Searcharxiv⌕ Search

arXiv subjects

R. Zhang

Publications and source records attributed to R. Zhang.

At least 19 recordsLinked to original sources
arXiv2026

Sustainable Air-Ground Integrated Coverage Networks: ISCC Architecture, Technologies, and Testbed

The rapid emergence of sixth-generation (6G) networks and the low-altitude economy has accelerated the evolution of wireless infrastructures toward air-ground integrated coverage networks (AGICNs), which seamlessly fuse terrestrial and aerial communication resources. However, existing AGICN studies primarily focus on coverage enhancement, while ignoring sustainability. Pursuing sustainable AGICNs introduces new challenges due to the multidimensional resource coupling across heterogeneous air-ground segments. In view of this, this paper presents a comprehensive survey and tutorial on sustainable AGICNs, aiming to balance coverage capacity with carbon efficiency in low-altitude economies. An integrated sensing, communication, and computation (ISCC)-driven architecture, which enables dynamic resource orchestration through closed-loop control, is proposed. We thus introduce a multi-dimensional sustainability metric system, which covers operational efficiency, task-oriented performance, and full lifecycle carbon emissions, to quantify energy and carbon footprints. We review enabling technologies, including artificial intelligence, hybrid precoding, integrated sensing and communication, and simultaneous wireless information and power transfer, and discuss their integration into the ISCC framework to minimize energy consumption while maintaining robust coverage. Experimental results on a real-world testbed demonstrate a 20% reduction in power consumption while achieving over 90% coverage probability, highlighting the feasibility of sustainable AGICNs for future green networks.

cs.IT↗
arXiv2026

Operational characterization of LAPPD Generation 2: charge sharing, delayed pulses, and dark-count behavior

We present a study of charge sharing and electronic cross-talk in second-generation Large-Area Picosecond Photodetectors (LAPPD Gen 2). The LAPPD is a vacuum-based device consisting of a photocathode, two microchannel plates, and a resistive anode that capacitively couples to an 8 $\times$ 8 pixelated readout board (25.4 mm $\times$ 25.4 mm pixel area). Using a picosecond pulsed laser, we measure signal distributions across the resistive anode and quantify coupling between target and neighboring pixels. We further examine the relationship between dark-count rate and LAPPD voltage settings, identifying decay behavior characterized by fast, intermediate, and slow relaxation timescales. We additionally observe the LAPPD behaving as a resonant cavity by injecting electrical pulses into the readout board. To further interpret observed signals, we develop a pulse-classification method and identify additional features at approximately 60 ns and 110 ns. Finally, we implement a first-principles Monte Carlo simulation to model the radial and temporal distributions of observed signals, including contributions from electron backscatter and potential ion afterpulsing. The simulation shows reasonable agreement with the experimentally derived pulse classifications.

physics.ins-det↗
arXiv2026

SDNator is Not Another SDN Controller: Enabling Extensible Data-Driven Control in Cyber-Physical Systems

An SDN-like centralized control architecture is increasingly popular and has been widely explored in cyber-physical systems (CPS) such as manufacturing, internet-of-things, and autonomous vehicle systems for higher flexibility, programmability and scalability. However, no existing frameworks can offer domain-agnostic, easily extensible support for data-driven CPS applications. In this work, we design, implement, and open-source \textit{SDNator}, the first framework to enable extensible, data-driven control in CPS. SDNator embraces an application- and data-driven design where applications function as data consumers and producers to collectively define the workflows of the controller. SDNator also incorporates two data store backends to support both event-driven and data-driven programming patterns. Benchmarks show that SDNator is highly scalable, and delivers comparable performance to Ryu, a widely used SDN controller. Moreover, we demonstrate the capabilities and usability of SDNator through our case studies of manufacturing and networking systems. By integrating applications from respective domains, we build different ``controllers'' for different scenarios. Most notably, we leverage SDNator to implement the first digital-twin-equipped central controller for additive manufacturing fleets. We show through extensive and realistic simulations that SDNator-based scheduling can (1) significantly shorten production time and improve reliability in the presence of anomalies compared to decentralized approaches, and (2) flexibly adjust and optimize production plans upon urgent requests such as producing Personal Protective Equipment during the COVID-19 pandemic.

cs.NI↗
arXiv2025

Lattice Boltzmann models for the hydrodynamic equations in multiphase flow with high density ratio

