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

WordPress大学
WordPress大学
J
Java Code Geeks
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
腾讯CDC
IT之家
IT之家
罗磊的独立博客
酷 壳 – CoolShell
酷 壳 – CoolShell
U
Unit 42
爱范儿
爱范儿
博客园 - 聂微东
F
Fortinet All Blogs
V
Visual Studio Blog
Blog — PlanetScale
Blog — PlanetScale
G
Google Developers Blog
aimingoo的专栏
aimingoo的专栏
L
LangChain Blog
雷峰网
雷峰网
B
Blog RSS Feed
宝玉的分享
宝玉的分享
T
Tailwind CSS Blog
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
Engineering at Meta
Engineering at Meta
H
Hackread – Cybersecurity News, Data Breaches, AI and More

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 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 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 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 Group-Algebraic Tensors: Provably-optimal Equivariant Learning and Physical Symmetry Discovery 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
On triviality and scalar curvature estimation of gradient...
[Submitted on 21 May 2026] · 2026-06-26 · via math updates on arXiv.org

View PDF HTML (experimental)

Abstract:In this study we have explored gradient $h$-almost Yamabe solitons on both compact and complete non-compact Riemannian manifolds. We have established several sufficient conditions for the triviality of such solitons with respect to integral inequalities involving the scalar curvature and the soliton function. In this regard, we have acquired scalar curvature estimation under certain $L^2$-integrability conditions, and defined signal of the function $h$. Our results extend and refine former works on almost and $h$-almost Yamabe solitons, and characterize the geometric structures of generalized Yamabe solitons.

Submission history

From: Absos Ali Shaikh Absos [view email]
[v1] Thu, 21 May 2026 06:42:32 UTC (9 KB)