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Victor Riabov

Publications and source records attributed to Victor Riabov.

2 recordsLinked to original sources

Performance of the MPD experiment in dielectron measurements at NICA

The Multi-Purpose Detector (MPD) experiment at NICA is designed to investigate strongly interacting matter at high net-baryon density through a broad program of heavy-ion measurements. Dielectrons constitute one of the key probes in this program, with contributions emitted throughout the entire space-time evolution of the collision. Their experimental measurement is, however, challenged by a large combinatorial background arising primarily from incompletely reconstructed photon conversions and Dalitz decays of light neutral mesons. In this work, we study the performance and capabilities of the MPD experiment for dielectron measurements using simulated minimum-bias $^{209}$Bi+$^{209}$Bi collisions at $\sqrt{s_{NN}}$ = 9.2 GeV. Electron identification is performed using the combined information from the TPC, the TOF detector and the ECal. A multilayer-perceptron classifier is used to optimize electron identification, leading to a substantial increase in electron detection efficiency relative to sequential one-dimensional selections while preserving an electron-sample purity close to unity over a broad momentum range. To address the dominant sources of combinatorial background, a pair-analysis strategy is developed that exploits partially reconstructed electron tracks. The method combines the pair opening angle, the TPC dE/dx signal, and an approximate reconstruction of the pair invariant mass to tag tracks from photon conversions and $π^0$ Dalitz decays at the pair level. In the mass interval 0.2 $< m_{ee}<0.7 $ GeV/$c^2$, the method improves the signal-to-background ratio by a factor of about 3.5 with the current track reconstruction algorithm. The study demonstrates the strong potential of the MPD experiment for dielectron measurements at NICA energies and highlights the importance of further improvements in low-$p_{\rm T}$ track reconstruction.

physics.ins-det↗

Generative Surrogates for Fast Simulation: TPC Case

Simulation of High Energy Physics experiments is widely used, necessary for both detector and physics studies. Detailed Monte-Carlo simulation algorithms are often limited due to the computational complexity of such methods, and therefore faster approaches are desired. Generative Adversarial Networks (GANs) are well suited for aggregating a number of detailed simulation steps into a surrogate probability density estimator readily available for fast sampling. In this work, we demonstrate the power of the GAN-based fast simulation model on the use case of simulating the response for the Time Projection Chamber (TPC) in the MPD experiment at the NICA accelerator complex. We show that our model can generate high-fidelity TPC responses, while accelerating the TPC simulation by at least an order of magnitude. We describe alternative representation approaches for this problem and also outline the roadmap for the deployment of our method into the software stack of the experiment.

hep-ex↗