arXiv subjects

Hua Zheng

Publications and source records attributed to Hua Zheng.

At least 73 records · Page 4Linked to original sources

arXiv2021

Centrality and transverse momentum dependence of hadrons in Pb+Pb collisions at LHC

The transverse momentum spectra of seven identified hadrons produced in Pb+Pb collisions at $\sqrt{s_{NN}}=2.76$ and 5.02 TeV at the CERN Large Hadron Collider (LHC) have been investigated in the framework of the recombination model (RM). Soft, semihard and hard partons all play important roles in our model and are uniformly treated for all hadrons produced.The investigation has been extended to non-central collisions and the parameters controlling the momentum degradation of semihard partons have been tuned. Our study shows good agreement between theoretical results and experimental data. To be able to provide a coherent explanation for the production of all identified hadrons ($π$, p, K, $Λ$, $ϕ$, $Ξ$, $Ω$) for transverse momenta as high as 14 GeV/c (for $π$, p and K), and for all centralities, is an unprecedented achievement that supports the RM as a sensible model to combine various mechanisms of parton production with a universal scheme of hadronization.

hep-ph↗

arXiv2021

Incorporating Connections Beyond Knowledge Embeddings: A Plug-and-Play Module to Enhance Commonsense Reasoning in Machine Reading Comprehension

Conventional Machine Reading Comprehension (MRC) has been well-addressed by pattern matching, but the ability of commonsense reasoning remains a gap between humans and machines. Previous methods tackle this problem by enriching word representations via pre-trained Knowledge Graph Embeddings (KGE). However, they make limited use of a large number of connections between nodes in Knowledge Graphs (KG), which could be pivotal cues to build the commonsense reasoning chains. In this paper, we propose a Plug-and-play module to IncorporatE Connection information for commonsEnse Reasoning (PIECER). Beyond enriching word representations with knowledge embeddings, PIECER constructs a joint query-passage graph to explicitly guide commonsense reasoning by the knowledge-oriented connections between words. Further, PIECER has high generalizability since it can be plugged into suitable positions in any MRC model. Experimental results on ReCoRD, a large-scale public MRC dataset requiring commonsense reasoning, show that PIECER introduces stable performance improvements for four representative base MRC models, especially in low-resource settings.

cs.CL↗

arXiv2020

Personalized Multimorbidity Management for Patients with Type 2 Diabetes Using Reinforcement Learning of Electronic Health Records

Comorbid chronic conditions are common among people with type 2 diabetes. We developed an Artificial Intelligence algorithm, based on Reinforcement Learning (RL), for personalized diabetes and multi-morbidity management with strong potential to improve health outcomes relative to current clinical practice. In this paper, we modeled glycemia, blood pressure and cardiovascular disease (CVD) risk as health outcomes using a retrospective cohort of 16,665 patients with type 2 diabetes from New York University Langone Health ambulatory care electronic health records in 2009 to 2017. We trained a RL prescription algorithm that recommends a treatment regimen optimizing patients' cumulative health outcomes using their individual characteristics and medical history at each encounter. The RL recommendations were evaluated on an independent subset of patients. The results demonstrate that the proposed personalized reinforcement learning prescriptive framework for type 2 diabetes yielded high concordance with clinicians' prescriptions and substantial improvements in glycemia, blood pressure, cardiovascular disease risk outcomes.

cs.CY↗

arXiv2020

Inductively Representing Out-of-Knowledge-Graph Entities by Optimal Estimation Under Translational Assumptions

Conventional Knowledge Graph Completion (KGC) assumes that all test entities appear during training. However, in real-world scenarios, Knowledge Graphs (KG) evolve fast with out-of-knowledge-graph (OOKG) entities added frequently, and we need to represent these entities efficiently. Most existing Knowledge Graph Embedding (KGE) methods cannot represent OOKG entities without costly retraining on the whole KG. To enhance efficiency, we propose a simple and effective method that inductively represents OOKG entities by their optimal estimation under translational assumptions. Given pretrained embeddings of the in-knowledge-graph (IKG) entities, our method needs no additional learning. Experimental results show that our method outperforms the state-of-the-art methods with higher efficiency on two KGC tasks with OOKG entities.

cs.CL↗

arXiv2020

Green Simulation Assisted Reinforcement Learning with Model Risk for Biomanufacturing Learning and Control

