arXiv subjects

Tao Liu

Publications and source records attributed to Tao Liu.

At least 181 records · Page 10Linked to original sources

arXiv2024

GS-EVT: Cross-Modal Event Camera Tracking based on Gaussian Splatting

Reliable self-localization is a foundational skill for many intelligent mobile platforms. This paper explores the use of event cameras for motion tracking thereby providing a solution with inherent robustness under difficult dynamics and illumination. In order to circumvent the challenge of event camera-based mapping, the solution is framed in a cross-modal way. It tracks a map representation that comes directly from frame-based cameras. Specifically, the proposed method operates on top of gaussian splatting, a state-of-the-art representation that permits highly efficient and realistic novel view synthesis. The key of our approach consists of a novel pose parametrization that uses a reference pose plus first order dynamics for local differential image rendering. The latter is then compared against images of integrated events in a staggered coarse-to-fine optimization scheme. As demonstrated by our results, the realistic view rendering ability of gaussian splatting leads to stable and accurate tracking across a variety of both publicly available and newly recorded data sequences.

cs.CV↗

arXiv2024

Irreversible Diagonalization of Mechanical Quantities and the EPR Paradox

The closure relation of quantum mechanical projection operators is not entirely true; it can be strictly falsified under unitary transformations in Fock states. The angular momentum $J_x$, $J_y$ and $J_z$ are simultaneously diagonalized under the orthonormal set $\{|ϕ_n\rangle\}$ of continuous rotation transformations in Fock states. $\{|ϕ_n\rangle\}$'s time reversal $\{ \mathcal{T} |ϕ_n\rangle \}$ is the zero point of coordinates q and momentum p, and its arbitrary translation transformation $\{ \mathcal{D} \mathcal{T} |ϕ_n\rangle \}$ diagonalizes both coordinates and momentum simultaneously. The abstract representation of the Dirac state vector implies the symmetry breaking of the non-Abelian group unit matrix $\{ \mathcal{U}^ \mathcal{H} \mathcal{U} \neq \mathcal{U} \mathcal{U} ^\mathcal{H} \}$. The EPR paradox is merely a fallacy under the reversible diagonalization of physical reality, it is resolved under irreversible diagonalization.

quant-ph↗

arXiv2024

Multi-robot Task Allocation and Path Planning with Maximum Range Constraints

This letter presents a novel multi-robot task allocation and path planning method that considers robots' maximum range constraints in large-sized workspaces, enabling robots to complete the assigned tasks within their range limits. Firstly, we developed a fast path planner to solve global paths efficiently. Subsequently, we propose an innovative auction-based approach that integrates our path planner into the auction phase for reward computation while considering the robots' range limits. This method accounts for extra obstacle-avoiding travel distances rather than ideal straight-line distances, resolving the coupling between task allocation and path planning. Additionally, to avoid redundant computations during iterations, we implemented a lazy auction strategy to speed up the convergence of the task allocation. Finally, we validated the proposed method's effectiveness and application potential through extensive simulation and real-world experiments. The implementation code for our method will be available at https://github.com/wuuya1/RangeTAP.

cs.RO↗

arXiv2024

Commensurate and Incommensurate Chern Insulators in Magic-angle Bilayer Graphene

The interplay between strong electron-electron interaction and symmetry breaking can have profound influence on the topological properties of materials. In magic angle twisted bilayer graphene (MATBG), the flat band with a single SU(4) flavor associated with the spin and valley degrees of freedom gains non-zero Chern number when C2z symmetry or C2zT symmetry is broken. Electron-electron interaction can further lift the SU(4) degeneracy, leading to the Chern insulator states. Here we report a complete sequence of zero-field Chern insulators at all odd integer fillings (v = +-1, +-3) with different chirality (C = 1 or -1) in hBN aligned MATBG which structurally breaks C2z symmetry. The Chern states at hole fillings (v = -1, -3), which are firstly observed in this work, host an opposite chirality compared with the electron filling scenario. By slightly doping the v = +-3 states, we have observed new correlated insulating states at incommensurate moiré fillings which is highly suggested to be intrinsic Wigner crystals according to our theoretical calculations. Remarkably, we have observed prominent Streda-formula violation around v = -3 state. By doping the Chern gap at v = -3 with notable number of electrons at finite magnetic field, the Hall resistance Ryx robustly quantizes to ~ h/e2 whereas longitudinal resistance Rxx vanishes, indicating that the chemical potential is pinned within a Chern gap, forming an incommensurate Chern insulator. By providing the first experimental observation of zero-field Chern insulators in the flat valence band, our work fills up the overall topological framework of MATBG with broken C2z symmetry. Our findings also demonstrate that doped topological flat band is an ideal platform to investigate exotic incommensurate correlated topological states.

