arXiv subjects

Rui Chen

Publications and source records attributed to Rui Chen.

At least 325 records · Page 18Linked to original sources

arXiv2023

Magnetic field effects on the quantum spin liquid behaviors of NaYbS$_2$

Spin-orbit coupling is an important ingredient to regulate the many-body physics, especially for many spin liquid candidate materials such as rare-earth magnets and Kitaev materials. The rare-earth chalcogenides NaYbCh$_2$ (Ch = O, S, Se) is a congenital frustrating system to exhibit the intrinsic landmark of spin liquid by eliminating both the site disorders between Na$^{+}$ and Yb$^{3+}$ ions with the big ionic size difference and the Dzyaloshinskii-Moriya interaction with the perfect triangular lattice of the Yb$^{3+}$ ions. The temperature versus magnetic-field phase diagram is established by the magnetization, specific heat, and neutron-scattering measurements. Notably, the neutron diffraction spectra and the magnetization curve might provide microscopic evidence for a series of spin configuration for in-plane fields, which include the disordered spin liquid state, 120$^{o}$ antiferromagnet, and one-half magnetization state. Furthermore, the ground state is suggested to be a gapless spin liquid from inelastic neutron scattering, and the magnetic field adjusts the spin orbit coupling. Therefore, the strong spin-orbit coupling in the frustrated quantum magnet substantially enriches low-energy spin physics. This rare-earth family could offer a good platform for exploring the quantum spin liquid ground state and quantum magnetic transitions.

cond-mat.str-el↗

arXiv2023

Close the Optical Sensing Domain Gap by Physics-Grounded Active Stereo Sensor Simulation

In this paper, we focus on the simulation of active stereovision depth sensors, which are popular in both academic and industry communities. Inspired by the underlying mechanism of the sensors, we designed a fully physics-grounded simulation pipeline that includes material acquisition, ray-tracing-based infrared (IR) image rendering, IR noise simulation, and depth estimation. The pipeline is able to generate depth maps with material-dependent error patterns similar to a real depth sensor in real time. We conduct real experiments to show that perception algorithms and reinforcement learning policies trained in our simulation platform could transfer well to the real-world test cases without any fine-tuning. Furthermore, due to the high degree of realism of this simulation, our depth sensor simulator can be used as a convenient testbed to evaluate the algorithm performance in the real world, which will largely reduce the human effort in developing robotic algorithms. The entire pipeline has been integrated into the SAPIEN simulator and is open-sourced to promote the research of vision and robotics communities.

cs.RO↗

arXiv2023

Non-volatile electrically programmable integrated photonics with a 5-bit operation

Scalable programmable photonic integrated circuits (PICs) can potentially transform the current state of classical and quantum optical information processing. However, traditional means of programming, including thermo-optic, free carrier dispersion, and Pockels effect result in either large device footprints or high static energy consumptions, significantly limiting their scalability. While chalcogenide-based non-volatile phase-change materials (PCMs) could mitigate these problems thanks to their strong index modulation and zero static power consumption, they often suffer from large absorptive loss, low cyclability, and lack of multilevel operation. Here, we report a wide-bandgap PCM antimony sulfide (Sb2S3)-clad silicon photonic platform simultaneously achieving low loss, high cyclability, and 5-bit operation. We switch Sb2S3 via an on-chip silicon PIN diode heater and demonstrate components with low insertion loss (<1.0 dB), high extinction ratio (>10 dB), and high endurance (>1,600 switching events). Remarkably, we find that Sb2S3 can be programmed into fine intermediate states by applying identical and thermally isolated pulses, providing a unique approach to controllable multilevel operation. Through dynamic pulse control, we achieve on-demand and accurate 5-bit (32 levels) operations, rendering 0.50 +- 0.16 dB contrast per step. Using this multilevel behavior, we further trim random phase error in a balanced Mach-Zehnder interferometer. Our work opens an attractive pathway toward non-volatile large-scale programmable PICs with low-loss and on-demand multi-bit operations.

physics.optics↗

arXiv2022

Bring Your Own View: Graph Neural Networks for Link Prediction with Personalized Subgraph Selection

