arXiv subjects

Tao Liu

Publications and source records attributed to Tao Liu.

At least 91 records · Page 5Linked to original sources

arXiv2026

A Vehicle-portable Ultra-stable Laser for Operating on Highways

Portable ultra-stable lasers are essential for high-precision measurements. This study presents a 1550 nm vehicle-portable ultra-stable laser designed for continuous real-time operation on highways. We implement several measures to mitigate environmental impacts, including active temperature control with a standard deviation of mK/day to reduce frequency drift of the optical reference cavity, all-polarization-maintaining fiber devices to enhance the robustness of the optical path, and highly integrated electronic units to diminish thermal effects. The performance of the ultra-stable laser is evaluated through real-time beat frequency measurements with another similar ultra-stable laser over a transport distance of approximately 100 km, encompassing rural roads, national roads, urban roads, and expressways. The results indicate frequency stability of approximately 10-12/(0.01s-100 s) during transport, about 5E-14/s while the vehicle is stationary with the engine running, and around 3E-15/s with the engine off, all without active vibration isolation. This work marks the first recorded instance of a portable ultra-stable laser achieving continuous real-time operation on highways and lays a crucial foundation for non-laboratory applications, such as mobile laser communication and dynamic free-space time-frequency comparison.

physics.optics↗

arXiv2025

Entanglement of General Subregions in Time-Dependent States

We develop a unified framework for computing Rényi and entanglement entropies of arbitrary spacetime intervals in time-dependent states of $(1+1)$-dimensional conformal field theories. By combining the spacetime density matrix formalism with the replica method, we show that entanglement entropy is well defined for both spacelike and timelike separations. Applying this framework to global quenches prepared by boundary states and to local quenches generated by operator insertions, we obtain analytic expressions for the entanglement entropy in general spacetime configurations. The results reveal qualitative differences between spacelike and timelike intervals: the timelike entanglement entropy is time-independent in the global quench model, depends solely on the temporal separation, and universally exhibits a constant imaginary contribution. These features are naturally explained by a generalized quasiparticle picture in which entanglement is produced precisely when one worldline of each quasiparticle pair intersects the interval. Furthermore, we demonstrate that the linear sum rule relating time- and spacelike entanglement persists in both global and local quenches, indicating a broader universality of spacetime entanglement in real-time quantum dynamics.

hep-th↗

arXiv2025

IMTalker: Efficient Audio-driven Talking Face Generation with Implicit Motion Transfer

Talking face generation aims to synthesize realistic speaking portraits from a single image, yet existing methods often rely on explicit optical flow and local warping, which fail to model complex global motions and cause identity drift. We present IMTalker, a novel framework that achieves efficient and high-fidelity talking face generation through implicit motion transfer. The core idea is to replace traditional flow-based warping with a cross-attention mechanism that implicitly models motion discrepancy and identity alignment within a unified latent space, enabling robust global motion rendering. To further preserve speaker identity during cross-identity reenactment, we introduce an identity-adaptive module that projects motion latents into personalized spaces, ensuring clear disentanglement between motion and identity. In addition, a lightweight flow-matching motion generator produces vivid and controllable implicit motion vectors from audio, pose, and gaze cues. Extensive experiments demonstrate that IMTalker surpasses prior methods in motion accuracy, identity preservation, and audio-lip synchronization, achieving state-of-the-art quality with superior efficiency, operating at 40 FPS for video-driven and 42 FPS for audio-driven generation on an RTX 4090 GPU. We will release our code and pre-trained models to facilitate applications and future research.

cs.CV↗

arXiv2025

Observation of gigantic orbital mixing conductance

We report that due to the orbital Hall effect, orbital pumping effects can occur in materials with weak spin-orbit coupling. Moreover, there is a positive correlation between the strength of the orbital Hall effect and the size of spin-pumping. During the spin-pumping, with the enhancement of the orbital Hall effect, the resonant absorption of orbital current and the damping of the ferromagnetic layer also increase. Especially, when the thickness of Ti reaches 60 nm, the orbital -mixing conductance of Ti/Co is an order of magnitude higher than spin-mixing conductance of heavy metal/Co, reaching 474.1 3 ^18 m^(-2). The results indicate that the orbital current is more easily transmitted across the interface