cond-mat.mes-hall↗

arXiv2024

FlashGS: Efficient 3D Gaussian Splatting for Large-scale and High-resolution Rendering

This work introduces FlashGS, an open-source CUDA Python library, designed to facilitate the efficient differentiable rasterization of 3D Gaussian Splatting through algorithmic and kernel-level optimizations. FlashGS is developed based on the observations from a comprehensive analysis of the rendering process to enhance computational efficiency and bring the technique to wide adoption. The paper includes a suite of optimization strategies, encompassing redundancy elimination, efficient pipelining, refined control and scheduling mechanisms, and memory access optimizations, all of which are meticulously integrated to amplify the performance of the rasterization process. An extensive evaluation of FlashGS' performance has been conducted across a diverse spectrum of synthetic and real-world large-scale scenes, encompassing a variety of image resolutions. The empirical findings demonstrate that FlashGS consistently achieves an average 4x acceleration over mobile consumer GPUs, coupled with reduced memory consumption. These results underscore the superior performance and resource optimization capabilities of FlashGS, positioning it as a formidable tool in the domain of 3D rendering.

cs.CV↗

arXiv2024

CMoralEval: A Moral Evaluation Benchmark for Chinese Large Language Models

What a large language model (LLM) would respond in ethically relevant context? In this paper, we curate a large benchmark CMoralEval for morality evaluation of Chinese LLMs. The data sources of CMoralEval are two-fold: 1) a Chinese TV program discussing Chinese moral norms with stories from the society and 2) a collection of Chinese moral anomies from various newspapers and academic papers on morality. With these sources, we aim to create a moral evaluation dataset characterized by diversity and authenticity. We develop a morality taxonomy and a set of fundamental moral principles that are not only rooted in traditional Chinese culture but also consistent with contemporary societal norms. To facilitate efficient construction and annotation of instances in CMoralEval, we establish a platform with AI-assisted instance generation to streamline the annotation process. These help us curate CMoralEval that encompasses both explicit moral scenarios (14,964 instances) and moral dilemma scenarios (15,424 instances), each with instances from different data sources. We conduct extensive experiments with CMoralEval to examine a variety of Chinese LLMs. Experiment results demonstrate that CMoralEval is a challenging benchmark for Chinese LLMs. The dataset is publicly available at \url{https://github.com/tjunlp-lab/CMoralEval}.

cs.CL↗

arXiv2024

Learning Based Toolpath Planner on Diverse Graphs for 3D Printing

This paper presents a learning based planner for computing optimized 3D printing toolpaths on prescribed graphs, the challenges of which include the varying graph structures on different models and the large scale of nodes & edges on a graph. We adopt an on-the-fly strategy to tackle these challenges, formulating the planner as a Deep Q-Network (DQN) based optimizer to decide the next `best' node to visit. We construct the state spaces by the Local Search Graph (LSG) centered at different nodes on a graph, which is encoded by a carefully designed algorithm so that LSGs in similar configurations can be identified to re-use the earlier learned DQN priors for accelerating the computation of toolpath planning. Our method can cover different 3D printing applications by defining their corresponding reward functions. Toolpath planning problems in wire-frame printing, continuous fiber printing, and metallic printing are selected to demonstrate its generality. The performance of our planner has been verified by testing the resultant toolpaths in physical experiments. By using our planner, wire-frame models with up to 4.2k struts can be successfully printed, up to 93.3% of sharp turns on continuous fiber toolpaths can be avoided, and the thermal distortion in metallic printing can be reduced by 24.9%.

cs.RO↗

arXiv2024

EVIT: Event-based Visual-Inertial Tracking in Semi-Dense Maps Using Windowed Nonlinear Optimization

