arXiv subjects

Weijia Han

Publications and source records attributed to Weijia Han.

15 recordsLinked to original sources

arXiv2026

When the Martingale Never Stops Firing: Anytime-Valid Gating on Real Forecast Streams

Machine learning systems are increasingly corrected while they run, and the decision of when to intervene is increasingly delegated to statistical monitors. Anytime-valid inference promises evidence that can be acted on at any moment, exactly the guarantee this setting needs, and it is moving from theory into deployed monitoring. Conformal test martingales are the change-detection instrument, and Ville's inequality caps their false-alarm probability on exchangeable data. The guarantee is conditional. A deployment inherits it only if the stream it monitors behaves exchangeably. The premise is hardest to satisfy where these monitors are most useful, on dependent data and inside loops where the monitor modifies the learner whose scores it reads. It is also rarely measured. We measure it in a pre-specified case study, where such a monitor gates the online updates of a Kalman adapter correcting frozen time-series foundation models on five forecasting streams. On exchangeable synthetic streams, the same implementation fires in at most 1 of 60 runs. On the real streams, at alpha = 0.05, 135 of 135 clean-stream runs fired. The construction does not explain the firing; the failure comes from the deployed score stream itself. Repeated fires hold the gate's drift response active, and the gated filter amplifies the very transient it was designed to prevent. The component worth keeping makes no validity claim. Huber-style gating of the filter's own updates cuts isolated-spike degradation by an order of magnitude with no dataset specific tuning. Anytime-valid methods proposed for dependent data should therefore be accompanied by null-calibration controls and mechanism traces.

cs.LG↗

arXiv2026

The Label Complexity of Class-Conditional Coverage under Distribution Shift

Conformal prediction certifies that a classifier's prediction sets cover the truth, and that certificate is marginal. Many recognition benchmarks build distribution shift into evaluation, placing disjoint conditions in the training and test splits. Under that shift the certificate stays reassuring while per class coverage fails silently: on a real cross subject skeleton benchmark marginal coverage holds near ninety percent while the worst class is covered about seventy percent and ten of sixty classes fall below eighty percent. This class specific undercoverage stays hidden behind a single reassuring marginal number. Once the shift acts jointly on covariates and labels, the target class conditional score law is unidentified, so no label free method is at once per class valid and efficient uniformly over target laws consistent with the observed source joint distribution and target covariate marginal. The per class labels needed to recover every class threshold to a given tolerance grow as the inverse square of that tolerance and the logarithm of the class count, with matching bounds for classwise threshold procedures. Pseudo labels do not shortcut it: the best prediction powered estimator gains at most a small constant factor where coverage collapses. Across three real shifts and an image corruption benchmark, source label calibration recovers much of the gap while marginal coverage holds, and stops once it breaks.

cs.LG↗

arXiv2026

Decomposing Runtime, Kernel, and Quantization Speedups via a Matched FP16 Intermediate: A Hardware-Conditioned Case Study on Four NVIDIA RTX A5000 GPUs

Reported serving speedups from quantized kernels typically bundle the weight format, the kernel, and the inference runtime into one number. We present an attribution study on four NVIDIA RTX A5000 GPUs, 24 GiB each, on a single host with NVLink-bridged pairs. A matched intermediate stack that keeps the faster runtime without the quantized kernel splits the full speedup into a runtime part and a kernel and quantization part. Under matched greedy decoding the full stack reaches $2.58\times$ end to end, with the runtime change accounting for about two thirds of that gain on a logarithmic scale; across three similar model families the kernel and quantization part moves by at most 1.5%. Sharding one instance across all four cards falls well below doubling: a profiler trace attributes about 80% of the per token shortfall to coordination, and an NVLink versus PCIe control on the same hardware shows similar realized bandwidth on both links, pointing away from link bandwidth as the cause. Whether to run one sharded instance or several independent ones depends on the workload and the model, with the ranking reversing on the larger model: the smaller model splits between sharding and multiple instances by workload, while the larger model favors two paired instances on every workload. Quantization extends sustainable concurrent users roughly four times past a reproducible half precision memory cliff. Differences in sampling mode and prompt pool between the two stacks are documented as threats to validity.

