### Conveners

#### Analysis tools: Session 1

- Fabrizio Parodi (Istituto Nazionale di Fisica Nucleare)
- Mikhail Mikhasenko (ORIGINS Excellence Cluster)

#### Analysis tools: Session 2

- Cesar Fernandez-Ramirez (UNED/ICN-UNAM)
- Ryan Mitchell (Indiana University)

#### Analysis tools: Session 3

- Mikhail Mikhasenko (ORIGINS Excellence Cluster)
- Ryan Mitchell (Indiana University)

#### Analysis tools: Session 4

- Cesar Fernandez-Ramirez (UNED/ICN-UNAM)
- Fabrizio Parodi (Istituto Nazionale di Fisica Nucleare)

with a focus on Machine Learning (ML) based optimizations of the TPC dE/dx response

Femtoscopy is a powerful technique to relate correlations between particles with low relative momentum to the emission source and the final state interaction (FSI). Recent research by the ALICE collaboration has demonstrated the realization of a common baryon-baryon emission source in pp collisions, opening up new avenues for studying the properties of the FSI. The well-constrained source...

Amplitude analysis is a powerful method for studying the intermediate processes of particle decays. However, considering the full kinematics, it can be a complex task that requires a deep understanding of particle physics. With the high statistics data provided by BESIII, analyzing this data simply and efficiently is a significant challenge. In this talk, we will provide a review of the...

The large heavy-flavor dataset collected by the LHCb experiment offers a good opportunity to investigate the inner structure of hadrons and help improve the knowledge of strong interactions. With the ever larger data samples collected by LHCb, constant improvements of analysis methods are in demand, including for example computing techniques and phenomenological tools to handle the huge data...

Recently, the LHCb collaboration has computed the *aligned polarimeter vector field* for the dominant hadronic decay mode of the $\Lambda_c$ baryon (arXiv:2301.07010). The polarimeter vector field is a model-independent representation of the decay rate for polarized decays that can be used to measure polarisation and to improve the sensitivity of amplitude...

Two-particle angular correlation is one of the most powerful tools to study the mechanism of particle production in pp collision systems by relating the difference between the azimuthal angle ($\Delta\varphi$) and the rapidity ($\Delta$y) of a pair of particles. Hadronization processes are influenced by various physical phenomena, such as resonance decays, Coulomb interactions, laws of...

COMPASS aims at extracting the excitation spectrum of light and strange mesons in diffractive scattering. Resonances are identified through partial wave analysis, which inherently relies on analysis models. Besides statistical uncertainties, systematic effects connected to the analysis methods are a key challenge. We will discuss some sources of systematics connected to $\pi^-\pi^-\pi^+$ and...

Mathematical ambiguities in partial wave analyses cause unavoidable problems in interpreting data from scattering experiments. These ambiguities appear as distinct sets of partial waves which can describe the same experimental data. In principle, these ambiguities may be resolved by leveraging knowledge about the physics of the process of interest, or by enforcing additional constraints. We...

The talk will summarize and relate different ideas from the field of complete-experiment analyses, both for full spin-amplitudes and for partial waves, for the illustrative example of single pseudoscalar-meson photoproduction. Then, the notion of a complete experiment as a minimal set of measurements sufficient to predict all other possible experiments will be reinterpreted using modern...

New models for photoproduction of kaons on the proton were constructed [1] utilizing new experimental data from LEPS, GRAAL, and particularly CLAS collaborations. The higher spin nucleon (spin-3/2 and spin-5/2) and hyperon (spin-3/2) resonances were included using a consistent formalism and they were found to play an important role in the data description. In order to account for the unitarity...

The data published by the Particle Data Group (PDG) in the Review of Particle Physics has traditionally been made available to the HEP community and beyond as a biennial publication in a scientific journal, in print as the PDG Book and the Particle Physics Booklet, and more recently primarily via the PDG website and the interactive pdgLive web application. Except for a number of data files...

Machine learning techniques have become very powerful and practical tools not only in our daily life but also in scientific research. We have performed several developments of machine learning models to study light hypernuclei, especially hypertriton, $^4_{\Lambda }$H and an nn$\Lambda $ state. We have developed a complex of analysis methods for analyzing the J-PARC E07 nuclear emulsion data...

A densely connected feed-forward neural network is capable to classify poles of scattering matrix if fed with experimentally measured values of energy-dependent production intensity. As shown in [1], such a neural network trained with synthetic differential intensities calculated with scattering length approximated amplitudes classifies the $P_c$(4312) signal as a virtual state located at the...

We present an approach that allows one to obtain information on the compositeness of molecular states from combined information of the scattering length of the hadronic components, the effective range, and the binding energy. We consider explicitly the range of the interaction in the formalism and show it to be extremely important to improve on the formula of Weinberg obtained in the limit of...

From unitarized chiral perturbation theory analyses, the structure of $D^*_0(2300)$ and $D_1(2430)$ can be understood as the interplay of two poles, corresponding to two scalar/axial-vector isospin doublet states with different SU(3) flavor content. These states emerge from non-perturbative dynamics of $D$ mesons scattering off the Goldstone boson octet. This two pole picture solves various...

Analysis techniques based on statistical learning algorithms such as artificial neural networks or decision trees are known to offer significant improvements in the analysis of large samples of data. Belle II developed and implements a variety of such algorithms in several aspects of physics analysis including online event selection, beam-background prediction, identification of collisions...