Tootfinder

Phase-field and lip-field approaches for fracture with extreme mesh deformation (X-Mesh): a one-dimensional study
Nicolas Mo\"es, Beno\^it L\'e, Nicolas Chevaugeon, Jean-Fran\c{c}ois Remacle
https://arxiv.org/abs/2509.04971

Phase-field and lip-field approaches for fracture with extreme mesh deformation (X-Mesh): a one-dimensional study
We consider a one-dimensional fracture problem modelled using either the phase-field or lip-field approach. In both cases, we optimise the incremental potential with respect to the displacement and damage fields and the nodal coordinates of the mesh. This is thus a variational mesh study. We observe that, as the damage reaches its maximum value, the optimisation drives the most damaged element to zero size as the damage reaches its maximum value. This peculiar element provides a precise displac…

Lagrange-Mesh Method in Momentum Space: an Alternative Formulation
Cyrille Chevalier, Joachim Viseur
https://arxiv.org/abs/2510.03015 https://arxiv.org/pdf…

Lagrange-Mesh Method in Momentum Space: an Alternative Formulation
This work presents a new methodology for computing potential matrix elements within the Lagrange-mesh method in momentum space. The proposed approach extends the range of treatable potentials to include previously inaccessible cases, such as Coulomb and linear interactions. The method is validated across a variety of systems. A particular attention is given to the representation of both momentum and position probability densities.

A Position- and Energy-Aware Routing Strategy for Subterranean LoRa Mesh Networks
Nalith Udugampola, Xiaoyu Ai, Binghao Li, Henry Gong, Aruna Seneviratne
https://arxiv.org/abs/2510.03714

A Position- and Energy-Aware Routing Strategy for Subterranean LoRa Mesh Networks
Although LoRa is predominantly employed with the single-hop LoRaWAN protocol, recent advancements have extended its application to multi-hop mesh topologies. Designing efficient routing for LoRa mesh networks remains challenging due to LoRa's low data rate and ALOHA-based MAC. Prior work often adapts conventional protocols for low-traffic, aboveground networks with strict duty cycle constraints or uses flooding-based methods in subterranean environments. However, these approaches inefficiently …

Task-Based Programming for Adaptive Mesh Refinement in Compressible Flow Simulations
Anjiang Wei, Hang Song, Mert Hidayetoglu, Elliott Slaughter, Sanjiva K. Lele, Alex Aiken
https://arxiv.org/abs/2508.05020

Task-Based Programming for Adaptive Mesh Refinement in Compressible Flow Simulations
High-order solvers for compressible flows are vital in scientific applications. Adaptive mesh refinement (AMR) is a key technique for reducing computational cost by concentrating resolution in regions of interest. In this work, we develop an AMR-based numerical solver using Regent, a high-level programming language for the Legion programming model. We address several challenges associated with implementing AMR in Regent. These include dynamic data structures for patch refinement/coarsening, mes…

Was able to get up close for a pic of this fine looking katydid.
#Insects

Integrable self-adaptive moving mesh schemes for multi-component short pulse type equations under general boundary conditions
Ayako Hori, Ken-ichi Maruno, Yasuhiro Ohta, Bao-Feng Feng
https://arxiv.org/abs/2507.03880

Integrable self-adaptive moving mesh schemes for multi-component short pulse type equations under general boundary conditions
In this paper, we construct integrable self-adaptive moving mesh schemes for multi-component modified short pulse and short pulse equations under general boundary conditions including periodic boundary conditions by using the consistency condition with the hodograph transformation. We also construct multi-soliton solutions expressed by Pfaffian for our self-adaptive moving mesh schemes. Using self-adaptive moving mesh schemes presented in this paper, we perform numerical experiments to evaluate…

The Nobel physics prize on quantum tunneling stuff is nice, but the images used are terrible! The Nobel prizes own diagrams are line drawn cartoonish things, The BBC have a very arty drawing of a glowing thing with a mesh and cage and...wtf knows what!

https://www.cnbc.com/2025/07/07/jack-dorsey-whatsapp-bluetooth.html
This is interesting, and I'm curious to see how he's going to fuck it up.

Jack Dorsey launches a WhatsApp messaging rival built on Bluetooth
Block CEO Jack Dorsey has launched Bitchat, a new peer-to-peer messaging app that works entirely over Bluetooth mesh networks.

An Improved Physically-Based Surface Triangulation Method
Lei Shangyu, Fan Wei, Ren Hui
https://arxiv.org/abs/2508.05099 https://arxiv.org/pdf/2508.05099…

An Improved Physically-Based Surface Triangulation Method
This paper proposes improvements to the physically-based surface triangulation method, bubble meshing. The method simulates physical bubbles to automatically generate mesh vertices, resulting in high-quality Delaunay triangles. Despite its flexibility in local mesh size control and the advantage of local re-meshing, bubble meshing is constrained by high computational costs and slow convergence on complex surfaces. The proposed approach employs conformal mapping to simplify surface bubble packin…

Nach Bugfix: Bitchat Mesh von Jack Dorsey nun im App Store
Bitchat Mesh, ein auf Bluetooth basierendes Kommunikationswerkzeug kann fürs iPhone geladen werden. Erst mit Update klappt die Verbindung zu Android.
http…

On Riedtmann's well-behaved functors and applications to composites of irreducible morphisms
Viktor Chust, Fl\'avio U. Coelho
https://arxiv.org/abs/2507.03121

On Riedtmann's well-behaved functors and applications to composites of irreducible morphisms
In this survey, we summarize some results in the literature involving the mesh category, which is a combinatorial representation of the category of modules over a finite-dimensional associative algebra. We discuss Riedtmann's well-behaved functors, which compare the mesh category with the module category, and discuss how the properties of these functors can be applied to study the problem of composing irreducible morphisms, which is the problem of deciding when the composition of n irreducible …

GaussianMorphing: Mesh-Guided 3D Gaussians for Semantic-Aware Object Morphing
Mengtian Li, Yunshu Bai, Yimin Chu, Yijun Shen, Zhongmei Li, Weifeng Ge, Zhifeng Xie, Chaofeng Chen
https://arxiv.org/abs/2510.02034

GaussianMorphing: Mesh-Guided 3D Gaussians for Semantic-Aware Object Morphing
We introduce GaussianMorphing, a novel framework for semantic-aware 3D shape and texture morphing from multi-view images. Previous approaches usually rely on point clouds or require pre-defined homeomorphic mappings for untextured data. Our method overcomes these limitations by leveraging mesh-guided 3D Gaussian Splatting (3DGS) for high-fidelity geometry and appearance modeling. The core of our framework is a unified deformation strategy that anchors 3DGaussians to reconstructed mesh patches, …

A mesh-free, derivative-free, matrix-free, and highly parallel localized stochastic method for high-dimensional semilinear parabolic PDEs
Shuixin Fang, Changtao Sheng, Bihao Su, Tao Zhou
https://arxiv.org/abs/2510.02635

A mesh-free, derivative-free, matrix-free, and highly parallel localized stochastic method for high-dimensional semilinear parabolic PDEs
We develop a mesh-free, derivative-free, matrix-free, and highly parallel localized stochastic method for high-dimensional semilinear parabolic PDEs. The efficiency of the proposed method is built upon four essential components: (i) a martingale formulation of the forward backward stochastic differential equation (FBSDE); (ii) a small scale stochastic particle method for local linear regression (LLR); (iii) a decoupling strategy with a matrix-free solver for the weighted least-squares system us…

Deep vs. Shallow: Benchmarking Physics-Informed Neural Architectures on the Biharmonic Equation
Akshay Govind Srinivasan, Vikas Dwivedi, Balaji Srinivasan
https://arxiv.org/abs/2510.04490

Deep vs. Shallow: Benchmarking Physics-Informed Neural Architectures on the Biharmonic Equation
Partial differential equation (PDE) solvers are fundamental to engineering simulation. Classical mesh-based approaches (finite difference/volume/element) are fast and accurate on high-quality meshes but struggle with higher-order operators and complex, hard-to-mesh geometries. Recently developed physics-informed neural networks (PINNs) and their variants are mesh-free and flexible, yet compute-intensive and often less accurate. This paper systematically benchmarks RBF-PIELM, a rapid PINN varian…