Multiphase flows with high density ratios, such as water and air flows, have recently been simulated using the lattice Boltzmann (LB) method. This approach corresponds to solving the phase field equations, such as the Cahn-Hilliard and Allen-Cahn equations, and the hydrodynamic equations, typically the Navier-Stokes and pressure equations for pseudo-incompressible fluids. Due to the high density ratio, the higher-order numerical truncation errors associated with spatial density gradients can become significant. These errors can lead to problems such as inaccuracies in shear stress, violations of Galilean invariance, and undesirable dependencies on absolute pressure for the pseudo-incompressible solutions. To overcome such problems, the moments of the distribution function and the equilibrium state must be carefully designed while ensuring robustness. In this work, we propose a new scheme based on the lattice kinetic scheme (LKS), which directly solves the velocity and pressure fields in the similar discrete space as the LB method. When mapping the LKS-based models to the LB models, the original LKS models are simplified for computational efficiency and the filter collision operator is implemented. Benchmark test cases confirm that the proposed scheme effectively addresses these issues, achieving high accuracy and robustness while eliminating the iterative steps typically required in the LKS. One of the most significant improvements is the accuracy of the airflow field induced by water motion, likely due to improved momentum transfer across the interface.

physics.flu-dyn↗
arXiv2025

Capillary flow simulation with the phase-field-based lattice Boltzmann solver

The phase-field-based lattice Boltzmann (LB) model has been developed to perform high fidelity multiphase flow simulations. Its ability to accurately handle high density ratio and surface tension effects is expected to be beneficial for capillary flow simulation, leading to accurate reproduction of flow patterns such as slug flow, droplet flow, and film flow. This is critical in many engineering cases because the flow patterns significantly affect the velocity and pressure fields. In this study, on top of the LB models based on the conservative Allen-Cahn equation and the volumetric boundary conditions for the complex geometries, an optimized wettability and friction model are implemented. With these models, we conducted a set of benchmark test cases, including static and dynamic multiphase flow scenarios such as the droplet on the curved surfaces, water-filling channel for the Lucas-Washburn law, and the critical pressure in the three-dimensional channel, an air-driven multiphase flow in the experiments. In all of these cases, the solver produces results that are consistent with both theory and experiment, even with respect to the pressure field accuracy, which has often been overlooked in many previous studies.

physics.flu-dyn↗
arXiv2025

Calibration Plan for the SBC 10-kg Liquid Argon Detector with 100 eV Target Threshold

The Scintillating Bubble Chamber (SBC) Collaboration is designing a new generation of low background, noble liquid bubble chamber experiments with sub-keV nuclear recoil threshold. These experiments combine the electronic recoil blindness of a bubble chamber with the energy resolution of noble liquid scintillation, and maintain electron recoil discrimination at higher degrees of superheat (lower nuclear recoil thresholds) than Freon-based bubble chambers. A 10-kg liquid argon bubble chamber has the potential to set world leading limits on the dark matter nucleon cross-section for $O(\mathrm{GeV}/c^{2})$ masses, and to perform a high statistics coherent elastic neutrino nuclear scattering measurement with reactor neutrinos. This work presents a detailed calibration plan to measure the detector response of these experiments, combining photoneutron scattering with two new techniques to induce sub-keV nuclear recoils: nuclear Thomson scattering and thermal neutron capture.

physics.ins-det↗
arXiv2025

PREDICT-GBM: A multi-center platform to advance personalized glioblastoma radiotherapy planning

Glioblastoma recurrence is largely driven by diffuse infiltration beyond radiologically visible tumor margins, yet standard radiotherapy, the mainstay of glioblastoma treatment, relies on uniform expansions that ignore patient-specific biological and anatomical factors. While computational models promise to map this invisible growth and guide personalized treatment planning, their clinical translation is hindered by the lack of standardized, large-scale benchmarking and reproducible validation workflows. To bridge this gap, we present PREDICT-GBM, a comprehensive open-source platform that integrates a curated, longitudinal, multi-center dataset of 243 patients with a standardized evaluation pipeline, and fuels model development and validation. We demonstrate PREDICT-GBM's potential by training and benchmarking a novel U-Net-based recurrence prediction model against state-of-the-art biophysical and data-driven methods. Our results show that both biophysical and deep-learning approaches significantly outperform standard-of-care protocols in predicting future recurrence sites while maintaining iso-volumetric treatment constraints. Notably, our U-Net model achieved a superior coverage of enhancing recurrence (79.37 +/- 2.08 %), markedly surpassing the standard-of-care (paired Wilcoxon signed-rank test, p = 0.0000057). Furthermore, the biophysical model GliODIL reached 78.91 +/- 2.08 % (p = 0.00045), validating the platform's ability to compare diverse modeling paradigms. By providing the first rigorous, reproducible ecosystem for model training and validation, PREDICT-GBM eliminates a major bottleneck for personalized, computationally guided radiotherapy. This work establishes a new standard for developing computationally guided, personalized radiotherapy, with the platform, models, and data openly available at github.com/BrainLesion/PredictGBM

