arXiv subjects

Shuzhe Shi

Publications and source records attributed to Shuzhe Shi.

At least 55 records · Page 3Linked to original sources

arXiv2023

Dynamical magnetic fields in heavy-ion collisions

The magnetic fields in heavy-ion collisions are important ingredients for many interesting phenomena, such as the Chiral Magnetic Effect, Chiral Magnetic Wave, the directed flow $v_1$ of $D^0$ mesons and the splitting of the spin polarization of the $Λ$/$\barΛ$. Quantitative studies of these phenomena however suffer from limited understanding on the dynamical evolution of these fields in the medium created by the collisions, which remains a critical and challenging problem. The initial magnetic fields from the colliding nuclei decay very fast in the vacuum but their lifetime could be extended through medium response due to electrically conducting quarks and antiquarks. Here we perform a detailed analysis of such medium effect on the dynamical magnetic fields by numerically solving the Maxwell's equations concurrently with the expanding medium described by viscous hydrodynamics, under the assumption of negligible back reaction of the fields on the fluid evolution. Our results suggest a considerable enhancement of late time magnetic fields, the magnitude of which depends sensitively on the fireball expansion as well as the medium electric conductivity both before and during hydrodynamic stage.

hep-ph↗

arXiv2023

Accessing Topological Fluctuations of Gauge Fields with Chiral Magnetic Effect

Gauge fields provide the fundamental interactions in the Standard Model of particle physics. Gauge field configurations with nontrivial topological windings are known to play crucial roles in many important phenomena, from matter-anti-matter asymmetry of today's universe to spontaneous chiral symmetry breaking in strong interaction. Their presence is however elusive for direct detection in experiments. Here we show that measurements of the chiral magnetic effect (CME) in heavy ion collisions can be used for accessing the topological fluctuations of the non-Abelian gauge fields in the Quantum Chromodynamics (QCD). To achieve this, we implemented a key ingredient, the stochastic dynamics of gauge field topological fluctuations, into a state-of-the-art framework for simulating the CME in these collisions. This new framework provides the necessary tool to quantify initial topological fluctuations from any definitive CME signal to be extracted from experimental data. It also reveals a universal scaling relation between initial topological fluctuations and particle multiplicity produced in the corresponding collision events.

hep-ph↗

arXiv2023

Comparing the MARTINI and CUJET models for jet-quenching: Medium modification of jets and jet substructure

Jets produced by the initial hard scattering in heavy ion collision events lose energy due to interactions with the color-deconfined medium formed around them: the quark-gluon plasma (QGP). Jet-medium interactions constitute an important theoretical and experimental field for studies of QGP, and various models with different assumptions have been proposed to describe them. A fair and direct comparison of these models requires that all other aspects of the simulation be fixed, which is achieved in this work by relying on the JETSCAPE framework. We employ JETSCAPE to directly and comprehensively compare two successful energy loss models: CUJET and MARTINI. We compare the models with the results of measurements of jet spectra and substructure observables. With the strong coupling tuned separately, we find that the two models broadly agree with each other in nuclear modification factors for charged hadrons and jets with cone size $R=0.4$. Systematic differences are reported in fragmentation functions, jet shape, and cone size dependent jet $R_{\mathrm{AA}}$.

hep-ph↗

arXiv2022

Jet-medium photons as a probe of parton dynamics

Photons resulting from jet-medium interactions offer the opportunity of studying the evolving quark distribution in a heavy ion collision. The spectra of jet-medium photons is presented within the JETSCAPE framework for two different energy loss models, MARTINI and CUJET. Jet-medium photons can contribute significantly to the spectrum of direct photons in the intermediate $p_T$ range.