New Secret Knots. Basically about the Tech Sector.
Fantastic.
(Original title: The Mesh)
https://thesecretknots.com/comic/the-mesh/

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh
Shuangkang Fang, I-Chao Shen, Yufeng Wang, Yi-Hsuan Tsai, Yi Yang, Shuchang Zhou, Wenrui Ding, Takeo Igarashi, Ming-Hsuan Yang
https://arxiv.org/abs/2508.01242

MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Mesh
We present MeshLLM, a novel framework that leverages large language models (LLMs) to understand and generate text-serialized 3D meshes. Our approach addresses key limitations in existing methods, including the limited dataset scale when catering to LLMs' token length and the loss of 3D structural information during mesh serialization. We introduce a Primitive-Mesh decomposition strategy, which divides 3D meshes into structurally meaningful subunits. This enables the creation of a large-scale da…

Numerical Modeling of Prominences and Coronal Rain with the MPI-AMRVAC Code
Valeriia Liakh, Jack Jenkins
https://arxiv.org/abs/2510.04222 https://arxiv.org…

Numerical Modeling of Prominences and Coronal Rain with the MPI-AMRVAC Code
This review surveys recent advances in the numerical modeling of solar prominences and coronal rain achieved with the fully open-source adaptive-grid, parallelized Adaptive Mesh Refinement Versatile Advection Code (MPI-AMRVAC). We examine how these models have contributed to our understanding of the formation and evolution of cool plasma structures in the solar corona. We first discuss prominence models that focus on prominence formation and their dynamic behavior. We then turn to coronal rain,…

A Hybrid AI Methodology for Generating Ontologies of Research Topics from Scientific Paper Corpora
Alessia Pisu, Livio Pompianu, Francesco Osborne, Diego Reforgiato Recupero, Daniele Riboni, Angelo Salatino
https://arxiv.org/abs/2508.04213

A Hybrid AI Methodology for Generating Ontologies of Research Topics from Scientific Paper Corpora
Taxonomies and ontologies of research topics (e.g., MeSH, UMLS, CSO, NLM) play a central role in providing the primary framework through which intelligent systems can explore and interpret the literature. However, these resources have traditionally been manually curated, a process that is time-consuming, prone to obsolescence, and limited in granularity. This paper presents Sci-OG, a semi-auto\-mated methodology for generating research topic ontologies, employing a multi-step approach: 1) Topic…

Comprehensive Numerical Hydrodynamic Analysis of Submarine in a Straight Course Simulation Using Wall-Resolved RANS Models
Noh Zainal Abidin (GeM), Frederic Grondin (GeM), Pol Muller (Naval Expert), Jean-Fran\c{c}ois Sigrist (Naval Expert)
https://arxiv.org/abs/2510.04911

Comprehensive Numerical Hydrodynamic Analysis of Submarine in a Straight Course Simulation Using Wall-Resolved RANS Models
This research explores several critical factors affecting CFD-based prediction accuracy of submarine hydrodynamics and builds upon previous work on preliminary mesh and solver benchmarking. A scaled submarine model is analyzed numerically using the Reynolds-Averaged Navier-Stokes (RANS) turbulence model at a Reynold number (Re) of 3.6x106 with wall-resolved meshes targeting y+ <5. Based on prior work using a 13x106 cells mesh generated with SnappyHexMesh, a mesh convergence study was performed …

So gut ich die bisherigen Trikots fand, so wenig beeindruckt mich das #Wiesntrikot des #tsv1860
https://w…

Unser Wiesn-Trikot 2025: Tradition trifft Nachhaltigkeit.
Pünktlich zur Wiesn 2025 präsentieren wir gemeinsam mit unserem Ausrüster JOMA das neue Wiesn-Trikot – ein echtes limitiertes Highlight für Fans und Sammler. Das diesjährige Shirt besteht zu 100 % aus recyceltem Polyester und vereint modernes Design mit nachhaltigen Materialien wie atmungsaktivem Mesh und Rib-Gewebe.

Design and demonstration of a direct air capture system with moisture-driven CO2 delivery into aqueous medium
Justin Flory, Samantha Taylor, Shuqin Li, Sunil Tiwari, Garrett Cole, Amory Lowe, Lindsey Hamblin, Samuel Piorkowski, Matthew Ryan, Thiago Stangherlin Barbosa, Jason Kmon, Nick Lowery, Joel Eliston, Jason C. Quinn, John McGowen, Matthew D. Green, Klaus Lackner, Wim Vermaas

Design and demonstration of a direct air capture system with moisture-driven CO2 delivery into aqueous medium
A moisture-driven air capture (DAC) system was designed and demonstrated. A laboratory-scale system delivering ~1 g CO2 per day was demonstrated in a laminar flow hood and a small pilot-scale system that could deliver ~100 g CO2 daily was operated outdoors in a 4.2 m2 (areal surface area) raceway pond. Elongated mesh tube packets were designed to contain AER beads with high surface area for contacting the air and were found to reduce drying and CO2 loading time ~4-fold over larger mesh bags. Wh…

An Arbitrary-Order Moving-Mesh Finite Element Algorithm for One-Dimensional Implicit Moving Boundary Problems
Matthew E Hubbard, Thomas J Radley
https://arxiv.org/abs/2509.04409

An Arbitrary-Order Moving-Mesh Finite Element Algorithm for One-Dimensional Implicit Moving Boundary Problems
We present a one-dimensional high-order moving-mesh finite element method for moving boundary problems where the boundary velocity depends implicitly on the solution in the interior of the domain. The method employs a conservative arbitrary Lagrangian-Eulerian approach to predict the evolution of the approximate solution. It retains the order of accuracy of the underlying fixed-mesh method by (i) computing the boundary velocities using a high-order approximation to a distributed local conservat…

TeraNoC: A Multi-Channel 32-bit Fine-Grained, Hybrid Mesh-Crossbar NoC for Efficient Scale-up of 1000 Core Shared-L1-Memory Clusters
Yichao Zhang, Zexin Fu, Tim Fischer, Yinrong Li, Marco Bertuletti, Luca Benini
https://arxiv.org/abs/2508.02446

TeraNoC: A Multi-Channel 32-bit Fine-Grained, Hybrid Mesh-Crossbar NoC for Efficient Scale-up of 1000+ Core Shared-L1-Memory Clusters
A key challenge in on-chip interconnect design is to scale up bandwidth while maintaining low latency and high area efficiency. 2D-meshes scale with low wiring area and congestion overhead; however, their end-to-end latency increases with the number of hops, making them unsuitable for latency-sensitive core-to-L1-memory access. On the other hand, crossbars offer low latency, but their routing complexity grows quadratically with the number of I/Os, requiring large physical routing resources and …

The Las Vegas Raiders Are Dialed In https://www.si.com/nfl/raiders/las-vegas-chip-kelly-ashton-jeanty-training-camp-geno-smith-pete-carroll

A Survey of Medical Point Cloud Shape Learning: Registration, Reconstruction and Variation
Tongxu Zhang, Zhiming Liang, Bei Wang
https://arxiv.org/abs/2508.03057 https://…

A Survey of Medical Point Cloud Shape Learning: Registration, Reconstruction and Variation
Point clouds have become an increasingly important representation for 3D medical imaging, offering a compact, surface-preserving alternative to traditional voxel or mesh-based approaches. Recent advances in deep learning have enabled rapid progress in extracting, modeling, and analyzing anatomical shapes directly from point cloud data. This paper provides a comprehensive and systematic survey of learning-based shape analysis for medical point clouds, focusing on three fundamental tasks: registr…

New blog post
https://blog.ewonchang.com/2025/09/27/nebula-mesh-vpn-still-disappointing-after-4-years/

The Door to Policy Portability might be an IP Overlay
Behrooz Farkiani, Fan Liu, Patrick Crowley
https://arxiv.org/abs/2510.04052 https://arxiv.org/pdf/251…

