transport that increases sharply with flow shear. A reduced fluid model demonstrates that this is due to the spatial incompatibility of imposed and zonal shear layers. Simulations of spherical tokamak discharges place the inferred rotation shear at, or just below, the threshold of the sharp transport increase, implying that the toroidal rotation can be determined primarily by heat, rather than momentum, injection.

Plasmonic nanostructures offer an effective route for enhancing light-matter interaction in atomically thin semiconductors, whose optical response is intrinsically limited by their sub-nanometer active thickness. Here, we numerically investigate excitonic enhancement in monolayer (ML) Molybdenum Disulfide (MoS2) coupled to size-tuned gold (Au) nanocube arrays separated by thin aluminum oxide (Al2O3) and hexagonal boron nitride (h-BN) spacer layers. By varying the nanocube side length, the localized surface plasmon resonance is tuned across the visible spectral range to modulate the A- and B-excitonic transitions of monolayer MoS2. We show that the nanocube-size-dependent spectral redshift can be further controlled through the spacer material and thickness, enabling systematic tuning of the near-field distribution, carrier generation rate, quantum yield, and radiative decay enhancement. Localized plasmonic confinement yields excitation-rate enhancements of up to 4.35 at B-excitonic transition (605 nm) and 3.66 at A-excitonic transition (650 nm), while the radiative decay-rate enhancement exceeds 80, leading to 350-fold photoluminescence enhancement. Although both A- and B-excitonic channels are enhanced simultaneously, their relative contributions depend on nanocube size, spacer material, and spacer thickness, indicating wavelength-dependent excitonic modulation rather than strict exciton-selective switching. These findings establish Au nanocube arrays as a simple, scalable, and tunable plasmonic platform for enhancing excitonic carrier generation and emission in ML MoS2.

Kinetic instabilities, notably the whistler heat-flux instability (WHFI), are known to suppress thermal transport significantly in the moderate- to high-$\beta$ plasmas relevant to many astrophysical systems. This paper explores WHFI-regulated heat transport in a new regime: ultra-high-$\beta$ plasmas with $\beta_{e} \gtrsim L_{\mathrm{T}}/\rho_e$. Extrapolating previous theories of the WHFI to ultra-high-$\beta$ plasmas, we propose that the magnetic energy in unstable whistler fluctuations becomes comparable to that of the background magnetic field at saturation. We corroborate this hypothesis using 1D3V and 2D3V kinetic simulations using the particle-in-cell code OSIRIS. We find that, in ultra-high-$\beta$ plasmas, the heat flux is localised and no longer regulated primarily by resonant pitch-angle scattering of electrons; instead, thermal energy is transported predominantly by advection at the whistler phase velocity. Heat-flux suppression is observed in 1D3V and 2D3V simulations; however, we show that the saturation of the WHFI and the regulation of heat flux are sensitive to dimensionality in the ultra-high-$\beta$ regime. The amplitude and phase velocity of the heat-flux-regulating whistler waves scale differently with $\beta_e$, yielding parallel heat fluxes, normalised to the free-streaming value, of $q_{e\parallel} / q_\mathrm{fs} \approx 4.7 \beta_{e}^{-1}$ and $q_{e\parallel} / q_\mathrm{fs} \approx 0.3 \beta_{e}^{-1/2}$ in 2D3V and 1D3V simulations, respectively. We perform 2D3V simulations with background magnetic fields inclined to the temperature gradient, showing perpendicular heat transport remains negligible. We develop a heuristic theory from kinetic equations that explains these phenomena. Our work extends our understanding of how the WHFI modifies thermal transport to regimes applicable to high-energy-density physics and the reionised intergalactic medium.

We develop a Fokker-Planck description of the dynamics of wealth distribution in a stochastic multiplicative economic growth model with taxation and redistribution, as introduced by P.M.C. de Oliveira. Extending the original formulation, our theoretical framework includes general redistribution protocols, encompassing a broad class of state-dependent transfer mechanisms. As a particular case, we investigate a two-state protocol designed to emulate conditional cash transfer programs. Analytical expressions for the stationary wealth distributions are derived, revealing how the interplay between multiplicative noise, taxation, and redistribution shapes the emergence of inequality. The theoretical results are corroborated by agent-based simulations. To quantify and compare the impact of the different protocols, we employ the Gini index as a measure of inequality. Our analysis highlights how specific nonuniform redistribution schemes can significantly mitigate wealth disparities.