hep-ph↗

arXiv2022

Continuum-extrapolated NNLO Valence PDF of Pion at the Physical Point

We present lattice QCD calculations of valence parton distribution function (PDF) of pion employing next-to-next-leading-order (NNLO) perturbative QCD matching. Our calculations are based on three gauge ensembles of 2+1 flavor highly improved staggered quarks and Wilson--Clover valance quarks, corresponding to pion mass $m_π=140$~MeV at a lattice spacing $a=0.076$~fm and $m_π=300$~MeV at $a=0.04, 0.06$~fm. This enables us to present, for the first time, continuum-extrapolated lattice QCD results for NNLO valence PDF of the pion at the physical point. Applying leading-twist expansion for renormalization group invariant (RGI) ratios of bi-local pion matrix elements with NNLO Wilson coefficients we extract $2^{\mathrm{nd}}$, $4^{\mathrm{th}}$ and $6^{\mathrm{th}}$ Mellin moments of the PDF. We reconstruct the Bjorken-$x$ dependence of the NNLO PDF from real-space RGI ratios using a deep neural network (DNN) as well as from momentum-space matrix elements renormalized using a hybrid-scheme. All our results are in broad agreement with the results of global fits to the experimental data carried out by the xFitter and JAM collaborations.

hep-lat↗

arXiv2022

Reconstructing the neutron star equation of state from observational data via automatic differentiation

Neutron star observables like masses, radii, and tidal deformability are direct probes to the dense matter equation of state~(EoS). A novel deep learning method that optimizes an EoS in the automatic differentiation framework of solving inverse problems is presented. The trained neural network EoS yields narrow bands for the relationship between the pressure and speed of sound as a function of the mass density. The results are consistent with those obtained from conventional approaches and the observational bound on the tidal deformability inferred from the gravitational wave event, GW170817.

astro-ph.HE↗

arXiv2022

Leading order, next-to-leading order, and non-perturbative parton collision kernels: effects in static and evolving media

Energetic partons traveling in a strongly interacting medium lose energy by emitting radiation and through collisions with medium constituents. Non-perturbative, next-to-leading order and leading order collision kernels are implemented within AMY-McGill formalism. The resulting gluon emission rates are then evaluated and compared by considering scattering occurring in a brick of quark-gluon plasma, as well as in a realistic simulation of Pb-Pb, collisions at $\sqrt{s}=2.76$ ATeV using MARTINI. We find that the variations in quenching of hard partons resulting from using different kernels can be important, depending on the overall value of the strong coupling constant $α_s$.

hep-ph↗

arXiv2022

Implications of the isobar run results for chiral magnetic effect in heavy ion collisions

Chiral magnetic effect (CME) is a macroscopic transport phenomenon induced by quantum anomaly in the presence of chiral imbalance and an external magnetic field. Relativistic heavy ion collisions provide the unique opportunity to look for CME in a non-Abelian plasma, where the chiral imbalance is created by topological transitions similar to those occurring in the Early Universe. The isobar run at Relativistic Heavy Ion Collider was proposed as a way to separate the possible CME signal driven by magnetic field from the background. The first blind analysis results from this important experiment have been recently released by the STAR Collaboration. Under the pre-defined assumption of identical background in RuRu and ZrZr, the results are inconsistent with the presence of CME, as well as with all existing theoretical models (whether including CME or not). However the observed difference of backgrounds must be taken into account before any physical conclusion is drawn. In this paper, we show that once the observed difference in hadron multiplicity and collective flow are quantitatively taken into account, the STAR results could be consistent with a finite CME signal contribution of about $(6.8\pm2.6)\%$.

nucl-th↗

arXiv2022

Shear-induced anomalous transport and charge asymmetry of triangular flow in heavy-ion collisions

Chiral anomaly implies the existence of non-dissipative transport phenomena, such as the chiral magnetic effect. At second order in the derivative expansion, novel quantum transport phenomena emerge. In this paper, we focus on the anomalous transport driven by a combination of shear, vorticity and magnetic field. We find that the corresponding transport phenomena -- shear-induced chiral magnetic and chiral vortical effects (siCME and siCVE) -- induce characteristic charge correlations among the hadrons produced in heavy ion collisions. We propose the charge asymmetry of triangular flow as a signature of the anomalous transport, and estimate the strength of the signal, as well as the background, using hydrodynamical model simulations. We find that the signal-to-background ratio for the proposed observable is favorable for experimental detection.

hep-ph↗

arXiv2022

Rethinking the ill-posedness of the spectral function reconstruction -- why is it fundamentally hard and how Artificial Neural Networks can help