Biopharmaceutical manufacturing faces critical challenges, including complexity, high variability, lengthy lead time, and limited historical data and knowledge of the underlying system stochastic process. To address these challenges, we propose a green simulation assisted model-based reinforcement learning to support process online learning and guide dynamic decision making. Basically, the process model risk is quantified by the posterior distribution. At any given policy, we predict the expected system response with prediction risk accounting for both inherent stochastic uncertainty and model risk. Then, we propose green simulation assisted reinforcement learning and derive the mixture proposal distribution of decision process and likelihood ratio based metamodel for the policy gradient, which can selectively reuse process trajectory outputs collected from previous experiments to increase the simulation data-efficiency, improve the policy gradient estimation accuracy, and speed up the search for the optimal policy. Our numerical study indicates that the proposed approach demonstrates the promising performance.

cs.LG↗

arXiv2019

Extending the dynamic strain sensing rang of phase-OTDR with frequency modulation pulse and frequency interrogation

We propose and experimentally demonstrate a technique to extend the dynamic sensing range of phase sensitive optical time domain reflectometry system based on the frequency interrogation. Benefitting from the range Doppler coupling feature, the frequency modulation pulse is capable of measuring the frequency shift induced by the dynamic strain, thus the large dynamic strain can be recovered. The performance of the proposed method is experimentally evaluated by comparing it with phase unwrapping. The strain sensing rang can at least be increased by factor of hundreds, and fast dynamic strain with peak to peak 130 microstrain vibration frequency of 20 kHz is measured.

physics.app-ph↗

arXiv2019

Reinforcement Learning for Market Making in a Multi-agent Dealer Market

Market makers play an important role in providing liquidity to markets by continuously quoting prices at which they are willing to buy and sell, and managing inventory risk. In this paper, we build a multi-agent simulation of a dealer market and demonstrate that it can be used to understand the behavior of a reinforcement learning (RL) based market maker agent. We use the simulator to train an RL-based market maker agent with different competitive scenarios, reward formulations and market price trends (drifts). We show that the reinforcement learning agent is able to learn about its competitor's pricing policy; it also learns to manage inventory by smartly selecting asymmetric prices on the buy and sell sides (skewing), and maintaining a positive (or negative) inventory depending on whether the market price drift is positive (or negative). Finally, we propose and test reward formulations for creating risk averse RL-based market maker agents.

q-fin.TR↗

arXiv2019

Global-Local Metamodel Assisted Two-Stage Optimization via Simulation

To integrate strategic, tactical and operational decisions, the two-stage optimization has been widely used to guide dynamic decision making. In this paper, we study the two-stage stochastic programming for complex systems with unknown response estimated by simulation. We introduce the global-local metamodel assisted two-stage optimization via simulation that can efficiently employ the simulation resource to iteratively solve for the optimal first- and second-stage decisions. Specifically, at each visited first-stage decision, we develop a local metamodel to simultaneously solve a set of scenario-based second-stage optimization problems, which also allows us to estimate the optimality gap. Then, we construct a global metamodel accounting for the errors induced by: (1) using a finite number of scenarios to approximate the expected future cost occurring in the planning horizon, (2) second-stage optimality gap, and (3) finite visited first-stage decisions. Assisted by the global-local metamodel, we propose a new simulation optimization approach that can efficiently and iteratively search for the optimal first- and second-stage decisions. Our framework can guarantee the convergence of optimal solution for the discrete two-stage optimization with unknown objective, and the empirical study indicates that it achieves substantial efficiency and accuracy.

math.OC↗

arXiv2019

Systematic investigation of the particle spectra in Heavy-ion collisions at the Large Hadron Collider

We investigate the charged particle spectra produced in the heavy-ion collisions at nine centralities from different systems, i.e., Pb+Pb at $\sqrt{s_{NN}}=2.76$ TeV and 5.02 TeV as well as Xe+Xe at $\sqrt{s_{NN}}=5.44$ TeV, at Large Hadron Collider (LHC) using one empirical formula inspired by the solution of the Fokker-Planck equation, dubbed as the generalized Fokker-Planck solution (GFPS). Our results show that the GFPS can reproduce the experimental particle spectrum up to transverse momentum $p_T$ about 45 GeV/c with the maximum discrepancy 30\% covering 10 orders of magnitude. The discrepancy between the data and the results from the GFPS decreases to 15\% when the maximum of the charged particle transverse momentum is cut to 20 GeV/c. We confirmed that the Tsallis distribution derived from the non-extensive statistics, which can reproduce the particle spectra produced in small collision systems, such as p+p, up to few hundreds GeV/c, can only apply to systematically study the particle spectra up to 8 GeV/c in A+A collisions at LHC, as pointed out in the study of identified particle spectra in Pb+Pb collisions at $\sqrt{s_{NN}}=2.76$ TeV. The possible explanation why GFPS functions well is also discussed.