This paper establishes a conceptual and theoretical framework for multilevel communication between quantum, molecular, cellular, tissue-organ, whole body, and other biophysical spaces. The wave-mechanical description of electromagnetic signaling is developed, detailing how waves move through cellular structures and interact energetically with surrounding biomaterials. These regions transmit and receive partially coherent biomolecular signals within and across cells, tissues, organs, and neural networks, where resonant frequencies interfere, converge and respond. These processes introduce nonlinearities and stochastic delays that shape timing, coherence, and network-level dynamics, and can be integrated within a pragmatic framework linking mathematical modeling of the physical state to experiential outcomes. This contribution stands as an independent theoretical framework: it sets the foundation for the wave mechanical approach to understanding brain function, which may help to develop new methods to prevent aberrant brain behavior. Mathematical derivations of the inter-sector coupling operators and clinical and therapeutic applications are postponed for future work.

The recent advent of hyperpolarization techniques, which can enhance NMR signals by several orders of magnitude relative to thermally polarized samples, has enabled applications traditionally out of reach due to the inherently low sensitivity of NMR techniques. However, a high barrier to entry remains, as most hyperpolarization approaches either require complex instrumentation or are applicable only to a relatively small set of molecules. Here we introduce PHIPNOE, a platform that directly addresses both limitations. PHIPNOE is based on parahydrogen-induced polarization (PHIP), which is well-established as a scalable route to hyperpolarization requiring minimal instrumentation, but has been mostly restricted to molecules that undergo specific chemical reactions. We overcome this barrier by tailoring PHIP to create highly polarized, highly concentrated solutions of one specific molecule, which acts as an intermediate source of polarization. This 'source molecule' then distributes polarization to a broad range of target molecules mixed into the solution, via the spin polarization-induced nuclear Overhauser effect (SPINOE). We investigate chemical influences on PHIPNOE, and develop a predictive model to estimate enhancement based on molecular mass and T1 relaxation times. A complete run from PHIP hyperpolarization to PHIPNOE polarization transfer and signal detection takes less than one minute, the approach does not require any modifications to the NMR spectrometer, and enhancements are repeatable across molecular classes. PHIPNOE thus enables applications including single-shot multidimensional NMR, real-time monitoring of dynamic processes, and, with 300-fold signal amplification demonstrated on a benchtop spectrometer, practical low-field NMR, where we show enhanced sensitivity in detecting per- and polyfluoroalkyl substances (PFAS).

Correlation-consistent Gaussian basis sets are central to systematic molecular quantum chemistry, but their direct use in periodic solids is often limited by severe linear dependence from diffuse atomically optimized primitives. This problem is particularly acute for metallic and metal-containing systems, where reliable complete-basis-set (CBS) extrapolation is needed for correlated-wavefunction benchmarks. We introduce material-constrained atomic optimization (MCAO), a basis-set optimization framework that preserves the atomic and correlation-consistent character of Gaussian basis sets while penalizing large overlap-matrix condition numbers in representative solids. As a proof of concept, we generate Dunning-style MCAO-cc-pVXZ basis sets (X = D, T, Q) for Cu with all-electron, scalar-relativistic all-electron, effective core potential (ECP), and pseudopotential treatments. The resulting basis sets remain numerically stable for Cu solids and surfaces while reproducing molecular Cu dimer energetics and plane-wave reference properties of bulk Cu. CBS-extrapolated random-phase approximation calculations further enable a controlled assessment of pseudopotential, relativistic, and basis-set errors in bulk Cu and CO adsorption on Cu(111), providing scalar-relativistic all-electron Gaussian-basis benchmarks for the CO adsorption puzzle.

Prompt engineering is commonly presented as a technical competence for obtaining more accurate, relevant, or well-formatted outputs from large language models (LLMs). However, in STEM education, prompting should also be understood as a continuous epistemic practice. Students interpret contextual and disciplinary cues and adopt expectations about what kind of knowledge, representation, and action are appropriate. Drawing on epistemological framing, and AI-mediated concept-to-decision reasoning, the paper presents a new framework called epistemic prompting and proposes a multi-turn Framing-Prompting Loop. The educationally relevant outcome is a prompt framing trajectory: the sequence of prompts, model responses, learner uptake, disciplinary checks, and reframing moves through which a knowledge task develops. In this framework, an initial prompt establishes a provisional macro-frame by selecting the problem, representations, assumptions, criteria, and distribution of work between learner and model. Each subsequent learner turn can then maintain, specify, challenge, repair, or transform that organization. The implications for AI-mediated STEM instruction, and, specifically, on learner-LLM interaction are also discussed.

