arXiv subjects

Chuan Yue

Publications and source records attributed to Chuan Yue.

At least 19 recordsLinked to original sources

arXiv2026

Beyond Single-Episode Optimization: Sliding-Window Aware Generative Auto-Bidding for Long-Term Advertising Effectiveness

Auto-bidding systems optimize bids to maximize value under efficiency constraints such as Cost-Per-Action (CPA). Existing methods treat each day as an independent episode. However, many advertisers produce value so sparsely that per-day efficiency ratios become statistically unreliable, undermining advertiser retention. Platforms therefore evaluate window-level efficiency over sliding windows of $W{=}7$ days, ensuring fair evaluation and long-term advertising effectiveness. This creates cross-episode coupling: each day's bidding decisions affect up to $W$ overlapping windows, so setting daily targets requires anticipating future market conditions. We propose SWAG-Bid (Sliding-Window Aware Generative Auto-Bidding), a hierarchical framework decomposing this challenge into episode-level planning and step-level execution. The planner uses a Masked Trajectory Model to forecast markets and generate candidate plans, scored across all overlapping windows by Multi-Window Model Predictive Control Sampling (MWMS) with exponential confidence decay. The controller adjusts reliance on this guidance through a state-adaptive gate, Per-Step Gated Adaptive Layer Normalization (PSG-AdaLN), complemented by Return-to-Go and Cost-to-Go channels carrying budget and constraint information. Experiments on AuctionNet-Sparse and online A/B tests on AliExpress show that SWAG-Bid achieves competitive constraint satisfaction and value acquisition under sliding-window evaluation.

cs.LG↗

arXiv2026

PRO-Bid: Pareto-Prioritized Regret Optimization for Constraint-Aware Generative Auto-Bidding

Auto-bidding systems strive to maximize marketing value while maintaining high compliance with efficiency constraints, such as Target Cost-Per-Action (CPA). While Decision Transformers offer powerful sequence modeling capabilities, their application to this setting faces two challenges: 1) standard Return-to-Go conditioning causes state aliasing by ignoring the cost dimension, preventing precise resource pacing; and 2) standard regression constrains the policy to mimic historical averages, limiting its capacity to optimize performance near the high-efficiency boundary. To tackle these challenges, we propose PRO-Bid, a constraint-aware generative auto-bidding framework featuring systematic redesigns across data, architecture, and training via two synergistic mechanisms: 1) Constraint-Decoupled Pareto Representation (CDPR) separates global constraints into recursive cost and value contexts to restore resource perception, while reweighting trajectories based on the empirical Pareto frontier to prioritize high-efficiency data; and 2) Counterfactual Regret Optimization (CRO) employs a global predictor to evaluate alternative actions and identify promising local adjustments. By utilizing these high-utility outcomes as weighted regression targets, the model overcomes mean regression and approaches the empirical high-efficiency boundary. Extensive experiments on two public benchmarks and online A/B tests show that PRO-Bid achieves better constraint satisfaction and value acquisition than state-of-the-art baselines.

cs.LG↗

arXiv2025

Exploring the Effectiveness of Google Play Store's Privacy Transparency Channels

With the requirements and emphases on privacy transparency placed by regulations such as GDPR and CCPA, the Google Play Store requires Android developers to more responsibly communicate their apps' privacy practices to potential users by providing the proper information via the data safety, privacy policy, and permission manifest privacy transparency channels. However, it is unclear how effective those channels are in helping users make informed decisions in the app selection and installation process. In this article, we conducted a study for 190 participants to interact with our simulated privacy transparency channels of mobile apps. We quantitatively analyzed (supplemented by qualitative analysis) participants' responses to five sets of questions. We found that data safety provides the most intuitive user interfaces, privacy policy is most informative and effective, while permission manifest excels at raising participants' concerns about an app's overall privacy risks. These channels complement each other and should all be improved.

cs.CR↗

arXiv2025

Determination of the absolute energy scale of the DAMPE calorimeter with the geomagnetic rigidity cutoff method

The Dark Matter Particle Explorer (DAMPE) is a satellite-borne detector designed to detect high-energy cosmic ray particles with its core component being a BGO calorimeter capable of measuring energies from $\sim$GeV to $O(100)$ TeV. The 32 radiation lengths thickness of the calorimeter is designed to ensure full containment of showers produced by cosmic ray electrons and positrons (CREs) and $γ$-rays at energies below tens of TeV, providing high resolution in energy measurements. The absolute energy scale therefore becomes a crucial parameter for precise measurements of the CRE energy spectrum. The geomagnetic field induces a rapid drop in the low energy spectrum of electrons and positrons, a phenomenon that provides a method to determine the calorimeter's absolute energy scale. By comparing the cutoff energies of the measured spectra of CREs with those expected from the International Geomagnetic Reference Field model across 4 McIlwain $L$ bins - which cover most regions of the DAMPE orbit - we find that the calorimeter's absolute energy scale exceeds the calibration based on Geant4 simulation by $1.013\pm0.012_{\rm stat}\pm0.026_{\rm sys}$ for energies between 7 GeV and 16 GeV. The absolute energy scale should be taken into account when comparing the absolute CREs fluxes among different detectors.

