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Xiaojun Liu

Publications and source records attributed to Xiaojun Liu.

At least 19 recordsLinked to original sources

Resolving electronic evolution during bond dissociation

Coupled electronic and nuclear motions govern chemical reactions, yet resolving how electronic structure evolves during bond dissociation remains a central challenge. Here we investigate the photodissociation of Br2 using correlated photoelectron photoion coincidence measurements. A 400 nm pulse initiates dissociation, while strong field ionization probes the evolving molecular system. Coincident measurement of three dimensional photoion and photoelectron momenta provides simultaneous access to the internuclear separation and the accompanying electronic evolution. We identify multiple distinct stages of electronic evolution during bond dissociation. The reshaping of the ionizing molecular orbital occurs first, followed by redistribution and localization of the electronic charge density, and finally by the gradual decay of residual electronic coherence between the separating atomic centers. Between the molecular and atomic limits, we observe an intermediate bond-breaking state in which localized atomic character coexists with a partially delocalized electronic response. By combining correlated observables with semiclassical modelling, we resolve the temporal ordering of these coupled electronic and nuclear processes and determine their associated dynamical timescales. These results demonstrate how correlated momentum observables can disentangle different aspects of the molecular-to-atomic transition.

physics.chem-ph

Asynchronous Parallel Search for Exact Multi-Objective Shortest Paths with Versioned Frontier Snapshots and Indexed Dominance Pruning

Exact multi-objective shortest-path (MOSP) search computes the complete Pareto set between specified start and goal vertices, and its computational cost can grow rapidly with expanding nondominated label sets and frequent dominance tests over per-vertex Pareto frontiers. Efficiently parallelizing exact MOSP remains an open challenge. This paper presents SIP-MOSP (Snapshot-based Indexed-Pruning MOSP), an asynchronous exact framework that separates label expansion from frontier maintenance within a single cooperative search. SIP-MOSP combines immutable versioned frontier snapshots with indexed dominance pruning, enabling concurrent label processing without concurrent access to the same mutable frontier. Together, these mechanisms reduce synchronization overhead and accelerate dominance testing. We instantiate the framework with block-minimum (SIP-MOSP-BM) and segment-tree-minimum (SIP-MOSP-ST) indices and prove exactness. We evaluate both variants against four state-of-the-art exact MOSP baselines covering sequential and parallel search. Experiments across multiple objective dimensions on a road network, an Internet service provider topology, and an 180-vertex complete directed graph show that SIP-MOSP achieves speedups of up to 46.9* over the best-performing sequential baseline and up to 7.05* over the best-performing parallel baseline on mutually solved instances. In the 20-objective complete-graph setting, where many instances remain unsolved by the sequential baselines within one hour, SIP-MOSP-ST achieves a 3.34* speedup while reducing peak memory by a factor of 60.3 relative to the best-performing parallel baseline. These results demonstrate that SIP-MOSP is an efficient shared-memory framework for exact MOSP across structurally diverse graph topologies.

cs.DC

Simultaneous Determination of Multiple Nuclear Parameters of $^{229}$Th Using Highly Charged Ions

Development of a $^{229}$Th nuclear optical clock requires precise and model-insensitive nuclear-structure parameters, which presently suffer from limited accuracy and poor consistency. We propose a joint spectroscopy scheme using two highly charged $^{229}$Th ions with $J=1/2$ electronic ground states, where the lowest electronic excitation energy of each ion far exceeds the nuclear transition energy. This configuration effectively forms a three-level system comprising the electronic ground state and the nuclear ground ($g$) and isomeric ($m$) states, resulting in strongly enhanced nuclear hyperfine mixing. Within this framework, a unified analysis of precision measurements on both ions enables the simultaneous determination of five key nuclear parameters without relying on external nuclear inputs: the magnetic dipole moments $μ_g$ and $μ_m$, the bare-nucleus transition energy $ω_n$, the charge-radius difference $δ\langle r^{2}\rangle_{gm}$, and the $M1$ transition matrix element $T_{M1}$. With this approach, the uncertainties in $ω_n$ and $δ\langle r^{2}\rangle_{gm}$ are estimated to be reduced by factors of 3 and 2, respectively, relative to their current uncertainties. %compared with current values. This work could provide a useful benchmark for nuclear theory and serve as a foundation for future development of a $^{229}$Th-based nuclear optical clock.