eess.IV↗
arXiv2025

Reliable Clutter Suppression for Slow-Moving Weak Target Radar Detection

Reliable slow-moving weak target detection in complicated environments is challenging due to the masking effects from the surrounding strong reflectors. The traditional Moving Target Indication (MTI) may suppress the echoes from not only the static interference objects (IOs), but also the desired slow-moving weak target. According to the low-rank and sparse properties of the range-velocity maps across different radar scans, a novel clutter suppression scheme based on the Go decomposition (Godec) framework is proposed in this paper. The simulation results show that with the existence of masking effects, the target detection scheme based on Godec clutter suppression can reliably detect the slow-moving weak target, compared to the traditional MTI-based scheme. Besides, the time consumption comparison is conducted, demonstrating that the proposed solution is one that sacrifices time complexity in exchange for enhanced reliability. Additionally, the tradeoffs among the number of false alarm cells, the detection probability and the iteration times for convergence have been revealed, guiding parameter settings of the proposed solution in practical applications. Experiment validation is also conducted to verify the proposed solution, providing further insight into the scenarios where the solution is most applicable.

eess.SP↗
arXiv2025

HydroX, a light dark matter search with hydrogen-doped liquid xenon time projection chambers

Experimental efforts searching for dark matter particles over the last few decades have ruled out many candidates led by the new generation of tonne-scale liquid xenon. For light dark matter, hydrogen could be a better target than xenon as it would offer a better kinematic match to the low mass particles. This article describes the HydroX concept, an idea to expand the dark matter sensitivity reach of large liquid xenon detectors by adding hydrogen to the liquid xenon. We discuss the nature of signal generation in liquid xenon to argue that the signal produced at the interaction site by a dark matter-hydrogen interaction could be significantly enhanced over the same interaction on xenon, increasing the sensitivity to the lightest particles. We discuss the technical implications of adding hydrogen to a xenon detector, as well as some background considerations. Finally, we make projections as to the potential sensitivity of a HydroX implementation and discuss next steps.

hep-ex↗
arXiv2024

When LAMOST meets Gaia DR3 Exploring the metallicity of open clusters

Context. Open clusters (OCs) are valuable probes of stellar population characteristics. Their age and metallicity provide insights into the chemical enrichment history of the Milky Way. By studying the metallicity of OCs, we can explore the spatial distribution of composition across the Galaxy and understand stellar birth radii through chemical tagging. However, inferring the original positions of OCs remains a challenge. Aims. This study investigates the distribution of metallicity in the solar neighborhood using data from Gaia DR3 and LAMOST spectra. By measuring accurate ages and metallicities, we aim to derive birth radii and understand stellar migration patterns. Methods. We selected 1131 OCs within 3 kpc of the Sun from Gaia DR3 and LAMOST DR8 low-resolution spectra (R=1800). To correct the LAMOST data, we incorporated high-resolution spectra from GALAH DR3 (R=28000) using an artificial neural network. The average metallicity of the OCs was derived from reliable [Fe/H] values of their members. We examined the metallicity distribution across the Galaxy and calculated birth radii based on age and metallicity. Results. The correction method reduces the systematic offset in LAMOST data. We found a metallicity gradient as a function of Galactocentric distance and guiding radii. Comparisons with chemo-dynamic simulations show that observed metallicity values are slightly lower than predicted when uncertainties are ignored, but the metallicity gradients align with previous studies. We also inferred that many OCs near the Sun likely originated from the outer Galactic disk.

astro-ph.GA↗
arXiv2024

Low-threshold response of a scintillating xenon bubble chamber to nuclear and electronic recoils