cs.DC↗

arXiv2026

Hyperon-Nucleon Spectrometer

Chirality lies at the heart of low-energy QCD, governing the symmetry structure that shapes hadron masses and strong interaction dynamics. Among the most compelling open questions tied to chiral dynamics and spontaneous chiral symmetry breaking is the longstanding $\Lambda$ polarization puzzle, in which $\Lambda$ hyperons produced in unpolarized hadronic collisions exhibit a surprisingly large transverse polarization that remains theoretically unexplained. This whitepaper presents the proposal for the Hyperon-Nucleon Spectrometer (H-NS) at the High-Intensity heavy-ion Accelerator Facility (HIAF). Leveraging the high energy and high intensity of HIAF's proton and heavy-ion beams, the H-NS experiment will perform systematic studies of hyperon polarization phenomena and their underlying mechanisms in proton-proton ($pp$), proton-nucleus ($pA$), and nucleus-nucleus ($AA$) collisions in the fixed target mode. A wide-range beam energy scan, including proton beams from 3 GeV up to 9.3 GeV (HIAF) and up to 32 GeV (upgraded HIAF), will be conducted to examine the dependence of polarization on collision energy. The spectrometer is designed with specialized detectors capable of high-precision reconstruction of final-state baryon polarizations. Among its many interesting and important measurements, H-NS will simultaneously measure hyperon and proton spin observables to explore the polarization mechanism in hadronic interactions and the spin structure of baryons. Furthermore, the use of $pA$ and $AA$ collisions will enable detailed investigations of cold and hot nuclear matter effects on spin polarization. Its physics program and detector development will significantly benefit the future Electron-ion Collider in China.

physics.ins-det↗

arXiv2025

Huizhou Hadron Spectrometer -- a Proposed High-rate Experimental Setup at the High Intensity Heavy-ion Accelerator Facility

The High-Intensity Heavy-Ion Accelerator Facility (HIAF), currently under construction in Huizhou, Guangdong Province, China, is projected to be completed by 2025. This facility will be capable of producing proton and heavy-ion beams with energies reaching several GeV, thereby offering a versatile platform for advanced fundamental physics research. Key scientific objectives include exploring physics beyond the Standard Model through the search for novel particles and interactions, testing fundamental symmetries, investigating exotic hadronic states such as di-baryons, pentaquark states and multi-strange hypernuclei, conducting precise measurements of hadron and hypernucleus properties, and probing the phase boundary and critical point of nuclear matter. To facilitate these investigations, we propose the development of a dedicated experimental apparatus at HIAF - the Huizhou Hadron Spectrometer (HHaS). This paper presents the conceptual design of HHaS, comprising a solenoid magnet, a five-dimensional silicon pixel tracker, a Low-Gain Avalanche Detector (LGAD) for time-of-flight measurements, and a Cherenkov-scintillation dual-readout electromagnetic calorimeter. The design anticipates an unprecedented event rate of 1-100 MHz, extensive particle acceptance, a track momentum resolution at 1% level, an electromagnetic energy resolution of ~3% @ 1 GeV and multi-particle identification capabilities. Such capabilities position HHaS as a powerful instrument for advancing experimental studies in particle and nuclear physics. The successful realization of HHaS is expected to significantly bolster the development of medium- and high-energy physics research within China.

hep-ex↗

arXiv2023

A Cooperative Content Dissemination Framework for Fog-Based Internet of Vehicles

As the fog-based internet of vehicles (IoV) is equipped with rich perception, computing, communication and storage resources, it provides a new solution for the bulk data processing. However, the impact caused by the mobility of vehicles brings a challenge to the content scheduling and resource allocation of content dissemination service. In this paper, we propose a time-varying resource relationship graph to model the intertwined impact of the perception, computation, communication and storage resources across multiple snapshots on the content dissemination process of IoV. Based on this graph model, the content dissemination process is modeled as a mathematical optimization problem, where the quality of service of both delay tolerant and delay sensitive services are considered. Owing to its NP-completeness, the optimization problem is decomposed into a joint link and subchannel scheduling subproblem and as well a joint power and flow control subproblem. Then, a cascaded low complexity scheduling algorithm is proposed for the joint link and subchannel scheduling subproblem. Moreover, a robust resource management algorithm is developed for the power and flow control subproblem, where the channel uncertainties in future snapshots are fully considered in the algorithm. Finally, we conduct simulations to show that the effectiveness of the proposed approaches outperforms other state-of-art approaches.

