Tootfinder

MM2CT: MR-to-CT translation for multi-modal image fusion with mamba
Chaohui Gong, Zhiying Wu, Zisheng Huang, Gaofeng Meng, Zhen Lei, Hongbin Liu
https://arxiv.org/abs/2508.05476

MM2CT: MR-to-CT translation for multi-modal image fusion with mamba
Magnetic resonance (MR)-to-computed tomography (CT) translation offers significant advantages, including the elimination of radiation exposure associated with CT scans and the mitigation of imaging artifacts caused by patient motion. The existing approaches are based on single-modality MR-to-CT translation, with limited research exploring multimodal fusion. To address this limitation, we introduce Multi-modal MR to CT (MM2CT) translation method by leveraging multimodal T1- and T2-weighted MRI d…

Geometric quantum encoding of a turbulent field
Zhaoyuan Meng, Yue Yang
https://arxiv.org/abs/2508.05346 https://arxiv.org/pdf/2508.05346

Geometric quantum encoding of a turbulent field
The chaotic structure of multiscale systems presents a formidable challenge to their quantum encoding. We propose a three-stage hyperspherical encoding method for turbulent fields. This method comprises a symmetry-preserving perturbation of the ground state, a measurement-specific convolution, and a final deconvolution of observables. The latter two stages employ the Hopf fibration to map quantum observables onto vortex tubes, the building blocks of fluid turbulence. Using 27 qubits, we generat…

A generalized Hessian-based error estimator for an IPDG formulation of the biharmonic problem in two dimensions
Th\'eophile Chaumont-Frelet, Joscha Gedicke, Lorenzo Mascotto
https://arxiv.org/abs/2507.05776

A generalized Hessian-based error estimator for an IPDG formulation of the biharmonic problem in two dimensions
We consider a two dimensional biharmonic problem and its discretization by means of a symmetric interior penalty discontinuous Galerkin method. Based on the ``div-div'' complex, a novel split of an error measure based on a generalized Hessian into two terms measuring the conformity and nonconformity of the scheme is proven. This splitting is the departing point for the design of a new reliable and efficient error estimator, which does not involve any DG stabilization. Such an error estimator ca…

FineGrasp: Towards Robust Grasping for Delicate Objects
Yun Du, Mengao Zhao, Tianwei Lin, Yiwei Jin, Chaodong Huang, Zhizhong Su
https://arxiv.org/abs/2507.05978

FineGrasp: Towards Robust Grasping for Delicate Objects
Recent advancements in robotic grasping have led to its integration as a core module in many manipulation systems. For instance, language-driven semantic segmentation enables the grasping of any designated object or object part. However, existing methods often struggle to generate feasible grasp poses for small objects or delicate components, potentially causing the entire pipeline to fail. To address this issue, we propose a novel grasping method, FineGrasp, which introduces improvements in th…

Bit-Flip Fault Attack: Crushing Graph Neural Networks via Gradual Bit Search
Sanaz Kazemi Abharian, Sai Manoj Pudukotai Dinakarrao
https://arxiv.org/abs/2507.05531

Bit-Flip Fault Attack: Crushing Graph Neural Networks via Gradual Bit Search
Graph Neural Networks (GNNs) have emerged as a powerful machine learning method for graph-structured data. A plethora of hardware accelerators has been introduced to meet the performance demands of GNNs in real-world applications. However, security challenges of hardware-based attacks have been generally overlooked. In this paper, we investigate the vulnerability of GNN models to hardware-based fault attack, wherein an attacker attempts to misclassify output by modifying trained weight paramete…

Three bound states with prescribed angular momentum to the cubic-quintic NLS equations in $\mathbb{R}^{3}$
Shuai Yao, Juntao Sun
https://arxiv.org/abs/2507.04057

Three bound states with prescribed angular momentum to the cubic-quintic NLS equations in $\mathbb{R}^{3}$
In this paper, we investigate bound states with prescribed angular momentum and mass for the nonlinear Schrödinger equations (NLS) with the cubic-quintic nonlinearity in dimensions three. We demonstrate that there exist three solutions for the double constrained problem: a local minimizer, a mountain pass type solution, and a global minimizer. Moreover, by means of the minimax method, we construct a new mountain pass path and further obtain the geometric link among the three solutions as well …

Basic Computations in Fault Tree Analysis
Hamid Jahanian
https://arxiv.org/abs/2507.05509 https://arxiv.org/pdf/2507.05509

Basic Computations in Fault Tree Analysis
Fault Tree Analysis (FTA) is a well-established method in failure analysis and is widely used in safety and reliability assessments. While FTA tools enable users to manage complex analyses effectively, they can sometimes obscure the underlying calculation processes. As a result, the soundness of FTA results often hinges on the user's expertise and familiarity with the methodology and the tool. This paper aims to explore the fundamental principles underlying both qualitative and quantitative FTA…

A Lasry-Lions envelope approach for mathematical programs with complementarity constraints
Jia Wang, Andreas Themelis, Ivan Markovsky, Panagiotis Patrinos
https://arxiv.org/abs/2507.04694

A Lasry-Lions envelope approach for mathematical programs with complementarity constraints
We propose a homotopy method for solving mathematical programs with complementarity constraints (CCs). The indicator function of the CCs is relaxed by a Lasry-Lions double envelope, an extension of the Moreau envelope that enjoys an additional smoothness property that makes it amenable to fast optimization algorithms. The proposed algorithm mimics the behavior of homotopy methods for systems of nonlinear equations or penalty methods for constrained optimization: it solves a sequence of smooth s…

A Test for Jumps in Metric-Space Conditional Means
David Van Dijcke
https://arxiv.org/abs/2507.04560 https://arxiv.org/pdf/2507.04560…

A Test for Jumps in Metric-Space Conditional Means
Standard methods for detecting discontinuities in conditional means are not applicable to outcomes that are complex, non-Euclidean objects like distributions, networks, or covariance matrices. This article develops a nonparametric test for jumps in conditional means when outcomes lie in a non-Euclidean metric space. Using local Fréchet regression$\unicode{x2014}$which generalizes standard regression to metric-space valued data$\unicode{x2014}$the method estimates a mean path on either side of …

Energy-conserving Kansa methods for Hamiltonian wave equations
Xiaobin Li, Meng Chen, Zhengjie Sun, Leevan Ling, Siqing Li
https://arxiv.org/abs/2507.04361

Energy-conserving Kansa methods for Hamiltonian wave equations
We introduce a fast, constrained meshfree solver designed specifically to inherit energy conservation (EC) in second-order time-dependent Hamiltonian wave equations. For discretization, we adopt the Kansa method, also known as the kernel-based collocation method, combined with time-stepping. This approach ensures that the critical structural feature of energy conservation is maintained over time by embedding a quadratic constraint into the definition of the numerical solution. To address the co…