Papers

Minimal seeds are the smallest amplitude perturbations that trigger transition to turbulence in a subcritical flow. They are presented in the Stokes boundary layer, the oscillating flow of a viscous fluid above a flat plate, at a fixed initial phase corresponding to the timing of the Stokes boundary layer's optimal linear transient growth, at two moderate Reynolds numbers, and in two domains accommodating one and two wavelengths of the linearly optimal growing mode. Although the minimal seed trajectories are dominated by the flow's large linear transient growth at early times, only 77% of the initial energy is formed from the linearly optimal growing mode; the remainder ensures that nonlinear interaction transfers energy from spanwise- to streamwise- independent structures, and makes up for a timing mismatch between the end of linear transient growth and the production phase of the edge state (the saddle point separating the laminar and turbulent basins of attraction).

We numerically study topological effects of electromagnetic (EM) waves in a two-dimensional (2D) non-Hermitian photonic crystal (PhC) composed of lossy magneto-optical materials. In this system, not only the EM wavefunctions but also the complex eigenfrequencies exhibit nontrivial topological properties. We demonstrate that the non-Hermitian skin effect, protected by point gaps in the complex eigenfrequency spectrum, emerges at both the edges and corners of truncated structures. This phenomenon has no counterpart in Hermitian systems. In addition, we identify non-Hermitian topological edge states originating from the nontrivial topology of the bulk bands. While most previous studies of non-Hermitian topology have focused on tight-binding models, our work addresses a continuous photonic system, providing a more realistic platform and offering a concrete route toward experimental realization of non-Hermitian effects.

We investigate how models of fluid properties and boundary conditions influence predictions of convective mixing in confined porous media, with relevance to subsurface carbon dioxide storage. Using high-resolution simulations at high Rayleigh-Darcy numbers (O($10^4$)), we analyze miscible fluids with linear, nonlinear, and non-monotonic density-concentration relationships under fixed- and free-interface in 2D and 3D. We show that, across all cases, mixing is quantified by the mean scalar dissipation, providing a unifying framework for convective-diffusive interactions. The density-concentration relationship affects mixing via the effective density contrast driving convection and the position of the maximum density. Free interfaces enhance early-time mixing through deformation, while long-term behavior depends on fluid properties and dimensionality. We demonstrate that simplified modeling assumptions (e.g., monotonic density laws or 2D flow) can lead to deviations in predicted mixing rates of up to O(10-100)%. These results offer guidance for model selection and improving predictions of convective mixing in geophysical systems.

Drug-Filled Porous Implants (DFPIs) are an innovative solution for delivering drugs in a controlled and sustained manner to target sites. To optimize their performance across various physiological conditions, it is essential to understand how fluid flow and porous media properties influence the drug release process. In this work, we numerically investigate a wide range of flow conditions and their effects on drug release from DFPI. The DFPI is modeled as a homogeneous, saturated porous medium, with flow through the porous structure modeled using the Forchheimer-extended Darcy law. Drug diffusion within the DFPI and its transport through the surrounding channel are simulated using a diluted species transport approach. The results reveal the impact of flow conditions and porous media characteristics on the drug release profile of the implant and drug availability within the channel. The variations in drug release behavior are analyzed by modeling the release as an apparent first-order process with a time-dependent rate constant. Notably, the results highlight specific conditions under which the rate constant increases during the later stages of drug release from the DFPI, particularly at high Reynolds numbers, while also ensuring a prolonged operational time period of the implant. These findings suggest the potential for developing intelligent DFPI designs capable of delivering drugs in a manner more attuned to the specific needs of the application.

Recently, it was predicted that nonreciprocal magneto-electric effect in antiferromagnetic multilayered metamaterials occurs in two distinct versions. One is the conventional axion response, while another one is dual axion response captured by electrodynamics with magnetic charge. Here we investigate a model condensed matter system of spins coupled through antiferromagnetic exchange interaction and derive its effective electromagnetic properties. We predict that this system gives rise to the emergent dual axion field, support our conclusion by numerical simulations and put forward candidate materials.

