Related papers: Applying Deep Learning Technique to Chiral Magneti…
The chiral magnetic effect (CME) is a novel transport phenomenon, arising from the interplay between quantum anomalies and strong magnetic fields in chiral systems. In high-energy nuclear collisions, the CME may survive the expansion of the…
This study explores the Chiral Magnetic Effect (CME) in ultra-relativistic heavy-ion collisions. The CME, observed as back-to-back charge separation along the magnetic field axis, is investigated using the newly developed Sliding Dumbbell…
The hot and dense medium produced in relativistic heavy-ion collisions has been conjectured to be accompanied by an axial charge asymmetry that may lead to a separation of electric charges in the direction of the extremely strong magnetic…
This paper investigates the processing of Frequency Modulated-Continuos Wave (FM-CW) radar signals for vehicle classification. In the last years deep learning has gained interest in several scientific fields and signal processing is not one…
This work investigates the problem of detecting gravitational wave (GW) events based on simulated damped sinusoid signals contaminated with white Gaussian noise. It is treated as a classification problem with one class for the interesting…
The presence of a massive body between the Earth and a gravitational-wave source will produce the so-called gravitational lensing effect. In the case of strong lensing, it leads to the observation of multiple deformed copies of the initial…
Modulation recognition is a challenging task while performing spectrum sensing in a cognitive radio setup. Recently, the use of deep convolutional neural networks (CNNs) has shown to achieve state-of-the-art accuracy for modulation…
We report results of a public data-analysis challenge, hosted on the open data-science platform Kaggle, to detect simulated continuous gravitational-wave signals (CWs). These are weak signals from rapidly spinning neutron stars that remain…
The chiral magnetic effect (CME) refers to charge separation along a strong magnetic field of single-handed quarks, caused by interactions with topological gluon fields from QCD vacuum fluctuations. A major background of CME measurements in…
The search for primordial gravitational waves is a central goal of cosmic microwave background (CMB) surveys. Isolating the characteristic $B$-mode polarization signal sourced by primordial gravitational waves is challenging for several…
The interplay between the chiral anomaly and the strong magnetic or vortical fields created in noncentral heavy-ion collisions can lead to various anomalous chiral effects in the quark--gluon plasma, including the chiral magnetic effect…
Gravitational wave searches rely on a combination of methods, including matched filtering, coherent analyses, and more recent machine learning based pipelines. For compact binary coalescences, where signals originate from the relativistic…
Muon identification is crucial for elementary particle physics experiments. At the Belle II experiment, muons and pions with momenta greater than 0.7 GeV/c are distinguished by their penetration ability through the $K_L$ and Muon (KLM)…
Relativistic heavy-ion collisions provide an ideal environment to study the emergent phenomena in quantum chromodynamics (QCD). The chiral magnetic effect (CME) is one of the most interesting, arising from the topological charge…
Conditional Maximum Mean Discrepancy (CMMD) can capture the discrepancy between conditional distributions by drawing support from nonlinear kernel functions, thus it has been successfully used for pattern classification. However, CMMD does…
The experimental status is reviewed on the search for the chiral magnetic effect (CME) in relativistic heavy-ion collisions. Emphasis is put on background contributions to the CME-sensitive charge correlation measurements and their effects…
The Weyl semimetal, due to a non-zero energy difference in the pair of Weyl nodes shows chiral magnetic effect(CME). This leads to a flow of dissipationless electric current along an applied magnetic field. Such a chiral magnetic effect in…
The standard Bayesian technique for searching pulsar timing data for gravitational wave (GW) bursts with memory (BWMs) using Markov Chain Monte Carlo (MCMC) sampling is very computationally expensive to perform. In this paper, we explain…
Artificial intelligence offers the potential to automate challenging data-processing tasks in collider physics. To establish its prospects, we explore to what extent deep learning with convolutional neural networks can discriminate quark…
Machine learning advances chemistry and materials science by enabling large-scale exploration of chemical space based on quantum chemical calculations. While these models supply fast and accurate predictions of atomistic chemical…