Tootfinder

Boardwalk: Towards a Framework for Creating Board Games with LLMs
\'Alvaro Guglielmin Becker, Gabriel Bauer de Oliveira, Lana Bertoldo Rossato, Anderson Rocha Tavares
https://arxiv.org/abs/2508.16447

Boardwalk: Towards a Framework for Creating Board Games with LLMs
Implementing board games in code can be a time-consuming task. However, Large Language Models (LLMs) have been proven effective at generating code for domain-specific tasks with simple contextual information. We aim to investigate whether LLMs can implement digital versions of board games from rules described in natural language. This would be a step towards an LLM-assisted framework for quick board game code generation. We expect to determine the main challenges for LLMs to implement the board…

Hybrid Quantum-Classical Branch-and-Price Method for the Vertex Coloring Problem
Chiara Vercellino, M. Yassine Naghmouchi, Wesley Coelho, Giacomo Vitali, Alberto Scionti, Paolo Viviani, Olivier Terzo, Bartolomeo Montrucchio
https://arxiv.org/abs/2508.18887

Hybrid Quantum-Classical Branch-and-Price Method for the Vertex Coloring Problem
This paper introduces Quantum Classical Branch-and-Price (QCBP), a hybrid quantum-classical algorithm for the Vertex Coloring problem on neutral-atom Quantum Processing Units (QPUs). QCBP embeds quantum computation within the classical Branch-and-Price (BP) framework to address three bottlenecks in classical BP algorithms: the computational cost of Pricing Subproblems (PSPs), branching efficiency, and the quality of primal heuristics. It uses quantum-assisted Column Generation (CG) based on Qua…

AlgoTune: Can Language Models Speed Up General-Purpose Numerical Programs?
Ori Press, Brandon Amos, Haoyu Zhao, Yikai Wu, Samuel K. Ainsworth, Dominik Krupke, Patrick Kidger, Touqir Sajed, Bartolomeo Stellato, Jisun Park, Nathanael Bosch, Eli Meril, Albert Steppi, Arman Zharmagambetov, Fangzhao Zhang, David Perez-Pineiro, Alberto Mercurio, Ni Zhan, Talor Abramovich, Kilian Lieret, Hanlin Zhang, Shirley Huang, Matthias Bethge, Ofir Press

AlgoTune: Can Language Models Speed Up General-Purpose Numerical Programs?
Despite progress in language model (LM) capabilities, evaluations have thus far focused on models' performance on tasks that humans have previously solved, including in programming (Jimenez et al., 2024) and mathematics (Glazer et al., 2024). We therefore propose testing models' ability to design and implement algorithms in an open-ended benchmark: We task LMs with writing code that efficiently solves computationally challenging problems in computer science, physics, and mathematics. Our AlgoTu…

Realistic consecutive galaxy mergers form eccentric PTA sources
Federica Fastidio, Elisa Bortolas, Alessia Gualandris, Alberto Sesana, Justin Read, Walter Dehnen
https://arxiv.org/abs/2506.16539

Realistic consecutive galaxy mergers form eccentric PTA sources
Results from pulsar timing arrays (PTAs) show evidence of a gravitational wave background (GWB) consistent with a population of unresolved supermassive black hole binaries (BHBs). The observed spectrum shows a flattening at lower frequencies that can be explained by a population of eccentric BHBs. This study aims to determine the dynamical evolution and merger timescales of the most massive BHBs, which are potential sources of the GWB. We select successive galactic major mergers from the Illust…

Rare Events, Many Searchers, and Fast Target Reaching in a Finite Domain
Elisabetta Ellettari, Giacomo Nasuti, Alberto Bassanoni, Alessandro Vezzani, Raffaella Burioni
https://arxiv.org/abs/2507.09452

Rare Events, Many Searchers, and Fast Target Reaching in a Finite Domain
Finding a target in a complex environment is a fundamental challenge in nature, from chemical reactions to sperm reaching an egg. An effective strategy to reduce the time needed to reach a target is to deploy many searchers, increasing the likelihood that at least one will succeed by using the statistics of rare events. When the underlying stochastic process involves broadly distributed step sizes, rare long jumps dominate the dynamics, making the use of multiple searchers particularly powerful…

PySeizure: A single machine learning classifier framework to detect seizures in diverse datasets
Bartlomiej Chybowski, Shima Abdullateef, Hollan Haule, Alfredo Gonzalez-Sulser, Javier Escudero
https://arxiv.org/abs/2508.07253

PySeizure: A single machine learning classifier framework to detect seizures in diverse datasets
Reliable seizure detection is critical for diagnosing and managing epilepsy, yet clinical workflows remain dependent on time-consuming manual EEG interpretation. While machine learning has shown promise, existing approaches often rely on dataset-specific optimisations, limiting their real-world applicability and reproducibility. Here, we introduce an innovative, open-source machine-learning framework that enables robust and generalisable seizure detection across varied clinical datasets. We eva…

Stacks, Monodromy and Symmetric Cubic Surfaces
Alberto Landi
https://arxiv.org/abs/2507.00934 https://arxiv.org/pdf/2507.00934…

Stacks, Monodromy and Symmetric Cubic Surfaces
We investigate monodromy groups arising in enumerative geometry, with a particular focus on how these groups are influenced by prescribed symmetries. To study these phenomena effectively, we work in the framework of moduli stacks rather than moduli spaces. This perspective proves broadly useful for understanding and constructing monodromy. We illustrate these ideas through several examples, with special attention to the 27 lines on a cubic surface, assuming the surface admits a given symmetry g…

Deciphering the Physical Origin of GRB 240825A: A Long GRB Lacking a Bright Supernova
Rahul Gupta, Judith L. Racusin, R. Sanchez-Ramirez, Y. Hu, Andrea Rossi, Maria Dolores Caballero Garcia, Pi Nuessle, Alberto J. Castro-Tirado, Samantha Oates, Pragyan P. Bordoloi, Amar Aryan, Simone Dichiara, Peter Veres, Noel Klingler, Nicola Omodei, Elisabetta Maiorano, Donggeun Tak, S. Shilling, Jose E. Adsuara, P. H. Connell, E. Fernandez Garcia, Guillermo Garcia-Segura, Ankur Ghosh, Ersin G\&quot…

Deciphering the Physical Origin of GRB 240825A: A Long GRB Lacking a Bright Supernova
We present a comprehensive multiwavelength analysis of GRB 240825A, a bright gamma-ray burst (GRB) detected by Fermi and Swift, with a prompt duration ($T_{\rm 90}$ ~ 4 sec in 50-300 keV) near the boundary separating short and long GRBs, prompting a detailed investigation into its classification and progenitor. Using classical prompt metrics (duration, minimum variability timescale (MVT), lag, and spectral hardness) and modern classification techniques (machine-learning (ML) based t-SNE, suppor…

Reliable Image Transmission in CPS-based Pub/Sub
Everson Flores, Bruna Guterres, Thomaz Pereira Junior, Paula Barros, Alberto Cabral, Cristiana Lima Dora, Marcelo Malheiros, Marcelo Pias
https://arxiv.org/abs/2506.22875

Reliable Image Transmission in CPS-based Pub/Sub
Developments in communication and automation have driven the expansion of distributed networks, essential for IoT and CPS development in industrial applications requiring reliable image processing and real-time adaptability. Although broadly adopted, there is a literature gap regarding the performance of MQTT protocol for image sharing and transmission under high-traffic scenarios with intermittent connectivity, restricting its use in critical IoT and CPS applications. In this context, the pres…