The Door to Policy Portability might be an IP Overlay
Portable service mesh implementations enable layer 4 to layer 7 policy enforcement across diverse infrastructures, but they remain tied to infrastructure-specific layer 3 network policies. Network policies enable control over IP traffic flow regardless of whether traffic is authorized at the application level. However, not all infrastructure supports enforcing them, and achieving consistent enforcement across heterogeneous environments is challenging. For example, studies have shown that the ma…

Wer auf bonn.social nutzt denn #meshtastic, bzw. hat einen Node?
https://meshtastic.org/

Numerical investigation of engine position effects on contrail formation and evolution in the near-field of a realistic aircraft configuration
R\'emy Annunziata (ETS), Nicolas Bonne (ETS), Fran\c{c}ois Garnier (ETS)
https://arxiv.org/abs/2508.02706

Numerical investigation of engine position effects on contrail formation and evolution in the near-field of a realistic aircraft configuration
The present study investigates the impact of engine position on contrail formation and near-field evolution in a realistic three-dimensional aircraft configuration. Detailed numerical simulations are conducted using a Reynolds-Averaged Navier-Stokes (RANS) approach coupled with mesh adaptation techniques. A Eulerian microphysical model is used to characterize contrail ice crystal properties and their evolution under varying dilution conditions. The setup is based on a Boeing 777-like geometry, …

Real-Time Buoyancy Estimation for AUV Simulations Using Convex Hull-Based Submerged Volume Calculation
Ad-Deen Mahbub, Md Ragib Shaharear
https://arxiv.org/abs/2509.03804 https:…

Real-Time Buoyancy Estimation for AUV Simulations Using Convex Hull-Based Submerged Volume Calculation
Accurate real-time buoyancy modeling is essential for high-fidelity Autonomous Underwater Vehicle (AUV) simulations, yet NVIDIA Isaac Sim lacks a native buoyancy system, requiring external solutions for precise underwater physics. This paper presents a novel convex hull-based approach to dynamically compute the submerged volume of an AUV in real time. By extracting mesh geometry from the simulation environment and calculating the hull portion intersecting the water level along the z-axis, our m…

Physically Controllable Relighting of Photographs
Chris Careaga, Ya\u{g}{\i}z Aksoy
https://arxiv.org/abs/2508.05626 https://arxiv.org/pdf/2508.05626

Physically Controllable Relighting of Photographs
We present a self-supervised approach to in-the-wild image relighting that enables fully controllable, physically based illumination editing. We achieve this by combining the physical accuracy of traditional rendering with the photorealistic appearance made possible by neural rendering. Our pipeline works by inferring a colored mesh representation of a given scene using monocular estimates of geometry and intrinsic components. This representation allows users to define their desired illuminatio…

A posteriori error estimates and space-adaptive mesh refinements for time-dependent scattering problems
Th\'eophile Chaumont-Frelet, Heiko Gimperlein, Ignacio Labarca-Figueroa, J\"org Nick
https://arxiv.org/abs/2509.04217

A posteriori error estimates and space-adaptive mesh refinements for time-dependent scattering problems
This work studies a posteriori error estimates and their use for time-dependent acoustic scattering problems, formulated as a time-dependent boundary integral equation based on a single-layer ansatz. The integral equation is discretized by the convolution quadrature method in time and by boundary elements in space. We prove the reliability of an error estimator of residual type and study the resulting space-adaptive mesh refinements. Moreover, we present a simple modification of the convolution…

Adaptive direct search algorithms for constrained optimization
Charles Audet, Th\'eo Denorme, Youssef Diouane, S\'ebastien Le Digabel, Christophe Tribes
https://arxiv.org/abs/2507.23054

Adaptive direct search algorithms for constrained optimization
Two families of directional direct search methods have emerged in derivative-free and blackbox optimization (DFO and BBO), each based on distinct principles: Mesh Adaptive Direct Search (MADS) and Sufficient Decrease Direct Search (SDDS). MADS restricts trial points to a mesh and accepts any improvement, ensuring none are missed, but at the cost of restraining the placement of trial points. SDDS allows greater freedom by evaluating points anywhere in the space, but accepts only those yielding a…

Hierarchical Analysis and Control of Epidemic Spreading over Networks using Dissipativity and Mesh Stability
Shirantha Welikala, Hai Lin, Panos J. Antsaklis
https://arxiv.org/abs/2509.24665

Hierarchical Analysis and Control of Epidemic Spreading over Networks using Dissipativity and Mesh Stability
Analyzing and controlling spreading processes are challenging problems due to the involved non-linear node (subsystem) dynamics, unknown disturbances, complex interconnections, and the large-scale and multi-level nature of the problems. The dissipativity concept provides a practical framework for addressing such concerns, thanks to the energy-based representation it offers for subsystems and the compositional properties it provides for the analysis and control of interconnected (networked) syst…

Training Transformers for Mesh-Based Simulations
Paul Garnier, Vincent Lannelongue, Jonathan Viquerat, Elie Hachem
https://arxiv.org/abs/2508.18051 https://

Training Transformers for Mesh-Based Simulations
Simulating physics using Graph Neural Networks (GNNs) is predominantly driven by message-passing architectures, which face challenges in scaling and efficiency, particularly in handling large, complex meshes. These architectures have inspired numerous enhancements, including multigrid approaches and $K$-hop aggregation (using neighbours of distance $K$), yet they often introduce significant complexity and suffer from limited in-depth investigations. In response to these challenges, we propose a…

Replaced article(s) found for physics.bio-ph. https://arxiv.org/list/physics.bio-ph/new
[1/1]:
- Inverse 3D Microscopy Rendering for Cell Shape Inference with Active Mesh
Sacha Ichbiah, Anshuman Sinha, Fabrice Delbary, Herv\'e Turlier

Classification of twisted graded Calabi--Yau algebras on two-vertex quivers
Jason Gaddis, Daryl Zazycki
https://arxiv.org/abs/2508.01950 https://arxiv.org/…

Classification of twisted graded Calabi--Yau algebras on two-vertex quivers
We classify, up to isomorphism, twisted graded Calabi--Yau algebras of dimension two on two-vertex quivers. By work of Reyes and Rogalski, such algebras may be presented as quotients of translation quivers by mesh relations. We also consider the isomorphism problem for certain families of twisted graded Calabi--Yau algebras on larger quivers.

Started exploring Meshtastic recently (https://meshtastic.org/).
It's... surprisingly mature? I expected something much rougher, but it's basically a very functional text/gps-only whatsapp that just doesn't need an internet connection. Feels like magic.

Meshtastic
An open source, off-grid, decentralized, mesh network built to run on affordable, low-power devices

HART: Human Aligned Reconstruction Transformer
Xiyi Chen, Shaofei Wang, Marko Mihajlovic, Taewon Kang, Sergey Prokudin, Ming Lin
https://arxiv.org/abs/2509.26621 https://…

HART: Human Aligned Reconstruction Transformer
We introduce HART, a unified framework for sparse-view human reconstruction. Given a small set of uncalibrated RGB images of a person as input, it outputs a watertight clothed mesh, the aligned SMPL-X body mesh, and a Gaussian-splat representation for photorealistic novel-view rendering. Prior methods for clothed human reconstruction either optimize parametric templates, which overlook loose garments and human-object interactions, or train implicit functions under simplified camera assumptions,…

3D PixBrush: Image-Guided Local Texture Synthesis
Dale Decatur, Itai Lang, Kfir Aberman, Rana Hanocka
https://arxiv.org/abs/2507.03731 https://

3D PixBrush: Image-Guided Local Texture Synthesis
We present 3D PixBrush, a method for performing image-driven edits of local regions on 3D meshes. 3D PixBrush predicts a localization mask and a synthesized texture that faithfully portray the object in the reference image. Our predicted localizations are both globally coherent and locally precise. Globally - our method contextualizes the object in the reference image and automatically positions it onto the input mesh. Locally - our method produces masks that conform to the geometry of the refe…

