Tootfinder

GMIMS-DRAGONS: A Faraday Depth Survey of the Northern Sky Covering 350 to 1030 MHz
Anna Ordog, Rebecca A. Booth, T. L. Landecker, Ettore Carretti, Alex S. Hill, Jo-Anne C. Brown, Artem Davydov, Leonardo Moutinho Caffarello, Luca B. Galler, Jonas Flygare, Jennifer L. West, A. G. Willis, Mehrnoosh Tahani, G. J. Hovey, Dustin Lagoy, Stephen Harrison, Mike Smith, Charl Baard, Rob H. Messing, D. A. Del Rizzo, Benoit Robert, Timothy Robishaw, John M. Dickey, George Morgan, Ian R. Kennedy, Ma…

GMIMS-DRAGONS: A Faraday Depth Survey of the Northern Sky Covering 350 to 1030 MHz
Polarized synchrotron emission at meter to centimeter wavelengths provides an effective tracer of the Galactic magnetic field. Calculating Faraday depth, the most useful parameter for mapping the line-of-sight magnetic field, requires observations covering wide frequency bands with many channels. As part of the Global Magneto-Ionic Medium Survey we have observed polarized emission spanning 350-1030 MHz over the Northern sky, in the declination range ${-20^{\circ}}\leqδ\leq{90^{\circ}}$. We use…

Assessing the Impact of Post-Quantum Digital Signature Algorithms on Blockchains
Alison Gon\c{c}alves Schemitt (PUCRS), Henrique Fan da Silva (UNIPAMPA), Roben Castagna Lunardi (PUCRS, IFRS), Diego Kreutz (UNIPAMPA), Rodrigo Brand\~ao Mansilha (UNIPAMPA), Avelino Francisco Zorzo (PUCRS)
https://arxiv.org/abs/2510.09271

Assessing the Impact of Post-Quantum Digital Signature Algorithms on Blockchains
The advent of quantum computing threatens the security of traditional encryption algorithms, motivating the development of post-quantum cryptography (PQC). In 2024, the National Institute of Standards and Technology (NIST) standardized several PQC algorithms, marking an important milestone in the transition toward quantum-resistant security. Blockchain systems fundamentally rely on cryptographic primitives to guarantee data integrity and transaction authenticity. However, widely used algorithms…

DeMeVa at LeWiDi-2025: Modeling Perspectives with In-Context Learning and Label Distribution Learning
Daniil Ignatev, Nan Li, Hugh Mee Wong, Anh Dang, Shane Kaszefski Yaschuk
https://arxiv.org/abs/2509.09524

DeMeVa at LeWiDi-2025: Modeling Perspectives with In-Context Learning and Label Distribution Learning
This system paper presents the DeMeVa team's approaches to the third edition of the Learning with Disagreements shared task (LeWiDi 2025; Leonardelli et al., 2025). We explore two directions: in-context learning (ICL) with large language models, where we compare example sampling strategies; and label distribution learning (LDL) methods with RoBERTa (Liu et al., 2019b), where we evaluate several fine-tuning methods. Our contributions are twofold: (1) we show that ICL can effectively predict anno…

An AI dose engine for fast carbon ion treatment planning
Anastasiia Quarz, Angelica De Gregorio, Gaia Franciosini, Angelo Schiavi, Zolt\'an Perk\'o, Lennart Volz, Vincenzo Patera, Marco Durante, Christian Graeff
https://arxiv.org/abs/2510.11271

An AI dose engine for fast carbon ion treatment planning
Monte Carlo (MC) simulations provide gold-standard accuracy for carbon ion therapy dose calculations but are computationally intensive. Analytical pencil beam algorithms offer speed but reduced accuracy in heterogeneous tissues. We developed the first AI-based dose engine capable of predicting absorbed dose, the alpha and beta parameters for relative biological effectiveness (RBE)- weighted optimisation in carbon ion therapy, delivering MC-level accuracy with drastically reduced computation tim…

Local Rigidity of Quasi--Lie Brackets on Quaternionic Banach Modules and Applications to Nonlinear PDEs
Nassim Athmouni
https://arxiv.org/abs/2510.10124 https://

Local Rigidity of Quasi--Lie Brackets on Quaternionic Banach Modules and Applications to Nonlinear PDEs
We establish a local rigidity theorem for quasi--Lie brackets on quaternionic Banach right modules. Under quantitative control of antisymmetry and Jacobi defects, we construct an explicit bilinear correction that preserves right $\mathbb{H}$--linearity and restores the exact Lie property. The approach combines a radial homotopy operator, a controlled Neumann-series inversion, and a finite-rank adjustment, all with explicit operator estimates. This constructive framework bridges quaternionic fun…

What Were You Thinking? An LLM-Driven Large-Scale Study of Refactoring Motivations in Open-Source Projects
Mikel Robredo, Matteo Esposito, Fabio Palomba, Rafael Pe\~naloza, Valentina Lenarduzzi
https://arxiv.org/abs/2509.07763

What Were You Thinking? An LLM-Driven Large-Scale Study of Refactoring Motivations in Open-Source Projects
Context. Code refactoring improves software quality without changing external behavior. Despite its advantages, its benefits are hindered by the considerable cost of time, resources, and continuous effort it demands. Aim. Understanding why developers refactor, and which metrics capture these motivations, may support wider and more effective use of refactoring in practice. Method. We performed a large-scale empirical study to analyze developers refactoring activity, leveraging Large Language Mod…

An Hand der vorgezogenen Wahlen in den Niederlanden erläutert Ilja Leonard Pfeijffer den Unterschied zwischen einer konstitutionellen und einer absoluten Demokratie.
https://europa.blog/de/nichts-ruft-bei

„Nichts ruft bei den Wählern so viel Hass hervor wie Fachkompetenz“: Ilja Leonard Pfeijffer über die niederländischen Wahlen - Europa Blog
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Is it Gaussian? Testing bosonic quantum states
Filippo Girardi, Freek Witteveen, Francesco Anna Mele, Lennart Bittel, Salvatore F. E. Oliviero, David Gross, Michael Walter
https://arxiv.org/abs/2510.07305

Is it Gaussian? Testing bosonic quantum states
Gaussian states are widely regarded as one of the most relevant classes of continuous-variable (CV) quantum states, as they naturally arise in physical systems and play a key role in quantum technologies. This motivates a fundamental question: given copies of an unknown CV state, how can we efficiently test whether it is Gaussian? We address this problem from the perspective of representation theory and quantum learning theory, characterizing the sample complexity of Gaussianity testing as a fu…