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Machine Learning Methods for Large Population Games with Applications in Operations Research
Gokce Dayanikli, Mathieu Lauriere
https://arxiv.org/abs/2406.10441

Machine Learning Methods for Large Population Games with Applications in Operations Research
In this tutorial, we provide an introduction to machine learning methods for finding Nash equilibria in games with large number of agents. These types of problems are important for the operations research community because of their applicability to real life situations such as control of epidemics, optimal decisions in financial markets, electricity grid management, or traffic control for self-driving cars. We start the tutorial by introducing stochastic optimal control problems for a single ag…

Enhancing the light yield of He:CF$_4$ based gaseous detector
F. D. Amaro, R. Antonietti, E. Baracchini, L. Benussi, S. Bianco, R. Campagnola, C. Capoccia, M. Caponero, D. S. Cardoso, L. G. M. de Carvalho, G. Cavoto, I. Abritta Costa, A. Croce, E. Dan\'e, G. Dho, F. Di Giambattista, E. Di Marco, M. D'Astolfo, G. D'Imperio, D. Fiorina, F. Iacoangeli, Z. Islam, H. P. L. J\`unior, E. Kemp, G. Maccarrone, R. D. Passos Mano, R. R. M. Gregorio, D. J. Gaspar Marques, G. Mazzitelli…

Enhancing the light yield of He:CF$_4$ based gaseous detector
The CYGNO experiment aims to build a large ($\mathcal{O}(10)$ m$^3$) directional detector for rare event searches, such as nuclear recoils (NRs) induced by dark matter (DM), such as weakly interactive massive particles (WIMPs). The detector concept comprises a time projection chamber (TPC), filled with a He:CF$_4$ 60/40 scintillating gas mixture at room temperature and atmospheric pressure, equipped with an amplification stage made of a stack of three gas electron multipliers (GEMs) which are c…