Graph neural networks (GNNs) have received remarkable success in link prediction (GNNLP) tasks. Existing efforts first predefine the subgraph for the whole dataset and then apply GNNs to encode edge representations by leveraging the neighborhood structure induced by the fixed subgraph. The prominence of GNNLP methods significantly relies on the adhoc subgraph. Since node connectivity in real-world graphs is complex, one shared subgraph is limited for all edges. Thus, the choices of subgraphs should be personalized to different edges. However, performing personalized subgraph selection is nontrivial since the potential selection space grows exponentially to the scale of edges. Besides, the inference edges are not available during training in link prediction scenarios, so the selection process needs to be inductive. To bridge the gap, we introduce a Personalized Subgraph Selector (PS2) as a plug-and-play framework to automatically, personally, and inductively identify optimal subgraphs for different edges when performing GNNLP. PS2 is instantiated as a bi-level optimization problem that can be efficiently solved differently. Coupling GNNLP models with PS2, we suggest a brand-new angle towards GNNLP training: by first identifying the optimal subgraphs for edges; and then focusing on training the inference model by using the sampled subgraphs. Comprehensive experiments endorse the effectiveness of our proposed method across various GNNLP backbones (GCN, GraphSage, NGCF, LightGCN, and SEAL) and diverse benchmarks (Planetoid, OGB, and Recommendation datasets). Our code is publicly available at \url{https://github.com/qiaoyu-tan/PS2}

cs.IR↗

arXiv2022

Entropy Balancing for Causal Generalization with Target Sample Summary Information

In this paper, we focus on estimating the average treatment effect (ATE) of a target population when individual-level data from a source population and summary-level data (e.g., first or second moments of certain covariates) from the target population are available. In the presence of heterogeneous treatment effect, the ATE of the target population can be different from that of the source population when distributions of treatment effect modifiers are dissimilar in these two populations, a phenomenon also known as covariate shift. Many methods have been developed to adjust for covariate shift, but most require individual covariates from a representative target sample. We develop a weighting approach based on summary-level information from the target sample to adjust for possible covariate shift in effect modifiers. In particular, weights of the treated and control groups within a source sample are calibrated by the summary-level information of the target sample. Our approach also seeks additional covariate balance between the treated and control groups in the source sample. We study the asymptotic behavior of the corresponding weighted estimator for the target population ATE under a wide range of conditions. The theoretical implications are confirmed in simulation studies and a real data application.

stat.ME↗

arXiv2022

Adaptive Risk-Aware Bidding with Budget Constraint in Display Advertising

Real-time bidding (RTB) has become a major paradigm of display advertising. Each ad impression generated from a user visit is auctioned in real time, where demand-side platform (DSP) automatically provides bid price usually relying on the ad impression value estimation and the optimal bid price determination. However, the current bid strategy overlooks large randomness of the user behaviors (e.g., click) and the cost uncertainty caused by the auction competition. In this work, we explicitly factor in the uncertainty of estimated ad impression values and model the risk preference of a DSP under a specific state and market environment via a sequential decision process. Specifically, we propose a novel adaptive risk-aware bidding algorithm with budget constraint via reinforcement learning, which is the first to simultaneously consider estimation uncertainty and the dynamic risk tendency of a DSP. We theoretically unveil the intrinsic relation between the uncertainty and the risk tendency based on value at risk (VaR). Consequently, we propose two instantiations to model risk tendency, including an expert knowledge-based formulation embracing three essential properties and an adaptive learning method based on self-supervised reinforcement learning. We conduct extensive experiments on public datasets and show that the proposed framework outperforms state-of-the-art methods in practical settings.

cs.IR↗

arXiv2022

TANGO: Text-driven Photorealistic and Robust 3D Stylization via Lighting Decomposition

Creation of 3D content by stylization is a promising yet challenging problem in computer vision and graphics research. In this work, we focus on stylizing photorealistic appearance renderings of a given surface mesh of arbitrary topology. Motivated by the recent surge of cross-modal supervision of the Contrastive Language-Image Pre-training (CLIP) model, we propose TANGO, which transfers the appearance style of a given 3D shape according to a text prompt in a photorealistic manner. Technically, we propose to disentangle the appearance style as the spatially varying bidirectional reflectance distribution function, the local geometric variation, and the lighting condition, which are jointly optimized, via supervision of the CLIP loss, by a spherical Gaussians based differentiable renderer. As such, TANGO enables photorealistic 3D style transfer by automatically predicting reflectance effects even for bare, low-quality meshes, without training on a task-specific dataset. Extensive experiments show that TANGO outperforms existing methods of text-driven 3D style transfer in terms of photorealistic quality, consistency of 3D geometry, and robustness when stylizing low-quality meshes. Our codes and results are available at our project webpage https://cyw-3d.github.io/tango/.

