arXiv subjects

Lingling Ma

Publications and source records attributed to Lingling Ma.

9 recordsLinked to original sources

arXiv2026

Enhancing the Angular Resolution of Large Array of imaging atmospheric Cherenkov Telescope (LACT) at Ultra-High Energies

The Large Array of Imaging Atmospheric Cherenkov Telescopes (LACT) is dedicated to high-resolution morphological studies of PeVatrons. In this work, we present a fundamental investigation into stereoscopic direction reconstruction for the LACT array, specifically addressing the challenges of ultra-high-energy observations. We demonstrate that the standard Hillas parameterization introduces a significant reconstruction bias under severe image leakage. To mitigate this, we introduce an approach utilizing a 2D Gaussian fit, achieving an exceptional angular resolution of better than $0.06^\circ$ at $100\text{ TeV}$ within the central $0^\circ\text{--}1^\circ$ offset bin, and maintaining better than $0.12^\circ$ across offsets up to $4^{\circ}$. Building on this robust baseline, we evaluate advanced weighting schemes by utilizing a LightGBM-based quantile regression model to independently estimate single-image quality. Applying these quality-based weights yields a consistent improvement of $0.02^\circ$ to $0.03^\circ$ for high-energy, large-offset events using both the \textit{HillasWeightedSum} and \textit{HillasWeightedDisp} methods. Finally, to establish a theoretical performance ceiling, we explore a pixel-wise likelihood reconstruction technique utilizing Neural Ratio Estimation. While its practical realization depends heavily on minimizing the gap between Monte Carlo simulations and observational data, this exploratory approach demonstrates the potential to yield an overall improvement of approximately 15\% to 40\% at $100~\rm TeV$ across the entire field of view. Such high angular resolution is critical for disentangling complex emission regions and mapping the internal structures of PeVatrons.

astro-ph.HE↗

arXiv2025

A model reduction method based on nonlinear optimization for multiscale stochastic optimal control problems

This paper proposes a non-intrusive, data-driven reduced-order modeling framework for stochastic optimal control problems governed by partial differential equations. The control problem is formulated with a quadratic cost functional and stochastic PDE constraints, and an L2-optimal reduced-order model is constructed to directly approximate the parameter-to-output mapping. The model is obtained by minimizing the L2 norm of the output error via gradient-based optimization, requiring only input-output data without access to the full-order system matrices or state variables. To efficiently generate high-fidelity training data for multiscale problems, the Generalized Multiscale Finite Element Method (GMsFEM) is employed as an offline solver. The proposed framework ensures accuracy in control-relevant outputs while maintaining computational complexity independent of the original PDE dimension, making it suitable for real-time applications. Numerical experiments on stochastic diffusion and advection-diffusion equations demonstrate the accuracy, efficiency, and robustness of the method.

math.OC↗

arXiv2024

Unveiling the nature of the knee in the cosmic ray energy spectrum

The knee-like structure around 4 PeV is the most striking feature in the cosmic ray energy spectrum, whose origin remains enigmatic. We propose a novel concept of the total logarithmic mass energy spectrum to characterize the knee, taking into account LHAASO measurements of the all-particle energy spectrum and the mean logarithmic mass. The predominant role of proton in the knee formation is unearthed. The case of a mass-dependent knee is ruled out with a significance of 22.9${\sigma}$ and the rigidity-dependent knee feature is revealed. An ankle-like structure stemming from the excess of iron is discovered at 9.7${\pm}$ 0.2 PeV with a significance of 25.9${\sigma}$. Our findings pierce the mist of the puzzling knee for the first time since its discovery.

astro-ph.HE↗

arXiv2024

Layout optimization and Performance of Large Array of imaging atmospheric Cherenkov Telescope (LACT)

Large Array of imaging atmospheric Cherenkov Telescope (LACT) is an array of 32 Cherenkov telescopes with 6-meter diameter mirrors to be constructed at the LHAASO site. In this work, we present a study on the layout optimization and performance analysis of LACT. We investigate two observation modes: large zenith angle observations for ultra-high energy events and small zenith angle observations for lower energy thresholds. For large zenith angles (60{\deg}), simulations show that an 8-telescope subarray can achieve an effective area of $3 ~\rm km^2$ and excellent angular resolution. For small zenith angles, we optimize the layout of 4-telescope cells and the full 32-telescope array. The threshold of the full array is about $200~\rm GeV$, which is particularly crucial for studying transient phenomena, including gamma-ray bursts (GRBs) and active galactic nuclei (AGNs). This study provides important guidance for the final LACT layout design and performance estimates under different observational conditions, demonstrating LACT's potential for deep observations of ultra-high energy \gray sources and morphological studies of PeVatrons, as well as time-domain \gray astronomy.

astro-ph.HE↗

arXiv2024

Prospects for joint reconstruction of imaging air Cherenkov Telescope array and extensive air shower array

