Tootfinder

The cosmic web's Lyman-$\alpha$ glow at $z \approx 2.5$; varying hydrodynamic models, dust, and wide-field, narrow-band imaging detection
Oleksii Sokoliuk, John K. Webb, Kenneth M. Lanzetta, Michael M. Shara, Stefan Gromoll, James S. Bolton, Robert F. Carswell, Gaspar Galaz, C\'edric Ledoux, Gaspare Lo Curto, Alain Smette, David Valls-Gabaud, Anja von der Linden, Frederick M. Walter, Joris Witstok

The cosmic web's Lyman-$α$ glow at $z \approx 2.5$; varying hydrodynamic models, dust, and wide-field, narrow-band imaging detection
The diffuse glow of the cosmic web in Lyman-$α$ emission has long been predicted, yet remained elusive to direct wide field detection. We present theoretical calculations that, when compared with recent observations made using the Condor Array Telescope in New Mexico reported in Lanzetta et al. 2024, point to its discovery at $z \approx 2.5$. Synthetic Lyman-$α$ surface brightness maps are constructed from five state-of-the-art hydrodynamic simulations (Illustris-TNG, SIMBA, EAGLE, CROCODILE,…

Uncertainty-Aware Deep Learning for Wildfire Danger Forecasting
Spyros Kondylatos, Gustau Camps-Valls, Ioannis Papoutsis
https://arxiv.org/abs/2509.25017 https://

Uncertainty-Aware Deep Learning for Wildfire Danger Forecasting
Wildfires are among the most severe natural hazards, posing a significant threat to both humans and natural ecosystems. The growing risk of wildfires increases the demand for forecasting models that are not only accurate but also reliable. Deep Learning (DL) has shown promise in predicting wildfire danger; however, its adoption is hindered by concerns over the reliability of its predictions, some of which stem from the lack of uncertainty quantification. To address this challenge, we present an…

Staged Event Trees for Transparent Treatment Effect Estimation
Gherardo Varando, Manuele Leonelli, Jordi Cerd\`a-Bautista, Vasileios Sitokonstantinou, Gustau Camps-Valls
https://arxiv.org/abs/2509.26265

Staged Event Trees for Transparent Treatment Effect Estimation
Average and conditional treatment effects are fundamental causal quantities used to evaluate the effectiveness of treatments in various critical applications, including clinical settings and policy-making. Beyond the gold-standard estimators from randomized trials, numerous methods have been proposed to estimate treatment effects using observational data. In this paper, we provide a novel characterization of widely used causal inference techniques within the framework of staged event trees, dem…

Modeling Scintillation Photon Transport and Reconstruction Algorithms for the Time-of-Flight Detector in the T2K Neutrino Experiment
C. Alt, A. Blanchet, S. Bordoni, P. Collard, T. H. Bui, M. H. Bui, G. Ha, C. Jes\'us-Valls, V. S. Kasturi, A. Klustov\'a, A. Korzenev, T. A. Le, T. Lux, A. D. Nguyen, D. T. Nguyen, H. Nguyen, S. Samani, F. S\'anchez, M. Ta, T. Tha\'iduc, E. Villa

Modeling Scintillation Photon Transport and Reconstruction Algorithms for the Time-of-Flight Detector in the T2K Neutrino Experiment
The T2K ND280 upgrade aims to reduce the systematic uncertainty of the CP-violating phase, $δ_{CP}$, to reject non-CP violation hypothesis at $3σ$ confidence level. A crucial component of the ND280 upgrade, alongside the Super Fine Grained Detector (SuperFGD) and two High-Angle Time Projection Chambers (TPCs), is the Time-of-Flight (ToF) detector, which significantly enhances background rejection and particle identification capabilities. The ToF detector features six modules in a cube configu…