arXiv subjects

Xiaohui Zhao

Publications and source records attributed to Xiaohui Zhao.

15 recordsLinked to original sources

arXiv2026

All-optical reconstruction of valley polarization through helicity-resolved high-harmonic generation

We theoretically investigate valley-resolved high-order harmonic generation in gapped graphene driven by elliptically polarized laser fields. Using two-band density-matrix simulations and an electron-hole recombination trajectory model, we find that the two inequivalent valleys emit harmonics with opposite helicities. Under an elliptically polarized field, these emissions occur predominantly in different half cycles of the laser field. Time-dependent density functional theory calculations for monolayer MoS$_2$ show the same temporal separation of harmonic emissions with opposite helicities, supporting the generality of this valley-dependent chiral response. We further propose an all-optical scheme to reconstruct valley polarization from helicity-resolved harmonic signals. A circularly polarized pulse first prepares a valley population imbalance. A subsequent elliptically polarized laser induces different changes in the harmonic intensities of opposite helicities through Pauli blocking. The ratio of these intensity changes provides a direct measure of the valley polarization. Our results demonstrate that chiral high-harmonic emission can serve as an all-optical probe of ultrafast valley-dependent carrier dynamics.

physics.optics↗

arXiv2026

Efficient hot electron generation via low-coherence lasers

Hot electrons generated in laser-produced plasmas are a central focus in inertial confinement fusion, laboratory astrophysics, and high-energy-density physics. These electrons originate from instabilities in nonlinear laser-plasma interactions, which are critically modulated by laser bandwidth. Here, we experimentally demonstrate enhanced generation of hot electrons by utilizing instantaneous low-coherence lasers with two bandwidths (0.2% and 0.6%) at intensities of 2-8x10^{14} W/cm^2 and energies up to 620 J. A significant enhancement of hot electron temperature and hard X-ray yield is observed with the broadband lasers compared to a conventional narrowband laser. The results show that the hot electron energy conversion efficiency of the 0.6% broadband laser is approximately 4 times higher than that of the narrowband laser, reaching a maximum value of 2.8%. These findings validate a moderate-bandwidth laser as an efficient hot electron source and support the generation of bright X-ray sources for advanced imaging in high-energy-density physics.

physics.plasm-ph↗

arXiv2026

HT-GNN: Hyper-Temporal Graph Neural Network for Customer Lifetime Value Prediction in Baidu Ads

Lifetime value (LTV) prediction is crucial for news feed advertising, enabling platforms to optimize bidding and budget allocation for long-term revenue growth. However, it faces two major challenges: (1) demographic-based targeting creates segment-specific LTV distributions with large value variations across user groups; and (2) dynamic marketing strategies generate irregular behavioral sequences where engagement patterns evolve rapidly. We propose a Hyper-Temporal Graph Neural Network (HT-GNN), which jointly models demographic heterogeneity and temporal dynamics through three key components: (i) a hypergraph-supervised module capturing inter-segment relationships; (ii) a transformer-based temporal encoder with adaptive weighting; and (iii) a task-adaptive mixture-of-experts with dynamic prediction towers for multi-horizon LTV forecasting. Experiments on \textit{Baidu Ads} with 15 million users demonstrate that HT-GNN consistently outperforms state-of-the-art methods across all metrics and prediction horizons.

cs.LG↗

arXiv2025

Attosecond transient absorption spectroscopy in monolayer hexagonal boron nitride

We simulate the attosecond transient absorption spectroscopy (ATAS) of monolayer hexagonal boron nitride (hBN) using the time-dependent density functional theory and two-band density-matrix equations within the tight-binding approximation. The simulation results from the two methods are qualitatively consistent. We focus on the fishbone structure around the gap energy of the M point, which exhibits a temporal period equal to that of the pump laser. To gain deeper insight into this structure, we simplify the two-band model to a single-electron model located at the M point, allowing us to derive an analytical expression that can qualitatively reproduce the numerical results. By isolating the influence of the Berry connection on the ATAS, our analytical results reveal that both the interband transition dipole moments and the Berry connection play important roles in the fishbone structure of the ATAS. Moreover, we also have investigated the dependence of ATAS on the gap energy based the tight-binding approximation. The results demonstrate that the ATAS intensity is enhanced as the gap energy increases, in agreement with our analytical prediction. Our study may shed light on the generation mechanism of the fishbone structure of the ATAS in hBN.