A device filled with pure xenon first demonstrated the ability to operate simultaneously as a bubble chamber and scintillation detector in 2017. Initial results from data taken at thermodynamic thresholds down to ~4 keV showed sensitivity to ~20 keV nuclear recoils with no observable bubble nucleation by $\gamma$-ray interactions. This paper presents results from further operation of the same device at thermodynamic thresholds as low as 0.50 keV, hardware limited. The bubble chamber has now been shown to have sensitivity to ~1 keV nuclear recoils while remaining insensitive to bubble nucleation by $\gamma$-rays. A robust calibration of the chamber's nuclear recoil nucleation response, as a function of nuclear recoil energy and thermodynamic state, is presented. Stringent upper limits are established for the probability of bubble nucleation by $\gamma$-ray-induced Auger cascades, with a limit of $<1.1\times10^{-6}$ set at 0.50 keV, the lowest thermodynamic threshold explored.

physics.ins-det↗
arXiv2024

Batch VUV4 Characterization for the SBC-LAr10 scintillating bubble chamber

The Scintillating Bubble Chamber (SBC) collaboration purchased 32 Hamamatsu VUV4 silicon photomultipliers (SiPMs) for use in SBC-LAr10, a bubble chamber containing 10~kg of liquid argon. A dark-count characterization technique, which avoids the use of a single-photon source, was used at two temperatures to measure the VUV4 SiPMs breakdown voltage ($V_{\text{BD}}$), the SiPM gain ($g_{\text{SiPM}}$), the rate of change of $g_{\text{SiPM}}$ with respect to voltage ($m$), the dark count rate (DCR), and the probability of a correlated avalanche (P$_{\text{CA}}$) as well as the temperature coefficients of these parameters. A Peltier-based chilled vacuum chamber was developed at Queen's University to cool down the Quads to $233.15\pm0.2$~K and $255.15\pm0.2$~K with average stability of $\pm20$~mK. An analysis framework was developed to estimate $V_{\text{BD}}$ to tens of mV precision and DCR close to Poissonian error. The temperature dependence of $V_{\text{BD}}$ was found to be $56\pm2$~mV~K$^{-1}$, and $m$ on average across all Quads was found to be $(459\pm3(\rm{stat.})\pm23(\rm{sys.}))\times 10^{3}~e^-$~PE$^{-1}$~V$^{-1}$. The average DCR temperature coefficient was estimated to be $0.099\pm0.008$~K$^{-1}$ corresponding to a reduction factor of 7 for every 20~K drop in temperature. The average temperature dependence of P$_{\text{CA}}$ was estimated to be $4000\pm1000$~ppm~K$^{-1}$. P$_{\text{CA}}$ estimated from the average across all SiPMs is a better estimator than the P$_{\text{CA}}$ calculated from individual SiPMs, for all of the other parameters, the opposite is true. All the estimated parameters were measured to the precision required for SBC-LAr10, and the Quads will be used in conditions to optimize the signal-to-noise ratio.

physics.ins-det↗
arXiv2023

Stochastic p-Bits Based on Spin-Orbit Torque Magnetic Tunnel Junctions

Stochastic p-Bit devices play a pivotal role in solving NP-hard problems, neural network computing, and hardware accelerators for algorithms such as the simulated annealing. In this work, we focus on Stochastic p-Bits based on high-barrier magnetic tunnel junctions (HB-MTJs) with identical stack structure and cell geometry, but employing different spin-orbit torque (SOT) switching schemes. We conducted a comparative study of their switching probability as a function of pulse amplitude and width of the applied voltage. Through experimental and theoretical investigations, we have observed that the Y-type SOT-MTJs exhibit the gentlest dependence of the switching probability on the external voltage. This characteristic indicates superior tunability in randomness and enhanced robustness against external disturbances when Y-type SOT-MTJs are employed as stochastic p-Bits. Furthermore, the random numbers generated by these Y-type SOT-MTJs, following XOR pretreatment, have successfully passed the National Institute of Standards and Technology (NIST) SP800-22 test. This comprehensive study demonstrates the high performance and immense potential of Y-type SOT-MTJs for the implementation of stochastic p-Bits.

cond-mat.mes-hall↗
arXiv2023

Reanalysis of the X-ray burst associated FRB 200428 with Insight-HXMT observations

A double-peak X-ray burst from the Galactic magnetar SGR J1935+2154 was discovered as associated with the two radio pulses of FRB 200428 separated by 28.97+-0.02 ms. Precise measurements of the timing and spectral properties of the X-ray bursts are helpful for understanding the physical origin of fast radio bursts (FRBs). In this paper, we have reconstructed some information about the hard X-ray events, which were lost because the High Energy X-ray Telescope (HE) onboard the Insight-HXMT mission was saturated by this extremely bright burst, and used the information to improve the temporal and spectral analyses of the X-ray burst. The arrival times of the two X-ray peaks by fitting the new Insight-HXMT/HE lightcurve with multi-Gaussian profiles are 2.77+-0.45 ms and 34.30+-0.56 ms after the first peak of FRB 200428, respectively, while these two parameters are 2.57+-0.52 ms and 32.5+-1.4 ms if the fitting profile is a fast rise and exponential decay function. The spectrum of the two X-ray peaks could be described by a cutoff power-law with cutoff energy ~60 keV and photon index ~1.4, the latter is softer than that of the underlying bright and broader X-ray burst when the two X-ray peaks appeared.

