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A common statistical problem in particle physics is to extract the number of samples which originate from a statistical process in an ensemble containing a mix of several contributing processes. The probability density function of each process is usually not exactly known. Barlow and Beeston found an exact likelihood for the problem of fitting binned templates obtained from Monte-Carlo simulation to binned data, which propagates the uncertainty of the templates into the result. Solving the exact likelihood is technically challenging, however. The original paper also did not provide a way to use weighted simulation samples with varying weights. Other papers have introduced alternative likelihoods to address these points. In this paper, a new approximate likelihood is derived from the exact Barlow–Beeston one. The new likelihood is generalized to fits of weighted templates to weighted data. The performance of the new likelihood is evaluated based on toy examples. The performance is excellent – point estimates have small bias and confidence intervals have good coverage – and is comparable to the exact Barlow–Beeston likelihood when the templates are not weighted. The new likelihood evaluates faster than the Barlow–Beeston one when the number of bins is large.

The cosmic-ray database, CRDB, has been gathering cosmic-ray data for the community since 2013. We present a new release, CRDB v4.1, providing many new quantities and data sets, with several improvements made on the code and web interface, and with new visualisation tools. CRDB relies on the MySQL database management system, jquery and table-sorter libraries for queries and sorting, and PHP web pages and AJAX protocol for displays. A REST interface enables user queries from command line or scripts. A new (pip-installable) CRDB python library is developed and extensive jupyter notebook examples are provided. This release contains cosmic-ray dipole anisotropy data, high-energy p ¯ / p upper limits, some unpublished LEE and AESOP lepton time series, many more ultra-high energy data, and a few missing old data sets. It also includes high-precision data from the last three years, in particular the hundreds of thousands AMS-02 and PAMELA data time series (time-dependent plots are now enabled). All these data are shown in a gallery of plots, which can be easily reproduced from the public notebook examples. CRDB contains 316,126 data points from 504 publications, in 4111 sub-experiments from 131 experiments.

IceCube is a cubic-kilometer detector in the deep ice at South Pole. Its square-kilometer surface array, IceTop, is located at 2800 m altitude. IceTop is large and dense enough to cover the cosmic-ray energy spectrum from PeV to EeV energies with a remarkably small systematic uncertainty, thanks to being close to the shower maximum. The experiment offers new insights into hadronic physics of air showers by observing three components: the electromagnetic signal at the surface, GeV muons in the periphery of the showers, and TeV muons in the deep ice. The cosmic-ray flux is measured with the surface signal. The mass composition is extracted from the energy loss of TeV muons observed in the deep ice in coincidence with signals at the surface. The muon lateral distribution is obtained from GeV muons identified in surface signals in the periphery of the shower. The energy spectrum of the most energetic TeV muons is also under study, as well as special events with laterally separated TeV muon tracks which originate from high-pT TeV muons. A combination of all these measurements opens the possibility to perform powerful new tests of hadronic interaction models used to simulate air showers. The latest results will be reviewed from this perspective.

IceCube is a cubic-kilometer detector in the deep ice at South Pole. Its square-kilometer surface array, IceTop, is located at 2800 m altitude. IceTop is large and dense enough to cover the cosmic-ray energy spectrum from PeV to EeV energies with a remarkably small systematic uncertainty, thanks to being close to the shower maximum. The experiment offers new insights into hadronic physics of air showers by observing three components: the electromagnetic signal at the surface, GeV muons in the periphery of the showers, and TeV muons in the deep ice. The cosmic-ray flux is measured with the surface signal. The mass composition is extracted from the energy loss of TeV muons observed in the deep ice in coincidence with signals at the surface. The muon lateral distribution is obtained from GeV muons identified in surface signals in the periphery of the shower. The energy spectrum of the most energetic TeV muons is also under study, as well as special events with laterally separated TeV muon tracks which originate from high-pT TeV muons. A combination of all these measurements opens the possibility to perform powerful new tests of hadronic interaction models used to simulate air showers. The latest results will be reviewed from this perspective.

We present an update on CRDB, the cosmic-ray database for charged species. CRDB is based on MySQL, queried and sorted by jquery and table-sorter libraries, and displayed via PHP web pages through the AJAX protocol. We review the modifications made on the structure and outputs of the database since the first release (Maurin et al., 2014). For this update, the most important feature is the inclusion of ultra-heavy nuclei (Z>30), ultra-high energy nuclei (from 1015 to 1020 eV), and limits on antinuclei fluxes (Z≤−1 for A>1); more than 100 experiments, 350 publications, and 40,000 data points are now available in CRDB. We also revisited and simplified how users can retrieve data and submit new ones. For questions and requests, please contact crdb@lpsc.in2p3.fr.