We present the development of readout electronics and artificial-intelligence-based particle-identification methods for the SoLID Cherenkov detectors at Jefferson Lab. To operate in the high-rate, high-background SoLID environment, we designed a MAROC sum readout system for multianode photomultiplier tubes that provides simultaneous pixel, quadrant-sum, and total-sum signals. Bench studies show that the system can sustain rates at or above those expected for SoLID while maintaining acceptable pedestal behavior and signal linearity. Using realistic Geant4 simulations for the heavy-gas Cherenkov detector, we then investigate $\pi/K$ separation with beam-related background. A simple photoelectron-counting cut is insufficient under these conditions, whereas multilayer perceptron models trained on PMT, quad, and pixel readout data perform substantially better. The quad and pixel readout schemes achieve pion and kaon efficiencies above 90% and clearly outperform PMT-only readout. These results demonstrate that the combination of high-rate MAROC sum electronics and AIML-based pattern recognition provides a practical path toward robust SoLID Cherenkov PID.

The concept of homophily is pervasive in online social media. While many empirical studies have relied on external sociodemographic traits to investigate it, significantly less is known about homophily at the cognitive level, that is, at the level of shared opinions or values. For such "value homophily", in this paper we study interval-based patterns of opinion homophily from a bounded confidence perspective. We consider three heterogeneous datasets from Reddit and Twitter covering polarizing issues, with user opinions quantified via sentiment analysis and fact-checking, and analyze the interaction networks formed by weaker (reply-based) and stronger (follow-based) social ties. Our findings show that users' interaction neighborhoods are significantly more concentrated in opinion space than expected by chance, with tie strength and issue polarization further amplifying this effect. Moreover, users often exhibit asymmetric tolerance ranges, with asymmetry typically directed toward locally mainstream positions rather than more radical or opposing ones. These findings support a bounded confidence interpretation of online value homophily.

Soil salinity is a major environmental challenge in coastal Bangladesh, threatening agricultural productivity and local livelihoods. This study develops a machine-learning-based framework to predict and map soil salinity in Satkhira district by integrating field observations with Landsat-derived spectral indices. A total of 205 soil samples collected during 2024-2025 were used to train an Extreme Gradient Boosting (XGBoost) model, and predictions were further improved using a Generalized Additive Model (GAM). Spatial cross-validation was applied to reduce autocorrelation bias, and bootstrap resampling was used to quantify prediction uncertainty. The results show strong spatial variability of soil salinity, with higher concentrations in the southern and central coastal regions and lower levels in the northern inland areas. Vegetation indices, particularly NDVI, along with salinity-related spectral indicators, were identified as key predictors. 10-year-window peak-exposure maps generated for 2014-2023 reveal recurrent high-salinity zones and a persistent, expanding footprint of moderate-to-high salinity exposure across the central parts of the district. Uncertainty analysis indicates higher variability in coastal zones and improved prediction stability when multi-year datasets are combined. The proposed framework provides a robust and scalable approach for long-term monitoring of soil salinity. It supports climate-resilient agriculture, land-use planning, and evidence-based decision-making in coastal Bangladesh.

The flow condition at the leading edge governs the dynamics of the leading-edge vortex, which is crucial for understanding the separated flow over an airfoil at high angle of attack. Furthermore, with extensive applications in biomimetic flight, the wings encountering high-angle-of-attack situations in an unsteady manner are of great interest. The leading-edge suction parameter (LESP) is a dimensionless metric proposed to quantify the leading-edge flow condition, and is implemented in the LESP-modulated discrete vortex method, which successfully predicts aerodynamics of airfoils in motion. To discern the timing of leading-edge vortex formation, a critical threshold for LESP is chosen to control the onset of separation. However, it is not obvious that the same strategy could be applied to a stationary wing where the separation is not dominated by the motion of the airfoil. We conduct computational fluid dynamics (CFD) simulations for a stationary NACA0012 airfoil at high angles of attack, and extract the leading-edge flow quantities from the CFD data. In addition, vorticity flux, which contributes to the formation of vortices above the top surface of the airfoil, is also investigated to reveal the vorticity budget and its relevance to aerodynamic performance. We show that for the laminar case ($Re=1000$), the instantaneous LESP is well correlated with the lift, while for the turbulence ($Re=10^5$), the time-averaged LESP is well correlated with the lift. The result would provide insights into future improvements for vortex-based models of separated flows.

This paper reports on the status of the Tsinghua tabletop Kibble balance experiment, aiming to deliver a mass calibration instrument for kilogram realizations in accordance with the new International System of Units (SI). Major progress since 2024 in different aspects, i.e., electrical, magnetic, mechanical, and optical, is presented. The primary weighing and velocity measurement results are discussed.

This work evaluates the magnitude of the turbulent energy cascade in terms of forward and backward scattering by modeling the "stretch and fold" mechanism through a drift-free Hanggi-Klimontovich stochastic process. Mapping this dynamics onto an equivalent Ito process provides a statistical justification for the uniform distribution of the Lagrangian Lyapunov exponent via the associated Fokker-Planck equation. This continuous distribution is shown to be driven by a Lagrangian bifurcation rate significantly higher than the Lyapunov exponents themselves, reflecting the high frequency with which trajectories encounter the singular surfaces of the velocity gradient. The resulting PDF corresponds to the simultaneous maximization of the information entropy and the Kolmogorov-Sinai entropy. This stochastic formulation, framed within the author's Lyapunov-Liouville analysis, provides a non-diffusive analytical closure of the von Karman-Howarth and Corrsin equations. While forward scattering emerges from trajectory instabilities and bifurcations, backscattering is linked to fluid incompressibility. These phenomena are quantified through the continuously distributed Lyapunov exponents, allowing for an estimation of canonical exponents and fundamental transport properties, such as eddy viscosity, eddy thermal diffusivity, and the turbulent Prandtl number. These parameters, traditionally associated with diffusive models, are shown to emerge naturally from non-diffusive Lagrangian dynamics and bifurcation-driven fluctuations. The analytical results demonstrate close agreement with numerical data available in the literature.

Low-field MRI is increasingly considered accessible for imaging owing to its lower cost, simpler infrastructure requirements, and potential for mobile and point-of-care deployment. A central challenge is achieving clinically useful field strength and homogeneity while keeping the magnet lightweight and maintaining patient accessibility. This work presents the design and magnetostatic simulation of a pole-less, 0.2 T, C-type bipolar magnet comprising two cylindrical N52 permanent magnets and four concentric rings that replace traditional pole pieces to enhance field homogeneity and reduce weight in bipolar magnet designs. Geometric parameters, including each magnet ring thickness, height, angular anchorage, spacing between magnets, and the magnets' vertical offset relative to the horizontal yokes, were manually investigated to improve magnetic field homogeneity in a 20 cm DSV. Simulations were performed in CST Studio Suite, yielding a peak field of 0.2 T, with a peak inhomogeneity of 1.43 mT across the 20 cm DSV and a total weight of 590 kg. A pole piece design with comparable dimensions, used as a benchmark for inhomogeneity and weight, was designed and simulated. It yielded a peak field of 0.15 T and a weight of 890 kg, with a 0.7 mT inhomogeneity over a 20 cm DSV. This study demonstrates the feasibility of replacing the traditional pole pieces with magnet rings to reduce weight while enhancing patient access with the C-magnet structure in yoked MRI systems.

Orbital angular momentum (OAM) of light can be used as a degree of freedom for optical communication. However, the reliable transmission of OAM beams through time-varying scattering media remains challenging. In this paper, we report an approach for OAM transmission through time-varying scattering media using dual orthogonal-polarization channels. A perfect vortex beam (PVB) is generated and transmitted at one channel, and the plane wave is employed as a reference beam at another channel. With the cross-correlation obtained between the recorded speckle patterns at each single-shot measurement, the data can be retrieved without prior knowledge about time-varying scattering media. It is revealed that the multiplexed PVB can be applied to generate recognizable coherent-superposition patterns in cross-correlation images. Experimental results demonstrate that the proposed method can be applied to transmit the data through time-varying scattering media, and high robustness can be achieved. The proposed method could open up an avenue for the development of OAM transmission in harsh environments.

