arXiv subjects

Jibo He

Publications and source records attributed to Jibo He.

At least 19 recordsLinked to original sources

arXiv2026

Auxiliary-Channel-Assisted Cross-Talk Noise Removal in LISA Pathfinder

LISA Pathfinder (LPF) is the technology demonstration mission for the future Laser Interferometer Space Antenna (LISA). Besides the science interferometric channel, LPF is equipped with numerous auxiliary channels that monitor the instrument and environment disturbances, some of which contain information correlated with noise in the science channel. In this work, we investigate cross-talk noise subtraction in LPF using a frequency-domain transfer-function approach, in which the coherence between the science channel and auxiliary channels is used to estimate and remove correlated noise. The effectiveness of this method is first validated using simulated science and auxiliary channel data with a common disturbance. The simulation shows that the subtraction performance strongly depends on the auxiliary-channel noise level, providing a practical framework for determining the auxiliary-channel noise requirement needed to achieve a desired subtraction performance. This method is then used to analyze 9 auxiliary channels in publicly available LPF telemetry data. In the cross-talk dominated frequency band from $1\times10^{-2}$ to $6\times10^{-2}\,\mathrm{Hz}$, this method achieves cross-talk noise suppression comparable to the standard fitting based subtraction. Above $6\times10^{-2}\,\mathrm{Hz}$, it further suppresses the residual noise by avoiding the introduction of auxiliary-channel readout noise associated with the fitting procedure, resulting in better performance than the standard pipeline.

astro-ph.IM↗

arXiv2026

Long-algorithm based quantum search for gravitational wave

Gravitational wave astronomy is rapidly advancing with the development of new observatories, leading to an increasing volume and complexity of data. This trend places growing pressure on classical data analysis methods and motivates the exploration of quantum approaches. In this work, we introduce a quantum matched filtering framework for gravitational-wave detection based on the Long algorithm, marking its first application to the gravitational-wave data analysis. Numerical simulations show that the proposed approach preserves the quadratic speedup of quantum search while exhibiting significantly improved robustness, thereby overcoming key limitations of the Grover-algorithm based methods.

astro-ph.IM↗

arXiv2025

Pilot selection in the era of Virtual reality: algorithms for accurate and interpretable machine learning models

With the rapid growth of the aviation industry, there is a need for a large number of flight crew. How to select the right pilots in a cost-efficient manner has become an important research question. In the current study, twenty-three pilots were recruited from China Eastern Airlines, and 23 novices were from the community of Tsinghua University. A novel approach incorporating machine learning and virtual reality technology was applied to distinguish features between these participants with different flight skills. Results indicate that SVM with the MIC feature selection method consistently achieved the highest prediction performance on all metrics with an Accuracy of 0.93, an AUC of 0.96, and an F1 of 0.93, which outperforms four other classifier algorithms and two other feature selection methods. From the perspective of feature selection methods, the MIC method can select features with a nonlinear relationship to sampling labels, instead of a simple filter-out. Our new implementation of the SVM + MIC algorithm outperforms all existing pilot selection algorithms and perhaps provides the first implementation based on eye tracking and flight dynamics data. This study's VR simulation platforms and algorithms can be used for pilot selection and training.

cs.LG↗

arXiv2025

A Kalman-smoother based data imputation strategy to data gaps in spaceborne gravitational wave detectors

Massive black hole binaries (MBHBs) and other sources within the frequency band of spaceborne gravitational wave observatories like the Laser Interferometer Space Antenna (LISA), Taiji and Tianqin pose unique challenges, as gaps and glitches during the years-long observation lead to both loss of information and spectral leakage. We propose a novel data imputation strategy based on Kalman filter and smoother to mitigate gap-induced biases in parameter estimation. Applied to a scenario where traditional windowing and smoothing technique introduce significant biases, our method mitigates the biases and demonstrates lower computational cost compared to existing data augmentation techniques such as noise inpainting. This framework presents a new gap treatment approach that balances robustness and efficiency for space-based gravitational wave data analysis.

astro-ph.IM↗

arXiv2025

Test Gravitational-Wave Polarizations with Space-Based Detectors

In this work, we systematically investigate the capability of space-based gravitational wave detectors in constraining parameters of non-tensor polarization modes. Using Bayesian inference and Fisher Information Matrix methods, we analyze gravitational wave signals from the inspiral phase of supermassive binary black hole mergers. By starting with time-domain signals and applying Fourier transforms, we avoid the use of the stationary phase approximation. We found an asymmetry in the estimation of the vector-mode parameter $\alpha_x$ at inclination angles $\iota = 0$ and $\iota = \pi$, which has not been explicitly pointed out in previous studies. We also observe strong correlations between scalar-mode parameters, $\alpha_b$ and $\alpha_l$, which currently limit their independent estimation. These findings underscore the importance of using complete inspiral-merger-ringdown waveforms to enhance the ability to distinguish the non-tensor polarization modes. Finally, we employ a new LISA-Taiji network configuration, in which the orientation of spacecrafts of Taiji maintains a fixed phase offset relative to these of LISA. Under the adiabatic approximation and the assumption of equal arms, this phase is found to have no significant effect on data analysis.