nucl-th↗

arXiv2019

The symmetry energy of the nuclear EoS: a study of collective motion and low-energy reaction dynamics in semiclassical approaches

In the framework of mean-field based transport approaches, we discuss recent results concerning collective motion and low-energy heavy ion reactions involving neutron-rich systems. We focus on aspects which are particularly sensitive to the isovector terms of the nuclear effective interaction and the corresponding symmetry energy. As far as collective excitations are concerned, we discuss the mixed nature of dipole oscillations in neutron-rich systems. On the other hand, for reactions close to the Coulomb barrier, we investigate the structure of pre-equilibrium collective dipole oscillations, focusing on their sensitivity to the symmetry energy behavior below normal density. Nucleon emission is also considered within the same context. The possible impact of other relevant terms of the nuclear effective interaction on these mechanisms is also examined. From this analysis we expect to put further constraints on the nuclear Equation of State, of crucial importance also in the astrophysical context.

nucl-th↗

arXiv2018

Centrality and Transverse momentum dependencies of Hadrons in Xe+Xe collisions at $\sqrt{s_{NN}}=5.44$ TeV from a multi-phase transport model

In this paper, we study and predict the charged-particle pseudorapidity multiplicity density ($\frac{dN_{ch}}{dη}$), transverse momentum spectra of identified particles and their ratios in relativistic heavy ion collisions at the Large Hadron Collider (LHC), using the string-melting version of a multi-phase transport (AMPT) model with improved quark coalescence method. Results of the charged-particle pseudorapidity multiplicity density from AMPT model calculations for Pb+Pb collisions at $\sqrt{s_{NN}}=5.02$ TeV are compared with the experimental data. Good agreements are generally found between theoretical calculations and experimental data. We predict $\frac{dN_{ch}}{dη}$ for Xe+Xe collisions at $\sqrt{s_{NN}}=5.44$ TeV at different centralities, and $p_T$ spectra of charged pions, kaons and protons, and their ratios $K/π$ and $p/π$ in Pb+Pb collisions at $\sqrt{s_{NN}}=5.02$ TeV and Xe+Xe collisions at $\sqrt{s_{NN}}=5.44$ TeV that are being studied at LHC. The $p_T$ spectra of identified particles in Pb+Pb collisions from the improved AMPT model are compared and found to be consistent with results from the iEBE-VISHNU hybrid model with TRENTo initial condition.

hep-ph↗

arXiv2018

Spectra and flow of light nuclei in relativistic heavy ion collisions at RHIC and the LHC

Within the framework of the coalescence model based on the phase-space distributions of protons and neutrons generated from the {\tt iEBE-VISHNU} hybrid model with {\tt AMPT} initial conditions, we study the spectra and elliptic flow of deuterons and helium-3 in relativistic heavy ion collisions at the Relativistic Heavy Ion Collider (RHIC) and the Larger Hadron Collider (LHC). Results from our model calculations for Au + Au collisions at $\sqrt{s_{NN}}=200$ GeV at RHIC and Pb+Pb collisions at $\sqrt{s_{NN}}=2.76$ TeV at the LHC are compared with available experimental data. Good agreements are generally seen between theoretical results and experimental data, except that the calculated yield of helium-3 in Pb + Pb collisions at $\sqrt{s_{NN}}=2.76$ TeV underestimates the data by about a factor of two. Possible reasons for these discrepancies are discussed. We also make predictions on the spectra and elliptic flow of deuterons and helium-3 in Pb + Pb collisions at $\sqrt{s_{NN}}=5.02$ TeV that are being studied at LHC.

nucl-th↗

arXiv2018

Long range fading free phase-sensitive reflectometry based on multi-frequency NLFM pulse