Societal complexity may be at a historical peak. Distinct from entropy, complexity tends to rise as systems move away from order, crest at an intermediate state, and decline as entropy continues increasing. The use of a thermodynamic analogy and the timing of major technological milestones, from fire to artificial intelligence, shows that the acceleration and recent compression of transformative events fit the derivative of a logistic growth curve. This pattern suggests that the rapid rise in structural and technological novelty may soon begin slowing. Notably, the trajectory parallels the bell-shaped rate of global population growth, consistent with the view that demographic expansion fuels innovation. If complexity growth is indeed cresting, societies face the challenge of managing heightened fragility while adapting to diminishing returns in transformative change. This perspective explores whether the rapid acceleration of technological innovation observed in recent centuries may reflect a civilizational system approaching the region of maximal complexity often associated with the edge of chaos.

We examine whether the observer split of a covariantly conserved electric current in a rotating finite system can provide a physically constrained effective source for the scalar sector of extended Aharonov–Bohm electrodynamics. We first recall that rotation, a stationary gravitomagnetic background, or a change of coordinates cannot by themselves generate genuine microscopic charge non-conservation for standard locally $U(1)$-invariant matter; this simple no-go statement is used to delimit the phenomenological context. In a $3+1$ decomposition adapted to a rotating apparatus, the transport continuity equation contains the exact observer-split term $I_{\mathrm{split}}=N^{-1}D_i(\rho\beta^i)$, which reduces for weak rigid rotation to $I_G=\Omega\partial_\phi\rho$. We propose to use this restricted, congruence-dependent source as a phenomenological input to the extended scalar sector. The relevant observer/evolution structure is not an arbitrary coordinate choice: the laboratory synchronization and readout protocol select the foliation, while the rotor motion fixes the evolution field relative to it. We characterize which features of a genuine extra-current can and cannot be represented by this construction, and discuss falsifiable signatures, including rotation reversal, axisymmetric-source suppression, gradient scaling, and a recently proposed optically gated rotating-disc test. Analogue-gravity systems are also identified as a possible future setting in which a preferred material flow naturally selects the observer congruence.

Oscillation and frequency modulation have been leveraged for applications in detection (or sensing), data processing, and telemetry. This work provides a theoretical analysis of oscillation phenomena with negative impedance implemented using a cross-coupled transconductance pair. The negative impedance can consist not only of a negative resistance but also of a negative inductance and a negative capacitance, where the negative resistance supplies energy to the inductance and capacitance, causing oscillation at a resonant frequency. Also, the resonant frequency can be modulated by combining with passive components such as a resistor, an inductor, and a capacitor. In this work, a comprehensive circuit analysis employing small-signal models and transfer functions is performed to understand the oscillation phenomena and resonant frequencies arising from a combination of active and passive RLC circuits, in which the active RLC circuit is modeled as a negative impedance and implemented using a cross-coupled transconductance pair.

The primal-dual hybrid gradient (PDHG) algorithm for solving convex optimization problems that arise in tomographic imaging is revisited. In particular, simplification of the selection of step-size parameters is developed for optimization problems with multiple terms, each containing a linear transform subject to splitting. This simplification maintains algorithm efficiency while avoiding massive grid searches for the optimal parameter settings. The PDHG framework is demonstrated on an image reconstruction problem for wide-angle digital breast tomosythesis (DBT); use of the proposed optimization problem is enabled by the framework and it is demonstrated to have some advantage in quantitative accuracy of the reconstructed volume and in improving DBT depth resolution.

Optical cavities play a central role in photonic and quantum technologies by enhancing light-matter interactions. In semiconductor microcavities, achieving high quality (Q) factors typically relies on sophisticated epitaxial growth techniques, such as molecular beam epitaxy, which offer atomic-scale precision but are costly and limited in material compatibility. For dielectric microcavities, high Q factors can be achieved using dielectric Bragg mirrors. However, conventional deposition techniques for the top mirrors, such as plasma-enhanced chemical vapor deposition or sputtering, can damage embedded emitters. This limitation is particularly severe for van der Waals materials, especially atomically thin semiconductors. Moreover, the conventional top-mirror deposition can cover or degrade predefined metal contacts. Recovering electrical access typically requires additional lithography and etching steps. Here, a deterministic dry-transfer approach is developed to fabricate complete dielectric microcavities using both top and bottom SiO_2/TiO_2 Bragg mirrors without post-growth lift-off processes, reaching a Q factor ~ 4x10^3. Using a WS_2 monolayer as the active medium, clear signatures of strong exciton-photon coupling are observed at both room temperature and cryogenic temperatures. These results demonstrate an efficient cavity fabrication approach that preserves the integrity of the emitter of layered materials, enabling next generation integrated photonic devices.

