arXiv subjects

Jiong Yang

Publications and source records attributed to Jiong Yang.

At least 37 records · Page 2Linked to original sources

arXiv2024

Magnetic structure and Ising-like antiferromagnetism in the bilayer triangular lattice compound NdZnPO

The complex interplay of spin frustration and quantum fluctuations in low-dimensional quantum materials leads to a variety of intriguing phenomena. This research focuses on a detailed analysis of the magnetic behavior exhibited by NdZnPO, a bilayer spin-1/2 triangular lattice antiferromagnet. The investigation employs magnetization, specific heat, and powder neutron scattering measurements. At zero field, a long-range magnetic order is observed at $T_{\rm N}=1.64~\rm K$. Powder neutron diffraction experiments show the Ising-like magnetic moments along the $c$-axis, revealing a stripe-like magnetic structure with three equivalent magnetic propagation vectors. Application of a magnetic field along the $c$-axis suppresses the antiferromagnetic order, leading to a fully polarized ferromagnetic state above $B_{\rm c}=4.5~\rm T$. This transition is accompanied by notable enhancements in the nuclear Schottky contribution. Moreover, the absence of spin frustration and expected field-induced plateau-like phases are remarkable observations. Detailed calculations of magnetic dipolar interactions revealed complex couplings reminiscent of a honeycomb lattice, suggesting the potential emergence of Kitaev-like physics within this system. This comprehensive study of the magnetic properties of NdZnPO highlights unresolved intricacies, underscoring the imperative for further exploration to unveil the underlying governing mechanisms.

cond-mat.str-el↗

arXiv2023

Spring-IMU Fusion Based Proprioception for Feedback Control of Soft Manipulators

This paper presents a novel framework to realize proprioception and closed-loop control for soft manipulators. Deformations with large elongation and large bending can be precisely predicted using geometry-based sensor signals obtained from the inductive springs and the inertial measurement units (IMUs) with the help of machine learning techniques. Multiple geometric signals are fused into robust pose estimations, and a data-efficient training process is achieved after applying the strategy of sim-to-real transfer. As a result, we can achieve proprioception that is robust to the variation of external loading and has an average error of 0.7% across the workspace on a pneumatic-driven soft manipulator. The realized proprioception on soft manipulator is then contributed to building a sensor-space based algorithm for closed-loop control. A gradient descent solver is developed to drive the end-effector to achieve the required poses by iteratively computing a sequence of reference sensor signals. A conventional controller is employed in the inner loop of our algorithm to update actuators (i.e., the pressures in chambers) for approaching a reference signal in the sensor-space. The systematic function of closed-loop control has been demonstrated in tasks like path following and pick-and-place under different external loads.

cs.RO↗

arXiv2023

BOTT: Box Only Transformer Tracker for 3D Object Tracking

Tracking 3D objects is an important task in autonomous driving. Classical Kalman Filtering based methods are still the most popular solutions. However, these methods require handcrafted designs in motion modeling and can not benefit from the growing data amounts. In this paper, Box Only Transformer Tracker (BOTT) is proposed to learn to link 3D boxes of the same object from the different frames, by taking all the 3D boxes in a time window as input. Specifically, transformer self-attention is applied to exchange information between all the boxes to learn global-informative box embeddings. The similarity between these learned embeddings can be used to link the boxes of the same object. BOTT can be used for both online and offline tracking modes seamlessly. Its simplicity enables us to significantly reduce engineering efforts required by traditional Kalman Filtering based methods. Experiments show BOTT achieves competitive performance on two largest 3D MOT benchmarks: 69.9 and 66.7 AMOTA on nuScenes validation and test splits, respectively, 56.45 and 59.57 MOTA L2 on Waymo Open Dataset validation and test splits, respectively. This work suggests that tracking 3D objects by learning features directly from 3D boxes using transformers is a simple yet effective way.