gr-qc↗

arXiv2025

Quantum Search for Gravitational Wave of Massive Black Hole Binaries

Matched filtering is a common method for detecting gravitational waves. However, the computational costs of searching large template banks limit the efficiency of classical algorithms when searching for massive black hole binary (MBHB) systems. This work explores the application of a quantum matched filtering algorithm based on Grover's algorithm to MBHB signals. Under certain simplifying assumptions, quantum approach can reduce the computational complexity from $O(N)$ to $O(\sqrt{N})$ theoretically, where $N$ is the size of the template bank. Simulated results illustrate the potential reduction in computational costs, while also showing that the performance can degrade in some cases due to instability of the algorithm. These findings reveal both the potential and the limitations of quantum search for MBHB signals, pointing to the importance of developing more robust and stable search strategies alongside realistic modeling in future work.

astro-ph.IM↗

arXiv2025

Learning and Interpreting Gravitational-Wave Features from CNNs with a Random Forest Approach

Convolutional neural networks (CNNs) have become widely adopted in gravitational wave (GW) detection pipelines due to their ability to automatically learn hierarchical features from raw strain data. However, the physical meaning of these learned features remains underexplored, limiting the interpretability of such models. In this work, we propose a hybrid architecture that combines a CNN-based feature extractor with a random forest (RF) classifier to improve both detection performance and interpretability. Unlike prior approaches that directly connect classifiers to CNN outputs, our method introduces four physically interpretable metrics - variance, signal-to-noise ratio (SNR), waveform overlap, and peak amplitude - computed from the final convolutional layer. These are jointly used with the CNN output in the RF classifier to enable more informed decision boundaries. Tested on long-duration strain datasets, our hybrid model outperforms a baseline CNN model, achieving a relative improvement of 21\% in sensitivity at a fixed false alarm rate of 10 events per month. Notably, it also shows improved detection of low-SNR signals (SNR $\le$ 10), which are especially vulnerable to misclassification in noisy environments. Feature attribution via the RF model reveals that both CNN-extracted and handcrafted features contribute significantly to classification decisions, with learned variance and CNN outputs ranked among the most informative. These findings suggest that physically motivated post-processing of CNN feature maps can serve as a valuable tool for interpretable and efficient GW detection, bridging the gap between deep learning and domain knowledge.

cs.LG↗

arXiv2025

Accelerating Bayesian Sampling for Massive Black Hole Binaries with Prior Constraints from Conditional Variational Autoencoder

A Conditional Variational Autoencoder (CVAE) model is employed for parameter inference on gravitational waves (GW) signals of massive black hole binaries, considering joint observations with a network of three space-based GW detectors. Our experiments show that the trained CVAE model can estimate the posterior distribution of source parameters in approximately one second, while the standard Bayesian sampling method, utilizing parallel computation across 16 CPU cores, takes an average of 20 hours for a GW signal instance. However, the sampling distributions from CVAE exhibit lighter tails, appearing broader when compared to the standard Bayesian sampling results. By using CVAE results to constrain the prior range for Bayesian sampling, the sampling time is reduced by a factor of $\sim$6 while maintaining the similar precision of the Bayesian results.

astro-ph.IM↗

arXiv2024

Flavor Physics at the CEPC: a General Perspective

We discuss the landscape of flavor physics at the Circular Electron-Positron Collider (CEPC), based on the nominal luminosity outlined in its Technical Design Report. The CEPC is designed to operate in multiple modes to address a variety of tasks. At the $Z$ pole, the expected production of 4 Tera $Z$ bosons will provide unique and highly precise measurements of $Z$ boson couplings, while the substantial number of boosted heavy-flavored quarks and leptons produced in clean $Z$ decays will facilitate investigations into their flavor physics with unprecedented precision. We investigate the prospects of measuring various physics benchmarks and discuss their implications for particle theories and phenomenological models. Our studies indicate that, with its highlighted advantages and anticipated excellent detector performance, the CEPC can explore beauty and $\tau$ physics in ways that are superior to or complementary with the Belle II and Large-Hadron-Collider-beauty experiments, potentially enabling the detection of new physics at energy scales of 10 TeV and above. This potential also extends to the observation of yet-to-be-discovered rare and exotic processes, as well as testing fundamental principles such as lepton flavor universality, lepton and baryon number conservation, etc., making the CEPC a vibrant platform for flavor physics research. The $WW$ threshold scan, Higgs-factory operation and top-pair productions of the CEPC further enhance its merits in this regard, especially for measuring the Cabibbo-Kobayashi-Maskawa matrix elements, and Flavor-Changing-Neutral-Current physics of Higgs boson and top quarks. We outline the requirements for detector performance and considerations for future development to achieve the anticipated scientific goals.

