BM@N (Baryonic Matter at the Nuclotron) is the fixed target experiment aimed to study nuclear matter in the relativistic heavy ion collisions at the Nuclotron accelerator in JINR. Detectors based on Gas Electron multipliers (GEM) have been identified as appropriate for the BM@N tracking system, which is located inside the BM@N analyzing magnet. The structure of the GEM detectors and the results of study of their characteristics are presented. The GEM detectors are integrated into the BM@N experimental setup and data acquisition system. The performance of the GEM tracking system in the first technical run with the deuteron beam is shortly reviewed.
One of the most important problems of data processing in high energy and nuclear physics is the event reconstruction. Its main part is the track reconstruction procedure which consists in looking for all tracks that elementary particles leave when they pass through a detector among a huge number of points, so-called hits, produced when flying particles fire detector coordinate planes. Unfortunately, the tracking is seriously impeded by the famous shortcoming of multiwired, strip in GEM detectors due to the appearance in them a lot of fake hits caused by extra spurious crossings of fired strips. Since the number of those fakes is several orders of magnitude greater than for true hits, one faces with the quite serious difficulty to unravel possible track-candidates via true hits ignoring fakes. On the basis of our previous two-stage approach based on hits preprocessing using directed K-d tree search followed by a deep neural classifier we introduce here two new tracking algorithms. Both algorithms combine those two stages in one while using different types of deep neural nets. We show that both proposed deep networks do not require any special preprocessing stage, are more accurate, faster and can be easier parallelized. Preliminary results of our new approaches for simulated events are presented.
The shift ∆E of a maxon-roton 4 He excitation spectrum E via the 3 He admixture is considered theoretically. The Bogoliubov formula for E(ρ, g) as a function of Bose-condensate density ρ and of 4 He/ 4 He interaction g is used as an element of partition function formalism of the whole system, presented in the form of a path (functional) integral. The dependence of ρ on g, 4 He/ 3 He interaction λ as well as on the pressure P , induced by the 3 He admixture, is taken into account. The new model of g, suitable for analytical calculations, is used for a description of a change of P within the constant volume. The cases of positive and negative shifts are found as the result of competition between interactions g and λ.
Tracking is an important task in the field of High Energy physics. Modern experiments produceenormous amounts of data, and classical tracking algorithms cannot reach required computingefficiency. This lead to the need to develop new methods, some of them use neural network models.In our work we present modifications of previously developed model, TrackNetV2. This model and itsdescendants showed great results for Monte-Carlo simulations of experiments with microstrip-basedGEM detectors: BESIII and BM@N RUN6. In this work we adapt it to more complex scenario forBM@N RUN7. The work showed limitations in architecture and training procedure, which arereworked later.
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