相关论文: Transformer-Based Approach to Enhance Positron Tra…
The cylindrical drift chamber is the most innovative part of the MEG~II detector, the upgraded version of the MEG experiment. The MEG~II chamber differs from the MEG one because it is a single volume cylindrical structure, instead of a…
High backgrounds and detector ageing impact the track finding in the Belle II central drift chamber, reducing both track purity and track efficiency in events. This necessitates the development of new track finding algorithms to mitigate…
Optimization based tracking methods have been widely successful by integrating a target model prediction module, providing effective global reasoning by minimizing an objective function. While this inductive bias integrates valuable domain…
We propose a light-weight and highly efficient Joint Detection and Tracking pipeline for the task of Multi-Object Tracking using a fully-transformer architecture. It is a modified version of TransTrack, which overcomes the computational…
The reconstruction of the positron trajectory in the MEG-II experiment searching for the $\mu^+ \to e^+ \gamma$ decay uses a cylindrical drift chamber operated with a helium-isobutane gas mixture. A stable performance of the detector in…
The MEG experiment at the Paul Scherrer Institut searches for the charged-Lepton-Flavor-Violating mu+ -> e+ gamma decay. MEG has already set the world best upper limit on the branching ratio: BR<4.2x10^-13 @ 90% C.l. An upgrade (MEG II) of…
The muon \textit{g-2}/EDM experiment at J-PARC is designed to precisely measure the muon's magnetic moment and electric dipole moment, driven by discrepancies between theory and previous experiments. A key challenge is the fast…
Reconstructing charged particle tracks is a fundamental task in modern collider experiments. The unprecedented particle multiplicities expected at the High-Luminosity Large Hadron Collider (HL-LHC) pose significant challenges for track…
High-Energy Physics experiments are rapidly escalating in generated data volume, a trend that will intensify with the upcoming High-Luminosity LHC upgrade. This surge in data necessitates critical revisions across the data processing…
An automatic target monitoring method based on photographs taken by a CMOS photo-camera has been developed for the MEG II detector. The technique could be adapted for other fixed-target experiments requiring good knowledge of their target…
Transformer networks have been a focus of research in many fields in recent years, being able to surpass the state-of-the-art performance in different computer vision tasks. However, in the task of Multiple Object Tracking (MOT), leveraging…
The identification and reconstruction of charged particles, such as muons, is a main challenge for the physics program of the ATLAS experiment at the Large Hadron Collider. This task will become increasingly difficult with the start of the…
The contribution of Resistive Plate Chamber (RPC) to muon reconstruction in CMS has been studied on a sample of muons collected in proton-proton collisions at sqrt(s) = 7 TeV at the LHC in 2011. Muon reconstruction is performed using the…
The MEG II experiment searches for a charged-lepton-flavour-violating $\mu \to e \gamma$ with the target sensitivity of $6 \times 10^{-14}$. A liquid xenon calorimeter with VUV-sensitive photosensors measures photon position, timing, and…
The MEG-II experiment searches for the lepton flavor violating decay: mu in electron and gamma. The reconstruction of the positron trajectory uses a cylindrical drift chamber operated with a mixture of He and iC4H10 gas. It is important to…
We present an overview of the muon reconstruction and identification methods employed by the D0 Collaboration to analyze the Run II (2001-2011) ppbar data of the Fermilab Tevatron collider at sqrt s = 1.96 TeV. We discuss the performance of…
Micro pattern gaseous detectors have been widely used in position measurements of particle detection in the last two decades. In this work a novel method of track identification and reconstruction was developed for fast neutron detection by…
Transformer-based trackers have achieved strong accuracy on the standard benchmarks. However, their efficiency remains an obstacle to practical deployment on both GPU and CPU platforms. In this paper, to overcome this issue, we propose a…
The task of Stance Detection involves discerning the stance expressed in a text towards a specific subject or target. Prior works have relied on existing transformer models that lack the capability to prioritize targets effectively.…
In applied machine learning, concept drift, which is either gradual or abrupt changes in data distribution, can significantly reduce model performance. Typical detection methods,such as statistical tests or reconstruction-based models,are…