physics.atom-ph

SparseAD: Sparse Query-Centric Paradigm for Efficient End-to-End Autonomous Driving

End-to-End paradigms use a unified framework to implement multi-tasks in an autonomous driving system. Despite simplicity and clarity, the performance of end-to-end autonomous driving methods on sub-tasks is still far behind the single-task methods. Meanwhile, the widely used dense BEV features in previous end-to-end methods make it costly to extend to more modalities or tasks. In this paper, we propose a Sparse query-centric paradigm for end-to-end Autonomous Driving (SparseAD), where the sparse queries completely represent the whole driving scenario across space, time and tasks without any dense BEV representation. Concretely, we design a unified sparse architecture for perception tasks including detection, tracking, and online mapping. Moreover, we revisit motion prediction and planning, and devise a more justifiable motion planner framework. On the challenging nuScenes dataset, SparseAD achieves SOTA full-task performance among end-to-end methods and significantly narrows the performance gap between end-to-end paradigms and single-task methods. Codes will be released soon.

cs.CV

Table-Top Tunable Chiral Photonic Emitter

The increasing interest in chiral light stems from its spiral trajectory along the propagation direction, facilitating the interaction between different polarization states of light and matter. Despite tremendous achievements in chiral light-related research, the generation and control of chiral pulse have presented enduring challenges, especially at the terahertz and ultraviolet spectral ranges, due to the lack of suitable optical elements for effective pulse manipulation. Conventionally, chiral light can be obtained from intricate optical systems, by an external magnetic field, or by metamaterials, which necessitate sophisticated optical configurations. Here, we propose a versatile tunable chiral emitter, composed of only two planar Weyl semimetals slabs, addressing the challenges in both spectral ranges. Our results open the way to a compact tunable chiral emitter platform in both terahertz and ultra-violet frequency ranges. This advancement holds the potential to serve as the cornerstone for integrated chiral photonics.

physics.optics

Imagining density distribution of molecular orbitals in IR+XUV co-rotating circular laser fields by frequency-domain theory

We have investigated the angle-resolved ATI spectrum of oriented molecules in the IR+XUV co-rotating circular laser fields. According to the different roles of IR and XUV laser in the ionization process, we purposefully adjust the photon energy of XUV and the intensity of IR laser to make the ionization spectrum of the molecule distributed in a suitable momentum region. Moreover, under the same laser conditions, the background fringes in the ionization spectrum of the molecule can be removed by using the ionization spectrum of the atom with the same ionization energy as the molecule, so that the molecular orbital density distribution in the suitable momentum region can be obtained. That is, for any unknown molecule, as long as the ionization energy of the molecule can be measured, the density distribution of the molecular orbital can be imaged in a definite momentum region by adjusting the laser field conditions, which may shed light on the experimental detection of molecular orbitals.

physics.atom-ph

A Consumer-tier based Visual-Brain Machine Interface for Augmented Reality Glasses Interactions

Objective.Visual-Brain Machine Interface(V-BMI) has provide a novel interaction technique for Augmented Reality (AR) industries. Several state-of-arts work has demonstates its high accuracy and real-time interaction capbilities. However, most of the studies employ EEGs devices that are rigid and difficult to apply in real-life AR glasseses application sceniraros. Here we develop a consumer-tier Visual-Brain Machine Inteface(V-BMI) system specialized for Augmented Reality(AR) glasses interactions. Approach. The developed system consists of a wearable hardware which takes advantages of fast set-up, reliable recording and comfortable wearable experience that specificized for AR glasses applications. Complementing this hardware, we have devised a software framework that facilitates real-time interactions within the system while accommodating a modular configuration to enhance scalability. Main results. The developed hardware is only 110g and 120x85x23 mm, which with 1 Tohm and peak to peak voltage is less than 1.5 uV, and a V-BMI based angry bird game and an Internet of Thing (IoT) AR applications are deisgned, we demonstrated such technology merits of intuitive experience and efficiency interaction. The real-time interaction accuracy is between 85 and 96 percentages in a commercial AR glasses (DTI is 2.24s and ITR 65 bits-min ). Significance. Our study indicates the developed system can provide an essential hardware-software framework for consumer based V-BMI AR glasses. Also, we derive several pivotal design factors for a consumer-grade V-BMI-based AR system: 1) Dynamic adaptation of stimulation patterns-classification methods via computer vision algorithms is necessary for AR glasses applications; and 2) Algorithmic localization to foster system stability and latency reduction.