physics.app-ph↗

arXiv2025

Primal-Dual Bundle Methods for Linear Equality-Constrained Problems

Dual ascent (DA) and the method of multipliers (MM) are fundamental methods for solving linear equality-constrained convex optimization problems, and their dual updates can be viewed as the minimization of a proximal linear surrogate function of the negative Lagrange dual and augmented Lagrange dual function, respectively. However, the proximal linear surrogate function may suffer from low approximation accuracy, which leads to slow convergence of DA and MM. To accelerate their convergence, we adapt the proximal bundle surrogate framework that can incorporate a list of more accurate surrogate functions, to both the primal and the dual updates of DA and MM, leading to a family of novel primal-dual bundle methods. Our methods generalize the primal-dual gradient method, DA, the linearized MM, and MM. Under standard assumptions that allow for a broad range of surrogate functions, we prove theoretical convergence guarantees for the proposed methods. Numerical experiments demonstrate that our methods converge not only faster, but also significantly more robust with respect to the parameters compared to the primal-dual gradient method, DA, the linearized MM, and MM.

math.OC↗

arXiv2025

Tri-Level Stochastic-Robust Co-Planning of Distribution Networks and Renewable Charging Stations With an Adaptive iC&CG Algorithm

Renewable charging stations (RCSs) that co-locate electric-vehicle (EV) charging with distributed generation (DG) can raise renewable utilization and improve distribution-network (DN) efficiency, yet their variability and the siting-dependent charging demand can overload feeders if placed poorly. This paper proposes a tri-level, two-stage stochastic-robust optimization (SRO) co-planning framework that jointly determines RCS siting and DN expansion while accounting for transportation flows and population density. The model distinguishes two uncertainty classes: (i) decision-dependent uncertainty (DDU), under which EV charging loads vary with RCS siting; and (ii) decision-independent uncertainty (DIU), under which load fluctuations and renewable-generation variability do not depend on the RCS locations or the DN topology. At the upper level, the framework selects RCS sites and DN expansions. At the middle level, EV routing and charging are dispatched given the RCS siting to produce charging loads DDU. At the lower level, DN operation minimizes annualized loss costs under the worst-case DIU, reformulated via Karush-Kuhn-Tucker (KKT) conditions. To solve the resulting problem efficiently, we develop an adaptive inexact column-and-constraint generation (A-iC&CG) algorithm and prove finite-iteration convergence. Case studies on a 47-node DN coupled with a 68-hub transportation network in Shenzhen, China, show that A-iC&CG outperforms benchmark algorithms and that PV-EV hybrid stations are cost-optimal, with RCS siting concentrated near substations and high-flow hubs.

eess.SY↗

arXiv2025

DiffusionUavLoc: Visually Prompted Diffusion for Cross-View UAV Localization

With the rapid growth of the low-altitude economy, unmanned aerial vehicles (UAVs) have become key platforms for measurement and tracking in intelligent patrol systems. However, in GNSS-denied environments, localization schemes that rely solely on satellite signals are prone to failure. Cross-view image retrieval-based localization is a promising alternative, yet substantial geometric and appearance domain gaps exist between oblique UAV views and nadir satellite orthophotos. Moreover, conventional approaches often depend on complex network architectures, text prompts, or large amounts of annotation, which hinders generalization. To address these issues, we propose DiffusionUavLoc, a cross-view localization framework that is image-prompted, text-free, diffusion-centric, and employs a VAE for unified representation. We first use training-free geometric rendering to synthesize pseudo-satellite images from UAV imagery as structural prompts. We then design a text-free conditional diffusion model that fuses multimodal structural cues to learn features robust to viewpoint changes. At inference, descriptors are computed at a fixed time step t and compared using cosine similarity. On University-1652 and SUES-200, the method performs competitively for cross-view localization, especially for satellite-to-drone in University-1652.Our data and code will be published at the following URL: https://github.com/liutao23/DiffusionUavLoc.git.