cs.NI↗

arXiv2021

Slippery Polymer Monoliths: Surface Functionalization with Ordered MoS2 Microparticle Arrays

Components of technical systems and devices often require self-lubricating properties, which are implemented by means of dry lubricants. However, continuous lubricant coatings on the components' surfaces often suffer from poor adhesion, delamination and crack propagation. The replacement of continuous coatings with dense ordered arrays of microparticles consisting of dry lubricants may overcome these drawbacks. Using the well-established solid lubricant MoS2 as model system, we demonstrate that the sliding capability of polymeric monoliths can be significantly enhanced by integration of arrays of micron-sized dry lubricant microparticles into their contact surfaces. To synthesize the MoS2 microparticle arrays, we first prepared ordered hexagonal arrays of ammonium tetrathiomolybdate (ATM) microparticles on Si wafers by molding against poly(dimethylsiloxane) templates followed by high-temperature conversion of the ATM microparticles into MoS2 microparticles under Ar/H2 atmosphere in the presence of elemental sulfur. Finally, the obtained large-scale hexagonal MoS2 microparticle arrays were transferred to the surfaces of polymer monoliths under conservation of the array ordering. Self-lubrication of components of technical systems by incorporation of dry lubricant microparticle arrays into their contact surfaces is an example for overcoming the drawbacks of continuous functional coatings by replacing them with microparticle arrays.

physics.app-ph↗

arXiv2019

Evaluation of 3D gold nanodendrite layers obtained by templated galvanic displacement reactions for SERS sensing and heterogeneous catalysis

Dense layers of overlapping three-dimensional (3D) gold nanodendrites characterized by high specific surfaces as well as by abundance of sharp edges and vertices creating high densities of SERS hotspots are promising substrates for SERS-based sensing and catalysis. We have evaluated to what extent structural features of 3D gold nanodendrite layers can be optimized by the initiation of 3D gold nanodendrite growth at gold particles rationally positioned on silicon wafers. For this purpose, galvanic displacement reactions yielding 3D gold nanodendrites were guided by hexagonal arrays of parent gold particles with a lattice constant of 1.5 micrometers obtained by solid-state dewetting of gold on topographically patterned silicon wafers. Initiation of the growth of dendritic features at edges of the gold particles resulted in the formation of 3D gold nanodendrites while limitation of dendritic growth to the substrate plane was prevented. The regular arrangement of the parent gold particles supported the formation of dense layers of overlapping 3D gold nanodendrites that were sufficiently homogeneous within the resolution limits of Raman microscopes. Consequently, SERS mapping experiments revealed a reasonable degree of uniformity. The proposed preparation algorithm comprises only bottom-up process steps that can be carried out without use of costly instrumentation.

physics.app-ph↗

arXiv2018

Free-sustaining Three-dimensional S235 Steel-based Porous Electrocatalyst for Highly Efficient and Durable Oxygen Evolution

