physics.geo-ph papers | Gist.Science

Modeling resonance characteristics of the Chang'e-7 lander modulated by solar panel rotation under lunar south-pole thermal environment

This study establishes a high-fidelity finite-element model of the Chang'e-7 lander to demonstrate that extreme lunar south-pole thermal cycles, primarily affecting solar array stiffness, cause significant drift in the lander's fundamental resonance frequency (0.64–0.87 Hz), which critically overlaps with the seismic observation window and necessitates specific noise filtering strategies for accurate interior probing.

Lei Zhang, Jinhai ZhangWed, 11 Ma🔬 physics

Operator Learning for Consolidation: An Architectural Comparison for DeepONet Variants

This study systematically evaluates and enhances DeepONet architectures for geotechnical consolidation problems, demonstrating that a physics-inspired, Fourier feature-enhanced model (Model 4) significantly outperforms standard configurations and achieves up to 1,000-fold computational speedups in 3D scenarios, thereby enabling efficient uncertainty quantification and advancing the integration of scientific machine learning in geotechnics.

Yongjin Choi, Chenying Liu, Jorge MacedoWed, 11 Ma🤖 cs.LG

Well Log-Guided Synthesis of Subsurface Images from Sparse Petrography Data Using cGANs

This paper presents a conditional Generative Adversarial Network (cGAN) framework that synthesizes realistic, continuous pore-scale images of carbonate rock formations by conditioning on well log-derived porosity values, effectively bridging gaps between sparse petrography samples to enhance reservoir characterization for energy transition applications.

Ali Sadeghkhani, A. Assadi, B. Bennett, A. RabbaniWed, 11 Ma🤖 cs.LG

Analysis of Tidal Perturbations Due to Asymmetric Response of LARES 2 and LAGEOS

This study quantitatively analyzes asymmetric tidal perturbations on the LARES 2 and LAGEOS satellites by identifying 83 significant Earth tide constituents and demonstrating that the cumulative effect of the remaining minor constituents is non-negligible, thereby providing essential parameters for high-precision orbital dynamics and fundamental physics tests like the Lense-Thirring effect.

Xizhi Hu, Xiaodong Chen, Jianqiao Xu, Ignazio Ciufolini, Wei-Tou Ni, Antonio PaolozziWed, 11 Ma🔭 astro-ph

Universal scaling between precursory duration and event size across mechanically driven geohazards

By applying a physics-based framework to a global dataset of 109 geohazard events, this study reveals a universal, near-linear scaling relationship between precursory duration and failure volume, indicating that catastrophic failures across diverse mechanically driven systems are governed by common organizing mechanisms involving the progressive growth of correlated deformation toward a dynamical critical point.

Qinghua Lei, Didier SornetteTue, 10 Ma🔬 physics

A global well-posedness result for the three-dimensional inviscid quasi-geostrophic equation over a cylindrical domain

This paper establishes the global existence and uniqueness of generalized solutions for the three-dimensional inviscid quasi-geostrophic equation on a cylindrical domain with a multiply connected cross-section under specific Neumann and no-flux boundary conditions, assuming the initial potential vorticity is essentially bounded.

Qingshan ChenTue, 10 Ma🔬 physics

The direct spectral element method for the calculation of synthetic seismograms in self-gravitating, spherically symmetric planets

This paper introduces $\texttt{DSpecM1D}$ , a new implementation of the direct spectral element method using a displacement formulation to calculate synthetic seismograms in self-gravitating, spherically symmetric, anelastic, and transversely isotropic Earth models, which is validated against existing codes with excellent agreement.

Alex D. C. Myhill, David Al-AttarTue, 10 Ma🔬 physics

Magnetoconvection in a spherical shell: Equatorial symmetry during the transition from the weak- to the strong-field regime

This paper demonstrates that the transition between weak- and strong-field dynamo regimes in spherical shells is characterized by a breaking of equatorial symmetry, which is triggered by the sudden growth of the magnetic field and subsequently sustains the strong-field branch.

Luke J. Gostelow, Robert J. TeedTue, 10 Ma🔬 physics

DiffSIM: Unconditional and conditional facies simulation based on denoising diffusion generative models

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.

Minghui Xu, Suihong Song, Tapan MukerjiTue, 10 Ma🔬 physics

Topographic Effects on Steady-States of Non-Rotating Shallow Flows

This paper presents a novel theoretical and numerical framework to demonstrate that non-rotating quasi-2D viscous flows over topographies settle into steady states where large-scale vortices occupy topographic valleys, a behavior distinct from rotating systems and significant for understanding slow planetary flows.