physics.atom-ph↗

arXiv2025

Isolated elliptically-polarized attosecond pulse generation in gapped graphene driven by linearly polarized laser fields

We theoretically investigate high-order harmonic generation (HHG) and its ellipticity in gapped graphene, driven by a femtosecond short-pulse laser at various orientation angles, employing the two-band density-matrix equations within the tight-binding approximation. The orientation-dependent harmonic spectra exhibit pronounced enhancement of specific harmonics, which we attribute to the caustic effect. Using the recombination trajectory model, we reveal that the orientation dependence of these enhanced harmonics originates from the distinct band structures encountered by electrons ionized from the two inequivalent $\textrm{K}$ points. Moreover, we focus on the ellipticity of the enhanced harmonics at specific angles and demonstrate that it primarily depends on the phase difference between the parallel and perpendicular components, which can be accurately predicted by our recombination trajectory model. Based on these insights, we propose a two-color (fundamental plus second-harmonic) field scheme to generate isolated elliptically polarized attosecond pulses (IEAPs) in gapped graphene. Our findings may provide a promising pathway toward the generation of IEAPs in gapped graphene or transition metal dichalcogenides.

physics.atom-ph↗

arXiv2025

DP2FL: Dual Prompt Personalized Federated Learning in Foundation Models

Personalized federated learning (PFL) has garnered significant attention for its ability to address heterogeneous client data distributions while preserving data privacy. However, when local client data is limited, deep learning models often suffer from insufficient training, leading to suboptimal performance. Foundation models, such as CLIP (Contrastive Language-Image Pretraining), exhibit strong feature extraction capabilities and can alleviate this issue by fine-tuning on limited local data. Despite their potential, foundation models are rarely utilized in federated learning scenarios, and challenges related to integrating new clients remain largely unresolved. To address these challenges, we propose the Dual Prompt Personalized Federated Learning (DP2FL) framework, which introduces dual prompts and an adaptive aggregation strategy. DP2FL combines global task awareness with local data-driven insights, enabling local models to achieve effective generalization while remaining adaptable to specific data distributions. Moreover, DP2FL introduces a global model that enables prediction on new data sources and seamlessly integrates newly added clients without requiring retraining. Experimental results in highly heterogeneous environments validate the effectiveness of DP2FL's prompt design and aggregation strategy, underscoring the advantages of prediction on novel data sources and demonstrating the seamless integration of new clients into the federated learning framework.

cs.DC↗

arXiv2024

Amplifier scheme: driven by indirect-drive under 10 MJ laser toward inertial fusion energy

Burn efficiency is a key for commercial feasibility of fusion power station for inertial fusion energy, while burn efficiency is usually lower than 30% in the central ignition scheme of inertial confinement fusion (ICF). A recent conceptual design for a 10 MJ laser driver [Z. Sui and K. Lan et al., Matter Radiat. Extremes 9, 043002 (2024)] provides a new room for target design to achieve a higher burn efficiency. Here, we take the advantage of fuel density in reaction rate and propose a novel amplifier scheme for increasing burn efficiency via two cascading explosions by ICF. The amplifier scheme can be realized either by indirect-drive or by direct-drive. Here, we give a 1D design for an indirect-driven amplifier capsule containing 2.02 mg DT fuel under a 300 eV radiation generated by a 10 MJ and 1785 TW laser inside an octahedral spherical hohlraum. As a result, the amplifier capsule has a burn efficiency of 48% and a gain of 33 at a convergence ratio of 24. This novel scheme can achieve a relatively high burn efficiency at a relatively low convergence ratio, which can greatly relax the stringent requirements of high gain fusion on hot spot ignition conditions and engineering issues.