hep-ex↗

arXiv2023

Calibration of the in-orbit center-of-mass of TaiJi-1

Taiji program is a space mission aiming to detect gravitational waves in the low frequency band. Taiji-1 is the first technology demonstration satellite of the Taiji Program in Space, with the gravitational reference sensor (GRS) serving as one of its key scientific payloads. For accurate accelerometer measurements, the test-mass center of the GRS must be positioned precisely at the center of gravity of the satellite to avoid measurement disturbances caused by angular acceleration and gradient. Due to installation and measurement errors, fuel consumption during in-flight phase, and other factors, the offset between the test-mass center and the center-of-mass (COM) of the satellite can be significant, degrading the measurement accuracy of the accelerometer. Therefore, the offset needs to be estimated and controlled within the required range by the center-of-mass adjustment mechanism during the satellite's lifetime. In this paper, we present a novel method, the Extended Kalman Filter combined with Rauch-Tung-Striebel Smoother, to estimate the offset, while utilizing the chi-square test to eliminate outliers. Additionally, the nonlinear Least Squares estimation algorithm is employed as a crosscheck to estimate the offset of COM. The two methods are shown to give consistent results, with the offset estimated to be $dx \approx $$-$$0.19$ mm, $dy \approx 0.64$ mm, and $dz \approx $$-$$0.82$ mm. The results indicate a significant improvement on the noise level of GRS after the COM calibration, which will be of great help for the future Taiji program.

astro-ph.IM↗

arXiv2021

Heavy flavour production and spectroscopy

Latest results on the heavy flavour production and spectroscopy at the LHC are reviewed. These include measurements of production rates of the charmed and beauty hadrons, and observations of new excited charmed and beauty hadrons and exotic states.

hep-ex↗

arXiv2020

Prospects for quarkonium studies at the high-luminosity LHC

Prospects for quarkonium-production studies accessible during the upcoming high-luminosity phases of the CERN Large Hadron Collider operation after 2021 are reviewed. Current experimental and theoretical open issues in the field are assessed together with the potential for future studies in quarkonium-related physics. This will be possible through the exploitation of the huge data samples to be collected in proton-proton, proton-nucleus and nucleus-nucleus collisions, both in the collider and fixed-target modes. Such investigations include, among others, those of: (i) J/psi and Upsilon produced in association with other hard particles; (ii) chi(c,b) and eta(c,b) down to small transverse momenta; (iii) the constraints brought in by quarkonia on gluon PDFs, nuclear PDFs, TMDs, GPDs and GTMDs, as well as on the low-x parton dynamics; (iv) the gluon Sivers effect in polarised-nucleon collisions; (v) the properties of the quark-gluon plasma produced in ultra-relativistic heavy-ion collisions and of collective partonic effects in general; and (vi) double and triple parton scatterings.

hep-ph↗

arXiv2019

Phenomenological NLO analysis of eta(c) production at the LHC in the collider and fixed-target modes

In view of the good agreement between the LHCb prompt-eta(c) data at sqrt(s)=7 and 8 TeV and the NLO colour-singlet model predictions --i.e. the leading v^2 NRQCD contribution--, we provide predictions in the LHCb acceptance for the forthcoming 13 TeV analysis bearing on data taken during the LHC Run2. We also provide predictions for sqrt(s)=115 GeV for proton-hydrogen collisions in the fixed-target mode which could be studied during the LHC Run3. Our predictions are complemented by a full theoretical uncertainty analysis. In addition to cross section predictions, we elaborate on the uncertainties on the p bar-p branching ratio --necessary for data-theory comparison-- and discuss other usable branching fractions for future studies.

hep-ph↗

arXiv2018

A Practical Framework for Preventing Distracted Pedestrian-related Incidents using Wrist Wearables