Event cameras are an interesting visual exteroceptive sensor that reacts to brightness changes rather than integrating absolute image intensities. Owing to this design, the sensor exhibits strong performance in situations of challenging dynamics and illumination conditions. While event-based simultaneous tracking and mapping remains a challenging problem, a number of recent works have pointed out the sensor's suitability for prior map-based tracking. By making use of cross-modal registration paradigms, the camera's ego-motion can be tracked across a large spectrum of illumination and dynamics conditions on top of accurate maps that have been created a priori by more traditional sensors. The present paper follows up on a recently introduced event-based geometric semi-dense tracking paradigm, and proposes the addition of inertial signals in order to robustify the estimation. More specifically, the added signals provide strong cues for pose initialization as well as regularization during windowed, multi-frame tracking. As a result, the proposed framework achieves increased performance under challenging illumination conditions as well as a reduction of the rate at which intermediate event representations need to be registered in order to maintain stable tracking across highly dynamic sequences. Our evaluation focuses on a diverse set of real world sequences and comprises a comparison of our proposed method against a purely event-based alternative running at different rates.

cs.CV↗

arXiv2024

Deep Learning Meets OBIA: Tasks, Challenges, Strategies, and Perspectives

Deep learning has gained significant attention in remote sensing, especially in pixel- or patch-level applications. Despite initial attempts to integrate deep learning into object-based image analysis (OBIA), its full potential remains largely unexplored. In this article, as OBIA usage becomes more widespread, we conducted a comprehensive review and expansion of its task subdomains, with or without the integration of deep learning. Furthermore, we have identified and summarized five prevailing strategies to address the challenge of deep learning's limitations in directly processing unstructured object data within OBIA, and this review also recommends some important future research directions. Our goal with these endeavors is to inspire more exploration in this fascinating yet overlooked area and facilitate the integration of deep learning into OBIA processing workflows.

cs.CV↗

arXiv2024

Bistability in spatiotemporal mode-locking with dynamic multimode gain

Three-dimensional (3D) dissipative soliton existed in spatiotemporal mode-locked (STML) multimode fiber laser has been demonstrated to be a promising formalism for generating high-energy femtosecond pulses, which unfortunately exhibit diverse spatiotemporal dynamics that have not been fully understood. Completely modeling the STML multimode fiber lasers can shed new light on the underlying physics of the spatiotemporal dynamics and thus better manipulate the generation of high-quality energic femtosecond pulses, which however is still largely unmet. To this end, here we theoretically investigate a dynamic multimode gain model of the STML multimode fiber laser by exploring the multimode rate equation (MMRE) in the framework of generalized multimode nonlinear Schrödinger equation. Using this dynamic multimode gain model, the attractor dissection theory is revisited to understand the dominant effects that determine the modal composition of 3D dissipative soliton. Specifically, by varying the numerical aperture of the multimode gain fiber (MMGF), different gain dynamics that correspond to distinct types of gain attractors are observed. As a result, two distinguishing STML operation regimes, respectively governed by the multimode gain effect and spatiotemporal saturable absorption, are identified. In the latter regime, especially, 3D dissipative solitons present bistability that there exist bifurcated solutions with two different linearly polarized (LP) mode compositions. To verify the theoretical findings, the experimental implementation shows that the state of STML can be switched between different LP modes, and confirms the presence of bistability. Particularly, the 3D-soliton shaping mechanism that is governed by the multimode gain effect is testified for the first time, to the best of our knowledge.

physics.optics↗

arXiv2024

Applications of Bound States in the Continuum in Photonics

Bound states in the continuum (BICs) have attracted attention in photonics owing to their interesting properties. For example, BICs can effectively confine light in a counter-intuitive way and the far-field radiation of photonic structures that exhibit BICs manifests fascinating topological characteristics. Early research into photonic BICs was primarily focused on designing artificial structures to produce BICs. However, since the mid-2010s, exploring the potential applications of BICs has been a growing trend in research. In this Review, we detail the unique properties of BICs, including the ability to achieve enhanced light confinement, sharp Fano resonances, and topological characteristics. We also explore phenomena derived from BICs including the generation of circularly polarized states and unidirectional guided resonances and the impact of BICs on various applications such as lasing, nonlinear frequency conversion, waveguiding, sensing and wavefront control. We also discuss the insights provided by BICs in several emerging research frontiers, such as parity-time symmetric systems, higher-order topology, exciton-photon coupling, and moiré superlattices.

