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Li Huang

Publications and source records attributed to Li Huang.

At least 73 records · Page 4Linked to original sources
arXiv2024

Calibration of the in-orbit center-of-mass of TaiJi-1

Taiji program is a space mission aiming to detect gravitational waves in the low frequency band. Taiji-1 is the first technology demonstration satellite of the Taiji Program in Space, with the gravitational reference sensor (GRS) serving as one of its key scientific payloads. For accurate accelerometer measurements, the test-mass center of the GRS must be positioned precisely at the center of gravity of the satellite to avoid measurement disturbances caused by angular acceleration and gradient. Due to installation and measurement errors, fuel consumption during in-flight phase, and other factors, the offset between the test-mass center and the center-of-mass (COM) of the satellite can be significant, degrading the measurement accuracy of the accelerometer. Therefore, the offset needs to be estimated and controlled within the required range by the center-of-mass adjustment mechanism during the satellite's lifetime. In this paper, we present a novel method, the Extended Kalman Filter combined with Rauch-Tung-Striebel Smoother, to estimate the offset, while utilizing the chi-square test to eliminate outliers. Additionally, the nonlinear Least Squares estimation algorithm is employed as a crosscheck to estimate the offset of COM. The two methods are shown to give consistent results, with the offset estimated to be $dx \approx $$-$$0.19$ mm, $dy \approx 0.64$ mm, and $dz \approx $$-$$0.82$ mm. The results indicate a significant improvement on the noise level of GRS after the COM calibration, which will be of great help for the future Taiji program.

astro-ph.IM↗
arXiv2024

BUGFIX: towards a common language and framework for the AutomaticProgram Repair community

Techniques of Automatic Program Repair (APR) have the potential of thoroughly facilitating the task of producing quality software. After a promising start, however, progress in making APR practical has been hindered by the lack of a common framework to support the multiplicity of APR ideas and tools, and of target programming languages and environments. In this position paper we outline a general framework to enable the APR community to benefit from each otherś advances, in particular through a standard language for describing bugs and their fixes. Such a common framework (which is also applicable to work on fault seeding) could be a tremendous benefit to researchers and developers of Interactive Development Environments (IDEs) who are working to make APR an effective part of the practical experience of software developers.

cs.SE↗
arXiv2023

Combining Bayesian reconstruction entropy with maximum entropy method for analytic continuations of matrix-valued Green's functions

The Bayesian reconstruction entropy is considered an alternative to the Shannon-Jaynes entropy, as it does not exhibit the asymptotic flatness characteristic of the Shannon-Jaynes entropy and obeys the scale invariance. It is commonly utilized in conjunction with the maximum entropy method to derive spectral functions from Euclidean time correlators produced by lattice QCD simulations. This study expands the application of the Bayesian reconstruction entropy to the reconstruction of spectral functions for Matsubara or imaginary-time Green's functions in quantum many-body physics. Furthermore, it extends the Bayesian reconstruction entropy to implement the positive-negative entropy algorithm, enabling the analytic continuations of matrix-valued Green's functions on an element-wise manner. Both the diagonal and off-diagonal components of the matrix-valued Green's functions are treated equally. Benchmark results for the analytic continuations of synthetic Green's functions indicate that the Bayesian reconstruction entropy, when combined with the preblur trick, demonstrates comparable performance to the Shannon-Jaynes entropy. Notably, it exhibits greater resilience to noises in the input data, particularly when the noise level is moderate.

hep-lat↗
arXiv2023

Hund electronic correlation in La$_3$Ni$_2$O$_7$ under high pressure

By means of density functional theory plus dynamical mean-field theory (DFT+DMFT), we investigate the correlated electronic structures of La$_3$Ni$_2$O$_7$ under high pressure. Our calculations show that La$_3$Ni$_2$O$_7$ is a multi-orbital Hund metal. Both the 3$d_{z^2}$ and 3$d_{x^2 - y^2}$ orbitals of Ni are close to be half filled and contribute the bands across the Fermi level. Band renormalization and orbital selective electronic correlation are observed. Through imaginary-time correlation functions, the discovery of high-spin configuration, spin-frozen phase, and spin-orbital separation shows that the system is in a frozen moment phase at high temperatures above 290 K and is a Fermi liquid at low temperatures, which is further comfirmed by the calculated spin, orbital, and charge susceptibilities under high temperatures. Our study uncovers Hundness in La$_3$Ni$_2$O$_7$ under high pressure.