cs.CV

Quantitative phase imaging of opaque specimens with flexible endoscopic microscopy

The flexible endoscope is a minimally invasive tool in clinical settings, but most of them rely on exogenous staining for diagnosis to provide qualitative information. Here, we demonstrated a flexible endoscopic microscopy (FEM) with diffracted gradient light for quantitative phase imaging of unlabeled thick samples. Our instrument features a small form factor fiber bundle as the endoscope probe, cellular-level lateral and axial resolutions, and direct phase measurement via simple field modulation. By testing pathologic slices, thick opaque mammalian tissue ex vivo and wound healing in vivo, FEM identifies normal and tumor glandular structures, secreta, and tomographic skin layers. With the advantages of direct morphological and phase measurement, high resolution, and thin fiber tip, the label-free FEM could be an attractive tool for various clinical applications.

physics.optics

PSNet: a deep learning model based digital phase shifting algorithm from a single fringe image

As the gold standard for phase retrieval, phase-shifting algorithm (PS) has been widely used in optical interferometry, fringe projection profilometry, etc. However, capturing multiple fringe patterns in PS limits the algorithm to only a narrow range of application. To this end, a deep learning (DL) model based digital PS algorithm from only a single fringe image is proposed. By training on a simulated dataset of PS fringe patterns, the learnt model, denoted PSNet, can predict fringe patterns with other PS steps when given a pattern with the first PS step. Simulation and experiment results demonstrate the PSNet's promising performance on accurate prediction of digital PS patterns, and robustness to complex scenarios such as surfaces with varying curvature and reflectance.

physics.optics

CLTS+: A New Chinese Long Text Summarization Dataset with Abstractive Summaries

The abstractive methods lack of creative ability is particularly a problem in automatic text summarization. The summaries generated by models are mostly extracted from the source articles. One of the main causes for this problem is the lack of dataset with abstractiveness, especially for Chinese. In order to solve this problem, we paraphrase the reference summaries in CLTS, the Chinese Long Text Summarization dataset, correct errors of factual inconsistencies, and propose the first Chinese Long Text Summarization dataset with a high level of abstractiveness, CLTS+, which contains more than 180K article-summary pairs and is available online. Additionally, we introduce an intrinsic metric based on co-occurrence words to evaluate the dataset we constructed. We analyze the extraction strategies used in CLTS+ summaries against other datasets to quantify the abstractiveness and difficulty of our new data and train several baselines on CLTS+ to verify the utility of it for improving the creative ability of models.

cs.CL

Structure Information is the Key: Self-Attention RoI Feature Extractor in 3D Object Detection

Unlike 2D object detection where all RoI features come from grid pixels, the RoI feature extraction of 3D point cloud object detection is more diverse. In this paper, we first compare and analyze the differences in structure and performance between the two state-of-the-art models PV-RCNN and Voxel-RCNN. Then, we find that the performance gap between the two models does not come from point information, but structural information. The voxel features contain more structural information because they do quantization instead of downsampling to point cloud so that they can contain basically the complete information of the whole point cloud. The stronger structural information in voxel features makes the detector have higher performance in our experiments even if the voxel features don't have accurate location information. Then, we propose that structural information is the key to 3D object detection. Based on the above conclusion, we propose a Self-Attention RoI Feature Extractor (SARFE) to enhance structural information of the feature extracted from 3D proposals. SARFE is a plug-and-play module that can be easily used on existing 3D detectors. Our SARFE is evaluated on both KITTI dataset and Waymo Open dataset. With the newly introduced SARFE, we improve the performance of the state-of-the-art 3D detectors by a large margin in cyclist on KITTI dataset while keeping real-time capability.

