751 papers
This study demonstrates that Denoising Diffusion Probabilistic Models (DDPMs) and their latent-space variants (LDMs) provide high-accuracy, computationally efficient frameworks for predicting complex physical fields, including thermal distributions and flow regimes ranging from incompressible to hypersonic.
This paper reviews analytical methods for solving low-Reynolds-number wedge and corner flow problems using the Papkovich-Neuber representation and the Fourier-Kontorovich-Lebedev integral transform to characterize Stokeslet and rotlet solutions for applications in microfluidics and confined hydrodynamics.
A quasi-experimental study in a high school physics course found that while using tablets and smartphones as experimental tools did not significantly outperform conventional teaching methods in terms of learning gains or motivation, it proved to be an effective alternative that achieved comparable results without causing negative effects like distraction or cognitive overload.
This paper proposes a Federated Learning framework for LEO 6G Non-Terrestrial Networks that leverages High-Altitude Platform Stations to distribute beam selection tasks, demonstrating that a Graph Neural Network model outperforms a Multi-Layer Perceptron in prediction accuracy and stability, especially at low elevation angles.
This paper introduces "Pufflets" as inertial counterparts to Stokeslets to demonstrate that metachronal waves of cilia can drive highly efficient particle transport through inertial coasting, a mechanism impossible in low-Reynolds-number Stokes flow.
This study employs pump-probe numerical simulations to investigate the light-induced nonadiabatic photodissociation of the NaH molecule, revealing how the interplay between multiple electronic conical intersections, electron-rotation coupling, and rotational motion governs ultrafast dissociation probabilities, kinetic energy release, and fragment angular distributions.
This paper presents the findings of "Canadian Physics Counts," the first nationwide survey of the Canadian physics community, which reveals significant underrepresentation of Black, Indigenous, and gender-diverse individuals, highlights a severe lack of accommodations for those with disabilities, and underscores the urgent need for targeted interventions to retain a diverse workforce.
Using an intermediate-complexity climate model, this study reveals that the Atlantic Meridional Overturning Circulation (AMOC) undergoes a boundary crisis under rising CO levels, where the collapse of its stable state and the resulting long chaotic transients governed by edge states explain large ensemble variances and apparent stochastic bifurcations in Earth system models.
This paper presents a low-cost, wireless wearable Electrical Impedance Tomography system utilizing five synchronized parallel AD5933 chips and specialized signal conditioning to achieve high-precision, real-time imaging of biological tissues such as human lungs with a signal-to-noise ratio exceeding 50 dB.
This study assesses Earth orientation parameter (EOP) accuracy from concurrent VLBI observations, revealing that errors are primarily driven by seasonal atmospheric noise correlations rather than scheduling strategies or source structure, and scale with session duration as a broken power law.
This paper introduces LOREM, a graph neural network architecture that employs equivariant messages for long-range interactions to overcome the limitations of cutoff-based models in capturing non-local physical effects like electrostatics and electron delocalization, achieving consistent and superior performance across diverse datasets without requiring dataset-specific hyperparameter tuning.
This study investigates autocatalytic reaction fronts in turbulent aqueous flows using oscillating grids and optical diagnostics, revealing distinct propagation regimes and demonstrating that even minor density differences significantly influence front dynamics by coupling chemical kinetics with flow-induced mixing.
This paper experimentally demonstrates that passive plasma lenses can preserve free-electron-laser-quality slice emittance while focusing beams two orders of magnitude more strongly than quadrupole magnets, with controllable focal parameters.
This study introduces a computational framework combining Design-by-Morphing and Bayesian optimization to generate undulatory swimming profiles that achieve 16%–35% higher propulsive efficiency than traditional anguilliform and carangiform modes by optimizing kinematic parameters and redistributing energy through favorable surface stress distributions.
This paper investigates the over-damped dynamics of chiral active elastic filaments, deriving sixth-order nonlinear equations that reveal dynamic multi-stability in their shapes, and validates these theoretical predictions through linear stability analysis and numerical simulations.
This study characterizes the light yield and transmission properties of Saint-Gobain's BCF-91A and Eljen Technology's new EJ-160 wavelength-shifting fibers under ionizing radiation, revealing that the EJ-160 variants offer significantly higher light yields (5–7 times greater) despite varying attenuation lengths.
This paper presents an improved mechanistic model for wave energy attenuation in drifting sea ice that accounts for ice-water drag, successfully replicating observed non-exponential decay profiles and spatial variations in attenuation rates that traditional exponential models fail to capture.
This paper introduces an efficient preconditioning method derived from the metric tensor to accelerate gradient-based optimization of infinite projected entangled pair states (iPEPS), significantly improving computational efficiency and convergence for simulating strongly correlated quantum systems like the Heisenberg and Kitaev models.
Using molecular dynamics simulations and a validated one-dimensional theoretical framework, this study reveals that ion adsorption at the water-silica interface generates molecular-scale roughness and additional friction, significantly increasing apparent viscosity and governing ultra-confined ionic transport in wetting films.
Researchers have developed new 1 mm-thick Silicon Drift Detectors that significantly enhance quantum efficiency at 30 keV while maintaining excellent energy resolution, enabling the upcoming EXKALIBUR and VIP-3 experiments to study heavier kaonic atoms and test the Pauli Exclusion Principle with greater precision.