cs.CV↗

arXiv2023

Explaining SAT Solving Using Causal Reasoning

The past three decades have witnessed notable success in designing efficient SAT solvers, with modern solvers capable of solving industrial benchmarks containing millions of variables in just a few seconds. The success of modern SAT solvers owes to the widely-used CDCL algorithm, which lacks comprehensive theoretical investigation. Furthermore, it has been observed that CDCL solvers still struggle to deal with specific classes of benchmarks comprising only hundreds of variables, which contrasts with their widespread use in real-world applications. Consequently, there is an urgent need to uncover the inner workings of these seemingly weak yet powerful black boxes. In this paper, we present a first step towards this goal by introducing an approach called CausalSAT, which employs causal reasoning to gain insights into the functioning of modern SAT solvers. CausalSAT initially generates observational data from the execution of SAT solvers and learns a structured graph representing the causal relationships between the components of a SAT solver. Subsequently, given a query such as whether a clause with low literals blocks distance (LBD) has a higher clause utility, CausalSAT calculates the causal effect of LBD on clause utility and provides an answer to the question. We use CausalSAT to quantitatively verify hypotheses previously regarded as "rules of thumb" or empirical findings such as the query above. Moreover, CausalSAT can address previously unexplored questions, like which branching heuristic leads to greater clause utility in order to study the relationship between branching and clause management. Experimental evaluations using practical benchmarks demonstrate that CausalSAT effectively fits the data, verifies four "rules of thumb", and provides answers to three questions closely related to implementing modern solvers.

cs.AI↗

arXiv2023

Rounding Meets Approximate Model Counting

The problem of model counting, also known as #SAT, is to compute the number of models or satisfying assignments of a given Boolean formula $F$. Model counting is a fundamental problem in computer science with a wide range of applications. In recent years, there has been a growing interest in using hashing-based techniques for approximate model counting that provide $(\varepsilon, δ)$-guarantees: i.e., the count returned is within a $(1+\varepsilon)$-factor of the exact count with confidence at least $1-δ$. While hashing-based techniques attain reasonable scalability for large enough values of $δ$, their scalability is severely impacted for smaller values of $δ$, thereby preventing their adoption in application domains that require estimates with high confidence. The primary contribution of this paper is to address the Achilles heel of hashing-based techniques: we propose a novel approach based on rounding that allows us to achieve a significant reduction in runtime for smaller values of $δ$. The resulting counter, called RoundMC, achieves a substantial runtime performance improvement over the current state-of-the-art counter, ApproxMC. In particular, our extensive evaluation over a benchmark suite consisting of 1890 instances shows that RoundMC solves 204 more instances than ApproxMC, and achieves a $4\times$ speedup over ApproxMC.

cs.AI↗

arXiv2023

Giant phonon softening and avoided crossing in aliovalence-doped heavy-band thermoelectrics

Aliovalent doping has been adopted to optimize the electrical properties of semiconductors, while its impact on the phonon structure and propagation is seldom paid proper attention to. This work reveals that aliovalent doping can be much more effective in reducing the lattice thermal conductivity of thermoelectric semiconductors than the commonly employed isoelectronic alloying strategy. As demonstrated in the heavy-band NbFeSb system, a large reduction of 65% in the lattice thermal conductivity is achieved through only 10% aliovalent Hf-doping, compared to the 4 times higher isoelectronic Ta-alloying. It is elucidated that aliovalent doping introduces free charge carriers and enhances the screening, leading to the giant softening and deceleration of optical phonons. Moreover, the heavy dopant can induce the avoided-crossing of acoustic and optical phonon branches, further decelerating the acoustic phonons. These results highlight the significant role of aliovalent dopants in regulating the phonon structure and suppressing the phonon propagation of semiconductors.

cond-mat.mtrl-sci↗

arXiv2023

Quasi One-Dimensional Ising-like Antiferromagnetism in the Rare-earth Perovskite Oxide TbScO$_3$

The rare-earth perovskite TbScO$_3$ has been widely used as a substrate for the growth of epitaxial ferroelectric and multiferroic thin films, while its detailed low-temperature magnetic properties were rarely reported. In this paper, we performed detailed magnetization, specific heat and single crystal neutron scattering measurements, along with the crystalline electric field calculations to study the low-temperature magnetic properties of TbScO$_3$. All our results suggest the magnetic Tb$^{3+}$ has an Ising-like pseudo-doublet ground state at low temperatures. Due to the constrain of local point symmetry, these Tb$^{3+}$ Ising moments are confined in the $ab$ plane with a tilt angle of $φ= \pm48^{\mathrm{o}}$ to the $a$ axis. In zero field, the system undergoes an antiferromagnetic phase transition at $T_{\mathrm{N}}=2.53$ K, and forms a $G_xA_y$ noncollinear magnetic structure below $T_{\mathrm{N}}$. We find the dipole-dipole interactions play an important role to determine the magnetic ground state, which are also responsible for the quasi-one-dimensional magnetism in TbScO$_3$. The significant anisotropic diffuse scatterings further confirm the quasi-one-dimensional magnetism along the $c$ axis. The magnetic phase diagram with the field along the easy $b$ axis is well established. In addition to the $G_xA_y$ antiferromagnetic state, there is an exotic field-induced phase emerged near the critical field $B_{\mathrm{c}}\simeq0.7$ T, where three-dimensional magnetic order is suppressed but strong one-dimensional correlations may still exist.