cs.CV↗

arXiv2022

A new group of doubly charmed molecule with $T$-doublet charmed meson pair

Inspired by the observation of the doubly charmed tetraquark state $T_{cc}^+$ at the LHCb Collaboration, we systematically study the $S$-wave interactions between a pair of charmed mesons ($D_{1},\,D_{2}^{\ast}$) in the $T$-doublet, where we adopt the one-boson-exchange model and consider both the $S$-$D$ wave mixing and coupled channel effects. Our numerical results suggest that the prime doubly charmed molecular tetraquark candidates are the $S$-wave $D_1D_1$ state with $I(J^P)=0(1^+)$, the $S$-wave $D_1{D}_2^{\ast}$ states with $I(J^P)=0(1^+,\,2^+,\,3^+)$, and the $S$-wave ${D}_2^{\ast}{D}_2^{\ast}$ states with $I(J^P)=0(1^+,\,3^+)$. The $S$-wave $D_1D_1$ state with $I(J^P)=1(2^+)$, the $S$-wave $D_1{D}_2^{\ast}$ state with $I(J^P)=1(3^+)$, and the $S$-wave ${D}_2^{\ast}{D}_2^{\ast}$ state with $I(J^P)=1(4^+)$ may be the possible isovector doubly charmed molecular tetraquark candidates. We expect the experiments like the LHCb or Belle II collaborations to search for these predicted doubly charmed molecular tetraquarks near the $D_1D_1$, $D_1D_2^*$, and $D_2^*D_2^*$ thresholds in future.

hep-ph↗

arXiv2022

Controlled Ordering of Room-Temperature Magnetic Skyrmions in a Polar Van der Waals Magnet

Control and understanding of ensembles of skyrmions is important for realization of future technologies. In particular, the order-disorder transition associated with the 2D lattice of magnetic skyrmions can have significant implications for transport and other dynamic functionalities. To date, skyrmion ensembles have been primarily studied in bulk crystals, or as isolated skyrmions in thin film devices. Here, we investigate the condensation of the skyrmion phase at room temperature and zero field in a polar, Van der Waals magnet. We demonstrate that we can engineer an ordered skyrmion crystal through structural confinement on the $μ$m scale, showing control over this order-disorder transition on scales relevant for device applications.

cond-mat.mtrl-sci↗

arXiv2022

Density-driven higher-order topological phase transitions in amorphous solids

Amorphous topological states, which are independent of the specific spatial distribution of microscopic constructions, have gained much attention. Recently, higher-order topological insulators, which are a new class of topological phases of matter, have been proposed in amorphous systems. Here, we propose a density-driven higher-order topological phase transition in a two-dimensional amorphous system. We demonstrate that the amorphous system hosts a topological trivial phase at low density. With an increase in the density of lattice sites, the topological trivial phase converts to a higher-order topological phase characterized by a quantized quadrupole moment and the existence of topological corner states. Furthermore, we confirm that the density-driven higher-order topological phase transition is size dependent. In addition, our results should be general and equally applicable to three-dimensional amorphous systems. Our findings may greatly enrich the study of higher-order topological states in amorphous systems.

cond-mat.mes-hall↗

arXiv2022

Safe Interactive Industrial Robots using Jerk-based Safe Set Algorithm

The need to increase the flexibility of production lines is calling for robots to collaborate with human workers. However, existing interactive industrial robots only guarantee intrinsic safety (reduce collision impact), but not interactive safety (collision avoidance), which greatly limited their flexibility. The issue arises from two limitations in existing control software for industrial robots: 1) lack of support for real-time trajectory modification; 2) lack of intelligent safe control algorithms with guaranteed collision avoidance under robot dynamics constraints. To address the first issue, a jerk-bounded position controller (JPC) was developed previously. This paper addresses the second limitation, on top of the JPC. Specifically, we introduce a jerk-based safe set algorithm (JSSA) to ensure collision avoidance while considering the robot dynamics constraints. The JSSA greatly extends the scope of the original safe set algorithm, which has only been applied for second-order systems with unbounded accelerations. The JSSA is implemented on the FANUC LR Mate 200id/7L robot and validated with HRI tasks. Experiments show that the JSSA can consistently keep the robot at a safe distance from the human while executing the designated task.

cs.RO↗

arXiv2022

Task-Agnostic Adaptation for Safe Human-Robot Handover

Human-robot interaction (HRI) is an important component to improve the flexibility of modern production lines. However, in real-world applications, the task (\ie the conditions that the robot needs to operate on, such as the environmental lighting condition, the human subjects to interact with, and the hardware platforms) may vary and it remains challenging to optimally and efficiently configure and adapt the robotic system under these changing tasks. To address the challenge, this paper proposes a task-agnostic adaptable controller that can 1) adapt to different lighting conditions, 2) adapt to individual behaviors and ensure safety when interacting with different humans, and 3) enable easy transfer across robot platforms with different control interfaces. The proposed framework is tested on a human-robot handover task using the FANUC LR Mate 200id/7L robot and the Kinova Gen3 robot. Experiments show that the proposed task-agnostic controller can achieve consistent performance across different tasks.