Distracted pedestrians, like distracted drivers, are an increasingly dangerous threat and precursors to pedestrian accidents in urban communities, often resulting in grave injuries and fatalities. Mitigating such hazards to pedestrian safety requires employment of pedestrian safety systems and applications that are effective in detecting them. Designing such frameworks is possible with the availability of sophisticated mobile and wearable devices equipped with high-precision on-board sensors capable of capturing fine-grained user movements and context, especially distracted activities. However, the key technical challenge is accurate recognition of distractions with minimal resources in real-time given the computation and communication limitations of these devices. Several recently published works improve distracted pedestrian safety by leveraging on complex activity recognition frameworks using mobile and wearable sensors to detect pedestrian distractions. Their primary focus, however, was to achieve high detection accuracy, and therefore most designs are either resource intensive and unsuitable for implementation on mainstream mobile devices, or computationally slow and not useful for real-time pedestrian safety applications, or require specialized hardware and less likely to be adopted by most users. In the quest for a pedestrian safety system, we design an efficient and real-time pedestrian distraction detection technique that overcomes some of these shortcomings. We demonstrate its practicality by implementing prototypes on commercially-available mobile and wearable devices and evaluating them using data collected from participants in realistic pedestrian experiments. Using these evaluations, we show that our technique achieves a favorable balance between computational efficiency, detection accuracy and energy consumption compared to some other techniques in the literature.

cs.HC↗

arXiv2017

Side-Channel Inference Attacks on Mobile Keypads using Smartwatches

Smartwatches enable many novel applications and are fast gaining popularity. However, the presence of a diverse set of on-board sensors provides an additional attack surface to malicious software and services on these devices. In this paper, we investigate the feasibility of key press inference attacks on handheld numeric touchpads by using smartwatch motion sensors as a side-channel. We consider different typing scenarios, and propose multiple attack approaches to exploit the characteristics of the observed wrist movements for inferring individual key presses. Experimental evaluation using commercial off-the-shelf smartwatches and smartphones show that key press inference using smartwatch motion sensors is not only fairly accurate, but also comparable with similar attacks using smartphone motion sensors. Additionally, hand movements captured by a combination of both smartwatch and smartphone motion sensors yields better inference accuracy than either device considered individually.

cs.CR↗

arXiv2017

Towards a Practical Pedestrian Distraction Detection Framework using Wearables

Pedestrian safety continues to be a significant concern in urban communities and pedestrian distraction is emerging as one of the main causes of grave and fatal accidents involving pedestrians. The advent of sophisticated mobile and wearable devices, equipped with high-precision on-board sensors capable of measuring fine-grained user movements and context, provides a tremendous opportunity for designing effective pedestrian safety systems and applications. Accurate and efficient recognition of pedestrian distractions in real-time given the memory, computation and communication limitations of these devices, however, remains the key technical challenge in the design of such systems. Earlier research efforts in pedestrian distraction detection using data available from mobile and wearable devices have primarily focused only on achieving high detection accuracy, resulting in designs that are either resource intensive and unsuitable for implementation on mainstream mobile devices, or computationally slow and not useful for real-time pedestrian safety applications, or require specialized hardware and less likely to be adopted by most users. In the quest for a pedestrian safety system that achieves a favorable balance between computational efficiency, detection accuracy, and energy consumption, this paper makes the following main contributions: (i) design of a novel complex activity recognition framework which employs motion data available from users' mobile and wearable devices and a lightweight frequency matching approach to accurately and efficiently recognize complex distraction related activities, and (ii) a comprehensive comparative evaluation of the proposed framework with well-known complex activity recognition techniques in the literature with the help of data collected from human subject pedestrians and prototype implementations on commercially-available mobile and wearable devices.

cs.HC↗

arXiv2016

Real-time calibration and alignment of the LHCb RICH detectors

In 2015, the LHCb experiment established a new and unique software trigger strategy with the purpose of increasing the purity of the signal events by applying the same algorithms online and offline. To achieve this, real-time calibration and alignment of all LHCb sub-systems is needed to provide vertexing, tracking, and particle identification of the best possible quality. The calibration of the refractive index of the RICH radiators, the calibration of the Hybrid Photon Detector image, and the alignment of the RICH mirror system, are reported in this contribution. The stability of the RICH performance and the particle identification performance are also discussed.

physics.ins-det↗

arXiv2012

Investigating charmonium production at LHC with the p pbar final state

We propose to investigate various charmonium states using their common decay channel to p pbar at LHC. Having the branching ratios for charmonium decaying into the p pbar final state measured or calculated, we propose to measure the charmonium production rate for both hadroproduction including soft-diffraction and inclusive production from b-hadron decays. We discuss the theoretical impacts in QCD of measuring different charmonium production rates and also the experimental prospects at LHCb, in particular, those for yet unmeasured eta_c and h_c.

hep-ph↗