The LHCb experiment is designed to study flavor physics of b and c quarks. The detector is optimized for the study of identified hadrons produced in the forward direction, which also makes LHCb very interesting for the understanding of cosmic-ray induced air showers. LHCb is analysing proton-proton, protonlead, and lead-lead collisions. As a unique feature, LHCb is also studying beam interactions with noble gases using its SMOG system. We present recent measurements of charmed mesons, which are used to obtain production cross-sections, to constrain the parton PDF, to test pomeron and multi-particle interactions, nuclear and collective effects. These mostly have an indirect impact on the modeling of hadronic interactions. Finally, we present a direct measurement of the anti-proton production in proton collisions with helium gas, which are important for the understanding of AMS-02 and PAMELA data.

The LHCb experiment is designed to study flavor physics of b and c quarks. The detector is optimized for the study of identified hadrons produced in the forward direction, which also makes LHCb very interesting for the understanding of cosmic-ray induced air showers. LHCb is analysing proton-proton, protonlead, and lead-lead collisions. As a unique feature, LHCb is also studying beam interactions with noble gases using its SMOG system. We present recent measurements of charmed mesons, which are used to obtain production cross-sections, to constrain the parton PDF, to test pomeron and multi-particle interactions, nuclear and collective effects. These mostly have an indirect impact on the modeling of hadronic interactions. Finally, we present a direct measurement of the anti-proton production in proton collisions with helium gas, which are important for the understanding of AMS-02 and PAMELA data.

Boost.Histogram, a header-only C++14 library that provides multidimensional histograms and profiles, became available in Boost 1.70. It is extensible, fast, and uses modern C++ features. Using template metaprogramming, the most efficient code path for any given configuration is automatically selected. The library includes key features designed for the particle physics community, such as optional under- and overflow bins, weighted increments, reductions, growing axes, thread-safe filling, and memory-efficient counters with high-dynamic range. Python bindings for Boost.Histogram are being developed in the Scikit-HEP project to provide a fast, easy-to-install package as a backend for other Python libraries and for advanced users to manipulate histograms. Versatile and efficient histogram filling, effective manipulation, multithreading support, and other features make this a powerful tool. This library has also driven package distribution efforts in Scikit-HEP, allowing binary packages hosted on PyPI to be available for a very wide variety of platforms. Two other libraries fill out the remainder of the Scikit-HEP Python histogramming effort. Aghast is a library designed to provide conversions between different forms of histograms, enabling interaction between histogram libraries, often without an extra copy in memory. This enables a user to make a histogram in one library and then save it in another form, such as saving a Boost.Histogram in ROOT. And Hist is a library providing friendly, analyst-targeted syntax and shortcuts for quick manipulations and fast plotting using these two libraries.

Scikit-HEP is a community-driven and community-oriented project with the goal of providing an ecosystem for particle physics data analysis in Python. Scikit-HEP is a toolset of approximately twenty packages and a few “affiliated” packages. It expands the typical Python data analysis tools for particle physicists. Each package focuses on a particular topic, and interacts with other packages in the toolset, where appropriate. Most of the packages are easy to install in many environments; much work has been done this year to provide binary “wheels” on PyPI and conda-forge packages. The Scikit-HEP project has been gaining interest and momentum, by building a user and developer community engaging collaboration across experiments. Some of the packages are being used by other communities, including the astroparticle physics community. An overview of the overall project and toolset will be presented, as well as a vision for development and sustainability.

High-energy cosmic rays are observed indirectly by detecting the extensive air showers initiated in Earth’s atmosphere. The interpretation of these observations relies on accurate models of air shower physics, which is a challenge and an opportunity to test QCD under extreme conditions. Air showers are hadronic cascades, which give rise to a muon component through hadron decays. The muon number is a key observable to infer the mass composition of cosmic rays. Air shower simulations with state-of-the-art QCD models show a significant muon deficit with respect to measurements; this is called the Muon Puzzle. By eliminating other possibilities, we conclude that the most plausible cause for the muon discrepancy is a deviation in the composition of secondary particles produced in high-energy hadronic interactions from current model predictions. The muon discrepancy starts at the TeV scale, which suggests that this deviation is observable at the Large Hadron Collider. An enhancement of strangeness production has been observed at the LHC in high-density events, which can potentially explain the puzzle, but the impact of the effect on forward produced hadrons needs further study, in particular with future data from oxygen beam collisions.