Industrial design in fields such as vehicle and aerospace engineering often relies on large-scale numerical simulations to evaluate fluid dynamics performance, which can incur substantial computational costs. Deep neural networks have shown promise in improving simulation efficiency, especially graph neural networks (GNNs), which demonstrate great potential due to their flexibility with unstructured data. However, GNNs face challenges when dealing with tasks involving complex geometries and large-scale meshes. In this paper, we propose the Multi-scale Feature Enhanced Graph Neural Network (ME-GNN) to tackle these challenges. ME-GNN employs a graph neural network with a two-step message-passing mechanism to capture detailed local features effectively. Additionally, it integrates an Attention U-Net with uniform grid discretization, enabling the extraction of both fine and coarse features. The model also utilizes K-hop sampling to construct subgraphs, facilitating efficient training on large datasets while preserving detailed local features. We evaluated ME-GNN on three benchmark datasets and achieved state-of-the-art results: a relative L2 error of 0.0196 for the velocity field and 0.0556 for the surface pressure on ShapeNet-Car, a normalized mean squared error of 0.0033 for the flow field on AirfRANS, and a relative L2 error of 0.1416 for the surface pressure on DrivAerNet.

Near-field radiative heat transfer can exceed the blackbody limit through evanescent-mode coupling across nanoscale gaps. This enhancement underpins applications including thermophotovoltaic energy conversion, electroluminescent cooling, thermal rectification, and photon absorption in plasmon-assisted photodetection. These systems most often involve photon- or heat-exchange between dissimilar interfaces, particularly between a semiconductor and a metal. Despite the prevalence of this asymmetric configuration, no closed-form description of its near-field interaction exists. Here, we derive a closed-form analytical description of photon tunneling that clarifies the roles of material properties, namely the plasma frequency, optical loss, and semiconductor absorption, in the thermal exchange. We show that the dominant in-plane wave vector of the radiative heat transfer is an approximate average of the corresponding values for two symmetric reference systems: a plasmonic-plasmonic cavity and a semiconductor-semiconductor cavity. These results establish a compact analytical framework for near-field heat transfer between dissimilar materials.

4H-SiC is a wide-bandgap semiconductor with high displacement threshold energy, large critical electric field, and low intrinsic carrier concentration, making it attractive for radiation-hard detector applications. In this work, we investigate the electrical characteristics of 4H-SiC P$^{+}$-in-N (PN) diodes and Low-Gain Avalanche Detectors (LGADs) fabricated by onsemi before and after irradiation by 24 GeV/c protons, reactor neutrons, and $^{60}$Co gamma rays. Current-voltage (IV) and capacitance-voltage (CV) measurements were performed at room temperature for proton fluences up to $1\times10^{16}\;\mathrm{protons/cm^2}$, neutron fluences up to $1\times10^{18}\;\mathrm{1\;MeV\;n_{eq}/cm^2}$, and total ionizing doses up to 300 kGy. Hadron irradiation induces pronounced changes in both leakage current and bulk capacitance, consistent with radiation-induced formation of deep acceptor-like defects and strong compensation of the originally N-type material. For high proton fluences, the leakage current decreases and the bulk capacitance becomes bias-independent, indicating effective compensation of the epitaxial layer. Extreme neutron fluences lead to a substantial expansion of the depleted region into the originally highly doped substrate, as inferred from the measured capacitance values. Gamma irradiation up to 300 kGy results in significantly modified capacitance behavior, suggesting reduction of the effective doping concentration in the epitaxial and multiplication layers. The results demonstrate that radiation-induced compensation strongly modifies the effective space charge in 4H-SiC devices at high hadron fluences, while the leakage current is influenced by the enlarged depletion volume together with field-enhanced and surface-related generation mechanisms. In contrast, ionizing damage primarily affects the effective doping and electric-field distribution.

The solar chromosphere is permeated by complex magnetic fields that guide plasma flows and energy into the corona. This work presents a detailed analysis of a unique, high-resolution observation of a giant chromospheric spiral structure that emerges due to a large magnetic pore, captured by the Swedish 1-m Solar Telescope (SST). A comprehensive data analysis pipeline is developed to automatically detect the edges of 2255 plasma flows (loops) that constitute the spiral, and these are used to extract the kinematics of flows propagating along the magnetic field. The analysis reveals three primary insights into the spiral's physics. First, magnetic curvature is correlated with oscillatory flow dynamics, i.e. regions of high loop curvature exhibit a statistically significant excess of higher-order oscillation modes compared to straighter loops; it is also correlated with higher intensity and longer periods. Second, spatial distribution of oscillation period shows an inverse trend, decreasing from $\sim$3.5 minutes in the pore to $\sim$3 minutes in the outer spiral arms. This is interpreted as a signature of the overlying trans-equatorial quadrupolar coronal loop system compressing the pore's field lines into a near-horizontal orientation, producing a period gradient that challenges the standard expanding canopy model. Finally, the emission signature confirms that oscillating threads represent localised channels of brightness that lie within cooler, absorbing loop material. This study provides the first statistical analysis of oscillatory flows in a large-scale spiral, probing energy flow through the chromosphere through curved magnetic structure.