cs.CV↗

arXiv2025

ArchPilot: A Proxy-Guided Multi-Agent Approach for Machine Learning Engineering

Recent LLM-based agents have demonstrated strong capabilities in automated ML engineering. However, they heavily rely on repeated full training runs to evaluate candidate solutions, resulting in significant computational overhead, limited scalability to large search spaces, and slow iteration cycles. To address these challenges, we introduce ArchPilot, a multi-agent system that integrates architecture generation, proxy-based evaluation, and adaptive search into a unified framework. ArchPilot consists of three specialized agents: an orchestration agent that coordinates the search process using a Monte Carlo Tree Search (MCTS)-inspired novel algorithm with a restart mechanism and manages memory of previous candidates; a generation agent that iteratively generates, improves, and debugs candidate architectures; and an evaluation agent that executes proxy training runs, generates and optimizes proxy functions, and aggregates the proxy scores into a fidelity-aware performance metric. This multi-agent collaboration allows ArchPilot to prioritize high-potential candidates with minimal reliance on expensive full training runs, facilitating efficient ML engineering under limited budgets. Experiments on MLE-Bench demonstrate that ArchPilot outperforms SOTA baselines such as AIDE and ML-Master, validating the effectiveness of our multi-agent system.

cs.AI↗

arXiv2025

Discrete-Periodic Ambiguity Function of Random Communication Signals

This paper investigates the ambiguity function (AF) of communication signals carrying random data payloads, which is a fundamental metric characterizing sensing capability in ISAC systems. We first develop a unified analytical framework to evaluate the AF of communication-centric ISAC signals constructed from arbitrary orthonormal bases and independent identically distributed (i.i.d.) constellation symbols. Subsequently, we derive the discrete periodic ambiguity function (DP-AF) and provide closed-form expressions for its expected integrated sidelobe level (EISL) and average sidelobe level. Notably, we prove that the normalized EISL is invariant across all constellations and modulation bases. Finally, the theoretical findings are validated through simulations.

eess.SP↗

arXiv2025

Crab-waist interaction region design and integration for the Super Tau-Charm Facility

The Super Tau-Charm Facility (STCF) is a new-generation $e^+e^-$ collider proposed in China, designed to operate in the center-of-mass (CoM) energy range of 2-7 GeV. To achieve the design luminosity exceeding 5*10^34 cm^-2s^-1 at the optimal CoM energy of 4 GeV, a large crossing angle combined with the crab-waist correction scheme is adopted. However, this scheme introduces strong nonlinearities in the interaction region (IR) due to the extremely low vertical beta function of beta_y* <=1 mm, which significantly limits dynamic and momentum apertures of the collider ring. This paper presents a comprehensive modular optics design that addresses these challenges through several key features: 1) local chromaticity correction up to third order to enhance momentum bandwidth; 2) exact -I transformation between chromatic sextupole pairs for nonlinear cancellation; 3) minimization of the dispersion invariant along the IR to improve local momentum acceptance; 4) optimized beta functions at crab sextupole locations to reduce strength requirements and associated nonlinearities. Resonance driving terms analysis confirms effective suppression of geometric aberrations while preserving the intended crab-waist effects. When integrated into the collider ring, the design achieves a Touschek lifetime exceeding 300 s at beam energy of 2 GeV, meeting STCF requirements. The impact of fringe fields from superconducting quadrupoles is mitigated using octupole correctors, and detector solenoid effects are fully suppressed via local anti-solenoid compensation. Furthermore, the defined machine-detector interface layout ensures minimal synchrotron radiation background at the IP beryllium chamber, while ultra-high vacuum conditions are required to suppress beam-gas background. This IR design represents the current optimal solution for STCF and has been incorporated into the project's conceptual design report.

physics.acc-ph↗

arXiv2025

GUI-Rise: Structured Reasoning and History Summarization for GUI Navigation

While Multimodal Large Language Models (MLLMs) have advanced GUI navigation agents, current approaches face limitations in cross-domain generalization and effective history utilization. We present a reasoning-enhanced framework that systematically integrates structured reasoning, action prediction, and history summarization. The structured reasoning component generates coherent Chain-of-Thought analyses combining progress estimation and decision reasoning, which inform both immediate action predictions and compact history summaries for future steps. Based on this framework, we train a GUI agent, \textbf{GUI-Rise}, through supervised fine-tuning on pseudo-labeled trajectories and reinforcement learning with Group Relative Policy Optimization (GRPO). This framework employs specialized rewards, including a history-aware objective, directly linking summary quality to subsequent action performance. Comprehensive evaluations on standard benchmarks demonstrate state-of-the-art results under identical training data conditions, with particularly strong performance in out-of-domain scenarios. These findings validate our framework's ability to maintain robust reasoning and generalization across diverse GUI navigation tasks. Code is available at https://leon022.github.io/GUI-Rise.

