PELICAN: Permutation Equivariant and Lorentz Invariant or Covariant Aggregator Network for Particle Physics

Many current approaches to machine learning in particle physics use generic architectures that require large numbers of parameters and disregard underlying physics principles, limiting their applicability as scientific modeling tools. In this work, we present a machine learning architecture that uses a set of inputs maximally reduced with respect to the full 6-dimensional Lorentz symmetry, and is fully permutation-equivariant throughout. We study the application of this network architecture to the standard task of top quark tagging and show that the resulting network outperforms all existing competitors despite much lower model complexity. In addition, we present a Lorentz-covariant variant of the same network applied to a 4-momentum regression task

Analyzing technology acceptance and perception of privacy in ambient assisted living for using sensor-based technologies

People increasingly use various technologies that enable them to ease their everyday lives in different areas. Not only wearable devices are gaining ground, but also sensor-based ambient devices and systems are increasingly perceived as beneficial in supporting users. Especially older and/or frail persons can benefit from the so-called lifelogging technologies assisting the users in different activities and supporting their mobility and autonomy. This paper empirically investigates users' technology acceptance and privacy perceptions related to sensor-based applications implemented in private environments (i.e., passive infrared sensors for presence detection, humidity and temperature sensors for ambient monitoring, magnetic sensors for user-furniture interaction). For this purpose, we designed an online survey entitled "Acceptance and privacy perceptions of sensor-based lifelogging technologies"and collected data from N = 312 German adults. In terms of user acceptance, statistical analyses revealed that participants strongly agree on the benefits of such sensorbased ambient technologies, also perceiving these as useful and easy to use. Nevertheless, their intention to use the sensor-based applications was still rather limited. The evaluation of privacy perceptions showed that participants highly value their privacy and hence require a high degree of protection for their personal data. The potential users assessed the collection of data especially in the most intimate spaces of domestic environments, such as bathrooms and bedrooms, as critical. On the other hand, participants were also willing to provide complete data transparency in case of an acute risk to their health. Our results suggest that users' perceptions of personal privacy largely affect the acceptance and successful adoption of sensor-based lifelogging in home environments

Explainable Equivariant Neural Networks for Particle Physics: PELICAN

PELICAN is a novel permutation equivariant and Lorentz invariant or covariant aggregator network designed to overcome common limitations found in architectures applied to particle physics problems. Compared to many approaches that use non-specialized architectures that neglect underlying physics principles and require very large numbers of parameters, PELICAN employs a fundamentally symmetry group-based architecture that demonstrates benefits in terms of reduced complexity, increased interpretability, and raw performance. We present a comprehensive study of the PELICAN algorithm architecture in the context of both tagging (classification) and reconstructing (regression) Lorentz-boosted top quarks, including the difficult task of specifically identifying and measuring the $W$-boson inside the dense environment of the Lorentz-boosted top-quark hadronic final state. We also extend the application of PELICAN to the tasks of identifying quark-initiated vs.~gluon-initiated jets, and a multi-class identification across five separate target categories of jets. When tested on the standard task of Lorentz-boosted top-quark tagging, PELICAN outperforms existing competitors with much lower model complexity and high sample efficiency. On the less common and more complex task of 4-momentum regression, PELICAN also outperforms hand-crafted, non-machine learning algorithms. We discuss the implications of symmetry-restricted architectures for the wider field of machine learning for physics.Comment: 52 pages, 34 figures, 12 table

Resonances in the three-neutron system

A study of 3-body resonances has been performed in the framework of configuration space Faddeev equations. The importance of keeping a sufficient number of terms in the asymptotic expansion of the resonance wave function is pointed out. We investigated three neutrons interacting in selected force components taken from realistic nn forces.Comment: 38 pages, 11 tables, 4 figure

Use of CRISTA mesopause region temperatures for the intercalibration of gound-based instruments