Bio-inspired $\pmb \vee$ flight formation is a well known technique for energy saving among groups of fixed-wing aircraft, and as of recently, for groups of quad-rotors. Here, we study the effect of the formation angle on the performance of each of the members of a 5-member $\pmb \vee$-formation in terms of the flow field, and drag force. We employ axisymmetric cylinders, which are non-lifting in solo condition to reduce/eliminate the effect of the lift (lateral force) on the group performance, and use time-resolved, multi-illumination, consecutive-overlapping particle image velocimetry (PIV) to capture the velocity field around and in-between the members. Over a range of $\pmb \vee$-formation angles, we see various degree of drag reduction, with the highest drag reduction ($\sim 80\%$) for the interior members of the tightest formation (formation with the smallest $\pmb \vee$-angle and the most overlap in frontal views). All formation members experience some levels of drag reduction up for $\pmb \vee$-angle of around $50^{\circ}$ and in formation with $\pmb \vee$-angle greater than $50^{\circ}$, only the leading member experiences observable drag reduction. We explore the complex flow dynamics between the formation members in terms of wake-body and wake-wake interactions, and the bleeding (gap) flow. We present the mean and fluctuating quantities, as well as the dynamics of the vortex shedding and circulation in the wakes of the members, and discuss how these flow characteristics relate to the drag of each member, both as a function of their position within the $\pmb \vee$ and the angle of the formation. This current study serves as a baseline for further explorations of wake-body and wake-wake interactions of flow past groups of bodies, and demonstrates how changing formation angle can help achieve a desired group performance (like minimum drag).

Preclinical micro-CT reconstruction involves large projection sizes and volumes that make iterative methods costly - 5x to 50x slower than analytic alternatives on modern GPUs. Whether this cost is justified depends on the imaging task, yet head-to-head comparisons using task-based metrics on identical preclinical data are lacking. We benchmark four reconstruction methods on identical acquisitions from an eXplore CT 120 micro-CT scanner (Trifoil Imaging, USA): an open-source Feldkamp-Davis-Kress (FDK) pipeline, the proprietary vendor software, and two iterative toolboxes at default settings - ASTRA SIRT and TIGRE OS-SART. Using the modulation transfer function (MTF), noise power spectrum (NPS), and non-prewhitening detectability index (NPW d'), we show that single-metric rankings are misleading: the vendor software achieves the highest spatial resolution ($\mathrm{MTF}_{10} = 2.96$ lp/mm) but fails to reach the Rose criterion ($d'=3$) for 100 HU contrast objects on a half-scan acquisition. ASTRA SIRT, at 5x the computation time of FDK, provides the best low-contrast detectability, while TIGRE OS-SART at 50x the cost offers no additional benefit and exhibits instability across scan protocols. For high-contrast tasks, all methods perform comparably. We release our FDK pipeline as open-source software, providing a fast, transparent, and integrable reconstruction tool for the preclinical micro-CT community.