cs.AI↗

arXiv2025

Characterization of SiPMs at 40 K for neutrino coherent detection based on pure CsI

Silicon photomultiplier (SiPM), as the core photoelectric sensor for coherent neutrino detection in low-temperature pure CsI, its working performance directly determines the measurement accuracy of the scintillator light yield. Our previous research has fully demonstrated the performance of pure CsI at liquid nitrogen temperature. More intriguingly, its performance is expected to be even better at 40 K. However, the performance characteristics of SiPM in the 40 K temperature range still remain to be explored. In this study, a self-developed adjustable temperature control system ranging from 30 K to 293 K was built to investigate the key performance parameters of SiPM at different temperatures, such as single photoelectron spectrum, gain, breakdown voltage, dark count rate, after-pulse, internal crosstalk, and single photoelectron resolution. Special emphasis was placed on examining the key performance parameters of SiPM in the 40 K temperature range to evaluate its feasibility for light yield measurement in this temperature range. The results show that this study obtained the parameter variation trends and optimal working conditions of 3 types of SiPM at different temperatures, thereby improving the sensitivity of the detector. This research provides important technical support for low-temperature detection in neutrino physics experiments.

physics.ins-det↗

arXiv2025

ABACUS: An Electronic Structure Analysis Package for the AI Era

ABACUS (Atomic-orbital Based Ab-initio Computation at USTC) is an open-source software for first-principles electronic structure calculations and molecular dynamics simulations. It mainly features density functional theory (DFT) and molecular dynamics functions and is compatible with both plane-wave basis sets and numerical atomic orbital basis sets. ABACUS serves as a platform that facilitates the integration of various electronic structure methods, such as Kohn-Sham DFT, stochastic DFT, orbital-free DFT, and real-time time-dependent DFT, etc. In addition, with the aid of high-performance computing, ABACUS is designed to perform efficiently and provide massive amounts of first-principles data for generating general-purpose machine learning potentials, such as DPA models. Furthermore, ABACUS serves as an electronic structure platform that interfaces with several AI-assisted algorithms and packages, such as DeePKS-kit, DeePMD, DP-GEN, DeepH, DeePTB, HamGNN, etc.

cond-mat.mtrl-sci↗

arXiv2025

From Cradle to Cane: A Two-Pass Framework for High-Fidelity Lifespan Face Aging

Face aging has become a crucial task in computer vision, with applications ranging from entertainment to healthcare. However, existing methods struggle with achieving a realistic and seamless transformation across the entire lifespan, especially when handling large age gaps or extreme head poses. The core challenge lies in balancing age accuracy and identity preservation--what we refer to as the Age-ID trade-off. Most prior methods either prioritize age transformation at the expense of identity consistency or vice versa. In this work, we address this issue by proposing a two-pass face aging framework, named Cradle2Cane, based on few-step text-to-image (T2I) diffusion models. The first pass focuses on solving age accuracy by introducing an adaptive noise injection (AdaNI) mechanism. This mechanism is guided by including prompt descriptions of age and gender for the given person as the textual condition. Also, by adjusting the noise level, we can control the strength of aging while allowing more flexibility in transforming the face. However, identity preservation is weakly ensured here to facilitate stronger age transformations. In the second pass, we enhance identity preservation while maintaining age-specific features by conditioning the model on two identity-aware embeddings (IDEmb): SVR-ArcFace and Rotate-CLIP. This pass allows for denoising the transformed image from the first pass, ensuring stronger identity preservation without compromising the aging accuracy. Both passes are jointly trained in an end-to-end way. Extensive experiments on the CelebA-HQ test dataset, evaluated through Face++ and Qwen-VL protocols, show that our Cradle2Cane outperforms existing face aging methods in age accuracy and identity consistency. Code is available at https://github.com/byliutao/Cradle2Cane.

cs.CV↗

arXiv2025

Quantum-Squeezing-Induced Algebraic Non-Hermitian Skin Effects and Ultra Spectral Sensitivity

