This brief review is dedicated to the memory of Maxim V. Polyakov and his pioneering contributions to pentaquark physics. We focus on his seminal 1997 work with Diakonov and Petrov that predicted the ${\mit \Theta }^+$ pentaquark, a breakthrough that initiated an intense period of research in hadron physics. The field faced a significant setback when the CLAS Collaboration at Jefferson Lab reported null results in 2006, leading to a dramatic decline in light-pentaquark research. Nevertheless, Maxim maintained his scientific conviction, supported by continued positive signals from the DIANA and LEPS collaborations. Through recent experimental findings on the ${\mit \Theta }^+$ and the nucleon-like resonance $N^*(1685)$, we examine how Polyakov’s theoretical insights, particularly the prediction of a narrow width (${\mit \Gamma } \approx 0.5$–$1.0$ MeV), remain relevant to our understanding of the ${\mit \Theta }^+$ light pentaquark. Abstract Published by the Jagiellonian University 2025 authors

South Korea

H.-Ch. Kim

Pentaquarks and Maxim V. Polyakov

During the public Kaggle competition “IceCube – Neutrinos in Deep Ice”, thousands of reconstruction algorithms were created and submitted, aiming to estimate the direction of neutrino events recorded by the IceCube detector. Here we describe in detail the three ultimate best, award-winning solutions. The data handling, architecture, and training process of each of these machine learning models is laid out, followed up by an in-depth comparison of the performance on the Kaggle datatset. We show that on cascade events in IceCube above 10 TeV, the best Kaggle solution is able to achieve an angular resolution of better than 5 $$^{\circ }$$  <math> <mmultiscripts> <mrow></mrow> <mrow></mrow> <mo>∘</mo> </mmultiscripts> </math>  , and for tracks correspondingly better than 0.5 $$^{\circ }$$  <math> <mmultiscripts> <mrow></mrow> <mrow></mrow> <mo>∘</mo> </mmultiscripts> </math>  . These results indicate that the Kaggle solutions perform at a level comparable to the current state-of-the-art in the field, and that they may even be able to outperform existing reconstruction resolutions for certain types of events.