cs.CV

Computational interference microscopy enabled by deep learning

Quantitative phase imaging (QPI) has been widely applied in characterizing cells and tissues. Spatial light interference microscopy (SLIM) is a highly sensitive QPI method, due to its partially coherent illumination and common path interferometry geometry. However, its acquisition rate is limited because of the four-frame phase-shifting scheme. On the other hand, off-axis methods like diffraction phase microscopy (DPM), allows for single-shot QPI. However, the laser-based DPM system is plagued by spatial noise due to speckles and multiple reflections. In a parallel development, deep learning was proven valuable in the field of bioimaging, especially due to its ability to translate one form of contrast into another. Here, we propose using deep learning to produce synthetic, SLIM-quality, high-sensitivity phase maps from DPM, single-shot images as input. We used an inverted microscope with its two ports connected to the DPM and SLIM modules, such that we have access to the two types of images on the same field of view. We constructed a deep learning model based on U-net and trained on over 1,000 pairs of DPM and SLIM images. The model learned to remove the speckles in laser DPM and overcame the background phase noise in both the test set and new data. Furthermore, we implemented the neural network inference into the live acquisition software, which now allows a DPM user to observe in real-time an extremely low-noise phase image. We demonstrated this principle of computational interference microscopy (CIM) imaging using blood smears, as they contain both erythrocytes and leukocytes, in static and dynamic conditions.

eess.IV

Local probe of the interlayer coupling strength of few-layers SnSe by contact-resonance atomic force microscopy

The interlayer bonding in two dimensional materials is particularly important because it is not only related to their physical and chemical stability but also affects their mechanical, thermal, electronic, optical, and other properties. To address this issue, we report the direct characterization of the interlayer bonding in 2D SnSe using contact-resonance atomic force microscopy in this study. Site specific CR spectroscopy and CR force spectroscopy measurements are performed on both SnSe and its supporting SiO2 substrate comparatively. Based on the cantilever and contact mechanic models, the contact stiffness and vertical Young's modulus are evaluated in comparison with SiO2 as a reference material. The interlayer bonding of SnSe is further analyzed in combination with the semi-analytical model and density functional theory calculations. The direct characterization of interlayer interactions using this nondestructive methodology of CR AFM would facilitate a better understanding of the physical and chemical properties of 2D layered materials, specifically for interlayer intercalation and vertical heterostructures.

cond-mat.mtrl-sci

Resonant Asymmetric All-Dielectric Metasurface for Boosting Third-Harmonic Generation

Resonant metasurfaces have received extensive attention due to their sharp spectral feature and extraordinary field enhancement. In this work, by breaking the in-plane symmetry of silicon nanopillars, we achieve a sharp Fano resonance. The far-field radiation and near-field distribution of metasurfaces are calculated and analyzed to further uncover the resonant performance of metasurfaces. Moreover, the theoretical derivation and simulation exhibit an inverse quadratic dependence of Q-factors on asymmetry parameters, revealing that the resonance is governed by the symmetry-protected bound states in the continuum. Finally we experimentally demonstrate the sharp resonance, and employ it to effciently boost the third-harmonic generation. This enhancement can be attributed to the strong optical intensity enhancement inside the metasurface.

physics.optics

Understanding two-photon double ionization of helium from the perspective of the characteristic time of dynamic transitions