physics.optics↗

arXiv2024

Towards Open Domain Text-Driven Synthesis of Multi-Person Motions

This work aims to generate natural and diverse group motions of multiple humans from textual descriptions. While single-person text-to-motion generation is extensively studied, it remains challenging to synthesize motions for more than one or two subjects from in-the-wild prompts, mainly due to the lack of available datasets. In this work, we curate human pose and motion datasets by estimating pose information from large-scale image and video datasets. Our models use a transformer-based diffusion framework that accommodates multiple datasets with any number of subjects or frames. Experiments explore both generation of multi-person static poses and generation of multi-person motion sequences. To our knowledge, our method is the first to generate multi-subject motion sequences with high diversity and fidelity from a large variety of textual prompts.

cs.CV↗

arXiv2024

Unveiling mussel plaque core ductility: the role of pore distribution and hierarchical structure

The mussel thread-plaque system exhibits strong adhesion and high ductility, allowing it to adhere to various surfaces. While the microstructure of plaques has been thoroughly studied, the effect of their unique porous structure on ductility remains unclear. This study firstly investigated the porous structure of mussel plaque cores using scanning electron microscopy (SEM). Two-dimensional (2D) porous representative volume elements (RVEs) with scaled distribution parameters were generated, and the calibrated phase-field modelling method was applied to analyse the effect of the pore distribution and multi-scale porous structure on the failure mechanism of porous RVEs. The SEM analysis revealed that large-scale pores exhibited a lognormal size distribution and a uniform spatial distribution. Simulations showed that increasing the normalised mean radius value of the large-scale pore distribution can statistically lead to a decreasing trend in ductility, strength and strain energy, but cannot solely determine their values. The interaction between pores can lead to two different failure modes under the same pore distribution: progressive failure mode and sudden failure mode. Additionally, the hierarchical structure of multi-scale porous RVEs can further increase ductility by 40%-60% compared to single-scale porous RVEs by reducing stiffness, highlighting the hierarchical structure could be another key factor contributing to the high ductility. These findings deepen our understanding of how the pore distribution and multi-scale porous structure in mussel plaques contribute to their high ductility and affect other mechanical properties, providing valuable insights for the future design of highly ductile biomimetic materials.

physics.app-ph↗

arXiv2024

Quantum microwave photonic mixer with a large spurious-free dynamic range

As one of the most fundamental functionalities of microwave photonics, microwave frequency mixing plays an essential role in modern radars and wireless communication systems. However, the commonly utilized intensity modulation in the systems often leads to inadequate spurious-free dynamic range (SFDR) for many sought-after applications. Quantum microwave photonics technique offers a promising solution for improving SFDR in terms of higher-order harmonic distortion. In this paper, we demonstrate two types of quantum microwave photonic mixers based on the configuration of the intensity modulators: cascade-type and parallel-type. Leveraging the nonlocal RF signal encoding capability, both types of quantum microwave photonic mixers not only exhibit the advantage of dual-channel output but also present significant improvement in SFDR. Specifically, the parallel-type quantum microwave photonic mixer achieves a remarkable SFDR value of 113.6 dB.Hz1/2, which is 30 dB better than that of the cascade-type quantum microwave photonic mixer. When compared to the classical microwave photonic mixer, this enhancement reaches a notable 53.6 dB at the expense of 8 dB conversion loss. These results highlight the superiority of quantum microwave photonic mixers in the fields of microwave and millimeter-wave systems. Further applying multi-photon frequency entangled sources as optical carriers, the dual-channel microwave frequency conversion capability endowed by the quantum microwave photonic mixer can be extended to enhance the performance of multiple-paths microwave mixing which is essential for radar net systems.

physics.optics↗

arXiv2024

A versatile quantum microwave photonic signal processing platform based on coincidence window selection technique

Quantum microwave photonics (QMWP) is an innovative approach that combines energy-time entangled biphoton sources as the optical carrier with time-correlated single-photon detection for high-speed RF signal recovery. This groundbreaking method offers unique advantages such as nonlocal RF signal encoding and robust resistance to dispersion-induced frequency fading. This paper explores the versatility of processing the quantum microwave photonic signal by utilizing coincidence window selection on the biphoton coincidence distribution. The demonstration includes finely-tunable RF phase shifting, flexible multi-tap transversal filtering (with up to 15 taps), and photonically implemented RF mixing, leveraging the nonlocal RF mapping characteristic of QMWP. These accomplishments significantly enhance the capability of microwave photonic systems in processing ultra-weak signals, opening up new possibilities for various applications.