Plasma sheet bubbles, defined as entropy-depleted flux tubes, are widely regarded as an efficient mechanism for transporting plasma into the inner magnetosphere during geomagnetic storms. Equilibrium simulations using the Rice Convection Model (RCM-E) predict that bubbles can account for up to 60% of storm-time ring current energy during intense storms. However, global simulations and observations suggest a more moderate net contribution. In this study, we quantify the contribution of plasma sheet bubbles to ring current buildup using a Lagrangian particle backtracking technique applied to three idealized storm simulations conducted with the inertialized Rice Convection Model (RCM-I). A stratified ensemble of about 100,000 test particles, weighted by local plasma pressure and entropy, was traced backward in time to determine whether their energy originated from bubble injections, non-bubble plasma sheet transport, or pre-existing trapped populations. Our results show that bubble contributions increase with storm intensity but saturate near 40% of the total ring current energy inside R<6.6Re, even for strong storms (Dst about -180nT). The trapped population remains comparably important (about 40%), while non-bubble transport contributes about 15%. This saturation is notably lower than the 61% predicted by RCM-E and is attributed to inertial braking, which generates oscillatory flows and tailward return streams that remove approximately 40% of the inward bubble energy flux. When only newly transported plasma is considered, bubbles account for about 73% of the inward transport, consistent with global MHD and flux-based studies. These results reconcile equilibrium modeling, global simulations, and spacecraft observations by demonstrating that bubbles dominate inward transport but do not fully replace the resident ring current population due to inertial limitations.

At any sustained positive growth rate of energy demand, depletion of all terrestrial energy resources, including non-renewable deuterium fusion and renewable solar, occurs within a remarkably compressed period. The time to depletion is inversely proportional to the demand growth rate. Artificial Intelligence (AI) has the potential to increase the growth rate of electricity from three percent per year to fifteen percent per year, effectively collapsing multi-millennial expansion timelines into decades. To grow after terrestrial depletion will require capturing more of the sun's output than the earth's cross-sectional area, eventually capturing the entire sun's output (Kardashev Type~II civilization). Expansion beyond that threshold requires colonizing other star systems. Simple algebraic models yield the main conclusions of the paper, supported by a system dynamics simulation. This analysis reveals that even unthinkably vast resources, such as total oceanic deuterium or the full luminosity of the Sun, are decidedly finite when viewed through a logarithmic lens. Uncertainties in the exact remaining resources of coal, oil, natural gas, and uranium do not affect the conclusions of this paper, as the fundamental physical limit is dictated by the geometry of expansion and the universal speed of light.

We develop an angular momentum representation and implementation of the Clifford+T set of unitaries for qutrits. We show that local gates from this set can be realized by the sole use of suitable rotations and one-axis-twisting operations, which are at most quadratic in the angular momentum operators and thus can be experimentally realized in many quantum systems. Controlled rotations are shown to only require linear angular momentum couplings and, as a consequence, the full qutrit Clifford+T set is shown to be expressed solely in terms of two-body angular momentum couplings, rotations and one-axis-twisting operations. By employing the Jordan-Schwinger map, we show an analogous implementation in terms of bosonic modes, improving on the number of modes with regard to a previous scheme. Moreover, we employ the cross-Kerr interaction in order to obtain any qutrit Clifford+T gate for bosonic modes. We illustrate our findings with simple schemes for preparing entangled states of interest.

Environmental noise can enhance transport, an effect known as environmental noise-assisted quantum transport. Most theoretical studies focus on optimizing system parameters under spatially uniform system-environment coupling. Here, instead, we optimize the environmental noise itself by allowing for site-dependent dephasing. We investigate steady-state transport in one-dimensional lattices with either ramped or disordered energy landscapes, considering both short- and long-range coherent tunneling. In the absence of environmental effects, in the thermodynamic limit these systems can exhibit localization, and thus suppressed transport, arising from destructive interference. Using a Lindblad master equation framework, we implement local dephasing optimized to maximize steady-state population flux. We find that for ramp potentials, short-range tunneling favors selective dephasing on alternating sites, whereas long-range tunneling benefits from a dephasing profile that increases with distance from the injection site. In energetically disordered systems, strongly detuned sites require enhanced local dephasing under short-range tunneling to facilitate transport. In all cases, we find that site-optimized dephasing allows higher transport efficiency than uniform dephasing, and it is accompanied by increased spatial delocalization of the steady state. Our results provide microscopic insight into the interplay between coherent dynamics and environmental noise. Dephasing broadens energy levels locally, helping to overcome detuning and destructive interference. More generally, we establish spatially-structured environmental noise as a strategy for controlling both quantum transport and state coherence in open systems.