By using the B-spline numerical method, we investigate a two-photon double-ionization (TPDI) process of helium in a high-frequency laser field with its frequency ranging from 1.6~a.u. to 3.0~a.u. and the pulse duration ranging from 75 to 160~attoseconds. We found that there exists a characteristic time $t_{c}$ for a TPDI process, such that the pattern of energy distribution of two ionized electrons presents a peak or two, depending respectively on whether the pulse duration is shorter or longer than $t_{c}$. Especially, as the pulse duration is larger than $t_c$, the TPDI spectrum shows a double-peak structure which is attributed to the fact that most of the electron-electron Coulomb interaction energy is acquired by single electron during their oscillation around the nucleus before the two electrons leave. Additionally, if the photon energy is less than the ionization energy of He$^{+}$, $t_{c}$ is not a fixed value, and it increases as the photon energy decreases; while if the energy of a photon is greater than the ionization energy of He$^{+}$, $t_{c}$ is fixed at about 105 attoseconds. We further found that, for a helium-like ion in its ground state, the characteristic time for the case of the photon energy larger than the ionization energy of the second electron has a key relation with the Coulomb interaction energy $\overline{V}_{12}$ between the two electrons, which can be expressed as $t_{c}\overline{V}_{12}=4.192$, a type of quantum mechanical uncertainty relation between time and energy. In addition, this relation can be attributed to the existence of a minimal evolution time from the ground state to a double ionization state with two electrons carrying different energies. These results may shed light on deeper understanding of many-electron quantum dynamical processes.

physics.atom-ph

Long range dipole-dipole interaction in atomic vapors probed by double-quantum two-dimensional coherent spectroscopy

Optical double-quantum two-dimensional coherent spectroscopy (2DCS) was implemented to probe interatomic dipole-dipole interactions in both potassium and rubidium atomic vapors. The dipole-dipole interaction was detected at densities of $4.81 \times 10^8$ cm$^{-3}$ and $8.40 \times 10^9$ cm$^{-3}$ for potassium and rubidium, respectively, corresponding to a mean interatomic separation of 15.8 $μ$m or $3.0\times 10^5a_0$ for potassium and 6.1 $μ$m or $1.2\times 10^5a_0$ for rubidium, where $a_0$ is the Bohr radius. We report the lowest atomic density at which dipole-dipole interactions are detected. The experimental results confirm the long range nature of the dipole-dipole interaction which is critical for understanding many-body physics in atoms/molecules. The long range interaction also has implications in atom-based applications involving many-body interactions. Additionally, we demonstrated that double-quantum 2DCS is sufficiently sensitive to probe dipole-dipole interaction at densities that can be achieved with cold atom in a magneto-optical trap, paving the way for double-quantum 2DCS studies of cold atoms and molecules. The method can also open a new avenue to study long-range interactions in solid states systems such as quantum dots and color centers in diamonds.

physics.atom-ph

Observation of scalable and deterministic multi-atom Dicke states in an atomic vapor

Dicke state, a coherent state of multiple particles, is fundamentally responsible for various intriguing collective behaviors of many-body systems. Experimental access to Dicke states with a scalable and deterministic number of particles is essential to study how many-body properties depend on the particle number. We report the observation of Dicke states consisting of two, three, four, five, six, and seven atoms in an atomic vapor. Quantum coherences between the ground state and multi-atom states are created and detected by using optical two-dimensional coherent spectroscopy. The signal originated from multi-atom states is manifested as correlation between the multi-quantum coherence and the emission signal, providing direct and unambiguous detection of Dicke states. The manipulation of deterministic atomic Dicke states has possible implications in quantum information processing and fundamental many-body physics.

physics.atom-ph

Photoelectron angular distribution from the high-order above-threshold ionization process in IR+XUV two-color laser fields

High-order above-threshold ionization (HATI) spectrum in IR+XUV two-color laser fields has been investigated. We found that the quantum features corresponding to the absorption of the XUV photon is well illustrated by a peculiar dip structure in the second plateau of the HATI spectrum. By the channel analysis, we show that the angular distribution of the spectrum is attributed to the coherent summation over contributions of different channels, and the dip structure in the spectrum is directly related to the absorption of one XUV photon of the ionized electron during the laser-assisted collision (LAC) with its parent ion in the two-color laser fields. Moreover, by employing the saddle-point approximation, we obtain the classical energy orbit equation, and find that the dip structure comes from the fact that the LAC is limited at a certain direction by the momentum conservation law as the electron absorbs one XUV photon during the collision, where the probability of the HATI gets its minimum value. Finally, we find that the interference pattern in the whole spectrum is attributed to the interference of different orbits at collision moments $t_0$ and $2π/ω_1-t_0$ in the LAC process.

physics.atom-ph