cs.RO↗

arXiv2022

Multilinear Sets with Two Monomials and Cardinality Constraints

Binary polynomial optimization is equivalent to the problem of minimizing a linear function over the intersection of the multilinear set with a polyhedron. Many families of valid inequalities for the multilinear set are available in the literature, though giving a polyhedral characterization of the convex hull is not tractable in general as binary polynomial optimization is NP-hard. In this paper, we study the cardinality constrained multilinear set in the special case when the number of monomials is exactly two. We give an extended formulation, with two more auxiliary variables and exponentially many inequalities, of the convex hull of solutions of the standard linearization of this problem. We also show that the separation problem can be solved efficiently.

math.OC↗

arXiv2022

Half-Quantized Hall Effect at the Parity-Invariant Fermi Surface

Condensed matter realization of a single Dirac cone of fermions in two dimensions is a long-standing issue. Here we report the discovery of a single gapless Dirac cone of half-quantized Hall conductance in a magnetically-doped topological insulator heterostructure. It demonstrates that the Hall conductance is half-quantized in the unit e^{2}/h when the parity symmetry is invariant near the Fermi surface. The gapless Dirac point is stable and protected by the local parity symmetry and the topologically nontrivial band structure of the topological insulator. The one-half Hall conductance observed in a recent experiment [Mogi et al, Nat. Phys. 18, 390 (2022)] is attributed to the existence of the gapless Dirac cone. The results suggest a condensed matter realization of a topological phase with a one-half topological invariant.

cond-mat.mes-hall↗

arXiv2022

Unitary Friedberg-Jacquet periods

The main goal of this paper is to study the unitary Friedberg-Jacquet period through their connection with the unitary Shalika period. Locally we study the multiplicity of unitary Friedberg-Jacquet periods for discrete series. Globally we prove one direction of a conjecture of Xiao-Zhang, stating that the non-vanishing of a global unitary Friedberg-Jacquet period implies the non-vanishing of the central value of the (twisted) standard L-function.

math.RT↗

arXiv2022

Twisted Gan-Gross-Prasad conjecture for certain tempered L-packets

In this paper, we investigate the twisted GGP conjecture for certain tempered representations using the theta correspondence and establish some special cases, namely when the L-parameter of the unitary group is the sum of conjugate-dual characters of the appropriate sign.

math.RT↗

arXiv2022

From the isovector molecular explanation of the newly $T_{c\bar{s}}^{a0(++)}(2900)$ to possible charmed-strange molecular pentaquarks

In this work, we adopt the one-boson-exchange model to study the $D^{(*)}K^{(*)}$ interactions. With the same parameters, we can simultaneously reproduce the masses of the $D_{s0}(2317)$, $D_{s1}(2460)$, and $T_{c\bar{s}}^{a0(++)}(2900)$ recently observed by the LHCb collaboration in the hadronic molecular picture, where the $D_{s0}(2317)$, $D_{s1}(2460)$, and $T_{c\bar{s}}^{a0(++)}(2900)$ are regarded as the $DK[I(J^P)=0(0^+)]$, $D^*K[0(1^+)]$, and $D^*K^*[1(0^+)]$ charmed-strange molecular states, respectively. In addition, we extend to study the $Λ_cK^{(*)}$ and $Σ_cK^{(*)}$ interactions and predict two possible charmed-strange molecular pentaquarks, the single $Σ_cK^*$ state with $I(J^P)=1/2(1/2^-)$ and $3/2(3/2^-)$. After considering the coupled channel effects, our results show that the coupled $Λ_cK^*/Σ_cK^*$ molecular state with $I(J^P)=1/2(1/2^-)$ and the coupled $Σ_cK/Λ_cK^*$ molecular state with $I(J^P)=1/2(1/2^-)$ can be good hadronic molecular candidates, the $Λ_cK^*({}^2S_{1/2})$ and $Σ_cK({}^2S_{1/2})$ are the dominant channels, respectively.

hep-ph↗

arXiv2022

Layer Hall effect induced by hidden Berry curvature in antiferromagnetic insulators

The layer Hall effect describes electrons spontaneously deflected to opposite sides at different layers, which has been experimentally reported in the MnBi$_2$Te$_4$ thinfilms under perpendicular electric fields [Gao et al., Nature 595, 521 (2021)]. Here, we reveal a universal origin of the layer Hall effect in terms of the so-called hidden Berry curvature, as well as material design principles. Hence, it gives rise to zero Berry curvature in momentum space but nonzero layer-locked hidden Berry curvature in real space. We show that compared to that of a trivial insulator, the layer Hall effect is significantly enhanced in antiferromagnetic topological insulators. Our universal picture provides a paradigm for revealing the hidden physics as a result of the interplay between the global and local symmetries, and can be generalized in various scenarios.

cond-mat.mes-hall↗