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Gang Chen

Publications and source records attributed to Gang Chen.

At least 505 records · Page 28Linked to original sources

$R^4$ corrections to holographic Schwinger effect

We consider $R^4$ corrections to the holographic Schwinger effect in an AdS black hole background and a confining D3-brane background. The potential between a test particle pair are performed for both backgrounds. We find there is no potential barrier in the critical electric field, which means that the system becomes catastrophically unstable. It is shown that for both backgrounds increasing the inverse 't Hooft coupling parameter $1/λ$ enhances the Schwinger effect. We also discuss the possible relation between the Schwinger effect and the viscosity-entropy ratio $η/s$ in strong coupling.

hep-th↗

Possible gapless spin liquid in a rare-earth kagomé lattice magnet Tm$_{3}$Sb$_{3}$Zn$_{2}$O$_{14}$

We report the thermodynamic and muon spin relaxation ($μ$SR) evidences for a possible gapless spin liquid in Tm$_{3}$Sb$_{3}$Zn$_{2}$O$_{14}$, with the rare-earth ions Tm$^{3+}$ forming a two-dimensional kagomé lattice. We extract the magnetic specific heat of Tm$_{3}$Sb$_{3}$Zn$_{2}$O$_{14}$ by subtracting the phonon contribution of the non-magnetic isostructural material La$_{3}$Sb$_{3}$Zn$_{2}$O$_{14}$. We obtain a clear linear-$T$ temperature dependence of magnetic specific heat at low temperatures, with the heat-capacity coefficient $γ$ = 26.6(1) mJ mol-Tm$^{-1}$ K$^{-2}$ in the zero temperature limit. No long-range magnetic order was observed down to 0.35 K in the heat capacity measurement. A broad hump around 9 K was observed in the zero field magnetic specific heat and is gradually suppressed in the magnetic fields that also create a spin gap in the specific heat. The absence of magnetic order is further confirmed by the $μ$SR measurement down to 20 mK. We find that the spin-lattice relaxation time remains constant down to the lowest temperatures. We point out that the physics in Tm$_{3}$Sb$_{3}$Zn$_{2}$O$_{14}$ is fundamentally different from the Cu-based herbertsmithite and propose spin liquid ground states with non-Kramers doublets on the kagomé lattice to account for the experimental results.

cond-mat.str-el↗

Rare-earth chalcogenides: A large family of triangular lattice spin liquid candidate

Frustrated quantum magnets are expected to host many exotic quantum spin states like quantum spin liquid (QSL), and have attracted numerous interest in modern condensed matter physics. The discovery of the triangular lattice spin liquid candidate YbMgGaO$_4$ stimulated an increasing attention on the rare-earth-based frustrated magnets with strong spin-orbit coupling. Here we report the synthesis and characterization of a large family of rare-earth chalcogenides AReCh$_2$ (A = alkali or monovalent ions, Re = rare earth, Ch = O, S, Se). The family compounds share the same structure (R$\bar{3}$m) as YbMgGaO$_4$, and antiferromagnetically coupled rare-earth ions form perfect triangular layers that are well separated along the $c$-axis. Specific heat and magnetic susceptibility measurements on NaYbO$_2$, NaYbS$_2$ and NaYbSe$_2$ single crystals and polycrystals, reveal no structural or magnetic transition down to 50mK. The family, having the simplest structure and chemical formula among the known QSL candidates, removes the issue on possible exchange disorders in YbMgGaO$_4$. More excitingly, the rich diversity of the family members allows tunable charge gaps, variable exchange coupling, and many other advantages. This makes the family an ideal platform for fundamental research of QSLs and its promising applications.

cond-mat.str-el↗

Single string structure and multiple string interaction effect on strange particle production in pp collisions at $\sqrt{s}=7$ TeV