We derive equations of motion for capital deepening in a competitive economy directly from accounting identities, without assuming a production function. A profit imperative $\eta^* \equiv (w/\kappa + 1/\tau)/(1-f_p)$ sets the minimum viable capital productivity, where $\eta = Y/K$ [yr$^{-1}$] is capital productivity, $\kappa = K/L$ is capital per worker, $w$ is the wage rate, $\tau$ is the capital lifetime, and $f_p$ is the production tax share. Four coupled relaxation equations govern $\kappa$, $\eta$, the frontier productivity $\eta_{\rm new}$ of new investment, and the labor share $q \equiv w/y$, with the sandwich constraint $\eta^* \leq \eta_{\rm new} \leq \eta$ maintained as an exact invariant. The frontier equation separates two physically distinct channels: a structural cheapening channel ($\mu$, always active, drives $\eta_{\rm new}$ downward) and a productivity channel ($\phi$, historically zero). Calibration against BEA 2-digit NAICS sector data (1998–2023) confirms $\phi = 0$ for all identifiable sectors over 25 years; the 75-year postwar record extends this finding across four capital lifetimes. A step $\phi = 0.01$\,yr$^{-1}$ – a 1%/yr improvement in new-capital productivity, modest but historically unprecedented – nearly doubles the aggregate growth rate within one capital lifetime, a falsifiable prediction with a precise observable signature: upward-curving $\eta(t)$ in BEA sector data. Firms near the zero-profit threshold have a cash martingale, predicting establishment exit rate $\sim t^{-1/2}$; convolved with the Zipf firm-size distribution~\cite{WP}, this yields firm exit rate $\sim t^{-1/2}\!\log t$ with apparent exponent $b = 0.295 \pm 0.03$, confirmed against BDS data with no free parameters.

High-fidelity simulation of particle-matter interactions provides the essential theoretical reference for diverse physics disciplines, yet generating synthetic datasets at the scale of current and future experiments has become prohibitive. Here, we introduce PHIN-GAN, a novel physics-informed generative adversarial network designed to address this challenge. We derive a set of analytical probability density functions, that effectively describe the “straggling function” identified with Landau. For the first time, this enables their continuous evaluation across the entire phase-space. These analytical forms are leveraged to enforce a parametric distribution-level learning objective. Rooted in first principles, PHIN-GAN offers a generalizable, interpretable and scalable proof-of-concept approach for a lossless generative model that maintains the high fidelity of the standard-bearer for simulating such interactions, namely GEANT4, at a fraction of the computational cost.

Crystalline noble metal flakes are emerging as versatile platforms in nanophotonics, enabling a broad range of optical phenomena and applications. Their atomically flat surfaces, high crystallinity, and superior optical quality open new avenues in advanced plasmonics, quantum light generation, and hybrid photonic systems. In contrast to conventional polycrystalline metal films, which typically suffer from higher optical losses due to grain boundaries, surface roughness, and structural disorder, these monocrystalline flakes provide minimal scattering and enhanced performance. They serve as templates for precise nanostructuring through techniques like focused-ion beam (FIB) milling and are crucial for advanced applications in sensing and optoelectronics. Additionally, they facilitate frontier research in quantum plasmonics, enabling fundamental studies of nonlocal optical effects and the generation of nonclassical light. Furthermore, the well-defined $\{111\}$ facets of these flakes host Tamm–Shockley surface states that support 2D plasmons coexisting with bulk modes. At near-infrared wavelengths and beyond, crystalline flakes act as nearly ideal metallic mirrors, featuring surface roughness limited only to atomic terrace steps, making them highly suitable for integration with 2D materials in hybrid photonic architectures. This review surveys the key roles these flakes play, highlighting recent developments and discussing future prospects while emphasizing their unique benefits in addressing fundamental and applied challenges in modern nanophotonics.