cond-mat.str-el↗

arXiv2022

Data-based Polymer-Unit Fingerprint (PUFp): A Newly Accessible Expression of Polymer Organic Semiconductors for Machine Learning

In the process of finding high-performance organic semiconductors (OSCs), it is of paramount importance in material development to identify important functional units that play key roles in material performance and subsequently establish substructure-property relationships. Herein, we describe a polymer-unit fingerprint (PUFp) generation framework. Machine learning (ML) models can be used to determine structure-mobility relationships by using PUFp information as structural input with 678 pieces of collected OSC data. A polymer-unit library consisting of 445 units is constructed, and the key polymer units for the mobility of OSCs are identified. By investigating the combinations of polymer units with mobility performance, a scheme for designing polymer OSC materials by combining ML approaches and PUFp information is proposed to not only passively predict OSC mobility but also actively provide structural guidance for new high-mobility OSC material design. The proposed scheme demonstrates the ability to screen new materials through pre-evaluation and classification ML steps and is an alternative methodology for applying ML in new high-mobility OSC discovery.

cond-mat.mtrl-sci↗

arXiv2021

Projected Model Counting: Beyond Independent Support

The past decade has witnessed a surge of interest in practical techniques for projected model counting. Despite significant advancements, however, performance scaling remains the Achilles' heel of this field. A key idea used in modern counters is to count models projected on an \emph{independent support} that is often a small subset of the projection set, i.e. original set of variables on which we wanted to project. While this idea has been effective in scaling performance, the question of whether it can benefit to count models projected on variables beyond the projection set, has not been explored. In this paper, we study this question and show that contrary to intuition, it can be beneficial to project on variables beyond the projection set. In applications such as verification of binarized neural networks, quantification of information flow, reliability of power grids etc., a good upper bound of the projected model count often suffices. We show that in several such cases, we can identify a set of variables, called upper bound support (UBS), that is not necessarily a subset of the projection set, and yet counting models projected on UBS guarantees an upper bound of the true projected model count. Theoretically, a UBS can be exponentially smaller than the smallest independent support. Our experiments show that even otherwise, UBS-based projected counting can be more efficient than independent support-based projected counting, while yielding bounds of very high quality. Based on extensive experiments, we find that UBS-based projected counting can solve many problem instances that are beyond the reach of a state-of-the-art independent support-based projected model counter.

cs.AI↗

arXiv2020

Establishing the carrier scattering phase diagram for ZrNiSn-based half-Heusler thermoelectric materials

Chemical doping is one of the most important strategies for tuning electrical properties of semiconductors, particularly thermoelectric materials. Generally, the main role of chemical doping lies in optimizing the carrier concentration, but there can potentially be other important effects. Here, we show that chemical doping plays multiple roles for both electron and phonon transport properties in half-Heusler thermoelectric materials. With ZrNiSn-based half-Heusler materials as an example, we use high-quality single and polycrystalline crystals, various probes, including electrical transport measurements, inelastic neutron scattering measurement, and first-principles calculations, to investigate the underlying electron-phonon interaction. We find that chemical doping brings strong screening effects to ionized impurities, grain boundary, and polar optical phonon scattering, but has negligible influence on lattice thermal conductivity. Furthermore, it is possible to establish a carrier scattering phase diagram, which can be used to select reasonable strategies for optimization of the thermoelectric performance.

