726 papers
This paper presents and validates a generalized algorithm for efficient Monte-Carlo sampling of metastable systems using non-local updates in collective-variable space under underdamped Langevin dynamics, demonstrating substantial performance improvements over previous overdamped approaches and extending the applicability of machine-learning-based samplers to more realistic molecular systems.
This paper reports the successful calibration and performance assessment of a new room-temperature Cadmium Zinc Telluride (CZT) detector array at the DANE collider, demonstrating its excellent linearity and stability for future precision spectroscopy of kaonic atoms within the SIDDHARTA-2 program.
By modeling US House elections as a random field Ising system, this paper empirically validates a critical spending threshold of approximately $1.8 million that triggers a phase transition to high political polarization, where election outcomes become determined by voter alignment rather than total campaign expenditure.
This paper develops, simulates, and analytically derives a spatio-temporal random synthetic turbulent velocity field based on a divergence-free fractional Gaussian framework and Ornstein-Uhlenbeck temporal evolution, demonstrating that its statistical properties align with direct numerical simulations of the Navier-Stokes equations.
This paper presents a versatile analytic model for predicting the broadband Photon Detection Efficiency of VUV-sensitive Silicon Photomultipliers across various wavelengths, angles, and temperatures, validated by experimental data and demonstrated through successful extrapolation to liquid noble environments and optimization for astroparticle physics and quantum computing applications.
This paper introduces a novel, locally conservative spatial discretization for the compressible Euler equations of thermally perfect gases that guarantees discrete entropy conservation while preserving linear invariants and kinetic energy, offering improved accuracy and robustness over existing methods.
This paper proposes a method to distinguish between organic and artificial rumor virality by analyzing oscillatory patterns in autocorrelation using the modified Maki-Thompson model, while also demonstrating how targeted network interventions can manipulate a rumor's lifespan.
This paper presents a generalized theory of zonal flow growth in toroidal geometry, demonstrating that radial magnetic drifts drive a new propagating branch called the toroidal secondary mode and validating this framework against gyrokinetic simulations.
This paper demonstrates that strongly driven ion-scale turbulence in tokamak plasmas is regulated by a newly identified propagating zonal flow mode called the toroidal secondary mode, which nonlinearly shears turbulent eddies above a specific threshold to establish scaling laws for heat flux and fluctuation spectra that align with both simulations and experimental observations.
This paper extends Minkowski's theory to derive constitutive equations and boundary conditions for a mechano-driven media system under low-speed approximation, enabling the comprehensive modeling of engineering electromagnetism by coupling electric, magnetic, and mechanical force fields to account for medium deformation, rotation, and interfacial processes.
This paper demonstrates that on Geometric Inhomogeneous Random Graphs, majority-vote opinion dynamics lead to the stabilization of localized opinion domains rather than global consensus, a phenomenon rigorously explained by a mean-field model showing a stationary interface profile that supports persistent opinion diversity.
This paper proposes Multi-Kernel Gated Adapters (MKGA) and their residual variant (ResMKGA) to address asymmetric feature degradation under cross-center domain shifts in thyroid ultrasound by leveraging the complementary strengths of CNNs and ViTs to enhance both segmentation robustness and malignancy diagnostic accuracy.
This paper presents the design, construction, and initial performance evaluation of the IMAS system, a long axial field-of-view PET prototype that uniquely combines time-of-flight and depth-of-interaction capabilities, demonstrating sub-4 mm spatial resolution and improved tumor identification in pilot clinical results despite some performance limitations attributed to data transfer bottlenecks.
This paper demonstrates the application of the Sparse Identification of Nonlinear Dynamics (SINDy) method with a weak formulation to accurately identify effective microparticle interaction potentials from noisy simulation data, offering a promising approach for analyzing experimental dusty plasma systems like the PK-4 experiment.
This paper presents a physics-based pore-network model for yield-stress fluid flow in disordered porous media that accurately captures nonlinear transport and channelization by deriving pressure-flow relations from pore-scale mechanics, revealing that near-yield pressure losses are governed by constriction statistics rather than obstacle-scale length.
This paper proposes a unified methodological framework, drawing from diverse scientific fields such as soft matter, ecology, and machine learning, to analyze and redesign complex food systems in order to better predict critical transitions and optimize interventions for mitigating climate change.
This study utilizes optical-optical double-resonance spectroscopy with both frequency comb and continuous-wave probes to measure and assign hot-band transitions of ethylene between 3000 cm⁻¹ and 9000 cm⁻¹, providing improved center frequencies and tentative quantum assignments for numerous ladder-type and V-type transitions.
This paper presents a review of a statistical mechanics approach, based on Jaynes' information-theoretical entropy, which provides a manageable continuum-scale description of immiscible two-phase flow in porous media by deriving thermodynamics-like relations and identifying new emergent variables such as co-moving velocity.
This paper proposes a "bridge theory" framework, comprising partition, magnitude, and closure conditions, to explain how inter-level scientific connections require constructs that generate a "contingent space" of states not determined by either the underlying dynamical or observational theories alone.
This study demonstrates that strategically arranging slip and no-slip wall patterns in straight microchannels can induce secondary swirl flows to significantly enhance convective heat transfer efficiency without increasing hydraulic resistance or requiring additional pumping power.