physics.optics↗

arXiv2024

Non-Hermitian spacetime and generalized thermofield double formalism

In this paper, we explore the non-Hermitian transition matrix and its gravity dual. States in quantum field theories or gravity theories are typically prepared using Euclidean path integrals. We demonstrate that it is both natural and necessary to introduce non-Hermitian transitions to describe the state when employing different inner products in Euclidean quantum field theories. Transition matrices that are $η$-pseudo-Hermitian, with $η$ being positive-definite, play the same role as density matrices, where the operator $η$ is closely related to the definition of the inner product. Moreover, there exists a one-to-one correspondence between these transition matrices and density matrices. In the context of AdS/CFT correspondence, the Euclidean path integral in the boundary field theory can be translated to the bulk gravitational path integral. We provide an overview of the construction and interpretation of non-Hermitian spacetime. Specifically, we demonstrate the crucial role of the non-Hermitian transition matrix in realizing the thermofield concept in general cases and in understanding the gravity states dual to the eternal black hole. In this context, the pseudoentropy of the transition matrix can also be interpreted as black hole entropy. Finally, we highlight the strong subadditivity property of pseudoentropy, and the connection between non-Hermitian transition matrices and complex metrics.

hep-th↗

arXiv2024

Genshin: General Shield for Natural Language Processing with Large Language Models

Large language models (LLMs) like ChatGPT, Gemini, or LLaMA have been trending recently, demonstrating considerable advancement and generalizability power in countless domains. However, LLMs create an even bigger black box exacerbating opacity, with interpretability limited to few approaches. The uncertainty and opacity embedded in LLMs' nature restrict their application in high-stakes domains like financial fraud, phishing, etc. Current approaches mainly rely on traditional textual classification with posterior interpretable algorithms, suffering from attackers who may create versatile adversarial samples to break the system's defense, forcing users to make trade-offs between efficiency and robustness. To address this issue, we propose a novel cascading framework called Genshin (General Shield for Natural Language Processing with Large Language Models), utilizing LLMs as defensive one-time plug-ins. Unlike most applications of LLMs that try to transform text into something new or structural, Genshin uses LLMs to recover text to its original state. Genshin aims to combine the generalizability of the LLM, the discrimination of the median model, and the interpretability of the simple model. Our experiments on the task of sentimental analysis and spam detection have shown fatal flaws of the current median models and exhilarating results on LLMs' recovery ability, demonstrating that Genshin is both effective and efficient. In our ablation study, we unearth several intriguing observations. Utilizing the LLM defender, a tool derived from the 4th paradigm, we have reproduced BERT's 15% optimal mask rate results in the 3rd paradigm of NLP. Additionally, when employing the LLM as a potential adversarial tool, attackers are capable of executing effective attacks that are nearly semantically lossless.

cs.CL↗

arXiv2024

Dark Matter distinguished by skewed microlensing in the "Dragon Arc"

Microlensed stars recently discovered by JWST & HST follow closely the winding critical curve of A370 along all sections of the ``Dragon Arc" traversed by the critical curve. These transients are fainter than $m_{AB}>26.5$, corresponding to the Asymptotic Giant Branch (AGB) and microlensed by diffuse cluster stars observed with $\simeq 18M_\odot/pc^2$, or about $\simeq 1$\% of the projected dark matter density. Most microlensed stars appear along the inner edge of the critical curve, following an asymmetric band of width $\simeq 4$kpc that is skewed by $-0.7\pm0.2$kpc. Some skewness is expected as the most magnified images should form along the inner edge of the critical curve with negative parity, but the predicted shift is small $\simeq -0.04$kpc and the band of predicted detections is narrow, $\simeq 1.4$kpc. Adding CDM-like dark halos of $10^{6-8}M_\odot$ broadens the band as desired but favours detections along the outer edge of the critical curve, in the wrong direction, where sub-halos generate local Einstein rings. Instead, the interference inherent to ``Wave Dark Matter" as a Bose-Einstein condensate ($ψ$DM) forms a symmetric band of critical curves that favours negative parity detections. A de Broglie wavelength of $\simeq 10$pc matches well the observed $4$kpc band of microlenses and predicts negative skewness $\simeq -0.6$kpc, similar to the data. The implied corresponding boson mass is $\simeq 10^{-22}$eV, in good agreement with estimates from dwarf galaxy cores when scaled by momentum. Further JWST imaging may reveal the pattern of critical curves by simply ``joining the dots" between microlensed stars, allowing wave corrugations of $ψ$DM to be distinguished from CDM sub-halos

astro-ph.CO↗