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At the earliest times after a heavy-ion collision, the magnetic field created by the spectator nucleons will generate an extremely strong, albeit rapidly decreasing in time, magnetic field. The impact of this magnetic field may have…

High Energy Physics - Phenomenology · Physics 2020-04-22 Gabriele Inghirami , Mark Mace , Yuji Hirono , Luca Del Zanna , Dmitri E. Kharzeev , Marcus Bleicher

Employing a two-band model of Weyl semimetal, the existence of the chiral magnetic effect (CME) is established within the linear-response theory. The crucial role played by the limiting procedure in deriving correct transport properties is…

Mesoscale and Nanoscale Physics · Physics 2015-03-18 Ming-Che Chang , Min-Fong Yang

Machine learning approaches are widely studied in the production prediction of CBM wells after hydraulic fracturing, but merely used in practice due to the low generalization ability and the lack of interpretability. A novel methodology is…

Machine Learning · Computer Science 2022-12-22 Chao Min , Guoquan Wen , Liangjie Gou , Xiaogang Li , Zhaozhong Yang

Machine Learning (ML) algorithms have been demonstrated to be capable of predicting impact parameter in heavy-ion collisions from transport model simulation events with perfect detector response. We extend the scope of ML application to…

We study the impact of a non-uniform magnetic background field on the Chiral Magnetic Effect (CME) in equilibrium QCD using lattice simulations with 2+1 flavors of dynamical staggered quarks at the physical point. We show that in the…

High Energy Physics - Lattice · Physics 2025-09-17 B. B. Brandt , G. Endrődi , E. Garnacho-Velasco , G. Markó , A. D. M. Valois

The scaling properties of the $\Delta\gamma$ correlator, inferred from the Anomalous Viscous Fluid Dynamics (AVFD) model, are used to investigate a possible chiral-magnetically-driven (CME) charge separation in $p$+Au, $d$+Au, Ru+Ru, Zr+Zr,…

Nuclear Experiment · Physics 2022-06-23 Roy A. Lacey , Niseem Magdy

Measurement of the Chiral Magnetic Effect (CME) has been a popular topic of high-energy nuclear physics in the last decade. The flow correlation $\gamma$ between charged hadron pairs of the same and opposite charges and their difference…

Nuclear Theory · Physics 2025-03-20 Yu Wang , Hua Pei

The exponential amplification of initial seed magnetic fields in relativistic plasmas is a very important topic in astrophysics, from the conditions in the early Universe to the interior of neutron stars. While dynamo action in a turbulent…

High Energy Astrophysical Phenomena · Physics 2018-07-04 Luca Del Zanna , Niccolò Bucciatini

We demonstrate high prediction accuracy of three important properties that determine the initial geometry of the heavy-ion collision (HIC) experiments by using supervised Machine Learning (ML) methods. These properties are the impact…

High Energy Physics - Phenomenology · Physics 2022-11-23 Abhisek Saha , Debasis Dan , Soma Sanyal

The recent lattice calculation at finite axial chemical potential suggests that the induced current density of the chiral magnetic effect (CME) is somehow suppressed comparing with the standard analytical formula. We show in a NJL-type…

High Energy Physics - Phenomenology · Physics 2012-06-26 Zhao Zhang

We report on the mean-field study of the Chiral Magnetic Effect (CME) in static magnetic fields within a simple model of a parity-breaking Weyl semimetal given by the lattice Wilson-Dirac Hamiltonian with constant chiral chemical potential.…

Strongly Correlated Electrons · Physics 2015-12-07 P. V. Buividovich , M. Puhr , S. N. Valgushev

Computational Fluid Dynamics (CFD) is a major sub-field of engineering. Corresponding flow simulations are typically characterized by heavy computational resource requirements. Often, very fine and complex meshes are required to resolve…

Machine Learning · Computer Science 2021-02-26 Keefe Huang , Moritz Krügener , Alistair Brown , Friedrich Menhorn , Hans-Joachim Bungartz , Dirk Hartmann

Many large scale problems in computational fluid dynamics such as uncertainty quantification, Bayesian inversion, data assimilation and PDE constrained optimization are considered very challenging computationally as they require a large…

Computational Physics · Physics 2020-04-22 Kjetil O. Lye , Siddhartha Mishra , Deep Ray

We discuss a novel world-line framework for computations of the Chiral Magnetic Effect (CME) in ultrarelativistic heavy-ion collisions. Starting from the fermion determinant in the QCD effective action, we show explicitly how its real part…

High Energy Physics - Phenomenology · Physics 2017-09-13 Niklas Mueller , Raju Venugopalan

A number of recent progresses in the study of strong field effects in heavy ion collisions are discussed here: 1) the Chiral Magnetic Wave (CMW) and its experimental manifestation via splitting of positive/negative pions' elliptic flow; 2)…

High Energy Physics - Phenomenology · Physics 2013-06-24 Jinfeng Liao

The chiral magnetic effect (CME) is an exact statement that connects via the axial anomaly the electric current in a system consisting of interacting fermions and gauge field with chirality imbalance that is put into a strong external…

High Energy Physics - Phenomenology · Physics 2020-04-17 L. Ya. Glozman

Chiral Magnetic Effect (CME) is a phenomenon in which electric charge is separated by a strong magnetic field from local domains of chirality imbalance in quantum chromodynamics. The CME-sensitive, azimuthal correlator difference…

High Energy Physics - Phenomenology · Physics 2025-03-05 Han-Sheng Li , Yicheng Feng , Fuqiang Wang

Negative magnetoresistance in Dirac semimetals is typically considered as a manifestation of chiral magnetic effect (CME). The relation between these two phenomena has the status of a hypothesis and is based on sequence of assumptions. We…

Mesoscale and Nanoscale Physics · Physics 2026-01-13 R. A. Abramchuk , M. A. Zubkov

We present a first principles approach to study the Chiral Magnetic Effect during the pre-equilibrium stage of a heavy-ion collision. We discuss the dynamics of the Chiral Magnetic Effect and Chiral Magnetic Wave based on real-time lattice…

High Energy Physics - Lattice · Physics 2018-03-14 Mark Mace , Niklas Mueller , Soeren Schlichting , Sayantan Sharma

Over the last years, machine learning tools have been successfully applied to a wealth of problems in high-energy physics. A typical example is the classification of physics objects. Supervised machine learning methods allow for significant…

Data Analysis, Statistics and Probability · Physics 2017-09-26 Rüdiger Haake