We present a systematic study on the strange particle production at the Large Hadron Collider (LHC) in proton-proton (pp) collisions at $\sqrt{s}=$ 7 TeV based on PACIAE simulations. Two different mechanisms accounting for single string structure variations and multiple string interactions are implemented in the simulations. These modifications give rise to increased effective string tension in the Lund fragmentation model and generate more strange particles in the hadronic final state. By comparing the results with a wealth of the LHC data, it is turned out that the inclusion of variable effective string tension is capable to reach an improved agreement between theory and experiment, especially on the recently observed multiplicity dependence of strangeness enhancement in pp collisions. This approach provides us a new method to understand the microscopic picture of the novel high multiplicity pp events collected at the LHC in the string fragmentation framework.

hep-ph↗

Effective Exploration for Deep Reinforcement Learning via Bootstrapped Q-Ensembles under Tsallis Entropy Regularization

Recently deep reinforcement learning (DRL) has achieved outstanding success on solving many difficult and large-scale RL problems. However the high sample cost required for effective learning often makes DRL unaffordable in resource-limited applications. With the aim of improving sample efficiency and learning performance, we will develop a new DRL algorithm in this paper that seamless integrates entropy-induced and bootstrap-induced techniques for efficient and deep exploration of the learning environment. Specifically, a general form of Tsallis entropy regularizer will be utilized to drive entropy-induced exploration based on efficient approximation of optimal action-selection policies. Different from many existing works that rely on action dithering strategies for exploration, our algorithm is efficient in exploring actions with clear exploration value. Meanwhile, by employing an ensemble of Q-networks under varied Tsallis entropy regularization, the diversity of the ensemble can be further enhanced to enable effective bootstrap-induced exploration. Experiments on Atari game playing tasks clearly demonstrate that our new algorithm can achieve more efficient and effective exploration for DRL, in comparison to recently proposed exploration methods including Bootstrapped Deep Q-Network and UCB Q-Ensemble.

cs.LG↗

Partial-fraction Expansion of Lossless Negative Imaginary Property and A Generalized Lossless Negative Imaginary Lemma

This paper studies a partial-fraction expansion for lossless negative imaginary systems and presents a generalized lossless negative imaginary lemma by allowing poles at zero. First, a necessary and sufficient condition for a system to be non-proper lossless negative imaginary is developed, and a minor partial-fraction expansion of lossless negative imaginary property is studied. Second, according to the minor decomposition properties, two different and new relationships between lossless positive real and lossless negative imaginary systems are established. Third, according to one of the relationships, a generalized lossless negative imaginary lemma in terms of a minimal state-space realization is derived by allowing poles at zero. Some important properties of lossless negative imaginary systems are also studied in this paper, and three numerical examples are provided to illustrate the developed theory

math.OC↗

Emergent quantum criticality from spin-orbital entanglement in $d^8$ Mott insulators: the case of a diamond lattice antiferromagnet

Motivated by the recent activities on the Ni-based diamond lattice antiferromagnet NiRh$_2$O$_4$, we theoretically explore on a general ground the unique spin and orbital physics for the Ni$^{2+}$ ions with a $3d^8$ electron configuration in the tetrahedral crystal field environment and on a diamond lattice Mott insulator. The superexchange interaction between the local moments usually favors magnetic orders. Due to the particular electron configuration of the Ni$^{2+}$ ion with a partially filled upper $t_{2g}$ level and a fully filled lower $e_g$ level, the atomic spin-orbit coupling becomes active at the linear order and would favor a spin-orbital-entangled singlet with quenched local moments in the single-ion limit. Thus, the spin-orbital entanglement competes with the superexchange and could drive the system to a quantum critical point that separates the spin-orbital singlet and the magnetic order. We further explore the effects of magnetic field and uniaxial pressure. The non-trivial response to the magnetic field is intimately tied to the underlying spin-orbital structure of the local moments. We discuss the future experiments such as doping and pressure, and point out the correspondence between different electron configurations.

cond-mat.str-el↗

The Optimality Principle for MR signal excitation and reception: New physical insights into ideal radiofrequency coil design

