Model discrimination in pseudoscalar-meson photoproduction

To learn about a physical system of interest, experimental results must be able to discriminate among models. We introduce a geometrical measure to quantify the distance between models for pseudoscalar-meson photoproduction in amplitude space. Experimental observables, with finite precision, map to probability distributions in amplitude space, and the characteristic width scale of such distributions needs to be smaller than the distance between models if the observable data are going to be useful. We therefore also introduce a method for evaluating probability distributions in amplitude space that arise as a result of one or more measurements, and show how one can use this to determine what further measurements are going to be necessary to be able to discriminate among models

Interpretable machine learning for inferring the phase boundaries in a nonequilibrium system

Still under debate is the question of whether machine learning is capable of going beyond black-box modeling for complex physical systems. We investigate the generalizing and interpretability properties of learning algorithms. To this end, we use supervised and unsupervised learning to infer the phase boundaries of the active Ising model, starting from an ensemble of configurations of the system. We illustrate that unsupervised learning techniques are powerful at identifying the phase boundaries in the control parameter space, even in situations of phase coexistence. It is demonstrated that supervised learning with neural networks is capable of learning the characteristics of the phase diagram, such that the knowledge obtained at a limited set of control variables can be used to determine the phase boundaries across the phase diagram. In this way, we show that properly designed supervised learning provides predictive power to regions in the phase diagram that are not included in the training phase of the algorithm. We stress the importance of introducing interpretability methods in order to perform a physically relevant classification of the phases with deep learning

Amplitude analysis and the nature of the Zc(3900)

The microscopic nature of the XYZ states remains an unsettled topic. We show how a thorough amplitude analysis of the data can help constraining models of these states. Specifically, we consider the case of the Zc(3900) peak and discuss possible scenarios of a QCD state, virtual state, or a kinematical enhancement. We conclude that current data are not precise enough to distinguish between these hypotheses, however, the method we propose, when applied to the forthcoming high-statistics measurements should shed light on the nature of these exotic enhancements.Comment: 14 pages, 10 figures, 3 tables. Version accepted for publication on Phys.Lett.

On the η\eta and η′\eta' Photoproduction Beam Asymmetry at High Energies

We show that, in the Regge limit, beam asymmetries in $\eta$ and $\eta'$ photoproduction are sensitive to hidden strangeness components. Under reasonable assumptions about the couplings we estimate the contribution of the $\phi$ Regge pole, which is expected to be the dominant hidden strangeness contribution. The ratio of the asymmetries in $\eta'$ and $\eta$ production is estimated to be close to unity in the forward region $0 < -t/\text{GeV}^2 \leq 1$ at the photon energy $E_\text{lab} = 9$~GeV, relevant for the upcoming measurements at Jefferson Lab.Comment: 9 pages, 4 figure

Structure of Pion Photoproduction Amplitudes

We derive and apply the finite energy sum rules to pion photoproduction. We evaluate the low energy part of the sum rules using several state-of-the-art models. We show how the differences in the low energy side of the sum rules might originate from different quantum number assignments of baryon resonances. We interpret the observed features in the low energy side of the sum rules with the expectation from Regge theory. Finally, we present a model, in terms of a Regge-pole expansion, that matches the sum rules and the high-energy observables.Comment: 19 pages, 15 figures and 4 table

Analyticity constraints for hadron amplitudes : going high to heal low energy issues

Analyticity constitutes a rigid constraint on hadron scattering amplitudes. This property is used to relate models in different energy regimes. Using meson photoproduction as a benchmark, we show how to test contemporary low-energy models directly against high-energy data. This method pinpoints deficiencies of the models and treads a path to further improvement. The implementation of this technique enables one to produce more stable and reliable partial waves for future use in hadron spectroscopy and new physics searches

Finite-Energy Sum Rules in Eta Photoproduction off the Nucleon

The reaction ${\gamma}N \to {\eta}N$ is studied in the high-energy regime (with photon lab energies $E_{\gamma}^{\textrm{lab}} > 4$ GeV) using information from the resonance region through the use of finite-energy sum rules (FESR). We illustrate how analyticity allows one to map the t-dependence of the unknown Regge residue functions. We provide predictions for the energy dependence of the beam asymmetry at high energies.Comment: Joint Physics Analysis Cente