The distribution of income and wealth in developed economies exhibits a robust two-class structure: an exponential (Boltzmann–Gibbs) bulk covering $\sim\!97\%$ of the population, and a power-law (Pareto) tail in the upper $\sim\!3\%$. We derive this structure from first principles via an explicit mechanistic chain: Gibrat's law for firm growth implies a Zipf firm-size distribution; maximum entropy applied to within-firm wages, combined with mixture aggregation across firms, yields a Boltzmann–Gibbs income distribution with temperature $T_y$ for employees; additive-noise wealth dynamics with a reflecting wall at zero produce a Boltzmann–Gibbs employee wealth distribution with temperature $T_w$. For firm owners, multiplicative capital returns produce a Pareto wealth tail with exponent $\alpha_w = 1/\theta$, where $\theta$ encodes how total returns scale with firm size. The empirical value $\alpha_w \approx 1.30$ \cite{Yakovenko2009} is reproduced with no tuned parameters from the observed firm value scaling $V = V_0(s/s_0)^{0.77}$~\cite{Axtell2001}, and simultaneously yields the first quantitative estimate of the returns-per-employee size exponent: $\zeta = \theta - 1 \approx -0.23$. For empirical values $\nu \approx 0.3$, $c \approx 0.81$, $k \approx 0.15$ (BEA long-run savings rate $\approx 5\%$), the model gives $T_w/T_y \approx 1.7\,\text{yr}$, i.e.\ lower-class households hold roughly 1–2 years of income as wealth, with the precise ratio depending on savings and tax rates and testable cross-country. As a parameter-free empirical test, firms near zero profit have a cash martingale whose first-passage time gives establishment exit rate $\sim t^{-1/2}$; convolving with the Zipf firm-size distribution yields firm-level exit rate $\sim t^{-1/2}\!\log t$, with apparent exponent $b = 0.295 \pm 0.03$, confirmed against BDS firm-age data with no free parameters.

We develop a continuous Wilsonian renormalized-flow theory of weak wave turbulence directly in spectral frequency space, for finite cascades in experimentally driven Newtonian fluids. The central quantity is a scale-dependent effective coupling that governs nonlinear transfer across logarithmic frequency shells and organizes the cascade as a finite renormalized branch. Within this formulation, the inertial interval is constructed dynamically as a plateau of the running flow, whose non-autonomous character is expressed through its explicit dependence on the logarithmic distance from the injection scale and thereby encodes the cumulative action of forcing and degradation along the cascade. The ultraviolet cutoff follows internally as the terminal scale at which the plateau branch ceases to exist, whereas the integrated spectral response is fixed by infrared matching to the injection scale. In this way, the finite inertial branch is determined by the renormalized dynamics itself, while Kolmogorov–Zakharov (KZ) spectra arise only as its asymptotic constant-flux scaling states. The theory applies to both capillary and gravity wave turbulence and admits a physically transparent realization in monochromatically driven discrete cascades, which fix the topology-dependent exponent structure of the renormalized flow.

Bio-inspired propulsion using oscillating fins has gained attention for its potential to achieve high thrust, efficiency, and maneuverability. Many aquatic organisms generate propulsion through coordinated fin oscillations, and understanding these hydrodynamic mechanisms can inform the design of advanced underwater vehicles. A numerical framework is developed to simulate a NACA 0020 hydrofoil undergoing prescribed heave and pitch about the leading edge in a uniform freestream. Simulations are performed using WaterLily, a two-dimensional incompressible flow solver based on the Boundary Data Immersion Method (BDIM). Key kinematic parameters, frequency, heave amplitude, pitch amplitude, and phase offset, are characterized through nondimensional groups, primarily the Strouhal number. Reynolds number is held constant to isolate kinematic effects, while an additional parameter is introduced to describe phase driven interactions in multi fin systems. The study begins with a single fin to establish baseline force generation. A reduced order model incorporating a leading-edge torsional spring is then developed to emulate flexibility. The effects of asymmetric actuation, through heave speed, pitch bias, and stiffness variation, are also examined, demonstrating the generation of net lateral forces for maneuvering. Next multi-fin configurations investigated. Downstream fins interact with vortices shed by upstream fins, enabling energy extraction from the wake. Results show that tuning phase offsets and spacing can significantly enhance thrust, while poor timing reduces performance. To efficiently explore the growing parameter space, Bayesian optimization is applied to identify high performance configurations. This work provides insight into the hydrodynamic mechanisms of oscillating fin propulsion and establishes a framework for designing efficient, bio-inspired underwater propulsion systems.