physics.plasm-ph↗

arXiv2024

Amplifier scheme: driven by direct-drive under 10 MJ laser toward inertial fusion energy

The National Ignition Facility successfully achieved target gain 2.4 thus marginally entering into burn stage.Meanwhile, a recent conceptual design on 10 MJ laser driver [Matter Radiat. Extremes 9, 043002 (2024)] provides a new room for exploring novel target designs and interesting phenomena in a burning plasma after ignition. In this paper, we propose an amplifier scheme with extended burn stage, which includes secondary implosion, generates extremely hot and dense fusion fireball, and produces additional gain. The amplifier scheme can be realized either by direct-drive or by indirect-drive. Here, we present a direct-drive amplifier design. The amplifier scheme can be realized at a low convergence ratio, so it can greatly relax the \r{ho} RT hot spot condition and the stringent requirements on engineering issues by a high gain fusion. Especially, the fireball lasts for 30 ps, reaching 330 g/cc, 350 keV, 54 Tbar at center when the secondary explosion happens, which leaves an important room for novel target designs towards clean fusion energy.

physics.plasm-ph↗

arXiv2024

Have the VLMs Lost Confidence? A Study of Sycophancy in VLMs

In the study of LLMs, sycophancy represents a prevalent hallucination that poses significant challenges to these models. Specifically, LLMs often fail to adhere to original correct responses, instead blindly agreeing with users' opinions, even when those opinions are incorrect or malicious. However, research on sycophancy in visual language models (VLMs) has been scarce. In this work, we extend the exploration of sycophancy from LLMs to VLMs, introducing the MM-SY benchmark to evaluate this phenomenon. We present evaluation results from multiple representative models, addressing the gap in sycophancy research for VLMs. To mitigate sycophancy, we propose a synthetic dataset for training and employ methods based on prompts, supervised fine-tuning, and DPO. Our experiments demonstrate that these methods effectively alleviate sycophancy in VLMs. Additionally, we probe VLMs to assess the semantic impact of sycophancy and analyze the attention distribution of visual tokens. Our findings indicate that the ability to prevent sycophancy is predominantly observed in higher layers of the model. The lack of attention to image knowledge in these higher layers may contribute to sycophancy, and enhancing image attention at high layers proves beneficial in mitigating this issue.

cs.CV↗

arXiv2019

Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale

Probabilistic programming languages (PPLs) are receiving widespread attention for performing Bayesian inference in complex generative models. However, applications to science remain limited because of the impracticability of rewriting complex scientific simulators in a PPL, the computational cost of inference, and the lack of scalable implementations. To address these, we present a novel PPL framework that couples directly to existing scientific simulators through a cross-platform probabilistic execution protocol and provides Markov chain Monte Carlo (MCMC) and deep-learning-based inference compilation (IC) engines for tractable inference. To guide IC inference, we perform distributed training of a dynamic 3DCNN--LSTM architecture with a PyTorch-MPI-based framework on 1,024 32-core CPU nodes of the Cori supercomputer with a global minibatch size of 128k: achieving a performance of 450 Tflop/s through enhancements to PyTorch. We demonstrate a Large Hadron Collider (LHC) use-case with the C++ Sherpa simulator and achieve the largest-scale posterior inference in a Turing-complete PPL.

cs.LG↗

arXiv2019

CUTIE: Learning to Understand Documents with Convolutional Universal Text Information Extractor

Extracting key information from documents, such as receipts or invoices, and preserving the interested texts to structured data is crucial in the document-intensive streamline processes of office automation in areas that includes but not limited to accounting, financial, and taxation areas. To avoid designing expert rules for each specific type of document, some published works attempt to tackle the problem by learning a model to explore the semantic context in text sequences based on the Named Entity Recognition (NER) method in the NLP field. In this paper, we propose to harness the effective information from both semantic meaning and spatial distribution of texts in documents. Specifically, our proposed model, Convolutional Universal Text Information Extractor (CUTIE), applies convolutional neural networks on gridded texts where texts are embedded as features with semantical connotations. We further explore the effect of employing different structures of convolutional neural network and propose a fast and portable structure. We demonstrate the effectiveness of the proposed method on a dataset with up to $4,484$ labelled receipts, without any pre-training or post-processing, achieving state of the art performance that is much better than the NER based methods in terms of either speed and accuracy. Experimental results also demonstrate that the proposed CUTIE model being able to achieve good performance with a much smaller amount of training data.