A novel oxygen evolution reaction (OER) catalyst (3D S235-P steel) based on steel S235 substrate has been successfully prepared via a facile one-step surface modification. The standard Carbon Manganese steel was phosphorizated superficially leading to the formation of a unique 3D interconnected nanoporous surface with high specific area which facilitates the electrocatalytically initiated oxygen evolution reaction. The prepared 3D S235-P steel exhibits enhanced electrocatalytic OER activities in alkaline regime confirmed by a low overpotential ({\eta}=326 mV at j=10 mA cm-2) and a small Tafel slope of 68.7 mV dec-1. Moreover, the catalyst was found to be stable under long-term usage conditions functioning as oxygen evolving electrode at pH 13 as evidenced by the sufficient charge to oxygen conversion rate (Faradaic efficiency: 82.11% and 88.34% at 10 mA cm-2 and 5 mA cm-2, respectively). In addition, it turned out that the chosen surface modification renders steel S235 into an OER electrocatalyst sufficiently and stable to work in neutral pH condition. Our investigation revealed that the high catalytic activities are likely to stem from the generated Fe/(Mn) hydroxide/oxo-hydroxides generated during the OER process. The phosphorization treatment is therefore not only an efficient way to optimize the electrocatalytic performance of standard Carbon-Manganese steel, but also enables for the development of low cost and abundant steels in the field of energy conversion.

physics.chem-ph↗

arXiv2018

Steel-Based Electrocatalysts for Efficient and Durable Oxygen Evolution in Acidic Media

High overpotentials, particularly an issue of common anode materials, hamper the process of water electrolysis for clean energy generation. Thanks to immense research efforts up to date oxygen evolution electrocatalysts based on earth-abundant elements work efficiently and stably in neutral and alkaline regimes. However, non-noble metal-based anode materials that can withstand low pH regimes are considered to be an indispensable prerequisite for the water splitting to succeed in the future. All oxygen evolving electrodes working durably and actively in acids contain Ir at least as an additive. Due to its scarcity and high acquisition costs noble elements like Pt, Ru and Ir need to be replaced by earth abundant elements. We have evaluated a Ni containing stainless steel for use as an oxygen-forming electrode in diluted H2SO4. Unmodified Ni42 steel showed a significant weight loss after long term OER polarization experiments. Moreover, a substantial loss of the OER performance of the untreated steel specimen seen in linear sweep voltammetry measurements turned out to be a serious issue. However, upon anodization in LiOH, Ni42 alloy was rendered in OER electrocatalysts that exhibit under optimized synthesis conditions stable overpotentials down to 445 mV for 10 mA cm-2 current density at pH 0. Even more important: The resulting material has proven to be robust upon long-term usage (weight loss: 20 mug/mm2 after 50 ks of chronopotentiometry at pH 1) towards OER in H2SO4. Our results suggest that electrochemical oxidation of Ni42 steel in LiOH (sample Ni42Li205) results in the formation of a metal oxide containing outer zone that supports solution route-based oxygen evolution in acidic regime accompanied by a good stability of the catalyst.

physics.chem-ph↗

arXiv2018

Nanostructured submicron block copolymer dots by sacrificial stamping: a potential preconcentration platform for locally resolved sensing, chemistry and cellular interactions

Classical contact lithography involves patterning of surfaces by embossing or by transfer of ink. We report direct lithographic transfer of parts of sacrificial stamps onto counterpart surfaces. Using sacrificial stamps consisting of the block copolymer polystyrene-block-poly(2-pyridine) (PS-b-P2VP), we deposited arrays of nanostructured submicron PS-b-P2VP dots with heights of about 100 nm onto silicon wafers and glass slides. The sacrificial PS-b-P2VP stamps were topographically patterned with truncated-pyramidal contact elements and penetrated by spongy-continuous nanopore systems. The spongy nature of the sacrificial PS-b-P2VP stamps supported formation of adhesive contact to the counterpart surfaces and the rupture of the contact elements during stamp retraction. The submicron PS-b-P2VP dots generated by sacrificial stamping can be further functionalized, examples include loading submicron PS-b-P2VP dots with dyes and attachment of gold nanoparticles to their outer surfaces. The arrays of submicron PS-b-P2VP dots can be integrated into setups for advanced optical microscopy, total internal reflection fluorescence microscopy or Raman microscopy. Arrays of nanostructured submicron block copolymer dots may represent a preconcentration platform for locally resolved sensing and locally resolved monitoring of cellular interactions or might be used as microreactor arrays in lab-on-chip configurations.

physics.app-ph↗

arXiv2018

Ordered topographically patterned silicon by insect-inspired capillary submicron stamping

