惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

P
Privacy International News Feed
I
Intezer
T
Tenable Blog
S
Schneier on Security
Project Zero
Project Zero
G
GRAHAM CLULEY
酷 壳 – CoolShell
酷 壳 – CoolShell
小众软件
小众软件
Know Your Adversary
Know Your Adversary
博
博客园 - 司徒正美
The Cloudflare Blog
Recent Commits to openclaw:main
Recent Commits to openclaw:main
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
N
News and Events Feed by Topic
博
博客园 - 叶小钗
宝玉的分享
宝玉的分享
L
LINUX DO - 热门话题
aimingoo的专栏
aimingoo的专栏
S
Secure Thoughts
Forbes - Security
Forbes - Security
T
The Exploit Database - CXSecurity.com
D
Darknet – Hacking Tools, Hacker News & Cyber Security
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
博
博客园 - 【当耐特】
罗
罗磊的独立博客
IT之家
IT之家
H
Hacker News: Front Page
I
InfoQ
云风的 BLOG
云风的 BLOG
S
Security Affairs
M
MIT News - Artificial intelligence
GbyAI
GbyAI
Jina AI
Jina AI
Help Net Security
Help Net Security
Engineering at Meta
Engineering at Meta
大猫的无限游戏
大猫的无限游戏
Webroot Blog
Webroot Blog
L
Lohrmann on Cybersecurity
A
About on SuperTechFans
Attack and Defense Labs
Attack and Defense Labs
The Register - Security
The Register - Security
V
V2EX
G
Google Developers Blog
D
DataBreaches.Net
Apple Machine Learning Research
Apple Machine Learning Research
C
Cybersecurity and Infrastructure Security Agency CISA
J
Java Code Geeks
W
WeLiveSecurity
Cloudbric
Cloudbric
T
Tor Project blog

math updates on arXiv.org

Coupling-Robust Accuracy in Multiphysics Physics Informed Neural Networks via Kronecker-Preconditioned Optimization Non-normal spectral signatures of instability in neural network training dynamics Optimization of randomized neural networks for transfer operator approximation Selective Ambulance Dispatch Under Contextual Travel-Time Uncertainty LLAMA LIMA: A Living Meta-Analysis on the Effects of Generative AI on Learning Mathematics Learning Decision-Sufficient Representations for Linear Optimization Parameterized Complexity of Stationarity Testing for Piecewise-Affine Functions and Shallow CNN Losses Prabhakar function and unified fractional kinetic equation in bicomplex space Computing Gamma(p/q) with Beta function values Flows on Graded Manifolds Optimal embedding dimension in the Nash--Tognoli theorem An optimal first-order method for smooth and strongly convex composite optimization and its stationary limit Sharp Bohr-Type inequalities for certain classes of close-to-convex functions Invariants of real affine varieties based on their complexifications Topological symmetric and braid homologies A Formal Graph-Theoretic Framework for Pitch Class Set Analysis Finite groups with high commuting probability for Sylow subgroups Performance Bounds for Rollout Policies in Stochastic Shortest Path Problems Real 2-blocks in quasi-simple groups Maximal subalgebras of the Lie algebra $W_n(\mathbb{K})$ Cohomogeneity-One Ruled Hypersurfaces in $\mathbb{CP}^2$ and $\mathbb{C}H^2$ Global analysis of the Kuramoto flow Neural Flow Operators can Approximate any Operator: Abstract Frameworks and Universal Approximations LLMs as Noisy Channels: A Shannon Perspective on Model Capacity and Scaling Laws On the Stability of Spherical Hellinger-Kantorovich Flows and Their Implications for Differential Privacy Training-Free Looped Transformers Move on Muon : A Hamiltonian probability gradient flow perspective of Muon optimizer Entrywise Error Bounds for Spectral Ranking with Semi-Random Adversaries Asymmetric Scaling Laws from Sparse Features Is Dimensionality a Barrier for Retrieval Models? RA-DCA: A Randomized Active-Set DCA for Directional Stationarity in Max-Structured DC Programs Commutator-Induced Uncertainty in VAEs Weisfeiler-Leman Is Incomplete on Simple Spectrum Graphs, so Canonicalize Them Sparse In-Network Learning via Shortest-Path Backpropagation and Finite-Rate Gating Generalized Stochastic Approximation of the Log-Likelihood Ratio for Robust Sequential Change-Point Detection Instance-Optimal Estimation with Multiple LLM Judges on a Budget Entropy Equivalence Testing Expand More, Shrink Less: Shaping Effective-Rank Dynamics for Dense Scaling in Recommendation Any-Dimensional Invariant Universality Operationalizing Individual Fairness via Gradient Descent and Bradley-Terry Models Anytime Training with Schedule-Free Spectral Optimization Concise and elegant proofs of three formulas for complete Bell polynomials On Reed-Muller subcodes, Grassmannian partitions and sum-free functions Diffusion-based Denoising Beats Vanilla Score Matching in Parameter Estimation: A Theoretical Explanation Resilience Characterization of AI-Native Wireless Receivers via Persistent Homology The General Theory of Localization Methods A Comprehensive Study of Clique Graphs and Clique Regular Graphs Every signed planar graph is $5$-choosable: A short proof and refinements General Lower Bounds for Differentially Private Federated Learning with Arbitrary Public-Transcript Interactions PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels Proximal basin hopping: global optimization with guarantees Democratizing Large-Scale Re-Optimization with LLM-Guided Model Patches On Stability and Decomposition of Sample Quantiles under Heavy-Tailed Distributions Symmetry-Compatible Principle for Optimizer Design: Embeddings, LM Heads, SwiGLU MLPs, and MoE Routers Stochastic Non-Smooth Convex Optimization with Unbounded Gradients Dimension-Free Convergence of Discrete Diffusion Models: Adjoint Equations Induce the Right Space The Geometry of Cooperative Game Solutions: Stratified Egalitarian Shapley Values An Axiomatic Theory of Tie-Breaking: Impossibility, Characterization, and Decomposition PyCSP3-Scheduling: A Scheduling Extension for PyCSP3 Strategic PAC Learnability via Geometric Definability Proximal-Based Generative Modeling for Bayesian Inverse Problems Every Minimal Counterexample to the Erdős-Gyárfás Conjecture is Predominantly Cubic SPHERICAL KV: Angle-Domain Attention and Rate-Distortion Retention for Efficient Long-Context Inference NOVA: Fundamental Limits of Knowledge Discovery Through AI Model-based Bootstrap of Controlled Markov Chains TopoGeoScore: A Self-Supervised Source-Only Geometric Framework for OOD Checkpoint Selection Minimal Filling Architectures of Polynomial Neural Networks: Counterexamples, Frontier Search, and Defects Omni-scale Learning-based Sequential Decision Framework for Order Fulfillment of Tote-handling Robotic Systems Grokking or Glitching? How Low-Precision Drives Slingshot Loss Spikes Towards an Inferentialist Account of Information Through Proof-theoretic Semantics Random test functions, $H^{-1}$ norm equivalence, and stochastic variational physics-informed neural networks QUIVER: Cost-Aware Adaptive Preference Querying in Surrogate-Assisted Evolutionary Multi-Objective Optimization Robust and Fast Training via Per-Sample Clipping Beyond Continuity: Simulation-free Reconstruction of Discrete Branching Dynamics from Single-cell Snapshots Wasserstein Distributionally Robust Regret Optimization for Reinforcement Learning from Human Feedback Deep Learning of Solver-Aware Turbulence Closures from Nudged LES Dynamics Information bottleneck for learning the phase space of dynamics from high-dimensional experimental data QED: An Open-Source Multi-Agent System for Generating Mathematical Proofs on Open Problems Information-Theoretic Measures in AI: A Practical Decision Guide Inference of Online Newton Methods with Nesterov's Accelerated Sketching A Unified Fractional Regularization Framework for Sparse Recovery Mathematical Foundations for Peer-to-Peer Lattice Computation Geometric Layer-wise Approximation Rates for Deep Networks RateQuant: Optimal Mixed-Precision KV Cache Quantization via Rate-Distortion Theory ML-based approach to classification and generation of structured light propagation in turbulent media Zeroth-Order Optimization at the Edge of Stability Adaptive Learning via Off-Model Training and Importance Sampling for Fully Non-Markovian Optimal Stochastic Control. Complete version Beyond Fixed False Discovery Rates: Post-Hoc Conformal Selection with E-Variables Order-Optimal Sequential 1-Bit Mean Estimation in General Tail Regimes Training-Free Rate-Distortion-Perception Traversal With Diffusion Conformal Policy Control Linear Regression with Unknown Truncation Beyond Gaussian Features ArcMark: Distortion-Free Multi-Byte LLM Watermark via Optimal Transport Feature Learning Dynamics in Infinite-Depth Neural Networks ATHENA: Agentic Team for Hierarchical Evolutionary Numerical Algorithms Normalizing Flows on Quotient Manifolds via Boundary Quotients What Can Be Recovered Under Sparse Adversarial Corruption? Assumption-Free Theory for Linear Measurements TelecomTS: A Multi-Modal Observability Dataset for Time Series and Language Analysis Program Evaluation with Remotely Sensed Outcomes Efficient Gradient Estimation for Parameterized Quantum Systems with Lie Algebraic Symmetries
Global Well-Posedness and Numerical Approximation of a Coupled Darcy-Convection-Diffusion System with Exponential Nonlinearity
[Submitted on 25 Jan 2026 (v1), last revised 17 Jun 2026 (this v · 2026-06-18 · via math updates on arXiv.org

View PDF HTML (experimental)

Abstract:This paper investigates density driven flow in porous media, focusing on the roles of viscosity contrast, density contrast, and linear adsorption. In this setup, the fluid on top is heavier and more viscous than the fluid below. Under the effect of gravity, this system becomes unstable, and finger-like structures appear. The phenomenon is described mathematically by coupling Darcy's law with a convection-diffusion reaction equation. The nonlinearity in this model arises mainly from the concentration dependence of viscosity and the convective transport term. The existence of a unique pair of weak solutions is shown using the Galerkin approximation method and truncation technique. Moreover, an application of the maximum principle shows non-negativity of the concentration. Additionally, we analyze the long-time behavior of the solution and prove that the concentration converges exponentially to zero in the $L^p$-norm for all $1 \le p \le \infty$ as $t \to \infty.$ To complement the theoretical analysis, we perform numerical simulations based on a pressure formulation. By tracking total kinetic energy and mixing measures over time, we discuss the instability and the mixing efficiency, respectively. The present study reveals that although increasing the density contrast amplifies the total kinetic energy, the marginal impact diminishes with successive increments of density contrast. Similarly, while adsorption acts to suppress mixing, its efficiency in doing so tends to saturate with further increases. These behavior are consistent with the numerical simulations.

Submission history

From: Sahil Kundu [view email]
[v1] Sun, 25 Jan 2026 19:52:00 UTC (2,463 KB)
[v2] Wed, 17 Jun 2026 08:22:35 UTC (1,456 KB)

此内容由惯性聚合(RSS阅读器)自动聚合整理，仅供阅读参考。 原文来自 — 版权归原作者所有。