1164 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 presents a variational approach to Initial Boundary Value Problems that treats coordinate maps as dynamical degrees of freedom, ensuring exact conservation of space-time symmetries and Noether charges even in discrete settings, which naturally drives an automatic adaptive mesh refinement process.
This paper numerically investigates and proposes the "Space-Clock Elevator," a modular orbital transport architecture that utilizes synchronized rotating tethers and intermediate elliptical nodes to enable propellant-free, multi-stage payload transfers between different orbital regimes while maintaining dynamic stability.
This paper demonstrates that integrating nature-inspired hyperuniform nanohole patterning into the front glass of planar perovskite solar cells significantly enhances broadband light absorption and power conversion efficiency to 23.62% by optimizing light redistribution and angular tolerance while preserving electronic interfaces and maintaining robustness against fabrication-induced disorder.
This paper demonstrates that two-dimensional altermagnets, exemplified by CrSO, enable the ultrafast control of spin and valley degrees of freedom via linearly polarized femtosecond laser pulses, facilitating nearly 100% spin-polarized valley currents and a novel "ghost Hall" effect where spin and charge currents become orthogonal without traditional Hall physics.
This paper proposes a data-efficient, physics-informed transfer learning approach using a Bidirectional Long Short-Term Memory (Bi-LSTM) network to rapidly and accurately extract optical properties from 3D Monte Carlo time-resolved spectroscopy data, effectively bridging the gap between analytical models and stochastic simulations while enabling real-time inference.
The paper introduces HydroFirn, an efficient large-scale multidimensional numerical model for firn hydrology that overcomes the limitations of traditional one-dimensional approaches by simulating coupled unsaturated-saturated flows and dynamic ice layer formation, thereby improving the understanding of meltwater percolation and reducing uncertainties in sea-level rise estimates.
This paper reviews the generalization of Behler-Parrinello machine-learning architectures to metallic spin systems, introducing symmetry-aware descriptors and a generalized potential theory to enable accurate, large-scale simulations of both equilibrium magnetic orders and nonequilibrium spin dynamics driven by external voltages.
This paper analyzes the stability of quantum Krylov subspace methods and reveals that while they face numerical ill-conditioning in ideal settings, their performance in realistic noisy environments is primarily limited by statistical fluctuations, prompting the introduction of new filtering metrics to reliably assess solution quality without prior knowledge of the true spectrum.
This study numerically demonstrates that the length, shape, and stiffness of bicuspid valve leaflets critically determine their efficiency in preventing retrograde flow, explaining why shorter leaflets in abnormal or immature valves lead to reflux.
This study demonstrates that while finite temperatures can completely quench particle transport over high potential barriers at intermediate ranges for both Langevin and Basset-Boussinesq-Oseen (BBO) dynamics, hydrodynamic memory in BBO systems uniquely mitigates this effect by sustaining initial momentum, thereby enabling transport even in regimes where thermal fluctuations would otherwise halt it.