Insect-inspired capillary submicron stamping and subsequent surface-limited metal-assisted chemical etching (MACE) with ammonium bifluoride as HF source is employed for high-throughput production of ordered topographically patterned silicon (tpSi). Insect feet often possess hairy contact elements through which adhesive secretion is deployed. Thus, arrays of adhesive secretion drops remain as footprints on contact surfaces. Stamps for insect-inspired capillary submicron stamping having surfaces topographically patterned with contact elements mimic the functional principles of such insect feet. They contain spongy continuous nanopore networks penetrating the entire stamps. Any ink (organic, aqueous) may be supplied from the backside of the nanoporous stamps to the contact elements. We generated ordered arrays of AgNO3 dots extending mm^2 on Si by manual stamping with cycle times of a few seconds under ambient conditions; at higher load ordered holey AgNO3 films were obtained. Surface-limited MACE correspondingly yielded either macroporous tpSi or Si pillar arrays. Inkjet printing of polymer solutions onto tpSi yielded patterns of polymer blots conformally covering the tpSi. Such blot patterns could potentially represent a starting point for the development of persistent and scratch-resistant identity labels or QR codes on silicon surfaces.

physics.app-ph↗

arXiv2015

Power vs. Spectrum 2-D Sensing in Energy Harvesting Cognitive Radio Networks

Energy harvester based cognitive radio is a promising solution to address the shortage of both spectrum and energy. Since the spectrum access and power consumption patterns are interdependent, and the power value harvested from certain environmental sources are spatially correlated, the new power dimension could provide additional information to enhance the spectrum sensing accuracy. In this paper, the Markovian behavior of the primary users is considered, based on which we adopt a hidden input Markov model to specify the primary vs. secondary dynamics in the system. Accordingly, we propose a 2-D spectrum and power (harvested) sensing scheme to improve the primary user detection performance, which is also capable of estimating the primary transmit power level. Theoretical and simulated results demonstrate the effectiveness of the proposed scheme, in term of the performance gain achieved by considering the new power dimension. To the best of our knowledge, this is the first work to jointly consider the spectrum and power dimensions for the cognitive primary user detection problem.

cs.IT↗

arXiv2014

Cognitive Learning of Statistical Primary Patterns via Bayesian Network

In cognitive radio (CR) technology, the trend of sensing is no longer to only detect the presence of active primary users. A large number of applications demand for more comprehensive knowledge on primary user behaviors in spatial, temporal, and frequency domains. To satisfy such requirements, we study the statistical relationship among primary users by introducing a Bayesian network (BN) based framework. How to learn such a BN structure is a long standing issue, not fully understood even in the statistical learning community. Besides, another key problem in this learning scenario is that the CR has to identify how many variables are in the BN, which is usually considered as prior knowledge in statistical learning applications. To solve such two issues simultaneously, this paper proposes a BN structure learning scheme consisting of an efficient structure learning algorithm and a blind variable identification scheme. The proposed approach incurs significantly lower computational complexity compared with previous ones, and is capable of determining the structure without assuming much prior knowledge about variables. With this result, cognitive users could efficiently understand the statistical pattern of primary networks, such that more efficient cognitive protocols could be designed across different network layers.

cs.LG↗

arXiv2011

On the Performance of Cooperative Spectrum Sensing under Quantization

In cognitive radio, the cooperative spectrum sensing (CSS) plays a key role in determining the performance of secondary networks. However, there have not been feasible approaches that can analytically calculate the performance of CSS with regard to the multi-level quantization. In this paper, we not only show the cooperative false alarm probability and cooperative detection probability impacted by quantization, but also formulate them by two closed form expressions. These two expressions enable the calculation of cooperative false alarm probability and cooperative detection probability tractable efficiently, and provide a feasible approach for optimization of sensing performance. Additionally, to facilitate this calculation, we derive Normal approximation for evaluating the sensing performance conveniently. Furthermore, two optimization methods are proposed to achieve the high sensing performance under quantization.

cs.IT↗