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

J
Java Code Geeks
G
Google Developers Blog
有赞技术团队
有赞技术团队
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
Blog — PlanetScale
Blog — PlanetScale
罗磊的独立博客
博客园 - 聂微东
V
Visual Studio Blog
博客园_首页
D
DataBreaches.Net
腾讯CDC
I
InfoQ
F
Fortinet All Blogs
量子位
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
酷 壳 – CoolShell
酷 壳 – CoolShell
博客园 - 【当耐特】
Google DeepMind News
Google DeepMind News
人人都是产品经理
人人都是产品经理
云风的 BLOG
云风的 BLOG
月光博客
月光博客
Recent Announcements
Recent Announcements
MongoDB | Blog
MongoDB | Blog
C
Check Point 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 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
Emergent Dark Matter and Dark Energy from a Lattice Model
[Submitted on 24 Dec 2019 (v1), last revised 20 Jul 2026 (this v · 2026-06-11 · via math updates on arXiv.org

View PDF HTML (experimental)

Abstract:We propose a quantum bosonic qubit model on a fcc lattice that realizes the canonical source structure of mimetic dark matter as a defect of a rank-two lattice Gauss law. The standard contribution from general relativity is implemented similarly to previous work in the literature, while the mimetic sector modifies the constraint equations through additional source terms. Different theories such as mimetic dark matter, vector mimetic dark matter, and tensor-vector-scalar models are implemented on the lattice. In all these cases, a generalized Gauss law incorporates an additional Gauss-law (topological) defect depending on the type of generalization, but always fitting into the structure of the defects from the general relativity contribution. We also derive the resulting charge-selection rules for the defect sectors and show, in a worked example, that a localized defect sources a long-range rank-two field whose trace-free representative is exactly the Bowen-York momentum solution of canonical gravity. The mimetic constraint is treated in its full ADM form, retaining the normal derivative of the scalar field, and the known ghost and gradient instabilities of the minimal continuum mimetic theory are summarized. The lattice construction is therefore presented as a formal realization of the canonical source structure rather than as a complete cosmological model.

Submission history

From: Luis Lozano [view email]
[v1] Tue, 24 Dec 2019 06:42:22 UTC (100 KB)
[v2] Tue, 31 Dec 2019 17:24:26 UTC (101 KB)
[v3] Wed, 10 Jun 2026 05:57:52 UTC (110 KB)
[v4] Mon, 20 Jul 2026 18:15:44 UTC (119 KB)