arXiv subjects

Weihang Liu

Publications and source records attributed to Weihang Liu.

13 recordsLinked to original sources

arXiv2026

Two-dimensional beam compression for sub-femtosecond electron beam generation

Sub-femtosecond electron beams are powerful probes of ultrafast electronic, atomic, and nuclear dynamics, and promising drivers for ultrashort radiation generation from the extreme-ultraviolet to gamma-ray regimes. However, producing such beams at hundred-MeV energies with pC-level charge remains challenging. Here we develop a two-dimensional beam-compression scheme based on transverse--longitudinal coupling, in which dispersive beam optics convert the small transverse emittance of modern electron beams into an ultrashort bunch length. Linear analysis and particle tracking show that, after the dominant longitudinal and energy-spread contributions are cancelled, the compressed bunch length is governed primarily by transverse beam quality and collective-effect growth. We further derive and verify a scaling model that captures collective-effect-induced bunch-length degradation and provides a charge--energy operating map for sub-femtosecond compression. Start-to-end simulations of a realistic injector-to-compressor beamline produce a 200 MeV, pC-level bunch with a bunch length of 0.45 fs and a peak current of about 3.5 kA. Jitter studies over a broad range of beam energies show that the output bunch-length distribution narrows and then varies only weakly with increasing energy. These results suggest a feasible route toward compact, high-energy attosecond electron beam sources and may provide a basis for future sub-femtosecond radiation sources based on undulator emission or inverse Compton scattering.

physics.acc-ph↗

arXiv2026

ForeSplat: Optimization-Aware Foresight for Feed-Forward 3D Gaussian Splatting

Feed-forward 3D Gaussian Splatting models offer fast single-pass reconstruction,but scaling them to match per-scene optimization quality is fundamentally hindered by the scarcity of large-scale 3D annotations. A practical compromise is predict-then-refine,where post-prediction optimization compensates for the limited capacity of the feed-forward network. However,standard feed-forward 3DGS is trained solely for zero-step rendering error,ignoring whether its output constitutes a good initialization for the downstream optimizer. We present ForeSplat,an optimization-aware training framework that equips feed-forward 3DGS models to produce initializations explicitly designed for rapid,effective refinement. By offloading part of the scene-modeling burden to the optimizer,ForeSplat substantially reduces the capacity pressure on the feed-forward model,making high-quality reconstruction feasible even with compact networks. At its core is MetaGrad,a lightweight multi-anchor meta-gradient training rule that bypasses costly higher-order differentiation through the 3DGS optimizer. MetaGrad unrolls a short inner-loop refinement trajectory,samples anchor states,and back-propagates aggregated first-order gradients to the prediction head as a surrogate optimization-aware signal. This fine-tuning adds no inference cost and enables high-quality reconstruction within seconds after a few refinement steps. We instantiate ForeSplat on diverse backbones,including AnySplat,Pi3X,and a distilled variant tailored for edge deployment. Across all tested architectures,a ForeSplat-trained initialization converges in fewer refinement steps and reaches a higher peak reconstruction quality than its vanilla counterpart,even fully converged. The framework consistently bridges the gap between amortized prediction and per-scene optimization,establishing a practical path toward lightweight,high-fidelity 3D reconstruction.

cs.CV↗

arXiv2026

High-Harmonic Coherent Pulse Generation in a Storage Ring Using Multiple-Echo-Enabled Harmonic Generation

Fourth-generation storage-ring light sources have achieved transverse emittances approaching the diffraction limit at x-ray wavelengths, while their longitudinal coherence remains limited. Existing laser-modulation schemes can induce strong microbunching, but most storage-ring implementations produce only one useful coherent output from a given longitudinal region during each revolution, thereby underutilizing the intrinsic multi-user capability of storage rings. We propose a multiple-echo-enabled harmonic generation (multi-EEHG) scheme that applies successive excitation--echo cycles to the same longitudinal slice of a stored bunch within one revolution, enabling coherent-radiation delivery to multiple beamlines at different wavelengths. A general formulation of the n-stage EEHG bunching factor and a corresponding optimization procedure are derived. As an example, a triple-EEHG configuration is designed for the SAPS storage ring. Simulations demonstrate coherent radiation at multiple wavelengths with single-pulse photon numbers up to $10^9$, corresponding to an enhancement of approximately three orders of magnitude over synchrotron radiation for the same spectral bandwidth, while achieving few-meV bandwidth without a monochromator. The proposed scheme offers a scalable approach for multi-beamline coherent operation in next-generation storage-ring light sources.

