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Working Group Albrecht Junior Group Mitzel
Department of Physics
A lecture in the Audimax © Oliver Schaper​/​TU Dortmund
Particle physics

LHCb QCD & astroparticle physics

Cosmic-ray flux and its composition, as measured by multiple experiments [1].
Fig. 1: Cosmic-ray flux and its composition, as measured by multiple experiments [1].

In the QCD effective cross sections subgroup for astroparticle physics, led by Dr. Hans Dembinski, we measure the production cross sections of identified long-lived hadrons in minimum-bias collisions, which are needed to tune soft QCD models used in air shower simulations and to understand the anomaly of muon production in air showers.

In astroparticle physics, the extreme non-thermal universe is studied using messenger particles: Gamma rays, neutrinos and cosmic rays. Cosmic rays are high-energy nuclei, typically in the range of hydrogen to iron. Cosmic rays are the most energetic particles ever observed. Their sources are still largely unknown because they are randomly scattered in interstellar and intergalactic magnetic fields.

High-energy cosmic rays with energies above 100 TeV are detected indirectly via air showers. The properties of cosmic rays (energy, mass, direction) can be derived from the air shower, but this requires accurate simulations of the QCD interactions in the shower. When comparing results based on muon production in air showers with results based on the depth of the shower maximum, the Pierre Auger Observatory [2-5], IceCube [6] and other experiments [7,8] have found discrepancies between simulated muon production in air showers and actual production. This anomaly is known as the muon enigma.

Predicted muon production as function of depth of the shower maximum for cosmic nuclei from proton to iron (lines) and Auger data point [1].
Fig. 2: Predicted muon production as function of depth of the shower maximum for cosmic nuclei from proton to iron (lines) and Auger data point [1].

The most likely explanation [1] for the anomalous muon production is an increased production of hadrons and baryons with strange quarks in the forward region, which would reduce the so-called R-factor, the ratio of energy in neutral pions relative to energy in other hadrons (see Fig. 2). An unexpectedly high production of strange quarks as a function of the density of charged particles in the collision has already been observed in collisions at the LHC [9,10], but the R-factor in the forward production, which is crucial for air showers, is not yet precisely known. In this subgroup, we measure production cross sections of prompt long-lived hadrons in collisions that mimic those in air showers, and determine the R-factor and ultimately solve the anomaly around muon production.

An introductory talk about the muon puzzle appeared in the series "Faszination Astronomie Online" and can be watched on YouTube.

Spectra of identified prompt charged particles

We analyse the spectra of prompt charged pions, kaons and protons in proton-proton collisions at 13 TeV and proton-lead collisions at 8.16 TeV. This is a continuation of Ref [11], in which the spectra of prompt unidentified charged particles were measured. Particle identification in LHCb is based on measurements from the RICH detectors. The detector response is modelled with a neural network that has been trained using control measurements. The challenge for a precision measurement lies in the accurate modelling of this detector response. From the result, we gain valuable information about the R-factor.

Strangeness and baryon production cross-sections

We study the φ-production cross section in proton-proton collisions at 13 TeV via the decay φ → Κ⁺Κ⁻, as a continuation of earlier studies by the Dortmund group at 7 TeV. A new feature is to measure the dependence of the production cross section on the density of the charged particles produced in the collision. From this, we also gain information on the R factor, since the φ-production is proportional to the production of strange quarks.

We also investigate the K⁰/Λ ratio in the upcoming proton-proton collisions at 14 TeV in Run 3 via the decays K⁰ → π⁺π⁻ and Λ → pπ⁻. The analysis of φ-production will also be extended to Run 3. The decays of K⁰, Λ, and φ are ideal for an early measurement with the newly improved LHCb detector, as these decays are frequent and can be measured well due to their kinematics, even if the detector is not yet optimally calibrated. The measurement provides valuable data on the meson/baryon ratio, which is also included in the R-factor.

Furthermore, we investigate the production of strange quarks during collisions of the LHC beams with a gas target. Here, small amounts of gas are introduced into the vacuum of the LHCb detector, and the LHC beams collide with the gas. The main interest is in proton-oxygen (gas) collisions, which are planned for Run 3, and accurately mimic interactions of cosmic rays with air. The current work focuses on the previously recorded proton-helium(gas) and proton-neon(gas) data during Run 2, which can be used to interpolate towards proton-oxygen(gas).

Precision luminosity measurements

To measure absolute production cross sections, the luminosity of the LHC beams must be determined precisely. Measurements of the luminosity at LHCb are led by Dr. Elena Dall'Occo. We are using van der Meer and emittance scans in Run 3 to improve the previous record of 1.16% uncertainty in LHCb for proton-proton collisions at 8 TeV. The new PLUME detector [12] plays a crucial role in this, with which luminosity is measured accurately even during normal data taking. The previous analysis software is also being ported from the R language to the more familiar Python language and expanded.

Statistical methods and analysis software

The subgroup is actively developing software and new statistical methods used in LHCb and beyond. Dr. Hans Dembinski was convener of the Statistics and Machine Learning Working Group in LHCb and is member of the Scikit-HEP project and the Boost C++ project. He contributes to the Python scientific stack (matplotlib and scipy) and to CERN’s ROOT framework. A few highlights:

References

 

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