Removable adhesive systems such as 3M Command strips are designed to support substantial loads while allowing clean, damage-free removal from the substrate. These systems rely on a highly extensible adhesive strip that bonds strongly during use but releases when stretched, causing the adhesive layer to elongate and progressively debond from the surfaces. A central challenge in the design of stretch-release adhesives is therefore to maximize load-bearing capacity while minimizing the force required for removal. This study investigates the finite-deformation mechanics governing both load support and tape release in a hyperelastic stretch-release adhesive system, with particular focus on the 3M Command tape geometry. Explicit analytical expressions are derived for the energy release rate of interfacial cracks under both load-bearing and release conditions and are validated against $J$-integral evaluations from finite element simulations. The results show that the ratio of maximum supported load to release force scales linearly with the ratio of bonded length to adhesive thickness, which is typically very large. We also investigate geometry-driven alternating crack propagation between the backing and substrate interfaces, governing tape removal, by analytical solutions and simulations. Parametric studies of competing interfacial fracture toughnesses produce failure envelopes that provide a predictive framework for estimating release forces and unstable crack propagation in multilayer stretch-release adhesive systems.

Human choice behavior, including route choice, exhibits systematic behavioral biases that deviate from the assumptions of full rationality. Cumulative prospect theory (CPT) has been widely recognized as an effective framework for characterizing such behavioral patterns. However, its large-scale application, particularly in simulation and agent-based modeling, critically depends on specifying individual-level CPT parameters, which remain a major bottleneck. Conventional approaches typically rely on surveys and controlled experiments to calibrate CPT parameters, yet these methods are difficult to generalize and often fail to capture the full diversity of human decision-making. To address this challenge, this paper investigates whether large language models (LLMs) can reproduce human behavioral biases in choice-making without explicit specification of prospect-theoretic parameters. Using route choice as a representative scenario, we design a behavioral evaluation framework and systematically compare LLM-generated decisions with established human behavioral patterns predicted by CPT. Experimental results demonstrate that LLMs are capable of reproducing non-rational human choice biases and can exhibit decision behaviors consistent with prospect-theoretic effects under uncertainty. These findings suggest that generative AI models may provide a scalable alternative for modeling human decision processes and offer a promising foundation for next-generation large-scale agent-based simulation and AI-driven behavioral research.

Dielectric bowtie nanocavities can concentrate light into subwavelength regions without the ohmic losses of plasmonic metals. We show that this enhancement is the finite-geometry realization of a classical electromagnetic edge singularity. Unlike an isolated dielectric wedge, the scaling in a bowtie is governed by an exponent determined by a collective four-sector singularity. In a finite structure, this scale-free singular field is regularized by the gap size, while the bowtie length sets the outer scale. The tip radius, gap, and bowtie length therefore play distinct physical roles: curvature cuts off the local wedge singularity, the gap cuts off the collective bowtie singularity, and the outer length sets the range over which the field can build up. Electrostatic simulations confirm the predicted scaling laws, while three-dimensional quasinormal-mode simulations show how the same near-field mechanism is accessed and limited by realistic dielectric nanocavities.

The axion is a theoretical particle that could resolve multiple fundamental problems, most notably the strong Charge-conjugation-parity-symmetry (CP) problem in quantum chromodynamics and the nature of dark matter.To date, however, the axion has never been detected in any free-space experiment. In this work, we designed and constructed a laser-based system that generates a three-dimensional, closed trapping potential field with a null central region. Owing to its spindle-like geometry, we term this configuration an optical spindle trap (OST). Along the propagation axis, the photon population evolves in a distinct manner from the left to the right terminus of the trap: it first diminishes and then recovers to its baseline value.This behavior is analogous to the photon axion photon conversion process sought in light shining through wall experiments(LSW)1-3, in which a measured photon deficit would constitute evidence for axion conversion. The photon population was monitored with a single-photon counter (SPC) operated well below its saturation threshold, and the observed behavior was corroborated by charge-coupled device (CCD) imaging at extremely low optical powers, thereby excluding detector artefacts as the origin of the photon deficit.Under the constraint of energy conservation, the missing photons are attributed to conversion into axions that remain undetectable by both the SPC and the CCD. The underlying conversion mechanism is ascribed to spin-coupled axion photon interactions. This tens-of-millimeter-scale optical spindle trap thus provides a viable free-space axion source, generated by a table-top laser, for the study of the strong CP problem and axion-like dark matter candidates.