Implementing Pseudofractal Designs in Graphene-Based Quantum Hall Arrays using Minkowski-Bouligand Algorithms
Dominick S. Scaletta, Ngoc Thanh Mai Tran, Marta Musso, Dean G. Jarrett, Heather M. Hill, Massimo Ortolano, David B. Newell, Albert F. Rigosi
https://arxiv.org/abs/2507.23625

Implementing Pseudofractal Designs in Graphene-Based Quantum Hall Arrays using Minkowski-Bouligand Algorithms
This work introduces a pseudofractal analysis for optimizing high-resistance graphene-based quantized Hall array resistance standards (QHARS). The development of resistance standard device designs through star-mesh transformations is detailed, aimed at minimizing element count. Building on a recent mathematical framework, the approach presented herein refines QHARS device concepts by considering designs incorporating pseudofractals (which may be expressed as star-mesh transformations). To under…

Invisible shoes. Wicked Witch socks.
#Adidas #shoes #socks

Adaptive Crouzeix-Raviart finite elements for the first eigenpair of $p$-Laplacian
Guanglian Li, Yueqi Wang, Yifeng Xu
https://arxiv.org/abs/2508.02077 https://

Adaptive Crouzeix-Raviart finite elements for the first eigenpair of $p$-Laplacian
In this paper, we propose and analyze an adaptive Crouzeix-Raviart finite element method for computing the first Dirichlet eigenpair of the $p$-Laplacian problem. We prove that the sequence of error estimators produced by the adaptive algorithm has a vanishing limit and that, starting from a fine initial mesh, the relevant sequence of approximate eigenvalues converges to the first eigenvalue and the distance in a mesh-dependent broken norm between discrete eigenfunctions and the set composed of…

Photographic Conviviality: A Synchronic and Symbiotic Photographic Experience through a Body Paint Workshop
Chinatsu Ozawa, Tatsuya Minagawa, Yoichi Ochiai
https://arxiv.org/abs/2509.25968

Photographic Conviviality: A Synchronic and Symbiotic Photographic Experience through a Body Paint Workshop
This study explores "Photo Tattooing," merging photography and body ornamentation, and introduces the concept of "Photographic Conviviality." Using our instant camera that prints images onto mesh screens for immediate body art, we examine how this integration affects personal expression and challenges traditional photography. Workshops revealed that this fusion redefines photography's role, fostering intimacy and shared experiences, and opens new avenues for self-expression by transforming stat…

Empart: Interactive Convex Decomposition for Converting Meshes to Parts
Brandon Vu, Shameek Ganguly, Pushkar Joshi
https://arxiv.org/abs/2509.22847 https://

Empart: Interactive Convex Decomposition for Converting Meshes to Parts
Simplifying complex 3D meshes is a crucial step in robotics applications to enable efficient motion planning and physics simulation. Common methods, such as approximate convex decomposition, represent a mesh as a collection of simple parts, which are computationally inexpensive to simulate. However, existing approaches apply a uniform error tolerance across the entire mesh, which can result in a sub-optimal trade-off between accuracy and performance. For instance, a robot grasping an object nee…

Relaxed Total Generalized Variation Regularized Piecewise Smooth Mumford-Shah Model for Triangulated Surface Segmentation
Huayan Zhang, Shanqiang Wang, Xiaochao Wang
https://arxiv.org/abs/2507.19284

Relaxed Total Generalized Variation Regularized Piecewise Smooth Mumford-Shah Model for Triangulated Surface Segmentation
The Mumford-Shah (MS) model is an important technique for mesh segmentation. Many existing researches focus on piecewise constant MS mesh segmentation model with total variation regularization, which pursue the shortest length of boundaries. Different from previous efforts, in this article, we propose a novel piecewise smooth MS mesh segmentation model by utilizing the relaxed total generalized variation regularization (rTGV). The new model assumes that the feature function of a mesh can be app…

exaPD: A highly parallelizable workflow for multi-element phase diagram (PD) construction
Feng Zhang, Zhuo Ye, Maxim Moraru, Ying Wai Li, Weiyi Xia, Yongxin Yao, Ryan Richard, Cai-Zhuang Wang
https://arxiv.org/abs/2510.01400

exaPD: A highly parallelizable workflow for multi-element phase diagram (PD) construction
Phase diagrams (PDs) illustrate the relative stability of competing phases under varying conditions, serving as critical tools for synthesizing complex materials. Reliable phase diagrams rely on precise free energy calculations, which are computationally intensive. We introduce exaPD, a user-friendly workflow that enables simultaneous sampling of multiple phases across a fine mesh of temperature and composition for free energy calculations. The package employs standard molecular dynamics (MD) a…

Image-Guided Shape-from-Template Using Mesh Inextensibility Constraints
Thuy Tran, Ruochen Chen, Shaifali Parashar
https://arxiv.org/abs/2507.22699 https://

Image-Guided Shape-from-Template Using Mesh Inextensibility Constraints
Shape-from-Template (SfT) refers to the class of methods that reconstruct the 3D shape of a deforming object from images/videos using a 3D template. Traditional SfT methods require point correspondences between images and the texture of the 3D template in order to reconstruct 3D shapes from images/videos in real time. Their performance severely degrades when encountered with severe occlusions in the images because of the unavailability of correspondences. In contrast, modern SfT methods use a c…

On fourteen equidistribution conjectures of Lv and Zhang and monotone mesh patterns with corner shadings
Qi Fang, Shishuo Fu, Sergey Kitaev, Haijun Li
https://arxiv.org/abs/2507.04698

On fourteen equidistribution conjectures of Lv and Zhang and monotone mesh patterns with corner shadings
Three complementation-like involutions are constructed on permutations to prove, and in some cases generalize, all remaining fourteen joint symmetric equidistribution conjectures of Lv and Zhang. Further enumerative results are obtained for several classes of (mesh) pattern-avoiding permutations, where the shadings of all involved mesh patterns are restricted to an opposing pair of corners.

Modeling Multiphase Galactic Outflows: A Multifluid Moving Mesh Approach
Francesco Bollati, Rainer Weinberger
https://arxiv.org/abs/2508.16971 https://arxi…

Modeling Multiphase Galactic Outflows: A Multifluid Moving Mesh Approach
Outflows are a key part of the galactic gas cycle and crucial in shaping the star formation activity in their host galaxy. Yet, in simulations of galaxy evolution, modeling these outflows in their multi-phase nature and over the relevant timescales is an unsolved problem. We present a subgrid model for simulating multiphase galactic outflows in efficient, comparatively low-resolution simulations, designed for application in future cosmological simulations. The cold phase (T = 10000 K) is treate…

If you don't already own a non-Internet-based mesh communications node, get out your least-favourite €15 and buy one now, because they're currently speedrunning building the ultimate panopticon and destroying the Internet as we know it

On discrete Sobolev inequalities for nonconforming finite elements under a semi-regular mesh condition
Hiroki Ishizaka
https://arxiv.org/abs/2509.00505 https://

On discrete Sobolev inequalities for nonconforming finite elements under a semi-regular mesh condition
We derive a discrete $ L^q-L^p$ Sobolev inequality tailored for the Crouzeix--Raviart and discontinuous Crouzeix--Raviart finite element spaces on anisotropic meshes in both two and three dimensions. Subject to a semi-regular mesh condition, this discrete Sobolev inequality is applicable to all pairs $(q,p)$ that align with the local Sobolev embedding, including scenarios where $q \leq p$. Importantly, the constant is influenced solely by the domain and the semi-regular parameter, ensuring robu…

GATMesh: Clock Mesh Timing Analysis using Graph Neural Networks
Muhammad Hadir Khan, Matthew Guthaus
https://arxiv.org/abs/2507.05681 https://

GATMesh: Clock Mesh Timing Analysis using Graph Neural Networks
Clock meshes are essential in high-performance VLSI systems for minimizing skew and handling PVT variations, but analyzing them is difficult due to reconvergent paths, multi-source driving, and input mesh buffer skew. SPICE simulations are accurate but slow; yet simplified models miss key effects like slew and input skew. We propose GATMesh, a Graph Neural Network (GNN)-based framework that models the clock mesh as a graph with augmented structural and physical features. Trained on SPICE data, …