A long range phase-sensitive optical time domain reflectometer (phi-OTDR) with a multi-frequency non-linear frequency modulation (NLFM) optical pulse is proposed in this Letter. To boost the pulse energy while suppressing the optical nonlinear effects, the distortion of the amplified pulse is rectified, and a three-tone pulse is used. Combining with the NLFM technic which provides 42.7 dB side lobe suppression ration (SLSR), these two approaches guarantee that a sensing distance of 80 km is achieved in the experiment with 2.5 m spatial resolution, 49.6 dB dynamic range, and 45 dB phase signal-to-noise ratio (SNR). To the best of our knowledge, this is the first time that a phase-demodulated phi-OTDR over such a long sensing range has been reported with un-pumped sensing fiber.

physics.ins-det↗

arXiv2018

Distributed fiber sparse-wideband vibration sensing by sub-Nyquist additive random sampling

The round trip time of the light pulse limits the maximum detectable vibration frequency response range of phase-sensitive optical time domain reflectometry (ϕ-OTDR). Unlike the uniform laser pulse interval in conventional ϕ-OTDR, we randomly modulate the pulse interval, so that an equivalent sub-Nyquist additive random sampling (sNARS) is realized for every sensing point of the long interrogation fiber. For an ϕ-OTDR system with 10 km sensing length, the sNARS method is optimized by theoretical analysis and Monte Carlo simulation, and the experimental results verify that a wide-band spars signal can be identified and reconstructed. Such a method can broaden the vibration frequency response range of ϕ-OTDR, which is of great significance in sparse-wideband-frequency vibration signal detection, such as rail track monitoring and metal defect detection.

physics.ins-det↗

arXiv2017

Light nuclei production in Pb+Pb collisions at $\sqrt{s_{NN}}=2.76$ TeV

Using the coalescence model based on the phase-space distribution of nucleons from an extended blast-wave model that includes the space-momentum correlation of high momentum nucleons, we study the transverse momentum spectra and elliptic flows of deuteron and helium-3 in Pb+Pb collisions at the energy $\sqrt{s_{NN}}=2.76$ TeV. We find that the measured elliptic flows of deuteron can be satisfactorily described if nucleons of large transverse momenta are more spread in space when their momenta are more aligned along the reaction plane.

nucl-th↗

arXiv2017

A new two-component model for hadron production in heavy-ion collisions

Using the experimental data from the ALICE program on the centrality dependence of the transverse momentum ($p_T$) spectra in Pb+Pb collisions at $\sqrt{s_{NN}}=2.76$ TeV, we show that the double-Tsallis distribution and the generalized Fokker-Plank (FP) solution can not describe the spectra of pions, kaons and protons from central to peripheral collisions in the entire $p_T$ region, simultaneously. Hence, a new two-component distribution, which is a hydrodynamic extension of the generalized FP solution accounting for the collective motion effect in heavy-ion collisions, is proposed in order to reproduce all the particle spectra. Our results suggest that the particle production dynamics may be different for different particles, especially at very low $p_T$ region.

nucl-th↗

arXiv2017

Breaking through the bandwidth barrier in distributed fiber vibration sensing by sub-Nyquist randomized sampling

The round trip time of the light pulse limits the maximum detectable frequency response range of vibration in phase-sensitive optical time domain reflectometry (ϕ-OTDR). We propose a method to break the frequency response range restriction of ϕ-OTDR system by modulating the light pulse interval randomly which enables a random sampling for every vibration point in a long sensing fiber. This sub-Nyquist randomized sampling method is suits for detecting sparse-wideband-frequency vibration signals. Up to MHz resonance vibration signal with over dozens of frequency components and 1.153MHz single frequency vibration signal are clearly identified for a sensing range of 9.6km with 10kHz maximum sampling rate.

physics.ins-det↗

arXiv2013

Coulomb corrections to density and temperature of bosons in heavy ion collisions

A recently proposed method, based on quadrupole and multiplicity fluctuations in heavy ion collisions, is modified in order to take into account distortions due to the Coulomb field. This is particularly interesting for bosons produced in heavy ion collisions, such as $d$ and $α$ particles. We derive temperatures and densities seen by the bosons and compare to similar calculations for fermions. The resulting energy densities agree rather well with each other and with the one derived from neutrons. This suggests that a common phenomenon, such as the sudden opening of many reaction channels and/or a liquid gas phase transition, is responsible for the agreement.

nucl-th↗