734 papers
Using DMRG calculations on the Pariser-Parr-Pople model for polyene chains, this study quantifies the triplet-pair population of the $2^1A_g$ dark state, predicting a finite-size scaling value of approximately 75% that confirms its predominantly triplet-pair character and supports its role in singlet fission mechanisms.
This study utilizes dry idealized simulations to demonstrate that poleward-shifted, broader, and deeper jet streams accelerate cyclone intensification, promote anticyclonic Rossby wave breaking, increase the frequency of cyclone merging, and dynamically precondition the atmosphere for persistent stationary anticyclones, thereby modulating midlatitude weather extremes.
While Kossin et al. (2020) attributed a rising ratio of major tropical cyclones to a decline in weaker Category 1 storms, extending the data through 2023 reveals a genuine intensification trend driven by both fewer weak storms and an actual increase in strong Category 3 and 4 storms.
This paper proposes a Meta-PINNs framework that integrates meta-learning to enhance physics-informed neural networks, demonstrating significantly improved convergence, generalization, and accuracy with reduced computational costs for predicting turbomachinery flows under varying operating conditions compared to standard methods.
This study demonstrates that machine learning can effectively parameterize unresolved midlatitude mesoscale vertical fluxes in Earth system models by leveraging vertically non-local information from temperature, moisture, and meridional wind, thereby offering a targeted approach to improve the representation of complex processes like slantwise convection and frontal dynamics.
This paper presents a reduced mathematical model based on center manifold theory for open cavity flow, which successfully captures key dynamics such as unstable quasi-periodic edge states and limit-cycle switching by explaining the stability exchange through cross-coupling terms in amplitude equations.
The NUCLEUS experiment characterizes the unidentified low energy excess in its sapphire detector by demonstrating that the excess rate is independent of particle background levels but decreases with slower cooling procedures, following a universal power-law decay over time.
This paper argues that the late emergence of chaos theory in the 1960s, despite its mathematical foundations being established by Poincaré and his colleagues decades earlier, was primarily caused by the strict empiricist tenets of positivism, which led to the dismissal of chaotic systems as "useless" and "meaningless" mathematics due to their perceived lack of grounding in experience.
This paper extends the Statistical State Dynamics framework to shallow water magnetohydrodynamic turbulence, demonstrating how the interplay of Reynolds and Maxwell stresses leads to the formation and equilibration of zonal jet-toroidal field structures that explain both steady phenomena like solar super-rotation and time-dependent events such as the solar cycle.
This study employs global linear stability analysis and simulations to reveal that the stability of rising oblate bubble pairs is primarily governed by inclination-induced rotational feedback and lift rather than deformation, while also identifying distinct short-range and long-range coupling mechanisms for different instability modes and a new oscillatory mode driven by unsteady recirculation.
This paper argues that for steady, fully developed incompressible Navier-Stokes flows, the condition where the total mechanical energy gradient is perpendicular to the streamline causes the viscous term to vanish and the solution to lose -regularity, thereby creating a weak singularity where the equations degenerate into the Euler equations.
This study combines experiments and simulations to reveal that premixed NH3/H2/air flames are stabilized behind bluff bodies through a coupled feedback mechanism where preferential hydrogen diffusion creates a localized diffusion flame at the root, enhancing radical production and anchoring, while thermal expansion significantly alters the flow field to sustain a robust, carbon-free combustion regime.
This study evaluates four large language models on AP Physics free-response questions, finding that while they demonstrate strong capabilities in structured algebraic problem-solving, they exhibit significant limitations in spatial reasoning, visual interpretation, and conceptual integration, with performance varying notably across different years and exam levels.
This paper presents a general numerical framework that combines weighted interpolation with a conservative flux mapping algorithm to accurately reconstruct interfaces and transfer data between partitioned multiphysics domains, achieving high geometric and flux conservation accuracy across various applications.
This paper introduces DiffSIM, a denoising diffusion-based framework that utilizes DDPMs and DDIMs to efficiently generate geologically plausible facies models in both unconditional and well-constrained conditional settings, successfully reproducing realistic geological patterns while honoring hard data without additional loss weights.
This study improves the hydrodynamic modeling of free-swimming *Chlamydomonas reinhardtii* by demonstrating that a modified three-sphere model incorporating differential drag on flagellar spheres successfully reproduces experimental flow characteristics that the standard model fails to capture.
This study employs Bayesian structural time-series causal inference on multi-decadal satellite data to demonstrate that the rapid expansion of nickel processing facilities at Indonesia's Morowali Industrial Park has caused a significant, quantifiable degradation of coastal water clarity, posing potential risks to the region's high-biodiversity marine ecosystems.
This paper presents an extension of the GPU-accelerated Monte Carlo toolkit gPET to support flexible multi-layer detector geometries for Depth-of-Interaction (DOI) encoding, demonstrating through validation that the new framework enables efficient simulation and optimization of PET systems with significantly improved radial spatial resolution while maintaining comparable sensitivity and runtime performance.
This paper establishes a low-dimensional dynamical framework for two-dimensional vertical falling films to identify and characterize exact coherent states—such as travelling waves, relative periodic orbits, and equilibria—that underpin the system's chaotic interfacial dynamics.
Using Bayesian inference and generalised extreme value regression on five CMIP6 models, this study projects that extreme temperatures in Earth's desert regions will significantly increase over the next century, with the most pronounced rises in annual maximums under severe forcing scenarios.