Locality-Aware Automatic Differentiation on the GPU for Mesh-Based Computations
Ahmed H. Mahmoud, Jonathan Ragan-Kelley, Justin Solomon
https://arxiv.org/abs/2509.00406 https://…

Locality-Aware Automatic Differentiation on the GPU for Mesh-Based Computations
We present a high-performance system for automatic differentiation (AD) of functions defined on triangle meshes that exploits the inherent sparsity and locality of mesh-based energy functions to achieve fast gradient and Hessian computation on the GPU. Our system is designed around per-element forward-mode differentiation, enabling all local computations to remain in GPU registers or shared memory. Unlike reverse-mode approaches that construct and traverse global computation graphs, our method …

Characterizing Adaptive Mesh Refinement on Heterogeneous Platforms with Parthenon-VIBE
Akash Poptani, Alireza Khadem, Scott Mahlke, Jonah Miller, Joshua Dolence, Reetuparna Das
https://arxiv.org/abs/2509.19701

Characterizing Adaptive Mesh Refinement on Heterogeneous Platforms with Parthenon-VIBE
Hero-class HPC simulations rely on Adaptive Mesh Refinement (AMR) to reduce compute and memory demands while maintaining accuracy. This work analyzes the performance of Parthenon, a block-structured AMR benchmark, on CPU-GPU systems. We show that smaller mesh blocks and deeper AMR levels degrade GPU performance due to increased communication, serial overheads, and inefficient GPU utilization. Through detailed profiling, we identify inefficiencies, low occupancy, and memory access bottlenecks. W…

FastMesh:Efficient Artistic Mesh Generation via Component Decoupling
Jeonghwan Kim, Yushi Lan, Armando Fortes, Yongwei Chen, Xingang Pan
https://arxiv.org/abs/2508.19188 https:/…

FastMesh:Efficient Artistic Mesh Generation via Component Decoupling
Recent mesh generation approaches typically tokenize triangle meshes into sequences of tokens and train autoregressive models to generate these tokens sequentially. Despite substantial progress, such token sequences inevitably reuse vertices multiple times to fully represent manifold meshes, as each vertex is shared by multiple faces. This redundancy leads to excessively long token sequences and inefficient generation processes. In this paper, we propose an efficient framework that generates ar…

Context-Aware Hybrid Routing in Bluetooth Mesh Networks Using Multi-Model Machine Learning and AODV Fallback
Md Sajid Islam, Tanvir Hasan
https://arxiv.org/abs/2509.21490 https:…

Context-Aware Hybrid Routing in Bluetooth Mesh Networks Using Multi-Model Machine Learning and AODV Fallback
Bluetooth-based mesh networks offer a promising infrastructure for offline communication in emergency and resource constrained scenarios. However, traditional routing strategies such as Ad hoc On-Demand Distance Vector (AODV) often degrade under congestion and dynamic topological changes. This study proposes a hybrid intelligent routing framework that augments AODV with supervised machine learning to improve next-hop selection under varied network constraints. The framework integrates four pred…

Interpolation-supplemented lattice Boltzmann simulation of thermal convection on non-uniform meshes
Ao Xu, Zheng Zhao, Ben-Rui Xu, Li-Sheng Jiang
https://arxiv.org/abs/2509.01099

Interpolation-supplemented lattice Boltzmann simulation of thermal convection on non-uniform meshes
We present a systematic evaluation of an interpolation-supplemented lattice Boltzmann method (ISLBM) for simulating buoyancy-driven thermal convection on non-uniform meshes. The ISLBM extends the standard lattice Boltzmann framework by incorporating quadratic interpolation during the streaming step, enabling flexible mesh refinement near solid boundaries while maintaining algorithmic simplicity and parallel scalability. The method is implemented for a two-dimensional side-heated cavity at high …

Mesh based segmentation for automated margin line generation on incisors receiving crown treatment
Ammar Alsheghri, Ying Zhang, Farnoosh Ghadiri, Julia Keren, Farida Cheriet, Francois Guibault
https://arxiv.org/abs/2507.22859

Mesh based segmentation for automated margin line generation on incisors receiving crown treatment
Dental crowns are essential dental treatments for restoring damaged or missing teeth of patients. Recent design approaches of dental crowns are carried out using commercial dental design software. Once a scan of a preparation is uploaded to the software, a dental technician needs to manually define a precise margin line on the preparation surface, which constitutes a non-repeatable and inconsistent procedure. This work proposes a new framework to determine margin lines automatically and accurat…

Fast Feeder Reconfiguration via Mesh Adaptive Direct Search in Black-Box Distribution System Environments
Junyuan Zheng, Wenlong Shi, Zhaoyu Wang
https://arxiv.org/abs/2507.16027 …

Fast Feeder Reconfiguration via Mesh Adaptive Direct Search in Black-Box Distribution System Environments
Feeder reconfiguration is a critical operational strategy in power distribution systems. However, existing optimization approaches typically rely on explicit mathematical formulations and analytical models, which are often infeasible in practical utility environments characterized by heterogeneous, proprietary, and black-box simulation modules. To address this challenge, this paper proposes a fast feeder reconfiguration framework based on Mesh Adaptive Direct Search (MADS). The proposed approac…

Unsupervised Representation Learning for 3D Mesh Parameterization with Semantic and Visibility Objectives
AmirHossein Zamani, Bruno Roy, Arianna Rampini
https://arxiv.org/abs/2509.25094

Unsupervised Representation Learning for 3D Mesh Parameterization with Semantic and Visibility Objectives
Recent 3D generative models produce high-quality textures for 3D mesh objects. However, they commonly rely on the heavy assumption that input 3D meshes are accompanied by manual mesh parameterization (UV mapping), a manual task that requires both technical precision and artistic judgment. Industry surveys show that this process often accounts for a significant share of asset creation, creating a major bottleneck for 3D content creators. Moreover, existing automatic methods often ignore two perc…

Multi-fidelity Bayesian Data-Driven Design of Energy Absorbing Spinodoid Cellular Structures
Leo Guo, Hirak Kansara, Siamak F. Khosroshahi, GuoQi Zhang, Wei Tan
https://arxiv.org/abs/2507.22079

Multi-fidelity Bayesian Data-Driven Design of Energy Absorbing Spinodoid Cellular Structures
Finite element (FE) simulations of structures and materials are getting increasingly more accurate, but also more computationally expensive as a collateral result. This development happens in parallel with a growing demand of data-driven design. To reconcile the two, a robust and data-efficient optimization method called Bayesian optimization (BO) has been previously established as a technique to optimize expensive objective functions. In parallel, the mesh width of an FE model can be exploited…

Poroelasticity of bottlebrush and linear polymer networks
Nolan A. Miller, Alfred J. Crosby
https://arxiv.org/abs/2509.00022 https://arxiv.org/pdf/2509.000…

Poroelasticity of bottlebrush and linear polymer networks
The transport of solvent molecules through soft, swollen networks is critical in both natural and engineered systems. While this poroelastic flow has traditionally been explored in networks where the mesh size is comparable to the solvent molecule size, the effect of network architecture on permeability remains underexplored. Here we investigate solvent transport in linear polymer networks (LPN) and highly elastic bottlebrush elastomer networks (BBN), where the presence of densely grafted sidec…

Physics-informed approach for exploratory Hamilton--Jacobi--Bellman equations via policy iterations
Yeongjong Kim, Namkyeong Cho, Minseok Kim, Yeoneung Kim
https://arxiv.org/abs/2508.01720

Physics-informed approach for exploratory Hamilton--Jacobi--Bellman equations via policy iterations
We propose a mesh-free policy iteration framework based on physics-informed neural networks (PINNs) for solving entropy-regularized stochastic control problems. The method iteratively alternates between soft policy evaluation and improvement using automatic differentiation and neural approximation, without relying on spatial discretization. We present a detailed $L^2$ error analysis that decomposes the total approximation error into three sources: iteration error, policy network error, and PDE …

Replaced article(s) found for cs.CV. https://arxiv.org/list/cs.CV/new
[1/5]:
- LiDAR-HMR: 3D Human Mesh Recovery from LiDAR
Bohao Fan, Wenzhao Zheng, Jianjiang Feng, Jie Zhou