physics.acc-ph↗

arXiv2025

Duplex-GS: Proxy-Guided Weighted Blending for Real-Time Order-Independent Gaussian Splatting

Recent advances in 3D Gaussian Splatting (3DGS) have demonstrated remarkable rendering fidelity and efficiency. However, these methods still rely on computationally expensive sequential alpha-blending operations, resulting in significant overhead, particularly on resource-constrained platforms. In this paper, we propose Duplex-GS, a dual-hierarchy framework that integrates proxy Gaussian representations with order-independent rendering techniques to achieve photorealistic results while sustaining real-time performance. To mitigate the overhead caused by view-adaptive radix sort, we introduce cell proxies for local Gaussians management and propose cell search rasterization for further acceleration. By seamlessly combining our framework with Order-Independent Transparency (OIT), we develop a physically inspired weighted sum rendering technique that simultaneously eliminates "popping" and "transparency" artifacts, yielding substantial improvements in both accuracy and efficiency. Extensive experiments on a variety of real-world datasets demonstrate the robustness of our method across diverse scenarios, including multi-scale training views and large-scale environments. Our results validate the advantages of the OIT rendering paradigm in Gaussian Splatting, achieving high-quality rendering with an impressive 1.5 to 4 speedup over existing OIT based Gaussian Splatting approaches and 52.2% to 86.9% reduction of the radix sort overhead without quality degradation.

cs.CV↗

arXiv2025

Adaptive Time-step Training for Enhancing Spike-Based Neural Radiance Fields

Spiking Neural Networks (SNNs) provide an energy-efficient computing paradigm for neural rendering, but existing spike-based Neural Radiance Field (NeRF) models usually use a fixed inference time step for all scenes. This fixed temporal budget is inefficient because NeRF follows a scene-specific training paradigm, and different scenes require different temporal capacities to preserve rendering quality. This paper proposes Pretraining-based Adaptive Time-step Adjustment (PATA), a scene-wise adaptive time-step training framework for spike-based NeRF. PATA parameterizes the target inference time step as a trainable variable and optimizes it through a two-stage training process. A hybrid input mode strengthens early time-step outputs, while full-step soft supervision, smoothed rendering loss, and temporal-budget loss jointly maintain rendering fidelity and reduce temporal computation. The learned target time step is shared by all ray samples within a scene, preserving the parallel rendering structure of NeRF. Experiments on INGP-NeRF and TensoRF backbones across Synthetic-NeRF, Mip-NeRF 360, and LLFF show that PATA consistently reduces inference cost while maintaining competitive rendering quality. PATA reduces the estimated inference energy by up to 57.57\% on INGP-NeRF and 68.90\% on TensoRF, demonstrating its effectiveness across different neural rendering representations.

cs.CV↗

arXiv2025

Quantitative Error Feedback for Quantization Noise Reduction of Filtering over Graphs

This paper introduces an innovative error feedback framework designed to mitigate quantization noise in distributed graph filtering, where communications are constrained to quantized messages. It comes from error spectrum shaping techniques from state-space digital filters, and therefore establishes connections between quantized filtering processes over different domains. In contrast to existing error compensation methods, our framework quantitatively feeds back the quantization noise for exact compensation. We examine the framework under three key scenarios: (i) deterministic graph filtering, (ii) graph filtering over random graphs, and (iii) graph filtering with random node-asynchronous updates. Rigorous theoretical analysis demonstrates that the proposed framework significantly reduces the effect of quantization noise, and we provide closed-form solutions for the optimal error feedback coefficients. Moreover, this quantitative error feedback mechanism can be seamlessly integrated into communication-efficient decentralized optimization frameworks, enabling lower error floors. Numerical experiments validate the theoretical results, consistently showing that our method outperforms conventional quantization strategies in terms of both accuracy and robustness.

cs.LG↗

arXiv2025

CityGo: Lightweight Urban Modeling and Rendering with Proxy Buildings and Residual Gaussians

