Related papers: Feasibility Study of $\phi$(1020) Production at NI…
The emergence of Deep Neural Network (DNN) and machine learning-based applications paved the way for a new generation of hybrid hardware platforms. Hybrid platforms embed several cores and accelerators in a small package. However, in order…
The BM@N experiment (Baryonic Matter at the Nuclotron) is the first fixed-target experiment at the JINR NICA accelerator complex. In this work, data on the interactions of a carbon-ion beam with kinetic energies of 4.0A~GeV and 4.5A~GeV…
An electron-proton/ion collider facility (eRHIC) is under consideration at Brookhaven National Laboratory (BNL). An overview of the accelerator and detector design concepts will be provided.
The PANDA detector at the international accelerator Facility for Antiproton and Ion Research in Europe (FAIR) addresses fundamental questions of hadron physics. An excellent hadronic particle identification (PID) will be accomplished by two…
A major ingredient of the planned new accelerator complex FAIR, to be constructed at the GSI, Darmstadt, Germany, is the availability of antiproton beams with high quality and intensity. Among the experiments which will make use of this…
We have developed a silicon pixel detector to enhance the physics capabilities of the PHENIX experiment. This detector, consisting of two layers of sensors, will be installed around the beam pipe at the collision point and covers a…
The performance of a novel tracking detector developed for the focal plane of the NSCL/FRIB S800 magnetic spectrometer is presented. The detector comprises a large-area drift chamber equipped with a hybrid Micro-Pattern Gaseous Detector…
The current world status of plans for future particle-physics accelerators and accelerator research and development is outlined. The developments for a neutrino factory are placed in this context. Finally, a specific initiative relevant for…
To speedup Deep Neural Networks (DNN) accelerator design and enable effective implementation, we propose HybridDNN, a framework for building high-performance hybrid DNN accelerators and delivering FPGA-based hardware implementations. Novel…
The existence of Majorana neutrinos must lead to lepton-number violating processes, and the Majorana nature of neutrinos can only be experimentally verified via lepton-number violating processes. We propose a new approach to search for…
Transformer-based NLP models are powerful but have high computational costs that limit deployment. Finetuned encoder-decoder models are popular in specialized domains and can outperform larger more generalized decoder-only models, such as…
A dual-purpose ion-accelerator concept, capable of serving as radiation source in a versatile, nuclear-reaction-based cargo inspection system, is presented. The system will automatically and reliably detect small, operationally-relevant…
At Central Michigan University we are developing a high-precision Penning trap mass spectrometer (CHIP-TRAP)that will focus on measurements with long-lived radioactive isotopes. CHIP-TRAP will consist of a pair of hyperbolic…
Several future high-energy physics facilities are currently being planned. The proposed projects include high energy $e^+ e^-$ circular and linear colliders, hadron colliders and muon colliders, while the Electron-Ion Collider (EIC) has…
The U.S. Particle Physics Project Prioritization Panel (P5) report encouraged the realization of Fermilab's Proton Improvement Plan II (PIP-II) to support future neutrino programs in the United States. PIP-II aims at enhancing the…
The IsoDAR collaboration is developing a high-current cyclotron for a neutrino search experiment. Designed to deliver 10 mA of 60 MeV protons, the current and power of this cyclotron far exceed those of existing accelerators, opening new…
A large number of high-energy and heavy-ion experiments successfully used Time Projection Chamber (TPC) as central tracker and particle identification detector. However, the performance requirements on TPC for new high-rate particle…
Among the post-LHC generation of particle accelerators, the muon collider represents a unique machine with capability to provide very high energy leptonic collisions and to open the path to a vast and mostly unexplored physics programme.…
We present the multiple particle identification (MPID) network, a convolutional neural network (CNN) for multiple object classification, developed by MicroBooNE. MPID provides the probabilities of $e^-$, $\gamma$, $\mu^-$, $\pi^\pm$, and…
The construction of modern detectors used in high-energy physics experiments is typically guided by modeling with the Geant4 toolkit to evaluate detector performance in terms of geometrical acceptance and detection efficiency. Several…