Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userUsing Machine Learning techniques in phenomenological studies in flavour physics
190
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
An updated analysis of New Physics violating Lepton Flavour Universality, by using the Standard Model Effective Field Lagrangian with semileptonic dimension six operators at $Lambda = 1,mathrm{TeV}$ is presented. We perform a global fit, by discussing the relevance of the mixing in the first generation. We use for the first time in this context a Montecarlo analysis to extract the confidence intervals and correlations between observables. Our results show that machine learning, made jointly with the SHAP values, constitute a suitable strategy to use in this kind of analysis.
rate research
Read More
LHCb found hints for physics beyond the Standard Model (SM) in $Bto K^*mu^+mu^-$, $R(K)$ and $B_stophimu^+mu^-$. These intriguing hints for NP have recently been confirmed by the LHCb measurement of $R(K^*)$ giving a combined significance for NP above the $5,sigma$ level. In addition, the BABAR, BELLE and LHCb results for $Bto D^{(*)}tau u$ also point towards lepton flavour universality (LFU) violating new physics (NP). Furthermore, there is the long-standing discrepancy between the measurement and the theory prediction of the anomalous magnetic moment of the muon ($a_mu$) at the $3,sigma$ level. Concerning NP effects, $bto smu^+mu^-$ data can be naturally explained with a new neutral gauge bosons, i.e. a $Z^prime$ but also with heavy new scalars and fermions contributing via box diagrams. Another promising solution to $bto smu^+mu^-$, which can also explain $Bto D^{(*)}tau u$, are leptoquarks. Interestingly, leptoquarks provide also a viable explanation of $a_mu$ which can be tested via correlated effects in $Ztomu^+mu^-$ at future colliders. Considering leptoquark models, we show that an explanation of $Bto D^{(*)}tau u$ predicts an enhancement of $bto stau^+tau^-$ processes by around three orders of magnitude compared to the SM. In case of a simultaneous explanation of $Bto D^{(*)}tau u$ and $bto smu^+mu^-$ data, sizable effects in $bto staumu$ processes are predicted.
Disruption prediction and mitigation is of key importance in the development of sustainable tokamakreactors. Machine learning has become a key tool in this endeavour. In this paper multiple machinelearning models will be tested and compared. A particular focus has been placed on their portability.This describes how easily the models can be used with data from new devices. The methods used inthis paper are support vector machine, 2-tiered support vector machine, random forest, gradient boostedtrees and long-short term memory. The results show that the support vector machine performanceis marginally better among the standard models, while the gradient boosted trees performed the worst.The portable variant of each model had lower performance. Random forest obtained the highest portableperformance. Results also suggest that disruptions can be detected as early as 600ms before the event.An analysis of the computational cost showed all models run in less than 1ms, allowing sufficient timefor disruption mitigation.
Several experiments observed deviations from the Standard Model (SM) in the flavour sector: LHCb found a $4-5,sigma$ discrepancy compared to the SM in $bto smu^+mu^-$ transitions (recently supported by an Belle analysis) and CMS reported a non-zero measurement of $htomutau$ with a significance of $2.4,sigma$. Furthermore, BELLE, BABAR and LHCb founds hints for the violation of flavour universality in $Bto D^{(*)}tau u$. In addition, there is the long-standing discrepancy in the anomalous magnetic moment of the muon. Interestingly, all these anomalies are related to muons and taus, while the corresponding electron channels seem to be SM like. This suggests that these deviations from the SM might be correlated and we briefly review some selected models providing simultaneous explanations.
We give a brief introduction to flavour physics. The first part covers the flavour structure of the Standard Model, how the Kobayashi-Maskawa mechanism is tested and provides examples of searches for new physics using flavour observables, such as meson mixing and rare decays. In the second part we give a brief overview of the recent flavour anomalies and how the Higgs can act as a new flavour probe.
The determination of the fundamental parameters of the Standard Model (and its extensions) is often limited by the presence of statistical and theoretical uncertainties. We present several models for the latter uncertainties (random, nuisance, external) in the frequentist framework, and we derive the corresponding $p$-values. In the case of the nuisance approach where theoretical uncertainties are modeled as biases, we highlight the important, but arbitrary, issue of the range of variation chosen for the bias parameters. We introduce the concept of adaptive $p$-value, which is obtained by adjusting the range of variation for the bias according to the significance considered, and which allows us to tackle metrology and exclusion tests with a single and well-defined unified tool, which exhibits interesting frequentist properties. We discuss how the determination of fundamental parameters is impacted by the model chosen for theoretical uncertainties, illustrating several issues with examples from quark flavour physics.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