Purpose: Despite decades of collective experience, radiofrequency coil optimization for MR has remained a largely empirical process, with clear insight into what might constitute truly task-optimal, as opposed to merely 'good,' coil performance being difficult to come by. Here, a new principle, the Optimality Principle, is introduced, which allows one to predict, rapidly and intuitively, the form of optimal current patterns on any surface surrounding any arbitrary body. Theory: The Optimality Principle, in its simplest form, states that the surface current pattern associated with optimal transmit field or receive sensitivity at a point of interest (per unit current integrated over the surface) is a precise scaled replica of the tangential electric field pattern that would be generated on the surface by a precessing spin placed at that point. A more general perturbative formulation enables efficient calculation of the pattern modifications required to optimize signal-to-noise ratio in body-noise-dominated situations. Methods and Results: The unperturbed principle is validated numerically, and convergence of the perturbative formulation is explored in simple geometries. Current patterns and corresponding field patterns in a variety of concrete cases are then used to separate signal and noise effects in coil optimization, to understand the emergence of electric dipoles as strong performers at high frequency, and to highlight the importance of surface geometry in coil design. Conclusion: Like the Principle of Reciprocity from which it is derived, the Optimality Principle offers both a conceptual and a computational shortcut. In addition to providing quantitative targets for coil design, the Optimality Principle affords direct physical insight into the fundamental determinants of coil performance.

physics.ins-det↗

Simultaneously high electron and hole mobilities in cubic boron-V compounds: BP, BAs and BSb

Through first-principles calculations, the phonon-limited transport properties of cubic boron-V compounds (BP, BAs and BSb) are studied. We find that the high optical phonon frequency in these compounds leads to the substantial suppression of polar scattering and the reduction of inter-valley transition mediated by large-wavevector optical phonons, both of which significantly facilitate charge transport. We also discover that BAs simultaneously has a high hole mobility (2110 cm2/V-s) and electron mobility (1400 cm2/V-s) at room temperature, which is rare in semiconductors. Our findings present a new insight in searching high mobility polar semiconductors, and point to BAs as a promising material for electronic and photovoltaic devices in addition to its predicted high thermal conductivity.

cond-mat.mtrl-sci↗

Extended Coulomb liquid of paired hardcore boson model on a pyrochlore lattice

There is a growing interest in the $U(1)$ Coulomb liquid in both quantum materials in pyrochlore ice and cluster Mott insulators and cold atom systems. We explore a paired hardcore boson model on a pyrochlore lattice. This model is equivalent to the XYZ spin model that was proposed for rare-earth pyrochlores with "dipole-octupole" doublets. Since this model has no sign problem for quantum Monte Carlo (QMC) simulations in a large parameter regime, we carry out both analytical and QMC calculations. We find that the $U(1)$ Coulomb liquid is quite stable and spans a rather large portion of the phase diagram with boson pairing. Moreover, we numerically find thermodynamic evidence that the boson pairing could induce a possible $\mathbb{Z}_2$ liquid in the vicinity of the phase boundary between Coulomb liquid and $\mathbb{Z}_2$ symmetry-broken phase. Besides the materials' relevance with quantum spin ice, we point to quantum simulation with cold atoms on optical lattices.

cond-mat.str-el↗

Unusual double-peak specific heat and spin freezing in a spin-2 triangular lattice antiferromagnet FeAl$_{2}$Se$_{4}$

We report the properties of a triangular lattice iron-chalcogenide antiferromagnet FeAl$_{2}$Se$_{4}$. The spin susceptibility reveals a significant antiferromagnetic interaction with a Curie-Weiss temperature Θ$_{CW}$ ~ -200K and a spin-2 local moment. Despite a large spin and a large |Θ$_{CW}$|, the low-temperature behaviors are incompatible with conventional classical magnets. No long-range order is detected down to 0.4K. Similar to the well-known spin-1 magnet NiGa$_{2}$S$_{4}$, the specific heat of FeAl$_{2}$Se$_{4}$ exhibits an unusual double-peak structure and a T$^{2}$ power law at low temperatures, which are attributed to the underlying quadrupolar spin correlations and the Halperin-Saslow modes, respectively. The spin freezing occurs at ~ 14K, below which the relaxation dynamics is probed by the ac susceptibility. Our results are consistent with the early theory for the spin-1 system with Heisenberg and biquadratic spin interactions. We argue that the early proposal of the quadrupolar correlation and gauge glass dynamics may be well extended to FeAl$_{2}$Se$_{4}$. Our results provide useful insights about the magnetic properties of frustrated quantum magnets with high spins.