astro-ph.HE↗
arXiv2022

Stellar Population Astrophysics (SPA) with the TNG. alpha-elements, lithium, sodium and aluminum in 16 open clusters

Exploring the Galactic chemical evolution and enrichment scenarios with open clusters allows us to understand the history of the Milky Way disk. High-resolution spectra of OCs are a crucial tool, as they provide precise chemical information, to combine with precise distances and ages. The aim of the Stellar Population Astrophysics project is to derive homogeneous and accurate comprehensive chemical characterization of a number of poorly studied OCs.Using the HARPS-N echelle spectrograph at the Telescopio Nazionale Galileo, we obtained high-resolution spectra of giant stars in 18 OCs, 16 of which are chemically characterized for the first time, and two of which are well studied for comparison. The OCs in this sample have ages from a few tens of Myr to 4 Gyr, with a prevalence of young clusters. We already presented the radial velocities and atmospheric parameters for them in a previous SPA paper. Here, we present results for the alpha-elements O, and the light elements, all determined by the equivalent width method. We also measured Li abundance through the synthesis method.We discuss the behaviors of lithium, sodium and aluminum in the context of stellar evolution. We study the radial, vertical, and age trends for the measured abundance ratios in a sample that combines our results and recent literature for OCs, finding significant gradients only for [Mg/Fe] and [Ca/Fe] in all cases. Finally,we compare O and Mg in the combined sample with chemo-dynamical models, finding a good agreement for intermediate-age and old clusters. There is a sharp increase in the abundance ratios measured among very young clusters, accompanied by a poorer fit with the models for O and Mg, likely related to the inadequacy of traditional model atmospheres and methods in the derivation of atmospheric parameters and abundance ratios for stars of such young ages

astro-ph.GA↗
arXiv2022

Snowmass 2021 Scintillating Bubble Chambers: Liquid-noble Bubble Chambers for Dark Matter and CE$\nu$NS Detection

The Scintillating Bubble Chamber (SBC) Collaboration is developing liquid-noble bubble chambers for the quasi-background-free detection of low-mass (GeV-scale) dark matter and coherent scattering of low-energy (MeV-scale) neutrinos (CE$\nu$NS). The first physics-scale demonstrator of this technique, a 10-kg liquid argon bubble chamber dubbed SBC-LAr10, is now being commissioned at Fermilab. This device will calibrate the background discrimination power and sensitivity of superheated argon to nuclear recoils at energies down to 100 eV. A second functionally-identical detector with a focus on radiopure construction is being built for SBC's first dark matter search at SNOLAB. The projected spin-independent sensitivity of this search is approximately $10^{-43}$ cm$^2$ at 1 GeV$/c^2$ dark matter particle mass. The scalability and background discrimination power of the liquid-noble bubble chamber make this technique a compelling candidate for future dark matter searches to the solar neutrino fog at 1 GeV$/c^2$ particle mass (requiring a $\sim$ton-year exposure with non-neutrino backgrounds sub-dominant to the solar CE$\nu$NS signal) and for high-statistics CE$\nu$NS studies at nuclear reactors.

physics.ins-det↗
arXiv2021

Exponentially selective molecular sieving through angstrom pores

Two-dimensional crystals with angstrom-scale pores are widely considered as candidates for a next generation of molecular separation technologies aiming to provide extreme, exponentially large selectivity combined with high flow rates. No such pores have been demonstrated experimentally. Here we study gas transport through individual graphene pores created by low intensity exposure to low kV electrons. Helium and hydrogen permeate easily through these pores whereas larger species such as xenon and methane are practically blocked. Permeating gases experience activation barriers that increase quadratically with molecules' kinetic diameter, and the effective diameter of the created pores is estimated as ~2 angstroms, about one missing carbon ring. Our work reveals stringent conditions for achieving the long sought-after exponential selectivity using porous two-dimensional membranes and suggests limits on their possible performance.

cond-mat.mes-hall↗