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Inefficient data transfer between computation and memory inspired emerging processing-in-memory (PIM) technologies. Many PIM solutions enable storage and processing using memristors in a crossbar-array structure, with techniques such as…
IDEA (Innovative Detector for an Electron-positron Accelerator) is a general-purpose detector concept, designed to study electron-positron collisions in a wide energy range from a very large circular leptonic collider. Its drift chamber is…
The ANTARES neutrino telescope is presently being built in the Mediterranean Sea at a depth of 2500 m. The primary aim of the experiment is the detection of high energy cosmic muon neutrinos, which are identified by the muons that are…
The High-Altitude Water Cherenkov experiment (HAWC) observatory is located 4100 meters above sea level. HAWC is able to detect secondary particles from extensive air showers (EAS) initiated in the interaction of a primary particle (either a…
A well-established procedure for the photoelectrochemical (PEC) splitting of water relies on using porous electrodes of WO3 sensitized with BiVO4 as a visible scavenger photoanode semiconductor. In this work, we propose an evolved…
The lepton identification is essential for the physics programs at high-energy frontier, especially for the precise measurement of the Higgs boson. For this purpose, a Toolkit for Multivariate Data Analysis (TMVA) based lepton…
This paper presents a simple model for predicting electrical conductivity of air with varying electrode separation and different moisture content present in air. Our system consists of a metallic thin film (Cu) coated sample and a needle…
A survey of machine learning techniques trained to detect ransomware is presented. This work builds upon the efforts of Taylor et al. in using sensor-based methods that utilize data collected from built-in instruments like CPU power and…
The Electron Ion Collider (EIC) is the next generation of precision QCD facility to be built at Brookhaven National Laboratory in conjunction with Thomas Jefferson National Laboratory. There are a significant number of software and…
Delay-coupled electro-optical systems have received much attention for their dynamical properties and their potential use in signal processing. In particular it has recently been demonstrated, using the artificial intelligence algorithm…
High-quality simulated data is crucial for particle physics discoveries. Therefore, parton shower algorithms are a major building block of the data synthesis in event generator programs. However, the core algorithms used to generate parton…
The Liquid Argon Time Projection Chamber (LAr-TPC) detectors provide excellent imaging and particle identification ability for studying neutrinos. An efficient and automatic reconstruction procedures are required to exploit potential of…
Compressed sensing algorithms are used to decrease electron microscope scan time and electron beam exposure with minimal information loss. Following successful applications of deep learning to compressed sensing, we have developed a…
Erbium-doped crystals offer a versatile platform for hybrid quantum devices because they combine magnetically-sensitive electron-spin transitions with telecom-wavelength optical transitions. At the high doping concentrations necessary for…
We investigate whether state-of-the-art classification features commonly used to distinguish electrons from jet backgrounds in collider experiments are overlooking valuable information. A deep convolutional neural network analysis of…
The SHiP-charm project was proposed to measure the associated charm production induced by 400 GeV/c protons in a thick target, including the contribution from cascade production. An optimisation run was performed in July 2018 at CERN SPS…
Recent work provides promising evidence that Physics-Informed Neural Networks (PINN) can efficiently solve partial differential equations (PDE). However, previous works have failed to provide guarantees on the worst-case residual error of a…
We present an error mitigation strategy composed of Echo Verification (EV) and Clifford Data Regression (CDR), the combination of which allows one to learn the effect of the quantum noise channel to extract error mitigated estimates for the…
Quantum error mitigation has been extensively explored to increase the accuracy of the quantum circuits in noisy-intermediate-scale-quantum (NISQ) computation, where quantum error correction requiring additional quantum resources is not…
Electron beam probe (EBP) is a new principle detector, which makes use of a low-intensity and low-energy electron beam to measure the transverse profile, bunch shape, beam neutralization and beam wake field of an intense beam with small…