cond-mat.str-el↗
arXiv2023

High-Performance and Low-Power Sub-5 nm Field-Effect Transistors Based on 7-9-7-AGNR

Recently, an extremely-air-stable one-dimensional 7-9-7-AGNR was successfully fabricated. To further reveal its potential application in sub-5-nm field-effect transistors (FETs), there is an urgent need to develop integrated circuits. Here, we report first-principles quantum-transport simulations on the performance limits of n- and p-type sub-5-nm one-dimensional 7-9-7-AGNR FET. We find that the on-state current (Ion) in 7-9-7-AGNR FET can be effectively manipulated by the length of the gate and underlap. Particularly, the optimized Ion in n-type (p-type) device can reach up to 2423 (4277) and 1988 (920) μA/μm for high-performance and low-power applications, respectively. The large Ion values are in the first class among the LD FETs, which can well satisfy the ITRS requirements. We also find that the 7-9-7-AGNR FET can have ultralow subthreshold swing below 60mV/dev, ultrashort delay time (<0.01 ps), and very small power-delay product (<0.01 fJ/μm). Our results show that the 7-9-7-AGNR based FETs have great potential applications in the high-speed and low-power consumption chips.

cond-mat.mes-hall↗
arXiv2023

Atomically-precise engineering of spin-orbit polarons in a kagome magnetic Weyl semimetal

Atomically-precise engineering of defects in topological quantum materials, which is essential for constructing new artificial quantum materials with exotic properties and appealing for practical quantum applications, remains challenging due to the hindrances in modifying complex lattice with atomic precision. Here, we report the atomically-precise engineering of the vacancy-localized spin-orbital polarons (SOP) in a kagome magnetic Weyl semimetal Co3Sn2S2, using scanning tunneling microscope. We achieve the step-by-step repairing of the selected vacancies, which results in the formation of artificial sulfur vacancy with elaborate geometry. We find that that the bound states localized around the vacancies experience a symmetry-dependent energy shift towards Fermi level with increasing vacancy size. Strikingly, as vacancy size increases, the localized magnetic moments of SOPs are tunable and ultimately extended to the negative magnetic moments resulting from spin-orbit coupling in the kagome flat band. These findings establish a new platform for engineering atomic quantum states in topological quantum materials, offering potential for kagome-lattice-based spintronics and quantum technologies.

cond-mat.mes-hall↗
arXiv2023

Reconstructing lattice QCD spectral functions with stochastic pole expansion and Nevanlinna analytic continuation

The reconstruction of spectral functions from Euclidean correlation functions is a well-known, yet ill-posed inverse problem in the fields of many-body and high-energy physics. In this paper, we present a comprehensive investigation of two recently developed analytic continuation methods, namely stochastic pole expansion and Nevanlinna analytic continuation, for extracting spectral functions from mock lattice QCD data. We examine a range of Euclidean correlation functions generated by representative models, including the Breit-Wigner model, the Gaussian mixture model, the resonance-continuum model, and the bottomonium model. Our findings demonstrate that the stochastic pole expansion method, when combined with the constrained sampling algorithm and the self-adaptive sampling algorithm, successfully recovers the essential features of the spectral functions and exhibits excellent resilience to noise of input data. In contrast, the Nevanlinna analytic continuation method suffers from numerical instability, often resulting in the emergence of spurious peaks and significant oscillations in the high-energy regions of the spectral functions, even with the application of the Hardy basis function optimization algorithm.