Replaced article(s) found for cs.RO. https://arxiv.org/list/cs.RO/new
[2/2]:
- Mesh-Learner: Texturing Mesh with Spherical Harmonics
Yunfei Wan, Jianheng Liu, Chunran Zheng, Jiarong Lin, Fu Zhang

3D Cardiac Anatomy Generation Using Mesh Latent Diffusion Models
Jolanta Mozyrska, Marcel Beetz, Luke Melas-Kyriazi, Vicente Grau, Abhirup Banerjee, Alfonso Bueno-Orovio
https://arxiv.org/abs/2508.14122

3D Cardiac Anatomy Generation Using Mesh Latent Diffusion Models
Diffusion models have recently gained immense interest for their generative capabilities, specifically the high quality and diversity of the synthesized data. However, examples of their applications in 3D medical imaging are still scarce, especially in cardiology. Generating diverse realistic cardiac anatomies is crucial for applications such as in silico trials, electromechanical computer simulations, or data augmentations for machine learning models. In this work, we investigate the applicati…

Design, Simulation, and Fabrication of a Hexagonal Microfluidic Platform for Culturing Neurons
Maxx Yung
https://arxiv.org/abs/2508.00425 https://arxiv.org…

Design, Simulation, and Fabrication of a Hexagonal Microfluidic Platform for Culturing Neurons
Developing an organoid computing platform from neurons in vitro demands stable, precisely controlled microenvironments. To address this requirement, we designed, simulated, and fabricated a microfluidic device featuring hexagonal wells ($34.64\,\mathrm{μm}$ side length) in a honeycomb array connected by $20\,\mathrm{μm}$ channels. Computational fluid dynamics (CFD) modeling, validated by high mesh quality ($0.934$ orthogonal quality) and robust convergence, confirmed the architecture supports…

On Quad Mesh Extraction From Messy Grid Preserving Maps
Nicolas Ray (PIXEL)
https://arxiv.org/abs/2507.15404 https://arxiv.org/pdf/25…

On Quad Mesh Extraction From Messy Grid Preserving Maps
Extracting a quad mesh from a grid preserving map is straightforward in theory, but typical inputs are not exactly grid preserving maps. Previous works can manage minor deviations from grid preserving maps, but without a clear specification of what is acceptable. This work clarifies how typical inputs differ from a grid preserving map, and shows how the differences with a grid preserving map can be reflected by a sequence of operations acting on a discrete structure. It opens research opportuni…

Automated $h$-adaptivity for finite element approximations of the Falkner-Skan equation
B. Veena S. N. Rao
https://arxiv.org/abs/2508.02677 https://arxiv.o…

Automated $h$-adaptivity for finite element approximations of the Falkner-Skan equation
This paper details the development and application of an $h$-adaptive finite element method for the numerical solution of the \textit{Falkner-Skan equation}. A posteriori error estimation governs the adaptivity of the mesh, specifically the well-established \textit{Kelly error estimator}, which utilizes the jump in the gradient across elements. The implementation of this method allowed for accurate and efficient resolution of the boundary layer behavior characteristic of Falkner-Skan flows. Num…

GRMM: Real-Time High-Fidelity Gaussian Morphable Head Model with Learned Residuals
Mohit Mendiratta, Mayur Deshmukh, Kartik Teotia, Vladislav Golyanik, Adam Kortylewski, Christian Theobalt
https://arxiv.org/abs/2509.02141

GRMM: Real-Time High-Fidelity Gaussian Morphable Head Model with Learned Residuals
3D Morphable Models (3DMMs) enable controllable facial geometry and expression editing for reconstruction, animation, and AR/VR, but traditional PCA-based mesh models are limited in resolution, detail, and photorealism. Neural volumetric methods improve realism but remain too slow for interactive use. Recent Gaussian Splatting (3DGS) based facial models achieve fast, high-quality rendering but still depend solely on a mesh-based 3DMM prior for expression control, limiting their ability to captu…

Discrete Facial Encoding: : A Framework for Data-driven Facial Display Discovery
Minh Tran, Maksim Siniukov, Zhangyu Jin, Mohammad Soleymani
https://arxiv.org/abs/2510.01662 htt…

Discrete Facial Encoding: : A Framework for Data-driven Facial Display Discovery
Facial expression analysis is central to understanding human behavior, yet existing coding systems such as the Facial Action Coding System (FACS) are constrained by limited coverage and costly manual annotation. In this work, we introduce Discrete Facial Encoding (DFE), an unsupervised, data-driven alternative of compact and interpretable dictionary of facial expressions from 3D mesh sequences learned through a Residual Vector Quantized Variational Autoencoder (RVQ-VAE). Our approach first extr…

An efficient spline-based scheme on Shishkin-type meshes for solving singularly perturbed coupled systems with Robin boundary conditions
Kousalya Ramanujam, Vembu Shanthi
https://arxiv.org/abs/2509.01575

An efficient spline-based scheme on Shishkin-type meshes for solving singularly perturbed coupled systems with Robin boundary conditions
In this paper, we investigate a weakly coupled system of singularly perturbed linear reaction-diffusion equations with Robin boundary conditions, where the leading terms are multiplied by small positive parameters that may differ in magnitude. The solution to this system exhibits overlapping and interacting boundary layers. To appropriately resolve these layers, we employ a standard Shishkin mesh and propose a novel modification of Bakhvalov-Shishkin mesh. A cubic spline approximation is applie…

XSpecMesh: Quality-Preserving Auto-Regressive Mesh Generation Acceleration via Multi-Head Speculative Decoding
Dian Chen, Yansong Qu, Xinyang Li, Ming Li, Shengchuan Zhang
https://arxiv.org/abs/2507.23777

XSpecMesh: Quality-Preserving Auto-Regressive Mesh Generation Acceleration via Multi-Head Speculative Decoding
Current auto-regressive models can generate high-quality, topologically precise meshes; however, they necessitate thousands-or even tens of thousands-of next-token predictions during inference, resulting in substantial latency. We introduce XSpecMesh, a quality-preserving acceleration method for auto-regressive mesh generation models. XSpecMesh employs a lightweight, multi-head speculative decoding scheme to predict multiple tokens in parallel within a single forward pass, thereby accelerating …

Mesh Interpolation Graph Network for Dynamic and Spatially Irregular Global Weather Forecasting
Zinan Zheng, Yang Liu, Jia Li
https://arxiv.org/abs/2509.20911 https://

Mesh Interpolation Graph Network for Dynamic and Spatially Irregular Global Weather Forecasting
Graph neural networks have shown promising results in weather forecasting, which is critical for human activity such as agriculture planning and extreme weather preparation. However, most studies focus on finite and local areas for training, overlooking the influence of broader areas and limiting their ability to generalize effectively. Thus, in this work, we study global weather forecasting that is irregularly distributed and dynamically varying in practice, requiring the model to generalize t…

3D Human Mesh Estimation from Single View RGBD
Ozhan Suat, Bedirhan Uguz, Batuhan Karagoz, Muhammed Can Keles, Emre Akbas
https://arxiv.org/abs/2508.08178 https://

3D Human Mesh Estimation from Single View RGBD
Despite significant progress in 3D human mesh estimation from RGB images; RGBD cameras, offering additional depth data, remain underutilized. In this paper, we present a method for accurate 3D human mesh estimation from a single RGBD view, leveraging the affordability and widespread adoption of RGBD cameras for real-world applications. A fully supervised approach for this problem, requires a dataset with RGBD image and 3D mesh label pairs. However, collecting such a dataset is costly and challe…

AJAHR: Amputated Joint Aware 3D Human Mesh Recovery
Hyunjin Cho, Giyun Choi, Jongwon Choi
https://arxiv.org/abs/2509.19939 https://arxiv.org/pdf/2509.19939…

