相关论文: Analytical model for event reconstruction in copla…
High quality spatiotemporal signal is vitally important for real application scenarios like energy management, traffic planning and cyber security. Due to the uncontrollable factors like abrupt sensors breakdown or communication fault, the…
We demonstrate transfer learning capabilities in a machine-learned algorithm trained for particle-flow reconstruction in high energy particle colliders. This paper presents a cross-detector fine-tuning study, where we initially pretrain the…
A track finding algorithm has been developed for reconstruction of e+e- pairs. It combines the information of the electromagnetic calorimeter with the information provided by the Tracker. Results on reconstruction efficiency of converted…
In this work, a serial on-line cluster reconstruction technique based on FPGA technology was developed to compress experiment data and reduce the dead time of data transmission and storage. At the same time, X-ray imaging experiment based…
The GammaTPC is an MeV-scale single-phase liquid argon time-projection-chamber gamma-ray telescope concept with a novel dual-scale pixel-based charge-readout system. It promises to enable a significant improvement in sensitivity to…
A large Time Projection Chamber is the main device for tracking and charged-particle identification in the ALICE experiment at the CERN LHC. After the second long shutdown in 2019/20, the LHC will deliver Pb beams colliding at an…
Jet flavour identification algorithms are of paramount importance to maximise the physics potential of future collider experiments. This work describes a novel set of tools allowing for a realistic simulation and reconstruction of particle…
Compression of the sign information of discrete cosine transform coefficients is an intractable problem in image compression schemes due to the equiprobable occurrence of the sign bits. To overcome this difficulty, we propose an efficient…
Online reconstruction is key for monitoring purposes and real time analysis in High Energy and Nuclear Physics experiments. A necessary component of reconstruction algorithms is particle identification that combines information left by a…
Large-scale data collection by means of wireless sensor network and internet-of-things technology poses various challenges in view of the limitations in transmission, computation, and energy resources of the associated wireless devices.…
Negatively weighted events, which appear in the simulation of particle collisions, significantly increase the computational requirements of collider experiments. A new technique called ARCANE reweighting has been introduced in a companion…
We introduce a novel energy formulation for Plug- and-Play (PnP) image recovery. Traditional PnP methods that use a convolutional neural network (CNN) do not have an energy based formulation. The primary focus of this work is to introduce…
The integration of machine learning techniques with triboelectric nanogenerators (TENGs) offers a transformative pathway for optimizing energy harvesting technologies. In this study, we propose a comprehensive framework that utilizes graph…
A reconstruction algorithm has been developed to capitalize on advances in Cherenkov technology for reactor antineutrino detection. Large gadolinium-doped water (Gd-H$_2$O) Cherenkov detectors are a developing technology which use Gd…
A macroscopic reconstruction is developed to infer iRPC performance using Geant4 observables and one experimental anchor. The Geant4 energy deposition is used to estimate the primary ionization yield, while the efficiency turn-on is modeled…
The outer water buffer is an economic option to shield the external radiative backgrounds for liquid-scintillator neutrino detectors. However, the consequential total reflection of scintillation light at the media boundary introduces extra…
Magnetic resonance imaging (MRI) based electrical properties tomography (EPT) is the quantification of the conductivity and permittivity of different tissues. These electrical properties can be obtained through different reconstruction…
Deep levels control the space charge in electrically compensated semi-insulating materials. They limit the performance of radiation detectors but their interaction with free carriers can be favorably exploited in these devices to manipulate…
In high energy physics, the ability to reconstruct particles based on their detector signatures is essential for downstream data analyses. A particle reconstruction algorithm based on learning hypergraphs (HGPflow) has previously been…
We report on the current simulation studies regarding the reconstruction of Jets and Missing Transverse Energy (MET) with the CMS detector at the CERN proton-proton LHC accelerator. The performance of various jet algorithms is compared,…