hep-lat↗
arXiv2023

Seeding Contradiction: a fast method for generating full-coverage test suites

The regression test suite, a key resource for managing program evolution, needs to achieve 100% coverage, or very close, to be useful. Devising a test suite manually is unacceptably tedious, but existing automated methods are often inefficient. The method described in this article, ``Seeding Contradiction'', inserts incorrect instructions into every basic block of the program, enabling an SMT-based Hoare-style prover to generate a counterexample for every branch of the program and, from the collection of all such counterexamples, a test suite. The method is static, works fast, and achieves excellent coverage.

cs.SE↗
arXiv2023

Chemical reaction mechanism of pre-curing process of two-component adhesive based on deformation behavior for automobile hood

Shearing test is carried out on the joint which bonded under different pre curing processes with two component adhesives of acrylic and epoxy resin respectively. The pre curing strength is obtained, which used to analyze the relationship between the pre curing strength and time. The hoods with different pre curing strength are baking with high temperature. The deformation of different areas of the hood is measured with gauges, and the deformation characteristics of the hood after baking are acquired with comparative analysis. Combining the components of two component adhesives and DSC test, the pre curing mechanism of different adhesive systems are studied. Therefore, the key factors and regular pattern of the deformation for the hood are obtained. The results indicate that, finally deformation of the hood after high temperature baking varies with the pre curing time. The key of the pre curing time of acrylic adhesives lies in the chain initiation stage of the free radical polymerization reaction. Due to the influence of the chemical properties of methyl acrylate and its initiator, the pre curing reaction induced by free radical polymerization is very fast. The shear strength of this joint can reach to 3.67 MPa with a pre curing time of 1 h, which quickly achieving the pre cure strength required for deformation control. For epoxy adhesives, the rate determining step in pre curing process is the esterification reaction. Due to the influence of the structure of carboxylic acid, the esterification process is relatively long. Shear strength of this joint can only reach 0.87 MPa after pre curing for 4 h without external heating.

physics.chem-ph↗
arXiv2023

Stochastic pole expansion method

In this paper, we propose a new analytic continuation method to extract real frequency spectral functions from imaginary frequency Green's functions of quantum many-body systems. This method is based on the pole representation of Matsubara Green's function and a stochastic sampling procedure is utilized to optimize the amplitudes and locations of poles. In order to capture narrow peaks and sharp band edges in the spectral functions, a constrained sampling algorithm and a self-adaptive sampling algorithm are developed. To demonstrate the usefulness and performance of the new method, we at first apply it to study the spectral functions of representative fermionic and bosonic correlators. Then we employ this method to tackle the analytic continuation problems of matrix-valued Green's functions. The synthetic Green's functions, as well as realistic correlation functions from finite temperature quantum many-body calculations, are used as input. The benchmark results demonstrate that this method is capable of reproducing most of the key characteristics in the spectral functions. The sharp, smooth, and multi-peak features in both low-frequency and high-frequency regions of spectral functions could be accurately resolved, which overcomes one of the main limitations of the traditional maximum entropy method. More importantly, it exhibits excellent robustness with respect to noisy and incomplete input data. The causality of spectral function is always satisfied even in the presence of sizable noises. As a byproduct, this method could derive a fitting formula for the Matsubara data, which provides a compact approximation to the many-body Green's functions. Hence, we expect that this new method could become a pivotal workhorse for numerically analytic continuation and be broadly useful in many applications.

cond-mat.str-el↗
arXiv2023

Novel correlated 5f electronic states in cubic AnSn3 (An=U, Np, Pu) intermetallics

The intricate interplay between itinerant-localized 5f states and strongly correlated electronic states have been systematically investigated in isostructural actinide compounds AnSn3 (An=U, Np, Pu) by using a combination of the density functional theory and the embedded dynamical mean-field approach. The obvious narrow flat 5f electronic band with remarkable spectral weight emerges in the vicinity of Fermi level for three compounds. Subsequently the significant hybridization between 5f states and conduction bands opens evident gaps together with conspicuous valence state fluctuations jointly indicating the partially itinerant 5f electrons. Especially, prominent quasiparticle multiplets only appear in PuSn3 due to the sizable valence state fluctuations and multiple competing atomic eigenstates. Therefore itinerant 5f states tend to involve in active chemical bonding, restraining the formation of local magnetic moment of actinide atoms, which partly elucidates the underlying mechanism of paramagnetic USn3 and PuSn3, as well as itinerant-electron antiferromagnetic NpSn3. Correspondingly, the 5f electronic correlation strength expressed in band renormalization and electron effective masse intertwines with itinerant-localized 5f states. Consequently, detail electronic structure of 5f states dependence on actinide series shall gain deep insight into our understanding of AnSn3 (An=U, Np, Pu) intermetallics and promote ongoing research.

