Tootfinder

Affine Hulls and Simplices: a Constructive Analysis
Douglas S. Bridges
https://arxiv.org/abs/2509.20633 https://arxiv.org/pdf/2509.20633

Affine Hulls and Simplices: a Constructive Analysis
This paper deals with certain fundamental results about affine hulls and simplices in a real normed linear space. The framework of the paper is Bishop's constructive mathematics, which, with its characteristic interpretation of existence as constructibility, often involves more subtle estimation than its classical-logic-based counterpart. As well as technically more involved proofs (for example, that of Theorem 29 on the perturbation of vertices), we have included a number of elementary ones fo…

Schema-Guided Response Generation using Multi-Frame Dialogue State for Motivational Interviewing Systems
Jie Zeng, Yukiko I. Nakano
https://arxiv.org/abs/2508.20635 https://

Schema-Guided Response Generation using Multi-Frame Dialogue State for Motivational Interviewing Systems
The primary goal of Motivational Interviewing (MI) is to help clients build their own motivation for behavioral change. To support this in dialogue systems, it is essential to guide large language models (LLMs) to generate counselor responses aligned with MI principles. By employing a schema-guided approach, this study proposes a method for updating multi-frame dialogue states and a strategy decision mechanism that dynamically determines the response focus in a manner grounded in MI principles.…

A Framework for Rapidly Developing and Deploying Protection Against Large Language Model Attacks
Adam Swanda, Amy Chang, Alexander Chen, Fraser Burch, Paul Kassianik, Konstantin Berlin
https://arxiv.org/abs/2509.20639

A Framework for Rapidly Developing and Deploying Protection Against Large Language Model Attacks
The widespread adoption of Large Language Models (LLMs) has revolutionized AI deployment, enabling autonomous and semi-autonomous applications across industries through intuitive language interfaces and continuous improvements in model development. However, the attendant increase in autonomy and expansion of access permissions among AI applications also make these systems compelling targets for malicious attacks. Their inherent susceptibility to security flaws necessitates robust defenses, yet …

Probing Bandwidth and Sensitivity in Rydberg Atom Sensing via Optical Homodyne and RF Heterodyne Detection
Dixith Manchaiah, Stone Oliver, Samuel Berweger, Christopher L. Holloway, Nikunjkumar Prajapati
https://arxiv.org/abs/2509.20632

Probing Bandwidth and Sensitivity in Rydberg Atom Sensing via Optical Homodyne and RF Heterodyne Detection
Rydberg atom based sensors allow for SI traceable measurements and show promise for applications in the field of communication and radar technologies. In this article, we investigate the bandwidth and sensitivity of a Rydberg atom-based sensor in a rubidium vapor cell using Rydberg electromagnetically induced transparency (EIT) spectroscopy. We employ a radio-frequency (RF) heterodyne measurement technique in combination with an optical homodyne setup to extend the achievable range between sens…

A Hierarchical Variational Graph Fused Lasso for Recovering Relative Rates in Spatial Compositional Data
Joaquim Valerio Teixeira, Ed Reznik, Sudpito Banerjee, Wesley Tansey
https://arxiv.org/abs/2509.20636

A Hierarchical Variational Graph Fused Lasso for Recovering Relative Rates in Spatial Compositional Data
The analysis of spatial data from biological imaging technology, such as imaging mass spectrometry (IMS) or imaging mass cytometry (IMC), is challenging because of a competitive sampling process which convolves signals from molecules in a single pixel. To address this, we develop a scalable Bayesian framework that leverages natural sparsity in spatial signal patterns to recover relative rates for each molecule across the entire image. Our method relies on the use of a heavy-tailed variant of th…

The Coverage Depth Problem in DNA Storage Over Small Alphabets
Matteo Bertuzzo, Alberto Ravagnani, Eitan Yaakobi
https://arxiv.org/abs/2507.20639 https://a…

The Coverage Depth Problem in DNA Storage Over Small Alphabets
The coverage depth problem in DNA data storage is about minimizing the expected number of reads until all data is recovered. When they exist, MDS codes offer the best performance in this context. This paper focuses on the scenario where the base field is not large enough to allow the existence of MDS codes. We investigate the performance for the coverage depth problem of codes defined over a small finite field, providing closed formulas for the expected number of reads for various code families…

Electromagnetic properties of heavy-light mesons
A. S. Miramontes, J. Papavassiliou, J. M. Pawlowski
https://arxiv.org/abs/2508.20631 https://arxiv.org/pdf…

Electromagnetic properties of heavy-light mesons
Within the Bethe-Salpeter framework, we present a computation of space-like electromagnetic form factors for pseudoscalar mesons, including light and heavy-light systems. Our approach employs a flavour-dependent variation of the standard Taylor effective charge, which contains key contributions from the quark-gluon vertices. This effective interaction is a common ingredient of all relevant dynamical equations, and accommodates the crucial mass differences between the various quark flavours. Par…

Exploring density dependent B as a suitable parameter in higher dimensional approach with a non-linear equation of state
Koushik Ballav Goswami, Debadri Bhattacharjee, Anirban Saha, Pradip Kumar Chattopadhyay
https://arxiv.org/abs/2508.20634

Exploring density dependent B as a suitable parameter in higher dimensional approach with a non-linear equation of state
In this investigation, we present a singularity free interior solution of the Einstein field equation for a class of anisotropic compact objects in dimensions $D\geq4$. In accordance with the concept of Vaidya and Tikekar, the geometry of the physical $(D-1)$-space of a star corresponding to $t=constant$ hypersurface is assumed to be of a $(D-1)$ spheroid. For the fulfilment of causality condition, a limit of the spheroidal parameter ($λ$) is noted depending on the values of amount of anisotro…

Convergent Weight and Activation Dynamics in Memristor Neural Networks
Mauro Di Marco, Mauro Forti, Luca Pancioni, Giacomo Innocenti, Alberto Tesi
https://arxiv.org/abs/2507.20634

Convergent Weight and Activation Dynamics in Memristor Neural Networks
Convergence of dynamic feedback neural networks (NNs), as the Cohen-Grossberg, Hopfield and cellular NNs, has been for a long time a workhorse of NN theory. Indeed, convergence in the presence of multiple stable equilibrium points (EPs) is crucial to implement content addressable memories and solve several other signal processing tasks in real time. There are two typical ways to use a convergent NN, i.e.: a) let the activations evolve while maintaining fixed weights and inputs (activation dynam…

High-order fully well-balanced numerical methods for one-dimensional blood flow with discontinuous properties, friction and gravity
Ernesto Pimentel-Garc\'ia, Lucas O. M\"uller, Carlos Par\'es
https://arxiv.org/abs/2508.20638

High-order fully well-balanced numerical methods for one-dimensional blood flow with discontinuous properties, friction and gravity
We present well-balanced, high-order, semi-discrete numerical schemes for one-dimensional blood flow models with discontinuous mechanical properties and algebraic source terms representing friction and gravity. While discontinuities in model parameters are handled using the Generalized Hydrostatic Reconstruction, the presence of algebraic source terms implies that steady state solutions cannot always be computed analytically. In fact, steady states are defined by an ordinary differential equati…