Accurate and efficient modeling of large-scale urban scenes is critical for applications such as AR navigation, UAV based inspection, and smart city digital twins. While aerial imagery offers broad coverage and complements limitations of ground-based data, reconstructing city-scale environments from such views remains challenging due to occlusions, incomplete geometry, and high memory demands. Recent advances like 3D Gaussian Splatting (3DGS) improve scalability and visual quality but remain limited by dense primitive usage, long training times, and poor suit ability for edge devices. We propose CityGo, a hybrid framework that combines textured proxy geometry with residual and surrounding 3D Gaussians for lightweight, photorealistic rendering of urban scenes from aerial perspectives. Our approach first extracts compact building proxy meshes from MVS point clouds, then uses zero order SH Gaussians to generate occlusion-free textures via image-based rendering and back-projection. To capture high-frequency details, we introduce residual Gaussians placed based on proxy-photo discrepancies and guided by depth priors. Broader urban context is represented by surrounding Gaussians, with importance-aware downsampling applied to non-critical regions to reduce redundancy. A tailored optimization strategy jointly refines proxy textures and Gaussian parameters, enabling real-time rendering of complex urban scenes on mobile GPUs with significantly reduced training and memory requirements. Extensive experiments on real-world aerial datasets demonstrate that our hybrid representation significantly reduces training time, achieving on average 1.4x speedup, while delivering comparable visual fidelity to pure 3D Gaussian Splatting approaches. Furthermore, CityGo enables real-time rendering of large-scale urban scenes on mobile consumer GPUs, with substantially reduced memory usage and energy consumption.

cs.GR↗

arXiv2024

Content-Aware Radiance Fields: Aligning Model Complexity with Scene Intricacy Through Learned Bitwidth Quantization

The recent popular radiance field models, exemplified by Neural Radiance Fields (NeRF), Instant-NGP and 3D Gaussian Splatting, are designed to represent 3D content by that training models for each individual scene. This unique characteristic of scene representation and per-scene training distinguishes radiance field models from other neural models, because complex scenes necessitate models with higher representational capacity and vice versa. In this paper, we propose content-aware radiance fields, aligning the model complexity with the scene intricacies through Adversarial Content-Aware Quantization (A-CAQ). Specifically, we make the bitwidth of parameters differentiable and trainable, tailored to the unique characteristics of specific scenes and requirements. The proposed framework has been assessed on Instant-NGP, a well-known NeRF variant and evaluated using various datasets. Experimental results demonstrate a notable reduction in computational complexity, while preserving the requisite reconstruction and rendering quality, making it beneficial for practical deployment of radiance fields models. Codes are available at https://github.com/WeihangLiu2024/Content_Aware_NeRF.

cs.CV↗

arXiv2024

Self-Cancelation of Coherent Synchrotron Radiation Kicks Using a Non-Symmetric S-shape Four-Bend Chicane

High peak current electron beams are essential for x-ray free-electron lasers (FELs), and generally realized through multi-stage compression with symmetric C-shape four-bend chicanes. However, the coherent synchrotron radiations (CSR), emitted for wavelengths longer than or comparable to the length of the electron bunch during the compression, may degrade the beam quality and finally affect the FEL performance. In this Letter, we show that zero net CSR kick cannot be achieved in a symmetric C-chicane by using an explicit point-kick analysis of the CSR effects, which is responsible for significant emittance growth when pursuing a peak current of $\gtrsim$ 10 kiloamperes. A four-bend chicane with non-symmetric S-shape geometry that can self-cancel the CSR kicks is proposed to effectively suppress the emittance growth. Compared to the symmetric C-chicane, beams with three times higher peak current and similar emittance growth can be achieved with the S-chicane for typical FEL operation parameters. We believe that this study provides a viable way of producing high quality and short intense electron beams, benefiting future development of FELs and other types of accelerator-based scientific facilities.