The well-established non-Bloch band theory predicts exponential localization of skin-mode eigenstates in one-dimensional (1D) non-Hermitian systems. Recent studies, however, have uncovered anomalous algebraic localization in higher dimensions. Here, we extend these ideas to Hermitian bosonic quadratic Hamiltonians incorporating quantum squeezing, offering a genuine quantum framework to explore non-Hermitian phenomena without external reservoirs. We construct a two-dimensional (2D) bosonic lattice model with two-mode squeezing and study its spectral properties of bosonic excitation within the Bogoliubov-de Gennes (BdG) formalism. We demonstrate an algebraic non-Hermitian skin effect (NHSE), characterized by quasi-long-range power-law localization of complex eigenstates. The system shows ultra spectral sensitivity to double infinitesimal on-site and long-range hopping impurities, while remaining insensitive to single impurities. Analytical treatment via the Green's function reveals that this sensitivity originates from the divergence of the nonlocal Green's function associated with the formation of nonlocal bound states between impurities. Our study establishes a framework for realizing novel higher-dimensional non-Hermitian physics in Hermitian bosonic platforms such as superconducting circuits, photonic lattices, and optomechanical arrays, with the demonstrated ultraspectral sensitivity enabling quantum sensing and amplification via bosonic squeezing.

quant-ph↗

arXiv2025

Searching for continuous gravitational waves in the Parkes Pulsar Timing Array Data Release 3

We present results from an all-sky search for continuous gravitational waves from individual supermassive binary black holes using the third data release (DR3) of the Parkes Pulsar Timing Array (PPTA). Even though we recover a common-spectrum stochastic process, potentially induced by a nanohertz gravitational wave background, we find no evidence of continuous waves. Therefore, we place upper limits on the gravitational-wave strain amplitude: in the most sensitive frequency range around 10 nHz, we obtain a sky-averaged 95\% credibility upper limit of $\approx 7 \times 10^{-15}$. Our search is sensitive to supermassive binary black holes with a chirp mass of $\geq 10^9M_{\odot}$ up to a luminosity distance of 50 Mpc for our least sensitive sky direction and 200 Mpc for the most sensitive direction. This work provides at least 4 times better sensitivity in the 1-200 nHz frequency band than our last search based on the PPTA's first data release. We expect that PPTA will continue to play a key role in detecting continuous gravitational waves in the exciting era of nanohertz gravitational wave astronomy.

gr-qc↗

arXiv2025

STARK: Strategic Team of Agents for Refining Kernels

The efficiency of GPU kernels is central to the progress of modern AI, yet optimizing them remains a difficult and labor-intensive task due to complex interactions between memory hierarchies, thread scheduling, and hardware-specific characteristics. While recent advances in large language models (LLMs) provide new opportunities for automated code generation, existing approaches largely treat LLMs as single-shot generators or naive refinement tools, limiting their effectiveness in navigating the irregular kernel optimization landscape. We introduce an LLM agentic framework for GPU kernel optimization that systematically explores the design space through multi-agent collaboration, grounded instruction, dynamic context management, and strategic search. This framework mimics the workflow of expert engineers, enabling LLMs to reason about hardware trade-offs, incorporate profiling feedback, and refine kernels iteratively. We evaluate our approach on KernelBench, a benchmark for LLM-based kernel optimization, and demonstrate substantial improvements over baseline agents: our system produces correct solutions where baselines often fail, and achieves kernels with up to 16x faster runtime performance. These results highlight the potential of agentic LLM frameworks to advance fully automated, scalable GPU kernel optimization.

cs.AI↗

arXiv2025

Impact of coherent wiggler radiation impedance in Tau-Charm factories

Coherent synchrotron radiation (CSR) has long been recognized as a significant source of longitudinal impedance driving microwave instability in electron storage rings. In the pursuit of higher luminosity, next-generation circular $e^+e^-$ colliders operating in the few-GeV energy range, such as B-factories and Tau-Charm factories, are being designed with low-emittance beams and high beam currents. Damping wigglers are commonly introduced to reduce damping times and control beam emittance. In this study, we systematically investigate the impact of coherent wiggler radiation (CWR), a specific form of CSR generated within wigglers, on beam stability in Tau-Charm factories. We revisit the threshold conditions for CWR-induced microwave instability and evaluate its effects under realistic lattice configurations of collider rings. Furthermore, we examine theoretical models of longitudinal CWR impedance and identify improved formulations that better capture its influence. As an illustrative example, the developed CWR impedance models are applied to simulate beam stability in the Super Tau-Charm Facility currently under design in China.

physics.acc-ph↗