hep-ex↗

arXiv2024

The calibrations of DAMPE $γ$-ray effective area

The DArk Matter Particle Explorer (DAMPE) is a cosmic-ray detector as well as a pair-converting $γ$-ray telescope. The effective area, reflecting the geometrical cross-section area, the $γ$-ray conversion probability and the photon selection efficiency, is important in the $γ$-ray analyses. In the work, we find a significant time variation in the effective area, as large as $\sim -4\%/{\rm yr}$ at 2 GeV for the high-energy trigger. We derive the data-based correction factors to the effective areas and apply corrections to both the effective areas and the exposure maps. The calibrated exposure can be $\sim 12\%$ smaller than the Monte Carlo one on average at 2 GeV. The calibration is further verified using the observation of the Vela pulsar, showing the spectral parameters with the correction are more consistent with those in the Fermi-LAT catalog than the ones without correction. All the corrections are now implemented in the latest version of the DAMPE $γ$-ray analysis toolkit DmpST.

astro-ph.IM↗

arXiv2024

On-orbit calibration and long-term performance of the DAMPE trigger system

The DArk Matter Particle Explorer (DAMPE) is a satellite-borne particle detector for measurements of high-energy cosmic rays and γ-rays. DAMPE has been operating smoothly in space for more than 8 years since launch on December 17, 2015. The trigger logic of DAMPE is designed according to the deposited energy information recorded by the calorimeter. The precise calibration of the trigger thresholds and their long-term evolutions are very important for the scientific analysis of DAMPE. In this work, we develop a new method for the threshold calibration, considering the influence from the electronic noise, and obtain the long-term evolutions of the trigger thresholds. The average increase rate of the trigger thresholds for the first 4 layers of the calorimeter is found to be about 0.9% per year, resulting in variations of the high-energy trigger efficiency of cosmic ray electrons by about -5% per year at 2 GeV and less than about -0.05% above 30 GeV.

physics.ins-det↗

arXiv2024

Simulation study of performance of the Very Large Area gamma-ray Space Telescope

The Very Large Area gamma-ray Space Telescope (VLAST) is a mission concept proposed to detect gamma-ray photons through both the Compton scattering and electron-positron pair production mechanisms, enabling the detection of photons with energies ranging from MeV to TeV. This project aims to conduct a comprehensive survey of the gamma-ray sky from a low Earth orbit using an anti-coincidence detector, a tracker detector that also serves as a low energy calorimeter, and a high energy imaging calorimeter. We developed a Monte Carlo simulation application of the detector with the GEANT4 toolkit to evaluate the instrument performance including the effective area, angular resolution and energy resolution, as well as explored specific optimizations of the detector configuration. Our simulation-based analysis indicates that the VLAST's current design is physically feasible, with an acceptance larger than 10~$\rm m^2\ sr$ which is four times larger than Fermi-LAT, an energy resolution better than 2\% at 10~GeV, and an angular resolution better than 0.2 degrees at 10~GeV. The VLAST project is expected to make significant contribution to the field of gamma-ray astronomy and to enhance our understanding of the cosmos.

astro-ph.IM↗

arXiv2024

Simulation of DAMPE silicon microstrip detectors in the $\rm Allpix^{2}$ framework

Silicon strip detectors have been widely utilized in space experiments for gamma-ray and cosmic-ray detections thanks to their high spatial resolution and stable performance. For a silicon micro-strip detector, the Monte Carlo simulation is recognized as a practical and cost-effective approach to verify the detector performance. In this study, a technique for the simulation of the silicon micro-strip detector with the $\rm Allpix^{2}$ framework is developed. By incorporating the electric field into the particle transport simulation based on Geant4, this framework could precisely emulate the carrier drift in the silicon micro-strip detector. The simulation results are validated using the beam test data as well as the flight data of the DAMPE experiment, which suggests that the $\rm Allpix^{2}$ framework is a powerful tool to obtain the performance of the silicon micro-strip detector.

physics.ins-det↗

arXiv2023

BGO quenching effect on spectral measurements of cosmic-ray nuclei in DAMPE experiment

