Related papers: Imaging particle collision data for event classifi…
There have been a number of recent proposals to enhance the performance of machine learning strategies for collider physics by combining many distinct events into a single ensemble feature. To evaluate the efficacy of these proposals, we…
A convolutional neural network-based classifier is elaborated to retrace the initial orientation of deformed nucleus-nucleus collisions by integrating multiple typical experimental observables. The isospin-dependent…
The motion of particles through density-stratified interfaces is a common phenomenon in environmental and engineering applications. However, the mechanics of particle-stratification interactions in various combinations of particle and fluid…
When are two collider events similar? Despite the simplicity and generality of this question, there is no established notion of the distance between two events. To address this question, we develop a metric for the space of collider events…
In collider experiments, the kinematic reconstruction of heavy, short-lived particles is vital for precision tests of the Standard Model and in searches for physics beyond it. Performing kinematic reconstruction in collider events with many…
Centrality selection has been observed to have a large effect on jet observables in pPb collisions at the Large Hadron Collider, stronger than that predicted by the nuclear modification of parton densities. We study to which extent simple…
Understanding the modification of jets and high-$p_T$ probes in small systems requires the integration of soft and hard physics. We present recent developments in extending the JETSCAPE framework to build an event generator, which includes…
In nuclear physics experiments involving in-flight fragmentation of ions, usually a large number of different nuclei is produced and various detection systems are employed to identify the species event by event, e.g. by measuring their…
We propose masked particle modeling (MPM) as a self-supervised method for learning generic, transferable, and reusable representations on unordered sets of inputs for use in high energy physics (HEP) scientific data. This work provides a…
Machine learning has become an essential tool in jet physics. Due to their complex, high-dimensional nature, jets can be explored holistically by neural networks in ways that are not possible manually. However, innovations in all areas of…
The classification of events involving jets as signal-like or background-like can depend strongly on the jet algorithm used and its parameters. This is partly due to the fact that standard jet algorithms yield a single partition of the…
The jets are the final state manifestation of the hard parton scattering. Since at LHC energies the production of hard processes in proton-proton collisions will be copious and varied, it is important to develop methods to identify them…
This paper presents a real-time solution for collision detection between objects based on the physics properties. Traditional approaches on collision detection often rely on the geometric relationships that computing the intersections…
The CMS Detector consists of a large volume silicon tracker immersed in a high four Tesla magnetic field, together with a high resolution/granularity electromagnetic calorimeter and a nearly full solid angle coverage hadronic calorimeter.…
In this note a study of hadronic event shapes in QCD events at the Large Hadron Collider (LHC) is presented. Calorimetric jet momenta, determined by various jet clustering algorithms, are used as input for calculating various event-shape…
A method is developed to calculate collision probability in this paper. Based on the encounter geometric features of space objects, it is reasonable to separate the radial orbital motions from that in the cross section for most encounter…
In complex plasmas, the behavior of freely floating micrometer sized particles is studied. The particles can be directly visualized and recorded by digital video cameras. To analyze the dynamics of single particles, reliable algorithms are…
Particle filters are computational techniques for estimating the state of dynamical systems by integrating observational data with model predictions. This work introduces a class of Localized Particle Filters (LPFs) that exploit spatial…
The Standard Model of particle physics makes it possible to simulate complete events for physics signatures and their backgrounds in high energy collisions. Knowledge of how the produced particles interact with the materials in a detector…
Soft pp interactions are considered in the framework of the phenomenological model with color strings formation. Under the assumption, that the elementary collision is realized as interaction of two color dipoles, the total inelastic cross…