cond-mat.str-el↗

Engineering a Full Gamut of Structural Colors in All-Dielectric Mesoporous Network Metamaterials

Structural colors are a result of the scattering of certain frequencies of the incident light on micro- or nanoscale features in a material. This is a quite different phenomenon from that of colors produced by absorption of different frequencies of the visible spectrum by pigments or dyes, which is the most common way of coloring used in our daily life. However, structural colors are more robust and can be engineered to span most of the visible spectrum without changing the base material, only its internal structure. They are abundant in nature, with examples as colorful as beetle shells and butterfly wings, but there are few ways of preparing them for large-scale commercial applications for real-world uses. In this work, we present a technique to create a full gamut of structural colors based on a low-cost, robust, and scalable fabrication of periodic network structures in porous alumina as well as the strategy to theoretically predict and engineer different colors on demand. We experimentally demonstrate mesoporous network metamaterial structures with engineered colors spanning the whole optical spectrum and discuss their applications in sensing, environmental monitoring, biomimetic tissues engineering, etc.

physics.optics↗

Selective measurements of intertwined multipolar orders: non-Kramers doublets on a triangular lattice

Motivated by the rapid experimental progress on the spin-orbit-coupled Mott insulators, we propose and study a generic spin model that describes the interaction between the non-Kramers doublets on a triangular lattice and is relevant for triangular lattice rare-earth magnets. We predict that the system supports both pure quadrupolar orders and intertwined multipolar orders in the phase diagram. Besides the multipolar orders, we explore the magnetic excitations to reveal the dynamic properties of the systems. Due to the peculiar properties of the non-Kramers doublets and the selective coupling to the magnetic field, we further study the magnetization process of the system in the magnetic field. We point out the selective measurements of the static and dynamic properties of the intertwined multipolarness in the neutron scattering, NMR and $μ$SR probes and predict the experimental consequences. The relevance to the existing materials such as TmMgGaO$_{4}$, Pr-based and Tb-based magnets, and many ternary chalcogenides is discussed. Our results illustrate the rich physics and the promising direction in the interplay between strong spin-orbit-entangled multipole moments and the geometrical frustration.

cond-mat.str-el↗

Spinon Fermi surface in a cluster Mott insulator model on a triangular lattice and possible application to 1T-TaS$_2$

1T-TaS$_2$ is a cluster Mott insulator on the triangular lattice with 13 Ta atoms forming a star of David cluster as the unit cell. We derive a two dimensional XXZ spin-1/2 model with four-spin ring exchange term to describe the effective low energy physics of a monolayer 1T-TaS$_2$, where the effective spin-1/2 degrees of freedom arises from the Kramers degenerate spin-orbital states on each star of David. A large scale density matrix renormalization group simulation is further performed on this effective model and we find a gapless spin liquid phase with spinon Fermi surface at moderate to large strength region of four-spin ring exchange term. All peaks in the static spin structure factor are found to be located on the "$2k_F$" surface of half-filled spinon on the triangular lattice. Experiments to detect the spinon Fermi surface phase in 1T-TaS$_2$ are discussed.

