# Neural-Network-Based Quark-Gluon Plasma Trigger for the CBM Experiment at FAIR
## 1 Introduction  
The upcoming heavy-ion physics experiment on compressed baryonic matter (CBM) at the Facility for Antiproton and Ion Research (FAIR) [1] is a fixed-target experiment designed to operate at extraordinarily high interaction rates. The combination of high-intensity beams with a high-rate detector system and a long beam time creates unparalleled conditions for the study of quantum chromodynamics (QCD) matter at the highest net-baryon densities achievable in a laboratory setting [2]. One of the main objectives of the CBM experiment is to explore the quark-gluon plasma (QGP) and its thermodynamic properties. The thermodynamic properties of a QCD system are expressed in terms of a \((T,\mu_{B})\) phase diagram, where \(T\) is the temperature and \(\mu_{B}\) is the baryonic chemical potential. The exploration of this complex phase diagram is still in its early stages. In particular, the high baryon-chemical potential region, marked by (\(\mu_{B}>500\) MeV), is of significant interest. Engineered as a multipurpose tool, the CBM experiment will have the ability to detect hadrons, electrons, and muons in both elementary nucleon and heavy-ion collisions in the entire FAIR beam energy range. To execute high-precision, multi-differential measurements of rare processes, the experiment is designed to run at event rates from 100 kHz up to10 MHz for several months annually [3]. Since it is challenging to generate a simple trigger signal for weakly decaying particles like hyperons and D-mesons, each event must be fully reconstructed. Furthermore, the decay topology needs to be identified online through fast algorithms. These algorithms will operate on a high-performance computing farm located at the GSI Green Cube [4]. At the planned CBM interaction rate of 10 MHz, one expects a data output rate of up to 1 TB/s from the detector's front-end electronics [5]. In order to optimize the storage cost, CBM requires a maximum archival rate of 3 GB/s. Therefore, there is a need to reduce the data output rate by a factor of at least 300 [6]. Thus, the experimental challenge is to identify and select (1/300 = 0.3%) rare events including complex decays in real time and discard the rest. Early classification, i.e., before data storage, will help with the efficient collection of important information from the collisions and storage of only the essential information. For this task, the CBM experiment has developed the First Level Event Selection (FLES) [7] package. The FLES package of the CBM experiment can reconstruct the full event topology, including the tracks of charged and short-lived particles. The FLES package consists of several modules (Figure 1): a track finder, a track fitter, a particle finder, and a physics analysis module. As input, the FLES package takes a simplified geometry of the tracking detectors and the hits created by charged particles crossing the detectors. The tracks of charged particles are reconstructed by the Cellular Automaton (CA) Track Finder. The Kalman Filter (KF)-based track fitter is used for a precise estimation of the track parameters. Short-lived particles, which decay before reaching the tracking detectors, can only be reconstructed via their decay products. The KF Particle Finder, based on the KFParticle package, is used to find and reconstruct the parameters of short-lived particles by combining tracks of long-lived charged particles that have already been found. Finally, a quality assurance module allows for the control of the reconstruction quality at every stage. The FLES package is platform- and operating-system-independent. It will be used in the CBM experiment for online selection and offline analysis on a dedicated multi-core CPU/GPU farm. A neural network for classification based on the ANN4 FLES package, which receives information about reconstructed particles from the KF Particle Finder package, will be integrated into the physics analysis module of the FLES package (shown in red in Figure 1) and will then be used as a QGP trigger for event selection.