Tootfinder

Morgen Dinogeburtstag, mit Kartoffelbreivulkan und Dinonuggets, Schatzsuche um das Dino-Ei zu retten, Ausgrabung im Sandkasten,..
..und als Soundtrack dazu natürlich #Heavysaurus 🤘
https://www.heavysaurus.de/…

Hamilton-Jacobi Reachability for Viability Analysis of Constrained Waste-to-Energy Systems under Adversarial Uncertainty
Achraf Bouhmady, Othman Cherkaoui Dekkaki
https://arxiv.org/abs/2510.11396

Hamilton-Jacobi Reachability for Viability Analysis of Constrained Waste-to-Energy Systems under Adversarial Uncertainty
This paper investigates the problem of maintaining the safe operation of Waste-to-Energy (WtE) systems under operational constraints and uncertain waste inflows. We model this as a robust viability problem, formulated as a zero-sum differential game between a control policy and an adversarial disturbance. Within a Hamilton-Jacobi framework, the viability kernel is characterized as the zero sublevel set of a value function satisfying a constrained Hamilton-Jacobi-Bellman (HJB) equation in the vi…

Engineering High-Order Harmonic Generation through Gas Confinement at Sub-Millimeter Lengths
Agata Azzolin, Gaia Giovannetti, Oliviero Cannelli, Sabine Rockenstein, Guangyu Fan, Md S. Ahsan, Lorenzo Colaizzi, Erik P. M{\aa}nsson, Noah Tettenborn, Linda Oberti, Davide Faccial\`a, Fabio Frassetto, Anna Gabriella Ciriolo, Dario W. Lodi, Alia Ashraf, Cristian Manzoni, Rebeca Mart\'inez V\'azquez, Michele Devetta, Roberto Osellame, Luca Poletto, Salvatore Stagira, Caterina Vozzi, Te…

Engineering High-Order Harmonic Generation through Gas Confinement at Sub-Millimeter Lengths
Attosecond light sources based on high-order harmonic generation (HHG) constitute to date the only table-top solution for producing coherent broadband radiation covering the spectral range from the extreme ultraviolet to the soft X-rays. The so-called emission cutoff can be extended towards higher photon energies by increasing the driving wavelength at the expense of conversion efficiency. An alternative route is to overdrive the process by using higher laser intensities, with the challenging r…

Identifying Memory Effects in Epidemics via a Fractional SEIRD Model and Physics-Informed Neural Networks
Achraf Zinihi
https://arxiv.org/abs/2509.22760 https://

Identifying Memory Effects in Epidemics via a Fractional SEIRD Model and Physics-Informed Neural Networks
We develop a physics-informed neural network (PINN) framework for parameter estimation in fractional-order SEIRD epidemic models. By embedding the Caputo fractional derivative into the network residuals via the L1 discretization scheme, our method simultaneously reconstructs epidemic trajectories and infers both epidemiological parameters and the fractional memory order $α$. The fractional formulation extends classical integer-order models by capturing long-range memory effects in disease prog…

The simulation chain for the Terzina Cherenkov telescope on board the NUSES space mission
M. Abdullahi, R. Aloisio, F. Arneodo, S. Ashurov, U. Atalay, F. C. T. Barbato, R. Battiston, M. Bertaina, E. Bissaldi, D. Boncioli, L. Burmistrov, F. Cadoux, I. Cagnoli, E. Casilli, D. Cortis, A. Cummings, M. D'Arco, S. Davarpanah, I. De Mitri, G. De Robertis, A. Di Giovanni, A. Di Salvo, L. Di Venere, J. Eser, Y. Favre, S. Fogliacco, G. Fontanella, P. Fusco, S. Garbolino, F. Gargano, M. Gilib…

The simulation chain for the Terzina Cherenkov telescope on board the NUSES space mission
The Terzina telescope is designed to detect ultra-high energy cosmic rays (UHECRs) and Earth-skimming neutrinos from a 550 km low-Earth orbit (LEO) by observing Cherenkov light emitted by Extensive Air Showers (EAS) in the Earth's atmosphere pointing towards the telescope and in the field of view. In this contribution, a simulation chain for the Terzina telescope on board the NUSES mission will be presented. The chain encompasses all stages of the detection process, from event generation and EA…

Extended AI Interactions Shape Sycophancy and Perspective Mimesis
Shomik Jain, Charlotte Park, Matheus Mesquita Viana, Ashia Wilson, Dana Calacci
https://arxiv.org/abs/2509.12517

Extended AI Interactions Shape Sycophancy and Perspective Mimesis
We investigate whether long-context interactions between users and LLMs lead to AI mirroring behaviors. We focus on two forms of mirroring: (1) sycophancy -- the tendency of models to be overly agreeable with users, and (2) perspective mimesis -- the extent to which models reflect a user's perspective. Using two weeks of interaction context collected from 38 users, we compare model responses with and without long-context for two tasks: political explanations and personal advice. Our results dem…

Exploring cosmological constraints on galaxy formation time
Agripino Sousa-Neto, Maria Aldin\^ez Dantas, Javier E. Gonz\'alez, Joel C. Carvalho, Jailson Alcaniz
https://arxiv.org/abs/2509.26611

Exploring cosmological constraints on galaxy formation time
The Universe consists of a variety of objects that formed at different epochs, leading to variations in the formation time which represents the time elapsed from the onset of structure formation until the formation time of a particular object. In this work, we present two approaches to reconstruct and constrain the galaxy formation time $t_f(z)$ using non-parametric reconstruction methods, such as Gaussian Processes (GP) and High-performance Symbolic Regression (SR). Our analysis uses age estim…

Sea-ing Through Scattered Rays: Revisiting the Image Formation Model for Realistic Underwater Image Generation
Vasiliki Ismiroglou, Malte Pedersen, Stefan H. Bengtson, Andreas Aakerberg, Thomas B. Moeslund
https://arxiv.org/abs/2509.15011

Sea-ing Through Scattered Rays: Revisiting the Image Formation Model for Realistic Underwater Image Generation
In recent years, the underwater image formation model has found extensive use in the generation of synthetic underwater data. Although many approaches focus on scenes primarily affected by discoloration, they often overlook the model's ability to capture the complex, distance-dependent visibility loss present in highly turbid environments. In this work, we propose an improved synthetic data generation pipeline that includes the commonly omitted forward scattering term, while also considering a …

Distributed Koopman Operator Learning from Sequential Observations
Ali Azarbahram, Shenyu Liu, Gian Paolo Incremona
https://arxiv.org/abs/2509.20071 https://

Distributed Koopman Operator Learning from Sequential Observations
This paper presents a distributed Koopman operator learning framework for modeling unknown nonlinear dynamics using sequential observations from multiple agents. Each agent estimates a local Koopman approximation based on lifted data and collaborates over a communication graph to reach exponential consensus on a consistent distributed approximation. The approach supports distributed computation under asynchronous and resource-constrained sensing. Its performance is demonstrated through simulati…