cond-mat.str-el↗
arXiv2023

Discovery and construction of surface kagome electronic states induced by p-d electronic hybridization

Kagome-lattice materials possess attractive properties for quantum computing applications, but their synthesis remains challenging. Herein, we show surface kagome electronic states (SKESs) on a Sn-terminated triangular Co3Sn2S2 surface, which are imprinted by vertical p-d electronic hybridization between the surface Sn (subsurface S) atoms and the buried Co kagome lattice network in the Co3Sn layer under the surface. Owing to the subsequent lateral hybridization of the Sn and S atoms in a corner-sharing manner, the kagome symmetry and topological electronic properties of the Co3Sn layer is proximate to the Sn surface. The SKESs and both hybridizations were verified via qPlus non-contact atomic force microscopy (nc-AFM) and density functional theory calculations. The construction of SKESs with tunable properties can be achieved by the atomic substitution of surface Sn (subsurface S) with other group III-V elements (Se or Te), which was demonstrated theoretically. This work exhibits the powerful capacity of nc-AFM in characterizing localized topological states and reveals the strategy for synthesis of large-area transition-metal-based kagome lattice materials using conventional surface deposition techniques.

cond-mat.mtrl-sci↗
arXiv2023

A Failed Proof Can Yield a Useful Test

A successful automated program proof is, in software verification, the ultimate triumph. In practice, however, the road to such success is paved with many failed proof attempts. Unlike a failed test, which provides concrete evidence of an actual bug in the program, a failed proof leaves the programmer in the dark. Can we instead learn something useful from it? The work reported here takes advantage of the rich internal information that some automatic provers collect about the program when attempting a proof. If the proof fails, the Proof2Test tool presented in this article uses the counterexample generated by the prover (specifically, the SMT solver underlying the proof environment Boogie, used in the AutoProof system to perform correctness proofs of contract-equipped Eiffel programs) to produce a failed test, which provides the programmer with immediately exploitable information to correct the program. The discussion presents the Proof2Test tool and demonstrates the application of the ideas and tool to a collection of representative examples.

cs.SE↗
arXiv2023

Human-Level Control through Directly-Trained Deep Spiking Q-Networks

As the third-generation neural networks, Spiking Neural Networks (SNNs) have great potential on neuromorphic hardware because of their high energy-efficiency. However, Deep Spiking Reinforcement Learning (DSRL), i.e., the Reinforcement Learning (RL) based on SNNs, is still in its preliminary stage due to the binary output and the non-differentiable property of the spiking function. To address these issues, we propose a Deep Spiking Q-Network (DSQN) in this paper. Specifically, we propose a directly-trained deep spiking reinforcement learning architecture based on the Leaky Integrate-and-Fire (LIF) neurons and Deep Q-Network (DQN). Then, we adapt a direct spiking learning algorithm for the Deep Spiking Q-Network. We further demonstrate the advantages of using LIF neurons in DSQN theoretically. Comprehensive experiments have been conducted on 17 top-performing Atari games to compare our method with the state-of-the-art conversion method. The experimental results demonstrate the superiority of our method in terms of performance, stability, robustness and energy-efficiency. To the best of our knowledge, our work is the first one to achieve state-of-the-art performance on multiple Atari games with the directly-trained SNN.