physics.acc-ph↗

arXiv2024

A method for reversing the laser modulation in a Storage ring

The pursuit of coherent radiation generation remains a key direction in the advancement of storage ring light sources. Despite the potential of laser modulation in achieving this goal, it leads to a significant decline in the quality of the electron beam. Efforts to mitigate this decline have resulted in the proposal of demodulation schemes. However, implementing modulation and demodulation within the storage ring presents significant challenges due to dynamical and spatial constraints within straight sections. In this study, we propose a straightforward and easily implementable method for achieving reversible laser modulation in a storage ring. Notably, our approach circumvents the need for special storage ring requirements, such as lengthy straight sections or bypass section. Simulation results demonstrate a substantial restoration of beam quality following demodulation. This innovative scheme holds great promise for the realization of high repetition rate coherent storage ring light sources.

physics.acc-ph↗

arXiv2024

Analytical formulas of coherent-synchrotron-radiation induced microbunching gain and emittance growth in an arbitrary achromatic four-bend chicane

Coherent synchrotron radiations (CSR) emitted by a high-brightness electron beam during transport in a bending magnet is a double-edged sword in electron accelerators. While CSR contributes to a stronger radiation field than the incoherent radiation, it simultaneously leads to degradation of the electron beam quality. Specifically, CSR effects manifest in increases of the beam energy spread and the projected emittance, and amplification of the microbunching instability. This paper presents analytical formulas for the CSR-induced microbunching instability gain and for the induced emittance growth in an arbitrary achromatic four-bend chicane with inclusion of both the steady-state and transient CSR effects. The analytical formulas are compared and show good agreement with Vlasov calculations and particle tracking simulations. The obtained analytical formulas are then applied to evaluate the CSR effects in the design of a general achromatic four-bend bunch compressor chicane, providing a quick estimate on the microbunching gain and the induced emittance growth. From the widely adopted symmetric C-shape chicane to a non-symmetric S-shape chicane, our analytical formulas offer insight into the evolution of the microbunching gain and the emittance growth with the variations of design parameters. In comparison to particle tracking simulations currently employed for CSR effect analyses, the analytical formulas presented in this paper significantly reduce the evaluation time, enabling systematic study of parametric dependencies with inclusion of CSR effects within specified design parameter ranges.

physics.acc-ph↗

arXiv2024

Suppressing Coherent Synchrotron Radiation Effects in Chicane Bunch Compressors

The most significant advances in the accelerator-based light sources (i.e., x-ray free electron lasers) are driven by the production of the high final peak current in the last several decades. As a prerequisite to attain the proposed high brightness, the symmetric C-chicane bunch compressor is typically exploited due to its simplicity, efficiency, and natural dispersion-free feature at all orders. However, during bunch compression for a high peak current requirement, a main contributing factor to the transverse emittance degradation is the emission of the coherent synchrotron radiation (CSR). Suppressing this effect is necessary to preserve the beam phase-space quality. To this end, this paper presents an analysis of one-dimensional CSR point-kick and derives the cancellation conditions in terms of compression factor. The CSR cancelation conditions indicate an asymmetric geometric design. We demonstrate concrete schemes for asymmetric C- and S-chicanes, and verify the CSR cancelation conditions using integration methods and ELEGANT simulations. Furthermore, the proposed asymmetric C- and S-chicanes can drastically suppress the emittance growth compared with the symmetric ones with identical bunch compression goals.

physics.acc-ph↗

arXiv2022

Multi-objective optimization of longitudinal injection based on a multi-frequency RF system for fourth-generation storage ring-based light sources

In the fourth-generation storage ring light sources (4GLSs), associated with the extremely strong nonlinearities inherent in the multi-bend achromat design, the dynamic acceptance is usually small and it is difficult to implement traditional off-axis local-bump injection. To release the requirement on dynamic acceptance, on-axis longitudinal injection schemes have been explored. In this paper, we present a multi-objective optimization of longitudinal injection with a multi-frequency RF system, based on the parameters of the Southern Advanced Photon Source, a 4GLS proposed in China. We show that by treating the optimal bunch lengthening condition as an optimizing objective rather than a condition that must be satisfied, a plethora of feasible candidate solutions can be found, showing different trade-offs among multi-objectives. From these candidate solutions, one can find an optimal RF parameter setting that is most adapted to a specific 4GLS physics design and the available technical level of injection kicker. Especially, it would be feasible to realize longitudinal injection within a static bucket enabled by a double-frequency RF system, suggesting an attractive longitudinal injection option for 4GLSs.

physics.acc-ph↗