cond-mat.mtrl-sci↗

arXiv2019

PointPillars: Fast Encoders for Object Detection from Point Clouds

Object detection in point clouds is an important aspect of many robotics applications such as autonomous driving. In this paper we consider the problem of encoding a point cloud into a format appropriate for a downstream detection pipeline. Recent literature suggests two types of encoders; fixed encoders tend to be fast but sacrifice accuracy, while encoders that are learned from data are more accurate, but slower. In this work we propose PointPillars, a novel encoder which utilizes PointNets to learn a representation of point clouds organized in vertical columns (pillars). While the encoded features can be used with any standard 2D convolutional detection architecture, we further propose a lean downstream network. Extensive experimentation shows that PointPillars outperforms previous encoders with respect to both speed and accuracy by a large margin. Despite only using lidar, our full detection pipeline significantly outperforms the state of the art, even among fusion methods, with respect to both the 3D and bird's eye view KITTI benchmarks. This detection performance is achieved while running at 62 Hz: a 2 - 4 fold runtime improvement. A faster version of our method matches the state of the art at 105 Hz. These benchmarks suggest that PointPillars is an appropriate encoding for object detection in point clouds.

cs.LG↗

arXiv2016

Exciton Brightening in Monolayer Phosphorene via Dimensionality Modification

Two-dimensional (2D) monolayer phosphorene, a 2D system with quasi-one-dimensional (quasi-1D) excitons, provides a unique 2D platform for investigating the dynamics of excitons in reduced dimensions and fundamental many-body interactions. However, on the other hand, the quasi-1D excitonic nature can limit the luminescence quantum yield significantly. Here, we report exciton brightening in monolayer phosphorene achieved via the dimensionality modification of excitons from quasi-1D to zero-dimensional (0D), through the transference of monolayer phosphorene samples onto defect-rich oxide substrate deposited by plasma-enhanced chemical vapor deposition (PECVD). The resultant interfacial luminescent local states lead to exciton localization and trigger efficient photon emissions at a new wavelength of ~920 nm. The luminescence quantum yield of 0D-like localized excitons is measured to be at least 33.6 times larger than that of intrinsic quasi-1D free excitons in monolayer phosphorene. This is primarily due to the reduction of non-radiative decay rate and the possibly enhanced radiative recombination probability. Owing to the large trapping energy, this new photon emission from the localized excitons in monolayer phosphorene can be observed at elevated temperature, which contrasts markedly with defect-induced photon emission from transition metal dichalcogenide (TMD) semiconductor monolayers that can only be observed at cryogenic temperatures. Our findings introduce new avenues for the development of novel photonic devices based on monolayer phosphorene, such as near-infrared lighting devices that are operable at elevated temperature. More importantly, 2D phosphorene with quasi-1D free excitons and 0D-like localized excitons provides a unique platform to investigate the fundamental phenomena in the ideal 2D-1D-0D hybrid system.

cond-mat.mtrl-sci↗

arXiv2015

Differential Operators for Siegel-Jacobi forms

For any positive integers $n$ and $m$, $\mathbb{H}_{n,m}:=\mathbb{H}_n\times\mathbb{C}^{(m,n)}$ is called the Siegel-Jacobi space, with the Jacobi group acting on it. The Jacobi forms are defined on this space. In this article we compute the Chern connection of the Siegel-Jacobi space and use it to obtain derivations of Jacobi forms. Using these results, we constructed a series of invariant differential operators for Siegel-Jacobi forms. Also two kinds of Maass-Shimura type differential operators for $\mathbb{H}_{n,m}$ are obtained.

math.NT↗

arXiv2015

Layer-dependent surface potential of phosphorene and anisotropic/layer-dependent charge transfer in phosphorene-gold hybrid system

The surface potential and the efficiency of interfacial charge transfer are extremely important for designing future semiconductor devices based on the emerging two-dimensional (2D) phosphorene. Here, we directly measured the strongly layer-dependent surface potential of mono- and few-layer phosphorene on gold, which confirms with the reported theoretical prediction. At the same time, we used an optical way - photoluminescence (PL) spectroscopy to probe the charge transfer in phosphorene-gold hybrid system. We firstly observed highly anisotropic and layer-dependent PL quenching in the phosphorene-gold hybrid system, which is attributed to the highly anisotropic/layer-dependent interfacial charge transfer.