cs.CV↗

arXiv2019

High-Efficiency Second Harmonic Generation of Low-Temporal-Coherent Light Pulse

The nonlinear frequency conversion of low-temporal-coherent light holds a variety of applications and has attracted considerable interest. However, its physical mechanism remains relatively unexplored, and the conversion efficiency and bandwidth are extremely insufficient. Here, considering the instantaneous broadband characteristic, we establish a model of second harmonic generation (SHG) of low-temporal-coherent pulse, and reveal its differences from the coherent conditions. It is found that the second harmonic (SH) of low-temporal-coherent light is produced by not only the degenerate SH processes but also crossed sum-frequency processes. On the basis of this, we propose a method for realizing low-temporal-coherent SHG with high efficiency and broad bandwidth, and experimentally demonstrate a conversion efficiency up to 70% with a bandwidth of 3.1 THz (2.9 nm centered at 528 nm). To the best of our knowledge, this is the highest efficiency and broadest bandwidth of low-temporal-coherent SHG, and its efficiency is almost the same with that of the narrowband coherent condition. Furthermore, the spectral evolution characteristics of the broadband low-temporal-coherent pulse in SHG process are revealed in experiments, that the SH power spectral density (PSD) is proportional to the self-convolution of the fundamental wave PSD, which is greatly different from that of the coherent process. Our research opens a door for the study of the low-coherent nonlinear optical processes.

physics.optics↗

arXiv2016

Enhancement of UV Second-Harmonic Radiation at Nonlinear Interfaces with Discontinuous Second-order Susceptibilities

We investigate the generation of ultraviolet (UV) second-harmonic radiation on the boundary of a UV transparent crystal, which is derived from the automatic partial phase matching of the incident wave and the total internal reflection. By adhering to another UV non-transparency crystal with larger second-order nonlinear coefficient χ^{(2)}, an nonlinear interface with large disparity in χ^{(2)} is formed and the enhancement of UV second-harmonic radiation is observed experimentally. The intensity of enhanced second harmonic wave generated at the nonlinear interface was up to 11.6 times at the crystal boundary. As a tunable phase-matching method, it may suggest potential applications in the UV, even vacuum-UV, spectral region.

physics.optics↗

arXiv2016

Surface enhanced nonlinear Cherenkov radiation in one-dimensional nonlinear photonic crystal

We study the configuration of efficient nonlinear Cerenkov diffraction generated from a one-dimensional nonlinear photonic crystal surface, which underlies the incorporation of both quasi-phase-matching and total internal reflection by the crystal surface. Multidirectional radiation spots with different Cerenkov angles are demonstrated experimentally, which results from different orders of reciprocal vectors. At specific angles, the incident light and total internal reflect light associating with quasi-phase-matching format completely phase-matching scheme, leading to great enhancement of harmonic efficiency.

physics.optics↗

arXiv2015

Coexisting Success Probability and Throughput of Multi-RAT Wireless Networks with Unlicensed Band Access

In this letter, the coexisting success probability and throughput of a wireless network consisting of multiple subnetworks of different radio access technologies (RATs) is investigated. The coexisting success probability that is defined as the average of all success probabilities of all subnetworks is found in closed-form and it will be shown to have the concavity over the number of channels in the unlicensed band. The optimal deployment densities of all different RATs access points (APs) that maximize the coexisting success probability are shown to exist and can be found under the derived constraint on network parameters. The coexisting throughput is defined as the per-channel sum of all spectrum efficiencies of all subnetworks and numerical results show that it is significantly higher than the throughput of the unlicensed band only accessed by WiFi APs.

cs.NI↗