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The high-order Hermite discrete correction function method for surface-driven electromagnetic problems
Yann-Meing Law
https://arxiv.org/abs/2509.09857 https://

The high-order Hermite discrete correction function method for surface-driven electromagnetic problems
The Hermite-Taylor method evolves all the variables and their derivatives through order $m$ in time to achieve a $2m+1$ order rate of convergence. The data required at each node of the staggered Cartesian meshes used by this method makes the enforcement of boundary and interface conditions challenging. In this work, we propose a novel correction function method, referred to as the discrete correction function method, which provides all the data required by the Hermite method near the surface wh…

Measuring dissimilarity between convex cones by means of max-min angles
Welington de Oliveira, Valentina Sessa, David Sossa
https://arxiv.org/abs/2511.10483 https://arxiv.org/pdf/2511.10483 https://arxiv.org/html/2511.10483
arXiv:2511.10483v1 Announce Type: new
Abstract: This work introduces a novel dissimilarity measure between two convex cones, based on the max-min angle between them. We demonstrate that this measure is closely related to the Pompeiu-Hausdorff distance, a well-established metric for comparing compact sets. Furthermore, we examine cone configurations where the measure admits simplified or analytic forms. For the specific case of polyhedral cones, a nonconvex cutting-plane method is deployed to compute, at least approximately, the measure between them. Our approach builds on a tailored version of Kelley's cutting-plane algorithm, which involves solving a challenging master program per iteration. When this master program is solved locally, our method yields an angle that satisfies certain necessary optimality conditions of the underlying nonconvex optimization problem yielding the dissimilarity measure between the cones. As an application of the proposed mathematical and algorithmic framework, we address the image-set classification task under limited data conditions, a task that falls within the scope of the \emph{Few-Shot Learning} paradigm. In this context, image sets belonging to the same class are modeled as polyhedral cones, and our dissimilarity measure proves useful for understanding whether two image sets belong to the same class.
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A novel spatial distribution method for wind farm parameterizations based on the Gaussian function
Bowen Du, Qi Li, Mingwei Ge, Xintao Li, Yongqian Liu
https://arxiv.org/abs/2510.11392

A novel spatial distribution method for wind farm parameterizations based on the Gaussian function
Wind farm parameterizations are crucial for quantifying the wind-farm atmosphere interaction, where wind turbines are typically modeled as elevated momentum sinks and sources of turbulence kinetic energy (TKE). These quantities must be properly distributed to the mesoscale grid. Existing parameterizations use the single-column method. However, this method can easily lead to the errors of the spatial distribution of the sink and source, thereby impacting the accuracy of mesoscale flow simulation…

Using the rejection sampling for finding tests
Markku Kuismin
https://arxiv.org/abs/2509.10325 https://arxiv.org/pdf/2509.10325

Using the rejection sampling for finding tests
A new method based on the rejection sampling for finding statistical tests is proposed. This method is conceptually intuitive, easy to implement, and applicable for arbitrary dimension. To illustrate its potential applicability, three distinct empirical examples are presented: (1) examine the differences between group means of correlated (repeated) or independent samples, (2) examine if a mean vector equals to a specific fixed vector, and (3) investigate if samples come from a specific populati…

On linear waves with memory in a Bessel-like medium
A. Giusti, I. Colombaro, A. Mentrelli
https://arxiv.org/abs/2510.11493 https://arxiv.org/pdf/2510.11493…

On linear waves with memory in a Bessel-like medium
We discuss the propagation of harmonic and transient waves for systems governed by a wave equation with memory whose integral kernel involves ratios of modified Bessel functions of the first kind in the Laplace domain. In particular, the investigation of transient waves is carried out by means of a fully numerical approach based on the Talbot method for the numerical inversion of Laplace transforms.

pyspect: An Extensible Toolbox for Automatic Construction of Temporal Logic Trees via Reachability Analysis
Kaj Munhoz Arfvidsson, Loizos Hadjiloizou, Frank J. Jiang, Karl H. Johansson, Jonas M{\aa}rtensson
https://arxiv.org/abs/2510.11316

pyspect: An Extensible Toolbox for Automatic Construction of Temporal Logic Trees via Reachability Analysis
In this paper, we present pyspect, a Python toolbox that simplifies the use of reachability analysis for temporal logic problems. Currently, satisfying complex requirements in cyber-physical systems requires significant manual effort and domain expertise to develop the underlying reachability programs. This high development effort limits the broader adoption of reachability analysis for complex verification problems. To address this, pyspect provides a method-agnostic approach to performing rea…

Fair Kernel-Lock-Free Claim/Release Protocol for Shared Object Access in Cooperatively Scheduled Runtimes
Kevin Chalmers, Jan B{\ae}kgaard Pedersen
https://arxiv.org/abs/2510.10818

Fair Kernel-Lock-Free Claim/Release Protocol for Shared Object Access in Cooperatively Scheduled Runtimes
We present the first spin-free, kernel-lock-free mutex that cooperates with user-mode schedulers and is formally proven FIFO-fair and linearizable using CSP/FDR. Our fairness oracle and stability-based proof method are reusable across coroutine runtime designs. We designed the claim/release protocol for a process-oriented language -- ProcessJ -- to manage the race for claiming shared inter-process communication channels. Internally, we use a lock-free queue to park waiting processes for gaining…

Dark gaps and resonances in barred galaxies
Taehyun Kim, Dimitri A. Gadotti, Myeong-gu Park, Yun Hee Lee, Francesca Fragkoudi, Minjin Kim, Woong-Tae Kim
https://arxiv.org/abs/2510.10427

Dark gaps and resonances in barred galaxies
Dark gaps, low surface brightness regions along the bar minor axis, are expected to form as a consequence of secular evolution in barred galaxies. Although several studies have proposed links between dark gap locations and dynamical resonances, the results remain inconclusive. Using DESI Legacy Imaging Survey data, we find that approximately 61% of barred galaxies exhibit pronounced dark gaps. We compare the location of dark gaps with resonance radii derived from the Tremaine-Weinberg method ap…

Homogenization-based optimization of wall thickness distribution for TPMS two-fluid heat exchangers
Kaito Ohtani, Hiroki Kawabe, Kentaro Yaji, Kikuo Fujita, Vikrant Aute
https://arxiv.org/abs/2510.10622

Homogenization-based optimization of wall thickness distribution for TPMS two-fluid heat exchangers
Triply Periodic Minimal Surface (TPMS) structures are attracting growing attention as promising geometries for next-generation high-performance heat exchangers (HXs), due to their continuous flow paths and high surface-area-to-volume ratio that enhance heat transfer performance. Among these, graded TPMS structures with spatially varying thickness have emerged as a potential means to further improve performance. This study proposes an optimization method of wall thickness distribution for TPMS H…

Near-Optimal Recovery Performance of PhaseLift for Phase Retrieval from Coded Diffraction Patterns
Meng Huang, Jinming Wen, Ran Zhang
https://arxiv.org/abs/2509.10300 https://…

Near-Optimal Recovery Performance of PhaseLift for Phase Retrieval from Coded Diffraction Patterns
The PhaseLift algorithm is an effective convex method for solving the phase retrieval problem from Fourier measurements with coded diffraction patterns (CDP). While exact reconstruction guarantees are well-established in the noiseless case, the stability of recovery under noise remains less well understood. In particular, when the measurements are corrupted by an additive noise vector $\mathbf{w} \in \mathbb{R}^m$, existing recovery bounds scale on the order of $\|\mathbf{w}\|_2$, whi…