Most available ground-based (GB) techniques for measuring temperatures in the upper mesosphere to lower thermosphere (or mesopause region) have systematic errors that are comparable to those of orbiting instruments. Determining these unknown biasses would normally require colocated observations that are only seldom feasible. Satellite measurements can be used as a ‘‘transfer standard’’ between GB observations that are not colocated. In this context, even with a reproducible or known bias in the satellite data, the comparison is still meaningful. Since Cryogenic Infrared Spectrometers and Telescopes for the Atmosphere (CRISTA) temperatures cover the mesopause region with very good accuracy (statistical errors do not exceed 1.5 K and systematic uncertainties range from about 3–7.5 K), they are quite suitable for this purpose. Because of the nearly constant precision over the height range of interest, also rotational temperatures of airglow emissions from different altitudes like the OH and O2 bands (or the OI 558 nm line) can be successfully compared with each other. In spite of the limited number of overpasses during the relatively short CRISTA missions, the feasibility of such an intercalibration is demonstrated for widely separated GB sites. Here, the results obtained for GB measurements at eight different sites, using CRISTA-1 and CRISTA-2 data, are presented. For OH temperatures, the standard deviation between the different instruments is only 5.4 K, confirming previous estimates.Fil: Scheer, Jurgen. Consejo Nacional de Investigaciónes Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; ArgentinaFil: Reisin, Esteban Rodolfo. Consejo Nacional de Investigaciónes Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; ArgentinaFil: Gusev, O. A.. University of Wuppertal; AlemaniaFil: French, W. J. R.. Australian Antarctic Division; AustraliaFil: Hernandez, G.. University of Washington; Estados UnidosFil: Huppi, R.. State University Of Utah; Estados UnidosFil: Ammosov, P.. Institute of Cosmophysical Research and Aeronomy; RusiaFil: Gavrilyeva, G. A.. Institute of Cosmophysical Research and Aeronomy; RusiaFil: Offermann, D.. University of Wuppertal; Alemani

Indications for the Nonexistence of Three-Neutron Resonances near the Physical Region

The pending question of the existence of three-neutron resonances near the physical energy region is reconsidered. Finite rank neutron-neutron forces are used in Faddeev equations, which are analytically continued into the unphysical energy sheet below the positive real energy axis. The trajectories of the three-neutron S-matrix poles in the states of total angular momenta and parity J^\pi=1/2 +- and J^\pi= 3/2 +- are traced out as a function of artificial enhancement factors of the neutron-neutron forces. The final positions of the S-matrix poles removing the artificial factors are found in all cases to be far away from the positive real energy axis, which provides a strong indication for the nonexistence of nearby three-neutron resonances. The pole trajectories close to the threshold E=0 are also predicted out of auxiliary generated three-neutron bound state energies using the Pad\'e method and agree very well with the directly calculated ones.Comment: 20 pages, 7 Postscript figures, fig.1 is corrected, uses relax.st

The f_LT Response Function of D(e,e'p)n at Q^2=0.33(GeV/c)^2

The interference response function f_LT (R_LT) of the D(e,e'p)n reaction has been determined at squared four-momentum transfer Q^2 = 0.33 (GeV/c)^2 and for missing momenta up to p_miss= 0.29 (GeV/c). The results have been compared to calculations that reproduce f_LT quite well but overestimate the cross sections by 10 - 20% for missing momenta between 0.1 (GeV/c) and 0.2 (GeV/c) .Comment: 12 Pages, 10 figure

Consistent alpha-cluster description of the 12C (0^+_2) resonance

The near-threshold 12C (0^+_2) resonance provides unique possibility for fast helium burning in stars, as predicted by Hoyle to explain the observed abundance of elements in the Universe. Properties of this resonance are calculated within the framework of the alpha-cluster model whose two-body and three-body effective potentials are tuned to describe the alpha - alpha scattering data, the energies of the 0^+_1 and 0^+_2 states, and the 0^+_1-state root-mean-square radius. The extremely small width of the 0^+_2 state, the 0_2^+ to 0_1^+ monopole transition matrix element, and transition radius are found in remarkable agreement with the experimental data. The 0^+_2-state structure is described as a system of three alpha-particles oscillating between the ground-state-like configuration and the elongated chain configuration whose probability exceeds 0.9

What factors influence training opportunities for older workers? Three factorial surveys exploring the attitudes of HR professionals

The core research questions addressed in this paper are: what factors influence HR professionals in deciding whether to approve training proposals for older workers? What kind of training are they more likely to recommend for older employees and in which organizational contexts? We administered three factorial surveys to 66 HR professionals in Italy. Participants made specific training decisions based on profiles of hypothetical older workers. Multilevel analyses indicated that access to training decreases strongly with age, while highly-skilled older employees with low absenteeism rates are more likely to enjoy training opportunities. In addition, older workers displaying positive performance are more likely to receive training than older workers who perform poorly, suggesting that training late in working life may serve as a reward for good performance rather than as a means of enhancing productivity. The older the HR professional evaluating training proposals, the higher the probability that older workers will be recommended for training. keywords: training; older workers; HR professionals; factorial survey; multilevel model