AJAHR: Amputated Joint Aware 3D Human Mesh Recovery
Existing human mesh recovery methods assume a standard human body structure, overlooking diverse anatomical conditions such as limb loss. This assumption introduces bias when applied to individuals with amputations - a limitation further exacerbated by the scarcity of suitable datasets. To address this gap, we propose Amputated Joint Aware 3D Human Mesh Recovery (AJAHR), which is an adaptive pose estimation framework that improves mesh reconstruction for individuals with limb loss. Our model in…

GALE: Leveraging Heterogeneous Systems for Efficient Unstructured Mesh Data Analysis
Guoxi Liu, Thomas Randall, Rong Ge, Federico Iuricich
https://arxiv.org/abs/2507.15230

GALE: Leveraging Heterogeneous Systems for Efficient Unstructured Mesh Data Analysis
Unstructured meshes present challenges in scientific data analysis due to irregular distribution and complex connectivity. Computing and storing connectivity information is a major bottleneck for visualization algorithms, affecting both time and memory performance. Recent task-parallel data structures address this by precomputing connectivity information at runtime while the analysis algorithm executes, effectively hiding computation costs and improving performance. However, existing approaches…

Uniform error analysis of a rectangular Morley finite element method on a Shishkin mesh for a 4th-order singularly perturbed boundary value problem
Xiangyun Meng, Martin Stynes
https://arxiv.org/abs/2508.20857

Uniform error analysis of a rectangular Morley finite element method on a Shishkin mesh for a 4th-order singularly perturbed boundary value problem
The singularly perturbed reaction-diffusion problem $\varepsilon^2Δ^2 u - \mathrm{div}\left(c\nabla u\right) = f$ is considered on the unit square $Ω$ in $\mathbb{R}^2$ with homogenous Dirichlet boundary conditions. Its solution typically contains boundary layers on all sides of~$Ω$. It is discretised by a finite element method that uses rectangular Morley elements on a Shishkin mesh. In an associated energy-type norm that is natural for this problem, we prove an $O(\varepsilon^{1/2}N^{-1}+\…

Extended Interface Physics-Informed Neural Networks Method for Moving Interface Problems
Ran Bi, Weibing Deng, Yameng Zhu
https://arxiv.org/abs/2508.01463 https://

Extended Interface Physics-Informed Neural Networks Method for Moving Interface Problems
Physics-Informed Neural Networks (PINNs) have emerged as a powerful class of mesh-free numerical methods for solving partial differential equations (PDEs), particularly those involving complex geometries. In this work, we present an innovative Extended Interface Physics-Informed Neural Network (XI-PINN) framework specifically designed to solve parabolic moving interface problems. The proposed approach incorporates a level set function to characterize the interface, which can be obtained either …

End-to-End 4D Heart Mesh Recovery Across Full-Stack and Sparse Cardiac MRI
Yihong Chen, Jiancheng Yang, Deniz Sayin Mercadier, Hieu Le, Juerg Schwitter, Pascal Fua
https://arxiv.org/abs/2509.12090

End-to-End 4D Heart Mesh Recovery Across Full-Stack and Sparse Cardiac MRI
Reconstructing cardiac motion from cine CMR sequences is critical for diagnosis, prediction, and intervention. Existing methods rely on complete CMR stacks to infer full heart motion, limiting their utility in intra-procedural scenarios where only sparse observations are available. We present TetHeart, the first end-to-end framework that unifies full 4D multi-structure heart mesh recovery from both offline full-stack acquisitions and intra-procedural sparse-slice observations. Our method levera…

A new Dune grid for scalable dynamic adaptivity based on the p4est software library
Carsten Burstedde, Mikhail Kirilin, Robert Kl\"ofkorn
https://arxiv.org/abs/2507.11386

A new Dune grid for scalable dynamic adaptivity based on the p4est software library
In this work we extend the Dune solver library with another grid interface to the open-source p4est software. While Dune already supports about a dozen different mesh implementations through its mesh interface Dune-Grid, we undertake this new coupling effort in order to inherit p4est's practically unlimited MPI scalability as well as its relatively thin data structures, and its native support for multi-block (forest) mesh topologies in both 2D and 3D. The presented implementation is compared …

SeamCrafte: Enhancing Mesh Seam Generation for Artist UV Unwrapping via Reinforcement Learning
Duoteng Xu, Yuguang Chen, Jing Li, Xinhai Liu, Xueqi Ma, Zhuo Chen, Dongyu Zhang, Chunchao Guo
https://arxiv.org/abs/2509.20725

SeamCrafte: Enhancing Mesh Seam Generation for Artist UV Unwrapping via Reinforcement Learning
Mesh seams play a pivotal role in partitioning 3D surfaces for UV parametrization and texture mapping. Poorly placed seams often result in severe UV distortion or excessive fragmentation, thereby hindering texture synthesis and disrupting artist workflows. Existing methods frequently trade one failure mode for another-producing either high distortion or many scattered islands. To address this, we introduce SeamCrafter, an autoregressive GPT-style seam generator conditioned on point cloud inputs…

Mesh Processing Non-Meshes via Neural Displacement Fields
Yuta Noma, Zhecheng Wang, Chenxi Liu, Karan Singh, Alec Jacobson
https://arxiv.org/abs/2508.12179 https://

Mesh Processing Non-Meshes via Neural Displacement Fields
Mesh processing pipelines are mature, but adapting them to newer non-mesh surface representations -- which enable fast rendering with compact file size -- requires costly meshing or transmitting bulky meshes, negating their core benefits for streaming applications. We present a compact neural field that enables common geometry processing tasks across diverse surface representations. Given an input surface, our method learns a neural map from its coarse mesh approximation to the surface. The f…

An unfitted HDG discretization for a model problem in shape optimization
Esteban Henr\'iquez, Tonatiuh S\'anchez-Vizuet, Manuel Solano
https://arxiv.org/abs/2509.22724 h…

An unfitted HDG discretization for a model problem in shape optimization
We apply an unfitted HDG discretization to a model problem in shape optimization. The method proposed uses a fixed, shape regular, non-geometry conforming mesh and a high order transfer technique to deal with the curved boundaries arising in the optimization process. The use of this strategy avoids the need for constant remeshing and enables a highly accurate description of the domain using a coarse computational mesh. We develop a rigorous analysis of the well-posedness of the problems that ar…

ARMesh: Autoregressive Mesh Generation via Next-Level-of-Detail Prediction
Jiabao Lei, Kewei Shi, Zhihao Liang, Kui Jia
https://arxiv.org/abs/2509.20824 https://

ARMesh: Autoregressive Mesh Generation via Next-Level-of-Detail Prediction
Directly generating 3D meshes, the default representation for 3D shapes in the graphics industry, using auto-regressive (AR) models has become popular these days, thanks to their sharpness, compactness in the generated results, and ability to represent various types of surfaces. However, AR mesh generative models typically construct meshes face by face in lexicographic order, which does not effectively capture the underlying geometry in a manner consistent with human perception. Inspired by 2D …

Numerical solution of 2D boundary value problems on merged Voronoi-Delaunay meshes
M. M. Chernyshov, P. N. Vabishchevich
https://arxiv.org/abs/2509.00557 https://

Numerical solution of 2D boundary value problems on merged Voronoi-Delaunay meshes
Computational technologies for the approximate solution of multidimensional boundary value problems often rely on irregular computational meshes and finite-volume approximations. In this framework, the discrete problem represents the corresponding conservation law for control volumes associated with the nodes of the mesh. This approach is most naturally and consistently implemented using Delaunay triangulations together with Voronoi diagrams as control volumes. In this paper, we employ meshes w…

Higher Order Unfitted Space-Time Methods for Transport Problems
Erik Burman, Fabian Heimann
https://arxiv.org/abs/2509.02253 https://arxiv.org/pdf/2509.022…

Higher Order Unfitted Space-Time Methods for Transport Problems
In this article, we present an Unfitted Space-Time Finite Element method for the scalar transport equation posed on moving domains. We consider the case of the domain boundary being transported by the same velocity field as the scalar concentration inside the physical domain. A standard continuous Galerkin Finite element space is considered on a fixed background mesh, as well as tensor product Space-Time elements, which can be discontinuous along time slice boundaries. For the computational geo…