The Dark Matter Particle Explorer (DAMPE) is a satellite-borne detector designed to measure high energy cosmic-rays and $γ$-rays. As a key sub-detector of DAMPE, the Bismuth Germanium Oxide (BGO) imaging calorimeter is utilized to measure the particle energy with a high resolution. The nonlinear fluorescence response of BGO for large ionization energy deposition, known as the quenching effect, results in an under-estimate of the energy measurement for cosmic-ray nuclei. In this paper, various models are employed to characterize the BGO quenching factors obtained from the experimental data of DAMPE. Applying the proper quenching model in the detector simulation process, we investigate the tuned energy responses for various nuclei and compare the results based on two different simulation softwares, i.e. GEANT4 and FLUKA. The BGO quenching effect results in a decrease of the measured energy by approximately $2.5\%$ ($5.7 \%$) for carbon (iron) at $\sim$10 GeV/n and $<1\%$ above 1 TeV/n, respectively. Accordingly, the correction of the BGO quenching effect leads to an increase of the low-energy flux measurement of cosmic-ray nuclei.

hep-ex↗

arXiv2023

Interpretations of the cosmic ray secondary-to-primary ratios measured by DAMPE

Precise measurements of the boron-to-carbon and boron-to-oxygen ratios by DAMPE show clear hardenings around $100$ GeV/n, which provide important implications on the production, propagation, and interaction of Galactic cosmic rays. In this work we investigate a number of models proposed in literature in light of the DAMPE findings. These models can roughly be classified into two classes, driven by propagation effects or by source ones. Among these models discussed, we find that the re-acceleration of cosmic rays, during their propagation, by random magnetohydrodynamic waves may not reproduce sufficient hardenings of B/C and B/O, and an additional spectral break of the diffusion coefficient is required. The other models can properly explain the hardenings of the ratios. However, depending on simplifications assumed, the models differ in their quality in reproducing the data in a wide energy range. The models with significant re-acceleration effect will under-predict low-energy antiprotons but over-predict low-energy positrons, and the models with secondary production at sources over-predict high-energy antiprotons. For all models high-energy positron excess exists.

astro-ph.HE↗

arXiv2022

An Unsupervised Machine Learning Method for Electron--Proton Discrimination of the DAMPE Experiment

Galactic cosmic rays are mostly made up of energetic nuclei, with less than $1\%$ of electrons (and positrons). Precise measurement of the electron and positron component requires a very efficient method to reject the nuclei background, mainly protons. In this work, we develop an unsupervised machine learning method to identify electrons and positrons from cosmic ray protons for the Dark Matter Particle Explorer (DAMPE) experiment. Compared with the supervised learning method used in the DAMPE experiment, this unsupervised method relies solely on real data except for the background estimation process. As a result, it could effectively reduce the uncertainties from simulations. For three energy ranges of electrons and positrons, 80--128 GeV, 350--700 GeV, and 2--5 TeV, the residual background fractions in the electron sample are found to be about (0.45 $\pm$ 0.02)$\%$, (0.52 $\pm$ 0.04)$\%$, and (10.55 $\pm$ 1.80)$\%$, and the background rejection power is about (6.21 $\pm$ 0.03) $\times$ $10^4$, (9.03 $\pm$ 0.05) $\times$ $10^4$, and (3.06 $\pm$ 0.32) $\times$ $10^4$, respectively. This method gives a higher background rejection power in all energy ranges than the traditional morphological parameterization method and reaches comparable background rejection performance compared with supervised machine learning~methods.

astro-ph.IM↗

arXiv2022

Study of the Global Alignment for the DAMPE Detector

The Dark Matter Particle Explorer (DAMPE) is designed as a high energy particle detector for probing cosmic-rays and $γ-$rays in a wide energy range. The trajectory of the incident particle is mainly measured by the Silicon-Tungsten tracKer-converter (STK) sub-detector, which heavily depends on the precise internal alignment correction as well as the accuracy of the global coordinate system. In this work, we carried out a global alignment method to validate the potential displacement of these sub-detectors, and particularly demonstrated that the track reconstruction of STK can well satisfy the required objectives by means of comparing flight data and simulations.

physics.ins-det↗

arXiv2021

Optimal gamma-ray selections for monochromatic line searches with DAMPE

The DArk Matter Particle Explorer (DAMPE) is a space high-energy cosmic-ray detector covering a wide energy band with a high energy resolution. One of the key scientific goals of DAMPE is to carry out indirect detection of dark matter by searching for high-energy gamma-ray line structure. To promote the sensitivity of gamma-ray line search with DAMPE, it is crucial to improve the acceptance and energy resolution of gamma-ray photons. In this paper, we quantitatively prove that the photon sample with the largest ratio of acceptance to energy resolution is optimal for line search. We therefore develop a line-search sample specifically optimized for the line search. Meanwhile, in order to increase the statistics, we also selected the so called BGO-only photons that convert into $e^+e^-$ pairs only in the BGO calorimeter. The standard, the line-search, and the BGO-only photon samples are then tested for line search individually and collectively. The results show that a significantly improved limit could be obtained from an appropriate combination of the date sets, and the increase is about 20\% for the highest case compared with using the standard sample only.