In this paper we proposed a joint reconstruction of \gray events using both extensive air array (EAS) and Imaging air Cherenkov Telescope array (IACT). We considered eight Cherenkov telescopes to be built on the LHAASO (Large High Altitude Air Shower Observatory) site and investigate the improvement in differential sensitivity when combining the information from both IACT and Moun detectors of LHAASO-KM2A. We found that due to the higher cosmic ray background rejection power and higher gamma ray retention ratio provided by muon detectors of LHAASO, such a joint reconstruction can significantly improve the sensitivity of IACTs, especially for extended sources and long exposure time. In this article, we have shown the performance of an eight-telescopes mini array, and our results indicate that above $10~\rm TeV$, the sensitivity can be improved by muon detector from $25\% - 60\%$ in different energy ranges.

astro-ph.HE↗

arXiv2024

Tailoring spatiotemporal wavepackets via two-dimensional space-time duality

Space-time (ST) beams, ultrafast optical wavepackets with customized spatial and temporal characteristics, present a significant contrast to conventional spatial-structured light and hold the potential to revolutionize our understanding and manipulation of light. However, the progress in ST beam research has been constrained by the absence of a universal framework for their analysis and generation. Here, we introduce the concept of "two-dimensional ST duality", establishing a foundational duality between spatial-structured light and ST beams. We show that breaking the exact balance between paraxial diffraction and narrow-band dispersion is crucial for guiding the dynamics of ST wavepackets. Leveraging this insight, we pioneer a versatile complex-amplitude modulation strategy, enabling the precise crafting of ST beams with an exceptional fidelity exceeding 97%. Furthermore, we uncover a new range of ST wavepackets by harnessing the exact one-to-one relationship between scalar spatial-structured light and ST beams. Our findings suggest a paradigm shift opportunity in ST beam research and may apply to a broader range of wave physics systems.

physics.optics↗

arXiv2022

Measuring the attenuation length of muon number in the air shower with muon detectors of 3/4 LHAASO array

LHAASO KM2A consists of 5915 scintillation detectors and 1188 muon detectors, and the muon detectors cover 4% area of the whole array with 30 m spacing. The muon number of air shower events, with very high energy, is investigated with the data recorded by muon detector of the 3/4 LHAASO array in 2021. The attenuation length of muon number in the air shower is measured by fitting the muon number with constant flux in various zenith angles, based on the constant intensity cut method. The variation of the attenuation length as shower energy from hundreds TeV to tens PeV is presented. The results of simulation also is presented for comparing.

physics.data-an↗

arXiv2022

The Large High Altitude Air Shower Observatory (LHAASO) Science Book (2021 Edition)

Since the science white paper of the Large High Altitude Air Shower Observatory (LHAASO) published on arXiv in 2019 [e-Print: 1905.02773 (astro-ph.HE)], LHAASO has completed the transition from a project to an operational gamma-ray astronomical observatory LHAASO is a new generation multi-component facility located in Daocheng, Sichuan province of China, at an altitude of 4410 meters. It aims at measuring with unprecedented sensitivity the spectrum, composition, and anisotropy of cosmic rays in the energy range between 10$^{12}$ and 10$^{18}$~eV, and acting simultaneously as a wide aperture (one stereoradiant) continuously operating gamma-ray telescope in the energy range between 10$^{11}$ and $10^{15}$~eV with the designed sensitivity of 1.3\% of the Crab Unit (CU) above 100 TeV. LHAASO's capability of measuring simultaneously different shower components (electrons, muons, and Cherenkov/fluorescence light), will allow it to investigate the origin, acceleration, and propagation of CR through measurement of the energy spectrum, elemental composition, and anisotropy with unprecedented resolution. The remarkable sensitivity of LHAASO will play a key role in CR physics and gamma-ray astronomy for a general and comprehensive exploration of the high energy universe and will allow important studies of fundamental physics (such as indirect dark matter search, Lorentz invariance violation, quantum gravity) and solar and heliospheric physics. The LHAASO Collaboration organized an editorial working group and finished all editorial work of this science book, to summarize the instrumental features and outline the prospects of scientific researches with the LHAASO experiment.

astro-ph.HE↗

arXiv2017

Local-global model reduction method for stochastic optimal control problems constrained by partial differential equations

In this paper, a local-global model reduction method is presented to solve stochastic optimal control problems governed by partial differential equations (PDEs). If the optimal control problems involve uncertainty, we need to use a few random variables to parameterize the uncertainty. The stochastic optimal control problems require solving coupled optimality system for a large number of samples in the stochastic space to quantify the statistics of the system response and explore the uncertainty quantification. Thus the computation is prohibitively expensive. To overcome the difficulty, model reduction is necessary to significantly reduce the computation complexity. We exploit the advantages from both reduced basis method and Generalized Multiscale Finite Element Method (GMsFEM) and develop the local-global model reduction method for stochastic optimal control problems with PDE constraints. This local-global model reduction can achieve much more computation efficiency than using only local model reduction approach and only global model reduction approach. We recast the stochastic optimal problems in the framework of saddle-point problems and analyze the existence and uniqueness of the optimal solutions of the reduced model. In the local-global approach, most of computation steps are independent of each other. This is very desirable for scientific computation. Moreover, the online computation for each random sample is very fast via the proposed model reduction method. This allows us to compute the optimality system for a large number of samples. To demonstrate the performance of the local-global model reduction method, a few numerical examples are provided for different stochastic optimal control problems.

math.NA↗