Pierpaolo Bilotto, Roberto VerziccoTue, 10 Ma🔬 physics

A semi-analytical pseudo-spectral method for 3D Boussinesq equations of rotating, stratified flows in unbounded cylindrical domains

This paper presents a robust semi-analytical pseudo-spectral method utilizing mapped associated Legendre polynomials and an advanced exponential time differencing scheme to efficiently and accurately simulate rotating, stratified flows in unbounded cylindrical domains by overcoming the numerical stiffness typically caused by strong shear and fast wave forces.

Jinge Wang, Philip S. MarcusTue, 10 Ma🔬 physics

On the coupled geometrical-mechanical origin of the earthquake b-value in fault networks

This paper establishes that the earthquake b-value arises from the power-law scaling of fault rupture area and slip magnitude within three-dimensional fault networks, linking earthquake statistics directly to fault mechanics and fracture energy dissipation.

Wenbo Pan, Zixin Zhang, Bjorn Lund, Qinghua LeiTue, 10 Ma🔬 physics

Physics-Informed Diffusion Model for Generating Synthetic Extreme Rare Weather Events Data

To address the critical data scarcity of extreme rare weather events that hinders robust machine learning models, this paper proposes a physics-informed diffusion model based on Context-UNet that generates physically consistent, multi-spectral synthetic satellite imagery conditioned on key atmospheric parameters, thereby effectively mitigating extreme class imbalance and enhancing operational weather detection algorithms.

Marawan Yakout, Tannistha Maiti, Monira Majhabeen, Tarry SinghTue, 10 Ma🤖 cs.LG

Dynamic restrengthening and fault heterogeneity explain megathrust earthquake complexity

This study demonstrates that the complex rupture dynamics of the 2011 Tohoku-Oki megathrust earthquake, including multiple rupture episodes and large tsunamigenic slip, can be self-consistently explained by the interplay of preexisting fault heterogeneity and rapid coseismic frictional restrengthening.

Jeremy Wing Ching Wong, Alice-Agnes Gabriel, Wenyuan FanThu, 12 Ma🔬 physics

EarthquakeNPP: A Benchmark for Earthquake Forecasting with Neural Point Processes

The paper introduces EarthquakeNPP, a rigorous benchmark for earthquake forecasting that reveals current Neural Point Process models fail to outperform the classical ETAS model, highlighting the need for improved collaboration between seismology and machine learning communities.

Samuel Stockman, Daniel Lawson, Maximilian WernerThu, 12 Ma🔬 physics

Monitoring of slopes, rock faces and masonry walls in a 19th century public park: the example of the Buttes Chaumont Park (Paris, France)

This paper outlines a comprehensive, multi-level geotechnical monitoring scheme implemented by BRGM and the Paris City Council since 2021 to assess and mitigate gravitational hazards in the historically unstable Buttes Chaumont Park by correlating displacement data with meteorological conditions to guide future restoration and safety efforts.

Marc Peruzzetto (IPGP, IPGP - UMR\_7154, BRGM), Isabelle Halfon (BRGM), Clara Lévy (BRGM), Florian Masson (BRGM), Aurore Ramage (BRGM), Gildas Noury (BRGM), Daoud Benazzouz, Marina Kudla, Laurence LejeuneThu, 12 Ma🔬 physics

Crustal Structure Imaging of Ghana from Single-Station Ambient Noise Autocorrelations and Earthquake Arrival Time Inversion

This study utilizes single-station ambient noise autocorrelation and joint earthquake arrival time inversion to generate a high-resolution crustal velocity model and seismicity catalog for southern Ghana, successfully imaging the Paleozoic basement beneath the Voltaian Basin and demonstrating the efficacy of passive seismic methods for crustal characterization in sparsely instrumented intraplate regions.

Hamzeh Mohammadigheymasi, Courage K. Letsa, Nasrin Tavakolizadeh, Zamir Khurshid, S. Mostafa Mousavi, Cyril D. Boateng, Paulina Amponsah, Martin SchimmelThu, 12 Ma🔬 physics

Shock Wave in the Beirut Explosion: Theory and Video Analysis

This paper combines non-linear shock wave theory with frame-by-frame video analysis of the 2020 Beirut explosion to derive the Landau-Whitham formula for overpressure layer thickness and demonstrate strong agreement between theoretical predictions and observational data.

Adam J. Czarnecki, Andrzej Czarnecki, Raquel Secrist, Julia WillseyThu, 12 Ma🌀 nlin

Assessment of the Earth orientation parameter accuracy from concurrent VLBI observations

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.

Leonid Petrov, Christian Ploetz, Matthias SchartnerMon, 09 Ma🔬 physics

An Efficient Self-supervised Seismic Data Reconstruction Method Based on Self-Consistency Learning

This paper proposes a self-supervised, lightweight deep learning method that leverages self-consistency learning and inter-component correlations to achieve high-quality reconstruction of irregularly acquired seismic data without requiring external training datasets.

Mingwei Wang, Junheng Peng, Yingtian Liu, Yong LiMon, 09 Ma🤖 cs.LG