hep-ex↗

arXiv2020

Comparison of proton shower developments in the BGO calorimeter of the Dark Matter Particle Explorer between GEANT4 and FLUKA simulations

The DArk Matter Particle Explorer (DAMPE) is a satellite-borne detector for high-energy cosmic rays and $γ$-rays. To fully understand the detector performance and obtain reliable physical results, extensive simulations of the detector are necessary. The simulations are particularly important for the data analysis of cosmic ray nuclei, which relies closely on the hadronic and nuclear interactions of particles in the detector material. Widely adopted simulation softwares include the GEANT4 and FLUKA, both of which have been implemented for the DAMPE simulation tool. Here we describe the simulation tool of DAMPE and compare the results of proton shower properties in the calorimeter from the two simulation softwares. Such a comparison gives an estimate of the most significant uncertainties of our proton spectral analysis.

physics.ins-det↗

arXiv2020

Correction Method for the Readout Saturation of the DAMPE Calorimeter

The DArk Matter Particle Explorer (DAMPE) is a space-borne high energy cosmic-ray and $γ$-ray detector which operates smoothly since the launch on December 17, 2015. The bismuth germanium oxide (BGO) calorimeter is one of the key sub-detectors of DAMPE used for energy measurement and electron proton identification. For events with total energy deposit higher than decades of TeV, the readouts of PMTs coupled on the BGO crystals would become saturated, which results in an underestimation of the energy measurement. Based on detailed simulations, we develop a correction method for the saturation effect according to the shower development topologies and energies measured by neighbouring BGO crystals. The verification with simulated and on-orbit events shows that this method can well reconstruct the energy deposit in the saturated BGO crystal.

physics.ins-det↗

arXiv2020

Calibration and performance of the neutron detector onboard of the DAMPE mission

The DArk Matter Particle Explorer (DAMPE), one of the four space-based scientific missions within the framework of the Strategic Pioneer Program on Space Science of the Chinese Academy of Sciences, has been successfully launched on Dec. 17th 2015 from Jiuquan launch center. One of the most important scientific goals of DAMPE is to search for the evidence of dark matter indirectly by measuring the spectrum of high energy cosmic-ray electrons. The neutron detector, one of the four sub-payloads of DAMPE, is designed to distinguish high energy electrons from hadron background by measuring the secondary neutrons produced in the shower. In this paper, a comprehensive introduction of the neutron detector is presented, including the design, the calibration and the performance. The analysis with simulated data and flight data indicates a powerful proton rejection capability of the neutron detector, which plays an essential role for TeV electron identification of DAMPE.

physics.ins-det↗

arXiv2019

Implications on the origin of cosmic rays in light of 10 TV spectral softenings

Precise measurements of the energy spectra of cosmic rays (CRs) show various kinds of features deviating from single power-laws, which give very interesting and important implications on their origin and propagation. Previous measurements from a few balloon and space experiments indicate the existence of spectral softenings around 10 TV for protons (and probably also for Helium nuclei). Very recently, the DArk Matter Particle Explorer (DAMPE) measurement about the proton spectrum clearly reveals such a softening with a high significance. Here we study the implications of these new measurements, as well as the groundbased indirect measurements, on the origin of CRs. We find that a single component of CRs fails to fit the spectral softening and the air shower experiment data simultaneously. In the framework of multiple components, we discuss two possible scenarios, the multiple source population scenario and the background plus nearby source scenario. Both scenarios give reasonable fits to the wide-band data from TeV to 100 PeV energies. Considering the anisotropy observations, the nearby source model is favored.

astro-ph.HE↗

arXiv2019

DmpIRFs and DmpST: DAMPE Instrument Response Functions and Science Tools for Gamma-Ray Data Analysis

GeV gamma ray is an important observation target of DArk Matter Particle Explorer (DAMPE) for indirect dark matter searching and high energy astrophysics. We present in this work a set of accurate instrument response functions of DAMPE (DmpIRFs) including the effective area, point-spread function and energy dispersion that are crucial for the gamma-ray data analysis based on the high statistics simulation data. A dedicated software named DmpST is developed to facilitate the scientific analyses of DAMPE gamma-ray data. Considering the limited number of photons and the angular resolution of DAMPE, the maximum likelihood method is adopted in the DmpST to better disentangle different source components. The basic mathematics and the framework regarding this software are also introduced in this paper.

astro-ph.HE↗