相关论文: Estimation of Impact Parameter on event-by-event b…
We demonstrate that the nuclear collision geometry (i.e. impact parameter) can be determined with 1.5 fm accuracy in an event-by-event analysis by measuring the transverse energy flow in the pseudorapidity region $3 \le |\eta| \le 5$ with a…
A deep learning based method with the convolutional neural network (CNN) algorithm for determining the impact parameters is developed using the constrained molecular dynamics model simulations, focusing on the heavy-ion collisions at the…
A new method of event characterization based on Deep Learning is presented. The PointNet models can be used for fast, online event-by-event impact parameter determination at the CBM experiment. For this study, UrQMD and the CBM detector…
The nucleus-nucleus impact parameter and collision geometry of a heavy ion collision are typically characterized by assigning a collision "centrality". In all present heavy ion experiments centrality is measured indirectly, by detecting the…
The determination of the centrality of nuclear collision or the value of the impact parameter of heavy nuclei is of great importance for the analysis of all experimental data and comparison with theory. One method is to measure the number…
An unfolding method, based on Bayes theorem is presented to obtain true event-by-event net-charge multiplicity distribution from a corresponding measured distribution, which is subjected to detector artifacts. The unfolding is demonstrated…
Event-based imaging is a neurmorphic detection technique whereby an array of pixels detects a positive or negative change in light intensity at each pixel, and is hence particularly well suited to detecting motion. As compared to standard…
In proton-nucleus and nucleus-nucleus collision experiments, one determines the centrality of a collision according to the multiplicity or energy deposited in a detector. This serves as a proxy for the true collision centrality, as defined…
The impact parameter characterizes the centrality in nucleus-nucleus collision geometry. The determination of impact parameters in real experiments is usually based on the reconstructed particle attributes or the derived event-level…
Machine Learning (ML) algorithms have been demonstrated to be capable of predicting impact parameter in heavy-ion collisions from transport model simulation events with perfect detector response. We extend the scope of ML application to…
The nuclear photo-emulsion technique is used to study the information carried by the medium energy nucleons produced in heavy ion collisions. Multiplicity, energies as well as the angular distribution of this type of particles are measured.…
A model in which a projectile like fragment can be simply regarded as a remnant after removal of some part of the projectile leads to an excited fragment. This excitation energy can be calculated with a Hamiltonian that gives correct…
Precise neutrino--nucleus interaction measurements in the sub-multi GeV region are important to reduce the systematic uncertainty in future neutrino oscillation experiments. Furthermore, the excess of ${\nu_e}$ interactions, as a possible…
We discuss a method to obtain the true event-by-event net-charge multiplicity distributions from a corresponding measured distribution which is subjected to detector effects such as finite particle counting efficiency. The approach is based…
We present a model-independent method to reconstruct the impact parameter distributions of experimental data for intermediate energy heavy ion collisions, adapted from a recently proposed approach for ultra-relativistic heavy ion…
There are a large number of physics programs one can explore in electron-nucleus collisions at a future electron-ion collider. Collision geometry is very important in these studies, while the measurement for an event-by-event geometric…
This report reviews methods of pattern recognition and event reconstruction used in modern high energy physics experiments. After a brief introduction into general concepts of particle detectors and statistical evaluation, different…
The Multi-Purpose Detector (MPD) is to be installed at the Nuclotron Ion Collider fAcility (NICA) of the Joint Institute for Nuclear Research (JINR). Its main goal is to study the phase diagram of the strongly interacting matter produced in…
Understanding nuclear effects is essential for improving the sensitivity of neutrino oscillation measurements. Validating nuclear models solely through neutrino scattering data is challenging due to limited statistics and the broad energy…
Event classification by centrality is one of the key tasks of the MPD (Multi-Purpose Detector) experiment at the NICA collider. Centrality characterizes the initial geometry of heavy-ion collisions through the correlation of measured…