Reconstructing hadron spectral functions through Euclidean correlation functions are of the important missions in lattice QCD calculations. However, in a Källen--Lehmann(KL) spectral representation, the reconstruction is observed to be ill-posed in practice. It is usually ascribed to the fewer observation points compared to the number of points in the spectral function. In this paper, by solving the eigenvalue problem of continuous KL convolution, we show analytically that the ill-posedness of the inversion is fundamental and it exists even for continuous correlation functions. We discussed how to introduce regulators to alleviate the predicament, in which include the Artificial Neural Networks(ANNs) representations recently proposed by the Authors in~[Phys. Rev. D 106 (2022) L051502]. The uniqueness of solutions using ANNs representations is manifested analytically and validated numerically. Reconstructed spectral functions using different regularization schemes are also demonstrated, together with their eigen-mode decomposition. We observe that components with large eigenvalues can be reliably reconstructed by all methods, whereas those with low eigenvalues need to be constrained by regulators.

hep-ph↗

arXiv2022

Reconstructing spectral functions via automatic differentiation

Reconstructing spectral functions from Euclidean Green's functions is an important inverse problem in many-body physics. However, the inversion is proved to be ill-posed in the realistic systems with noisy Green's functions. In this Letter, we propose an automatic differentiation(AD) framework as a generic tool for the spectral reconstruction from propagator observable. Exploiting the neural networks' regularization as a non-local smoothness regulator of the spectral function, we represent spectral functions by neural networks and use the propagator's reconstruction error to optimize the network parameters unsupervisedly. In the training process, except for the positive-definite form for the spectral function, there are no other explicit physical priors embedded into the neural networks. The reconstruction performance is assessed through relative entropy and mean square error for two different network representations. Compared to the maximum entropy method, the AD framework achieves better performance in the large-noise situation. It is noted that the freedom of introducing non-local regularization is an inherent advantage of the present framework and may lead to substantial improvements in solving inverse problems.

hep-ph↗

arXiv2022

Neural network reconstruction of the dense matter equation of state from neutron star observables

The Equation of State (EoS) of strongly interacting cold and hot ultra-dense QCD matter remains a major challenge in the field of nuclear astrophysics. With the advancements in measurements of neutron star masses, radii, and tidal deformabilities, from electromagnetic and gravitational wave observations, neutron stars play an important role in constraining the ultra-dense QCD matter EoS. In this work, we present a novel method that exploits deep learning techniques to reconstruct the neutron star EoS from mass-radius (M-R) observations. We employ neural networks (NNs) to represent the EoS in a model-independent way, within the range of $\sim$1-7 times the nuclear saturation density. The unsupervised Automatic Differentiation (AD) framework is implemented to optimize the EoS, so as to yield through TOV equations, an M-R curve that best fits the observations. We demonstrate that this method works by rebuilding the EoS on mock data, i.e., mass-radius pairs derived from a randomly generated polytropic EoS. The reconstructed EoS fits the mock data with reasonable accuracy, using just 11 mock M-R pairs observations, close to the current number of actual observations.

hep-ph↗

arXiv2022

Probe the color screening in proton-nucleus collisions with complex potentials

Color screening and parton inelastic scattering modify the heavy-quark antiquark potential in the medium that consists of particles from quantum chromodynamics (QCD), leading to suppression of quarkonium production in relativistic heavy-ion collisions. Due to small charm/anti-charm ($c\bar{c}$) pair production number in proton-nucleus (pA) collisions, the correlation between different $c\bar{c}$ pairs is negligible, which makes the Schrödinger equation viable for tracking the evolution of only one $c\bar{c}$ pair. We employ the time-dependent Schrödinger equation with in-medium $c\bar{c}$ potential to study the evolution of charmonium wave functions in the hydrodynamic like QCD medium produced in pA collisions. We explore different parametrizations of real and imaginary parts of $c\bar{c}$ potential and calculate the nuclear modification factors ($R_{\rm pA}$) of $J/ψ$ and $ψ(2S)$ in $\sqrt{s_{NN}}=5.02$ TeV energy p-Pb collisions at Large Hadron Collider (LHC). Comparing a strong and a weak screening scenario with experimental data in this approach, we arrive at the conclusion that the color screening is weak at temperature close to deconfined phase transition. Moreover, the imaginary part of the potential is crucial to describe the experimental data which is consistent with widely studied semi-classical approaches where the dissociation rates are essential.

nucl-th↗

arXiv2022

Multicomponent second-order dissipative relativistic hydrodynamics with binary reactive collisions