CraftMesh: High-Fidelity Generative Mesh Manipulation via Poisson Seamless Fusion
James Jincheng, Youcheng Cai, Ligang Liu
https://arxiv.org/abs/2509.13688 https://

CraftMesh: High-Fidelity Generative Mesh Manipulation via Poisson Seamless Fusion
Controllable, high-fidelity mesh editing remains a significant challenge in 3D content creation. Existing generative methods often struggle with complex geometries and fail to produce detailed results. We propose CraftMesh, a novel framework for high-fidelity generative mesh manipulation via Poisson Seamless Fusion. Our key insight is to decompose mesh editing into a pipeline that leverages the strengths of 2D and 3D generative models: we edit a 2D reference image, then generate a region-specif…

HodgeFormer: Transformers for Learnable Operators on Triangular Meshes through Data-Driven Hodge Matrices
Akis Nousias, Stavros Nousias
https://arxiv.org/abs/2509.01839 https://…

HodgeFormer: Transformers for Learnable Operators on Triangular Meshes through Data-Driven Hodge Matrices
Currently, prominent Transformer architectures applied on graphs and meshes for shape analysis tasks employ traditional attention layers that heavily utilize spectral features requiring costly eigenvalue decomposition-based methods. To encode the mesh structure, these methods derive positional embeddings, that heavily rely on eigenvalue decomposition based operations, e.g. on the Laplacian matrix, or on heat-kernel signatures, which are then concatenated to the input features. This paper propos…

MeshMosaic: Scaling Artist Mesh Generation via Local-to-Global Assembly
Rui Xu, Tianyang Xue, Qiujie Dong, Le Wan, Zhe Zhu, Peng Li, Zhiyang Dou, Cheng Lin, Shiqing Xin, Yuan Liu, Wenping Wang, Taku Komura
https://arxiv.org/abs/2509.19995

MeshMosaic: Scaling Artist Mesh Generation via Local-to-Global Assembly
Scaling artist-designed meshes to high triangle numbers remains challenging for autoregressive generative models. Existing transformer-based methods suffer from long-sequence bottlenecks and limited quantization resolution, primarily due to the large number of tokens required and constrained quantization granularity. These issues prevent faithful reproduction of fine geometric details and structured density patterns. We introduce MeshMosaic, a novel local-to-global framework for artist mesh gen…

A conservative invariant-domain preserving projection technique for hyperbolic systems under adaptive mesh refinement
Jake Harmon, Martin Kronbichler, Matthias Maier, Eric Tovar
https://arxiv.org/abs/2507.18717

A conservative invariant-domain preserving projection technique for hyperbolic systems under adaptive mesh refinement
We propose a rigorous, conservative invariant-domain preserving (IDP) projection technique for hierarchical discretizations that enforces membership in physics-implied convex sets when mapping between solution spaces. When coupled with suitable refinement indicators, the proposed scheme enables a provably IDP adaptive numerical method for hyperbolic systems where preservation of physical properties is essential. In addition to proofs of these characteristics, we supply a detailed construction o…

A nodally bound-preserving composite discontinuous Galerkin method on polytopic meshes
Abdolreza Amiri, Gabriel R. Barrenechea, Emmanuil H. Georgoulis, Tristan Pryer
https://arxiv.org/abs/2510.02094

A nodally bound-preserving composite discontinuous Galerkin method on polytopic meshes
We introduce a nodally bound-preserving Galerkin method for second-order elliptic problems on general polygonal/polyhedral, henceforth collectively termed as \emph{polytopic}, meshes. Starting from an interior penalty discontinuous Galerkin (DG) formulation posed on a polytopic mesh, the method enforces preservation of \emph{a priori} prescribed upper and lower bounds for the numerical solution at an arbitrary number of user-defined points \emph{within} each polytopic element. This is achieved …

A well-balanced gas-kinetic scheme with adaptive mesh refinement for shallow water equations
Gaocheng Liu, Fengxiang Zhao, Jianping Gan, Kun Xu
https://arxiv.org/abs/2508.14216 …

A well-balanced gas-kinetic scheme with adaptive mesh refinement for shallow water equations
This paper is about the construction of a well-balanced gas-kinetic scheme (GKS) with space-time adaptive mesh refinement (STAMR) for the shallow water equations (SWE). While the well-balanced GKS has been established on Cartesian and triangular meshes, the present STAMR framework employs arbitrary quadrilateral meshes with hanging nodes, posing additional challenges for constructing well-balanced schemes. Complementing spatial adaptivity, temporal adaptivity is achieved by selecting adaptive t…

Energy-Equidistributed Moving Sampling Physics-informed Neural Networks for Solving Conservative Partial Differential Equations
Qinjiao Gao, Longzhe Xu, Dongjiang Wang, Ran Zhang
https://arxiv.org/abs/2508.19561

Energy-Equidistributed Moving Sampling Physics-informed Neural Networks for Solving Conservative Partial Differential Equations
This paper presents a novel Energy-Equidistributed adaptive sampling framework for multi-dimensional conservative PDEs, introducing both location-based and velocity-based formulations of Energy-Equidistributed moving mesh PDEs (EMMPDEs). The framework utilizes the energy density function as the monitor function, ensuring that mesh adaptation dynamically tracks energy evolution during temporal integration. These theoretical developments are integrated with deep neural networks to establish the E…

A multi-resolution limiter for the Runge-Kutta discontinuous Galerkin method
Hua Shen, Bangwei She
https://arxiv.org/abs/2510.00511 https://arxiv.org/pdf/2…

A multi-resolution limiter for the Runge-Kutta discontinuous Galerkin method
We propose a novel multi-resolution (MR) limiter for the Runge-Kutta discontinuous Galerkin (RKDG) method for solving hyperbolic conservation laws on a general unstructured mesh. Unlike classical limiters, which detects only solution discontinuities to dichotomize cells into good or troubled, the proposed MR limiter also takes into account the derivative discontinuities to divide cells into several groups. The method operates by performing a successive comparison of the local DG polynomial's de…

Energy minimisation using overlapping tensor-product free-knot B-splines
Alexandre Magueresse, Santiago Badia
https://arxiv.org/abs/2508.17705 https://arxi…

Energy minimisation using overlapping tensor-product free-knot B-splines
Accurately solving PDEs with localised features requires refined meshes that adapt to the solution. Traditional numerical methods, such as finite elements, are linear in nature and often ineffective for such problems, as the mesh is not tailored to the solution. Adaptive strategies, such as $h$- and $p$-refinement, improve efficiency by sequentially refining the mesh based on a posteriori error estimates. However, these methods are geometrically rigid -- limited to specific refinement rules -- …

Asymptotically compatible entropy-consistent discretization for a class of nonlocal conservation laws
Nicola De Nitti, Kuang Huang
https://arxiv.org/abs/2510.00221 https://

Asymptotically compatible entropy-consistent discretization for a class of nonlocal conservation laws
We consider a class of nonlocal conservation laws modeling traffic flows, given by $ \partial_t ρ_\varepsilon + \partial_x(V(ρ_\varepsilon \ast γ_\varepsilon) ρ_\varepsilon) = 0 $ with a suitable convex kernel $ γ_\varepsilon $, and its Godunov-type numerical discretization. We prove that, as the nonlocal parameter $ \varepsilon $ and mesh size $ h $ tend to zero simultaneously, the discrete approximation $ W_{\varepsilon,h} $ of $ W_\varepsilon := ρ_\varepsilon \ast γ_\varepsilon $ conv…

Basis construction for polynomial spline spaces over arbitrary T-meshe
Shicong Zhong, Falai Chen, Bingru Huang
https://arxiv.org/abs/2508.12950 https://arx…

Basis construction for polynomial spline spaces over arbitrary T-meshe
This paper presents the first method for constructing bases for polynomial spline spaces over an arbitrary T-meshes (PT-splines for short). We construct spline basis functions for an arbitrary T-mesh by first converting the T-mesh into a diagonalizable one via edge extension, ensuring a stable dimension of the spline space. Basis functions over the diagoalizable T-mesh are constructed according to the three components in the dimension formula corresponding to cross-cuts, rays, and T $l$-edges i…