1048 papers
Computational physics bridges the gap between abstract theory and real-world observation by using powerful computers to solve complex physical problems. This field allows scientists to simulate everything from the collision of subatomic particles to the swirling dynamics of galaxies, offering insights that traditional experiments alone cannot provide.
On Gist.Science, we continuously process every new preprint in this category from arXiv to make these breakthroughs accessible to everyone. Each entry is accompanied by both a clear, plain-language explanation and a detailed technical summary, ensuring that researchers and curious readers alike can grasp the significance of the latest findings without getting lost in dense equations.
Below are the latest papers in computational physics, curated to keep you at the forefront of this rapidly evolving discipline.
This paper extends the statistical geometry of insertion space from equilibrium hard spheres to repulsive active matter in one and two dimensions, deriving closed-form expressions that reveal how activity increases total insertion volume, enhances connectivity, and encodes signatures of collective phase behaviors.
This paper introduces DiffARFNO, a two-stage framework combining an autoregressive Fourier-MIONet for coarse long-horizon forecasting with a conditional DDIM corrector for fine-detail refinement, which significantly improves the accuracy of droplet evolution predictions in inkjet printing compared to existing state-of-the-art models.
This paper utilizes high-resolution Vlasov-Poisson simulations to investigate the formation dynamics, stability, and mode coupling of phase space vortices in a collisionless plasma, revealing how a quasi-stationary ion scale inhomogeneity influences electron acoustic wave evolution and triggers ion trapped particle instability.
This study demonstrates that Kapitza resistance at graphene-copper interfaces in non-equilibrium molecular dynamics simulations is highly sensitive to lattice initialization and residual strain, which can cause a two-fold variation in thermal resistance through strain-dependent phonon spectral shifts and the formation of damping boundary layers, rather than being primarily determined by domain size or simple phonon spectral overlap.
This study utilizes a Vlasov-Poisson solver to investigate how background quasi-stationary ion scale inhomogeneity, previously established in Part I, influences the formation and dynamics of phase space vortices under chirped frequency drives, revealing distinct behaviors such as early Langmuir mode onset, suppressed vortex sizes, and altered particle trapping fractions compared to homogeneous plasma cases.
This paper introduces an efficient ISDF-xTC-CCSD method that combines interpolative separable density-fitting with the transcorrelated framework to enable accurate, large-scale coupled-cluster calculations for both linear chains and complex molecules like benzene, achieving state-of-the-art accuracy and robust complete-basis-set convergence.
This paper introduces an optimization-based calibration strategy for phase field modeling that embeds target sharp-interface response functions into dilute alloy simulations by treating interfacial diffusivity as a tunable parameter, thereby enabling accurate quantitative prediction of solute trapping, solute drag effects, and resulting microstructural transitions in rapidly solidified multicomponent alloys.
This paper demonstrates that for large language models reasoning about chemistry and materials, a tiered, database-grounded verification system that prioritizes detecting specific factual errors over blanket retrieval significantly reduces confabulation rates by enabling targeted repairs, thereby identifying error detection rather than correction as the primary bottleneck in improving model accuracy.
This paper introduces a novel physics-informed neural network (PINN) approach that solves Monge--Ampère equations to design phase profiles for flat optics, enabling the reshaping of incident beams into prescribed intensity distributions for both finite and far-field targets with performance validated against conventional methods.
This paper employs a dynamic partial equilibrium Stackelberg model to simulate the 2026–2036 supply chains of critical minerals under three scenarios, including a theoretical political reunification of China and Outer Mongolia, to evaluate how deep resource integration and infrastructure development impact global supply security and China's social welfare.