cond-mat.mtrl-sci↗

arXiv2015

Optical Tuning of Exciton and Trion Emissions in Monolayer Phosphorene

Monolayer phosphorene provides a unique two-dimensional (2D) platform to investigate the fundamental dynamics of excitons and trions (charged excitons) in reduced dimensions. However, owing to its high instability, unambiguous identification of monolayer phosphorene has been elusive. Consequently, many important fundamental properties, such as exciton dynamics, remain underexplored. We report a rapid, noninvasive, and highly accurate approach based on optical interferometry to determine the layer number of phosphorene, and confirm the results with reliable photoluminescence measurements. Furthermore, we successfully probed the dynamics of excitons and trions in monolayer phosphorene by controlling the photo-carrier injection in a relatively low excitation power range. Based on our measured optical gap and the previously measured electronic energy gap, we determined the exciton binding energy to be ~0.3 eV for the monolayer phosphorene on SiO2/Si substrate, which agrees well with theoretical predictions. A huge trion binding energy of ~100 meV was first observed in monolayer phosphorene, which is around five times higher than that in transition metal dichalcogenide (TMD) monolayer semiconductor, such as MoS2. The carrier lifetime of exciton emission in monolayer phosphorene was measured to be ~220 ps, which is comparable to those in other 2D TMD semiconductors. Our results open new avenues for exploring fundamental phenomena and novel optoelectronic applications using monolayer phosphorene.

cond-mat.mtrl-sci↗

arXiv2014

Unambiguous identification of monolayer phosphorene by phase-shifting interferometry

Monolayer phosphorene provides a unique two-dimensional (2D) platform to investigate the fundamental many-body interactions. However, owing to its high instability, unambiguous identification of monolayer phosphorene has been elusive. Consequently, many important fundamental properties, such as exciton dynamics, remain underexplored. We report a rapid, noninvasive, and highly accurate approach based on optical interferometry to determine the layer number of phosphorene, and confirm the results with reliable photoluminescence measurements. Based on the measured optical gap and the calculated electronic energy gap, we determined the exciton binding energy to be ~0.4 eV for the monolayer phosphorene on SiO2/Si substrate, which agrees well with theoretical predictions. Our results open new avenues for exploring fundamental phenomena and novel optoelectronic applications using monolayer phosphorene.

cond-mat.mtrl-sci↗

arXiv2014

Atomically Thin Optical Lenses and Gratings

Two-dimensional (2D) materials have emerged as promising candidates for miniaturized optoelectronic devices, due to their strong inelastic interactions with light. On the other hand, a miniaturized optical system also requires strong elastic light-matter interactions to control the flow of light. Here, we report giant optical path length (OPL) from a single-layer molybdenum disulfide (MoS2), which is around one order of magnitude larger than that from a single-layer graphene. Using such giant OPL to engineer the phase front of optical beams, we demonstrated, to the best of our knowledge, the world's thinnest optical lens consisting of a few layers of MoS2 less than 6.3 nm thick. Moreover, we show that MoS2 has much better dielectric response than good conductor (like gold) and other dielectric materials (like Si, SiO2 or graphene). By taking advantage of the giant elastic scattering efficiency in ultra-thin high-index 2D materials, we demonstrated high-efficiency gratings based on a single- or few-layers of MoS2. The capability of manipulating the flow of light in 2D materials opens an exciting avenue towards unprecedented miniaturization of optical components and the integration of advanced optical functionalities.

cond-mat.mtrl-sci↗

arXiv2014

Extraordinarily bound quasi-one-dimensional trions in two-dimensional phosphorene atomic semiconductors

The anisotropic nature of the new two-dimensional (2D) material phosphorene, in contrast to other 2D materials such as graphene and transition metal dichalcogenide (TMD) semiconductors, allows excitons to be confined in a quasi-one-dimensional (1D) space predicted in theory, leading to remarkable phenomena arising from the reduced dimensionality and screening. Here, we report a trion (charged exciton) binding energy of 190 meV in few-layer phosphorene at room temperature, which is nearly one to two orders of magnitude larger than those in 2D TMD semiconductors (20-30 meV) and quasi-2D quantum wells (1-5 meV). Such a large binding energy has only been observed in truly 1D materials such as carbon nanotubes, whose optoelectronic applications have been severely hurdled by their intrinsically small optical cross-sections. Phosphorene offers an elegant way to overcome this hurdle by enabling quasi-1D excitonic and trionic behaviors in a large 2D area, allowing optoelectronic integration. We experimentally validated the quasi-1D nature of excitonic and trionic dynamics in phospherene by demonstrating completely linearly polarized light emission from excitons and trions. The implications of the extraordinarily large trion binding energy in a higher-than-one-dimensional material are far-reaching. It provides a room-temperature 2D platform to observe the fundamental many-body interactions in the quasi-1D region. The strong photoluminescence emission in phosphorene has been electrically tuned over a large spectral range at room temperature, which opens a new route for tunable light sources.

cond-mat.mtrl-sci↗