We derive the multi-component second-order dissipative relativistic hydrodynamic equations using the moment-expansion method. By computing the transport coefficients using hard-sphere interactions, we investigate the role of multiple components and the reactive collisions. We find that both of these factors increase the effective cross-section and hence decrease the transport coefficients and relaxation times. We further compute such transport properties using leading-order perturbative QCD cross-sections. For both types of cross-sections, we find that the ratio between vector current relaxation time and conductivity for a multi-component fluid is notably different from that for a single-component fluid. Therefore, the current study provides a more applicable guideline for such a ratio in phenomenological hydrodynamics simulations.

hep-ph↗

arXiv2022

Family of New Exact Solutions for Longitudinally Expanding Ideal Fluids

We report on the discovery of new analytical solutions of the equations of relativistic ideal hydrodynamics. In this solution, the fluid expands in the longitudinal direction and contains a plateau structure that extends over a finite range in rapidity and can be either symmetric or asymmetric in that variable. We further calculate the corresponding pseudo-rapidity distribution of hadron yields, and find decent agreement with experimental measurements in high-energy Pb+Pb, Au+Au, p+Pb, and d+Au collisions.

hep-ph↗

arXiv2022

Magnetic field induced hair structure in charmonium gluon-dissociation

We study electromagnetic field effect on charmonium gluon-dissociation in quark-gluon plasma. With the effective Hamiltonian derived from QCD multipole expansion under an external electromagnetic field, we first solve the two-body Schrödinger equation for a pair of charm quarks with mean field potentials for color and electromagnetic interactions and obtain the charmonium binding energies and wave functions, and then calculate the gluon-dissociation cross-section and decay width by taking the color electric and magnetic dipole interactions as perturbations above the mean field and employing Fermi's Golden Rule. Considering the charmonium deformation in magnetic field, the discrete Landau energy levels make the dissociation cross-section grow hair, and the electric dipole channel is significantly changed, especially for the $P-$wave states $χ_{c0}$ and $χ_{c\pm}$. From our numerical calculation, the magnetic field strength $eB=5~m_π^2$ already changes the gluon dissociation strongly, which may indicate measurable effects in high-energy nuclear collisions.

nucl-th↗

arXiv2022

Heavy quark potential in quark-gluon Plasma: Deep neural network meets lattice quantum chromodynamics

Bottomonium states are key probes for experimental studies of the quark-gluon plasma (QGP) created in high-energy nuclear collisions. Theoretical models of bottomonium productions in high-energy nuclear collisions rely on the in-medium interactions between the bottom and antibottom quarks. The latter can be characterized by the temperature ($T$) dependent potential, with real ($V_R(T,r)$) and imaginary ($V_I(T,r)$) parts, as a function of the spatial separation ($r$). Recently, the masses and thermal widths of up to $3S$ and $2P$ bottomonium states in QGP were calculated using lattice quantum chromodynamics (LQCD). Starting from these LQCD results and through a novel application of deep neural network, here, we obtain $V_R(T,r)$ and $V_I(T,r)$ in a model-independent fashion. The temperature dependence of $V_R(T,r)$ was found to be very mild between $T\approx0-334$~MeV. For $T=151-334$~MeV, $V_I(T,r)$ shows a rapid increase with $T$ and $r$, which is much larger than the perturbation-theory-based expectations.

hep-ph↗

arXiv2021

Automatic differentiation approach for reconstructing spectral functions with neural networks

Reconstructing spectral functions from Euclidean Green's functions is an important inverse problem in physics. The prior knowledge for specific physical systems routinely offers essential regularization schemes for solving the ill-posed problem approximately. Aiming at this point, we propose an automatic differentiation framework as a generic tool for the reconstruction from observable data. We represent the spectra by neural networks and set chi-square as loss function to optimize the parameters with backward automatic differentiation unsupervisedly. In the training process, there is no explicit physical prior embedding into neural networks except the positive-definite form. The reconstruction accuracy is assessed through Kullback-Leibler(KL) divergence and mean square error(MSE) at multiple noise levels. It should be noted that the automatic differential framework and the freedom of introducing regularization are inherent advantages of the present approach and may lead to improvements of solving inverse problem in the future.

physics.comp-ph↗