cs.NE↗
arXiv2023

The Treasure Beneath Multiple Annotations: An Uncertainty-aware Edge Detector

Deep learning-based edge detectors heavily rely on pixel-wise labels which are often provided by multiple annotators. Existing methods fuse multiple annotations using a simple voting process, ignoring the inherent ambiguity of edges and labeling bias of annotators. In this paper, we propose a novel uncertainty-aware edge detector (UAED), which employs uncertainty to investigate the subjectivity and ambiguity of diverse annotations. Specifically, we first convert the deterministic label space into a learnable Gaussian distribution, whose variance measures the degree of ambiguity among different annotations. Then we regard the learned variance as the estimated uncertainty of the predicted edge maps, and pixels with higher uncertainty are likely to be hard samples for edge detection. Therefore we design an adaptive weighting loss to emphasize the learning from those pixels with high uncertainty, which helps the network to gradually concentrate on the important pixels. UAED can be combined with various encoder-decoder backbones, and the extensive experiments demonstrate that UAED achieves superior performance consistently across multiple edge detection benchmarks. The source code is available at \url{https://github.com/ZhouCX117/UAED}

cs.CV↗
arXiv2023

Twisted bilayer zigzag-graphene nanoribbon junctions with tunable edge states

Stacking two-dimensional layered materials such as graphene and transitional metal dichalcogenides with nonzero interlayer twist angles has recently become attractive because of the emergence of novel physical properties. Stacking of one-dimensional nanomaterials offers the lateral stacking offset as an additional parameter for modulating the resulting material properties. Here, we report that the edge states of twisted bilayer zigzag graphene nanoribbons (TBZGNRs) can be tuned with both the twist angle and the stacking offset. Strong edge state variations in the stacking region are first revealed by density functional theory (DFT) calculations. We construct and characterize twisted bilayer zigzag graphene nanoribbon (TBZGNR) systems on a Au(111) surface using scanning tunneling microscopy. A detailed analysis of three prototypical orthogonal TBZGNR junctions exhibiting different stacking offsets by means of scanning tunneling spectroscopy reveals emergent near-zero-energy states. From a comparison with DFT calculations, we conclude that the emergent edge states originate from the formation of flat bands whose energy and spin degeneracy are highly tunable with the stacking offset. Our work highlights fundamental differences between 2D and 1D twistronics and spurs further investigation of twisted one-dimensional systems.

cond-mat.mes-hall↗
arXiv2023

Emergent Electronic Kagome Lattice in Correlated Charge-Density-Wave State of 1T-TaS$_2$

Quantum materials with tunable correlated and/or topological electronic states, such as the electronic Kagome lattice, provide an ideal platform to study the exotic quantum properties. However, the real-space investigations on the correlated electronic Kagome lattice have been rarely reported. Herein, we report on the electronic Kagome lattice emerging in the correlated charge-density-wave (CDW) state of 1T-TaS$_2$ at ~200 K via variable-temperature scanning tunneling microscopy (VT-STM). This emergent Kagome lattice can be considered a fractional electron-filling superstructure with reduced translational and rotational symmetries, confirmed by STM measurements and density functional theory simulations. The characteristic band structure and density of states of this electronic Kagome lattice are further explored based on theoretical calculations. Our results demonstrate a self-organized electronic Kagome lattice from the correlated CDW state via the effective tuning parameter of temperature and provide a platform to directly explore the interplay of correlated electrons and topological physics.

cond-mat.mtrl-sci↗
arXiv2022

ACFlow: An open source toolkit for analytical continuation of quantum Monte Carlo data

The purpose of analytical continuation is to establish a real frequency spectral representation of single-particle or two-particle correlation function (such as Green's function, self-energy function, and dynamical susceptibilities) from noisy data generated in finite temperature quantum Monte Carlo simulations. It requires numerical solutions of a family of Fredholm integral equations of the first kind, which is indeed a challenging task. In this paper, an open source toolkit (dubbed ACFlow) for analytical continuation of quantum Monte Carlo data is presented. We at first give a short introduction to the analytical continuation problem. Next, three primary analytical continuation algorithms, including maximum entropy method, stochastic analytical continuation, and stochastic optimization method, as implemented in this toolkit are reviewed. And then we elaborate major features, implementation details, and basic usage of this toolkit. Finally, four representative examples are shown to demonstrate usefulness and flexibility of the ACFlow toolkit.

cond-mat.str-el↗