Tanmoy Sarkar: “Graph vertex model”

Z9/0-0 - F1 čajnica (Jamova)

I will present a new approach to studying epithelial mechanics, which is based on representing the tissue structure by a graph. Additionally, I will demonstrate the implementation of this approach within a custom computational framework, neoVM. https://indico.ijs.si/event/1645/

Purushottam Sahu: Neutrinoless double beta decay in a left-right symmetric model with a double seesaw mechanism

https://zoom.us/j/3601731049?pwd=bVNQRjUxU2ExZ0cveWcxYXNUUGdjZz09 (F1 tea room)

We discuss a left-right (L-R) symmetric model with the double seesaw mechanism at the TeV scale generating Majorana masses for the active left-handed (LH) flavour neutrinos$ u_{alpha L}$ and the heavy right-handed (RH) neutrinos $N_{beta R}$, $alpha,beta = e,mu,tau$, which in turn mediate … Read More

Santiago Tanco: Exploring unsupervised top tagging using Bayesian inference

https://zoom.us/j/3601731049?pwd=bVNQRjUxU2ExZ0cveWcxYXNUUGdjZz09 (F1 tea room)

Identifying hadronically decaying top-quark jets in a sample of jets is an important task in many LHC searches. Although there are outstanding supervised algorithms, their construction and expected performance rely on Monte Carlo simulations. After introducing the general framework of … Read More

Ahmed Youssef: MLHAD: A Machine Learning based Simulation for Hadronization

https://zoom.us/j/3601731049?pwd=bVNQRjUxU2ExZ0cveWcxYXNUUGdjZz09 (F1 tea room)

Hadronization, a crucial component of event generation, is traditionally simulated using fine-tuned empirical models. While current phenomenological models have been quite successful overall in simulating this process, there are still areas where they lack accuracy in describing the underlying physics. … Read More