cond-mat.str-el↗

PANDA: Facilitating Usable AI Development

Recent advances in artificial intelligence (AI) and machine learning have created a general perception that AI could be used to solve complex problems, and in some situations over-hyped as a tool that can be so easily used. Unfortunately, the barrier to realization of mass adoption of AI on various business domains is too high because most domain experts have no background in AI. Developing AI applications involves multiple phases, namely data preparation, application modeling, and product deployment. The effort of AI research has been spent mostly on new AI models (in the model training stage) to improve the performance of benchmark tasks such as image recognition. Many other factors such as usability, efficiency and security of AI have not been well addressed, and therefore form a barrier to democratizing AI. Further, for many real world applications such as healthcare and autonomous driving, learning via huge amounts of possibility exploration is not feasible since humans are involved. In many complex applications such as healthcare, subject matter experts (e.g. Clinicians) are the ones who appreciate the importance of features that affect health, and their knowledge together with existing knowledge bases are critical to the end results. In this paper, we take a new perspective on developing AI solutions, and present a solution for making AI usable. We hope that this resolution will enable all subject matter experts (eg. Clinicians) to exploit AI like data scientists.

cs.AI↗

Rashba and Weyl spin-orbit coupling in an optical lattice clock

Recent experimental realization of one-dimensional (1D) spin-orbit coupling (SOC) for ultracold alkaline-earth(-like) atoms in optical lattice clocks opens a new avenue for exploring exotic quantum matter because of the strongly suppressed heating of atoms from lasers comparing with alkaline atoms. Here we propose a scheme to realize two-dimensional (2D) Rashba and three-dimensional (3D) Weyl types of SOC in a 3D optical lattice clock and explore their topological phases. With 3D Weyl SOC, the system can support topological phases with various numbers as well as types (I or II) of Weyl points. The spin textures of such topological bands for 2D Rashba and 3D Weyl SOC can be detected using suitably designed spectroscopic sequences. Our proposal may pave the way for the experimental realization of robust topological quantum matters and their exotic quasiparticle excitations in ultracold atomic gases.

cond-mat.quant-gas↗

Rafiki: Machine Learning as an Analytics Service System

Big data analytics is gaining massive momentum in the last few years. Applying machine learning models to big data has become an implicit requirement or an expectation for most analysis tasks, especially on high-stakes applications.Typical applications include sentiment analysis against reviews for analyzing on-line products, image classification in food logging applications for monitoring user's daily intake and stock movement prediction. Extending traditional database systems to support the above analysis is intriguing but challenging. First, it is almost impossible to implement all machine learning models in the database engines. Second, expertise knowledge is required to optimize the training and inference procedures in terms of efficiency and effectiveness, which imposes heavy burden on the system users. In this paper, we develop and present a system, called Rafiki, to provide the training and inference service of machine learning models, and facilitate complex analytics on top of cloud platforms. Rafiki provides distributed hyper-parameter tuning for the training service, and online ensemble modeling for the inference service which trades off between latency and accuracy. Experimental results confirm the efficiency, effectiveness, scalability and usability of Rafiki.

cs.DB↗

An Adaptive Clipping Approach for Proximal Policy Optimization

Very recently proximal policy optimization (PPO) algorithms have been proposed as first-order optimization methods for effective reinforcement learning. While PPO is inspired by the same learning theory that justifies trust region policy optimization (TRPO), PPO substantially simplifies algorithm design and improves data efficiency by performing multiple epochs of \emph{clipped policy optimization} from sampled data. Although clipping in PPO stands for an important new mechanism for efficient and reliable policy update, it may fail to adaptively improve learning performance in accordance with the importance of each sampled state. To address this issue, a new surrogate learning objective featuring an adaptive clipping mechanism is proposed in this paper, enabling us to develop a new algorithm, known as PPO-$λ$. PPO-$λ$ optimizes policies repeatedly based on a theoretical target for adaptive policy improvement. Meanwhile, destructively large policy update can be effectively prevented through both clipping and adaptive control of a hyperparameter $λ$ in PPO-$λ$, ensuring high learning reliability. PPO-$λ$ enjoys the same simple and efficient design as PPO. Empirically on several Atari game playing tasks and benchmark control tasks, PPO-$λ$ also achieved clearly better performance than PPO.

cs.LG↗