Tootfinder

Examples of complete Calabi--Yau metrics on affine smoothings of irregular toric Calabi--Yau cones
Ronan J. Conlon, Tran-Trung Nghiem
https://arxiv.org/abs/2506.14118

Examples of complete Calabi--Yau metrics on affine smoothings of irregular toric Calabi--Yau cones
We present new examples of affine Calabi--Yau manifolds of Euclidean volume growth and quadratic curvature decay, whose tangent cones at infinity are irregular and have smooth links. In the process, we demonstrate (and provide the relevant computer code) how to explicitly compute the Reeb field and all Minkowski decompositions of a given toric Calabi--Yau cone with smooth link from the data of its toric polytope. Minkowski decompositions of this polytope into lattice segments and/or triangles g…

A High-Order Quadrature Method for Implicitly Defined Hypersurfaces and Regions
Zibo Zhao
https://arxiv.org/abs/2506.13078 https://ar…

A High-Order Quadrature Method for Implicitly Defined Hypersurfaces and Regions
This paper presents a high-order accurate numerical quadrature algorithm for evaluating integrals over curved surfaces and regions defined implicitly via a level set of a given function restricted to a hyperrectangle. The domain is divided into small tetrahedrons, and by employing the change of variables formula, the approach yields an algorithm requiring only one-dimensional root finding and standard Gaussian quadrature. The resulting quadrature scheme guarantees strictly positive weights and …

Replaced article(s) found for eess.SY. https://arxiv.org/list/eess.SY/new
[1/1]:
Sample Complexity of the Linear Quadratic Regulator: A Reinforcement Learning Lens

Near optimal controls for partially observed stochastic linear quadratic problems
Jingrui Sun, Jiaqiang Wen, Jie Xiong, Wen Xu
https://arxiv.org/abs/2506.11778

Near optimal controls for partially observed stochastic linear quadratic problems
In this article, we consider a stochastic linear quadratic control problem with partial observation. A near optimal control in the weak formulation is characterized. The main features of this paper are the presence of the control in the diffusion term of the state equation, the circular dependence between the control process and the filtration generated by the observation, and the observation process contains an unbounded drift term. We address these difficulties by first restricting the contro…

Observer Switching Strategy for Enhanced State Estimation in CSTR Networks
Lisbel B\'arzaga-Martell, Francisco Ib\'a\~nez, Angel L. Cede\~no, Maria Coronel, Francisco Concha, Norelys Aguila-Camacho, Jos\'e Ricardo P\'erez-Correa
https://arxiv.org/abs/2506.13878

Observer Switching Strategy for Enhanced State Estimation in CSTR Networks
Accurate state estimation is essential for monitoring and controlling nonlinear chemical reactors, such as continuous stirred-tank reactors (CSTRs), where limited sensor coverage and process uncertainties hinder real-time observability. This paper introduces a novel multi-observer switching framework that combines several advanced estimators: Extended Luenberger Observer (ELO), Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF), Quadrature Kalman Filter (QKF), and Particle Filter (PF),…

On Differential and Boomerang Properties of a Class of Binomials over Finite Fields of Odd Characteristic
Namhun Koo, Soonhak Kwon
https://arxiv.org/abs/2506.11486

On Differential and Boomerang Properties of a Class of Binomials over Finite Fields of Odd Characteristic
In this paper, we investigate the differential and boomerang properties of a class of binomial $F_{r,u}(x) = x^r(1 + uχ(x))$ over the finite field $\mathbb{F}_{p^n}$, where $r = \frac{p^n+1}{4}$, $p^n \equiv 3 \pmod{4}$, and $χ(x) = x^{\frac{p^n -1}{2}}$ is the quadratic character in $\mathbb{F}_{p^n}$. We show that $F_{r,\pm1}$ is locally-PN with boomerang uniformity $0$ when $p^n \equiv 3 \pmod{8}$. To the best of our knowledge, the second known non-PN function class with boomerang uniformi…

This https://arxiv.org/abs/2506.02450 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepp…

Muon (and Lepton) Anomalous Magnetic Moments and Limits on Their Radii
The limits on lepton radii and contact interaction scales are used to derive limits on the deviations of lepton anomalous magnetic dipole moments (g-2)/2 from the Standard Model predictions. In the case of quadratic dependence of the deviations on the lepton mass the limits for electrons are better compared to low energy measurements, for muons somewhat weaker than the latest precision experiments, and for taus by far the best.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention
Yeonju Ro, Zhenyu Zhang, Souvik Kundu, Zhangyang Wang, Aditya Akella
https://arxiv.org/abs/2506.09316

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention
Large language models (LLMs) excel at capturing global token dependencies via self-attention but face prohibitive compute and memory costs on lengthy inputs. While sub-quadratic methods (e.g., linear attention) can reduce these costs, they often degrade accuracy due to overemphasizing recent tokens. In this work, we first propose \textit{dual-state linear attention} (\textbf{\dsla}), a novel design that maintains two specialized hidden states-one for preserving historical context and one for tr…

This https://arxiv.org/abs/2411.10121 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Quadratic Form based Multiple Contrast Tests for Comparison of Group Means
Comparing the mean vectors across different groups is a cornerstone in the realm of multivariate statistics, with quadratic forms commonly serving as test statistics. However, when the overall hypothesis is rejected, identifying specific vector components or determining the groups among which differences exist requires additional investigations. Conversely, employing multiple contrast tests (MCT) allows conclusions about which components or groups contribute to these differences. However, they …

Partially-Supervised Neural Network Model For Quadratic Multiparametric Programming
Fuat Can Beylunioglu, Mehrdad Pirnia, P. Robert Duimering
https://arxiv.org/abs/2506.05567

Partially-Supervised Neural Network Model For Quadratic Multiparametric Programming
Neural Networks (NN) with ReLU activation functions are used to model multiparametric quadratic optimization problems (mp-QP) in diverse engineering applications. Researchers have suggested leveraging the piecewise affine property of deep NN models to solve mp-QP with linear constraints, which also exhibit piecewise affine behaviour. However, traditional deep NN applications to mp-QP fall short of providing optimal and feasible predictions, even when trained on large datasets. This study propos…