Spin Hydrodynamic Generation in the Charged Subatomic Swirl

Recently there have been significant interests in the spin hydrodynamic generation phenomenon from multiple disciplines of physics. Such phenomenon arises from global polarization effect of microscopic spin by macroscopic fluid rotation and is expected to occur in the hot quark-gluon fluid (the ``subatomic swirl'') created in relativistic nuclear collisions. This was indeed discovered in experiments which however revealed an intriguing puzzle: a polarization difference between particles and anti-particles. We suggest a novel application of a general connection between rotation and magnetic field: a magnetic field naturally arises along the fluid vorticity in the charged subatomic swirl. We establish this mechanism as a new way for generating long-lived in-medium magnetic field in heavy ion collisions. Due to its novel feature, this new magnetic field provides a nontrivial explanation to the puzzling observation of a difference in spin hydrodynamic generation for particles and anti-particles in heavy ion collisions.Comment: 10 pages, 3 figures, title changed according to published versio

The absence of mixed valency for Pr in pristine and hole-doped PrNiO2_2

Infinite-layer nickelates ($R$NiO$_2$) exhibit some distinct differences as compared to cuprate superconductors, leading to a debate concerning the role of rare-earth ions ($R$=La, Pr, Nd) in the low-energy many-body physics. Although rare-earth $4f$ orbitals are typically treated as inert `core' electrons in studies, this approximation has been questioned. An active participation of $4f$ states is most likely for PrNiO$_2$ based on an analogy to cuprates where Pr cuprates differ significantly from other cuprates. Here, we adopt density functional plus dynamical mean field theory (DFT+DMFT) to investigate the role of Pr $4f$ orbitals and more generally the correlated electronic structure of PrNiO$_2$ and its hole-doped variant. We find that the Pr $4f$ states are insulating and show no evidence for either a Kondo resonance or Zhang-Rice singlet formation as they do not have any hybridization channels near the Fermi energy. The biggest effects of hole doping are to shift the Pr $5d$ and $4f$ states further away from the Fermi energy while enhancing the Ni $3d$ - O $2p$ hybridization, thus reducing correlation effects as the O $2p$ states get closer to the Fermi energy. We again find no evidence for either Kondo or Zhang-Rice physics for the $4f$ states upon hole doping. We conclude by commenting on implications for other reduced valence nickelates.Comment: 12 pages, 13 figure

Medium-Assisted Enhancement of X(3872)X(3872) Production from Small to Large Colliding Systems

Studies of exotic hadrons such as the $\chi_{c1} (3872)$ state provide crucial insights into the fundamental force governing the strong interaction dynamics, with an emerging new frontier to investigate their production in high energy collisions where a partonic medium is present. Latest experimental measurements from the Large Hadron Collider show an intriguing evolution pattern of the $\chi_{c1} (3872)$-to-$\psi(2S)$ yield ratio from proton-proton collisions with increasing multiplicities toward proton-lead and lead-lead collisions. Here we propose a novel mechanism of medium-assisted enhancement for the $\chi_{c1} (3872)$ production, which competes with the more conventional absorption-induced suppression and results in a non-monotonic trend from small to large colliding systems. Realistic simulations from this model offer the first quantitative description of all available data. Predictions are made for the centrality dependence of this observable in PbPb collisions as well as for its system size dependence from OO and ArAr to XeXe and PbPb collisions. In both cases, a non-monotonic behavior emerges as the imprint of the competition between enhancement and suppression and can be readily tested by future data.Comment: 7 pages, 4 figure

Seismic Data Strong Noise Attenuation Based on Diffusion Model and Principal Component Analysis

Seismic data noise processing is an important part of seismic exploration data processing, and the effect of noise elimination is directly related to the follow-up processing of data. In response to this problem, many authors have proposed methods based on rank reduction, sparse transformation, domain transformation, and deep learning. However, such methods are often not ideal when faced with strong noise. Therefore, we propose to use diffusion model theory for noise removal. The Bayesian equation is used to reverse the noise addition process, and the noise reduction work is divided into multiple steps to effectively deal with high-noise situations. Furthermore, we propose to evaluate the noise level of blind Gaussian seismic data using principal component analysis to determine the number of steps for noise reduction processing of seismic data. We train the model on synthetic data and validate it on field data through transfer learning. Experiments show that our proposed method can identify most of the noise with less signal leakage. This has positive significance for high-precision seismic exploration and future seismic data signal processing research.Comment: 10 pages, 13 figures. This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl