arXiv subjects

Shaoyi Xu

Publications and source records attributed to Shaoyi Xu.

12 recordsLinked to original sources

arXiv2026

Molecular chiral discrimination through symmetry-breaking spin dynamics

Molecular chirality plays a crucial role in physics, chemistry, life sciences and pharmacology. Nowadays, the chiral discrimination and control at the single-molecule level is urgently needed to reveal the origin of the chirality-relevant phenomena by recovering the information disturbed by the ensemble averaging. The method of magnetic resonance (MR), as one of powerful tools for structure analysis, is blind to the molecular chirality in the absence of a chiral reagent. Here we propose and experimentally demonstrate a direct MR-based method for determining the chirality at the single-molecule level through constructing the symmetry-breaking dynamics of nearby nuclear spins. In principle, the mirror asymmetry of two enantiomers in real space is manifested by breaking the joint symmetry of the mirror reflection and time reversal in spin space under spin dynamics. Experimentally, two enantiomers are indistinguishable from the dynamics of strongly-coupled but unpolarized nuclear spins, but diverge evidently in the dynamical results that break the field-inversion symmetry after spins are polarized. Our method and results will benefit the study of chirality-induced properties in the fields of chemistry and biology.

quant-ph↗

arXiv2026

LEO-NA Walker Constellation Design with Bi-objective Optimisation Approaches

Low Earth Orbit (LEO) constellation design for navigation augmentation (NA) has attracted increasing attention in navigation satellite system studies, yet balancing navigation performance and deployment cost remains a fundamental challenge. To address this issue, this paper proposes a bi-objective optimization framework for LEO Walker constellation design. The problem is formulated as a bi-objective optimization model with constellation cost and positioning accuracy as objectives. In the formulation, PDOP tail risk and satellite visibility are incorporated into the objective formulation to better characterize navigation performance. The Pareto-optimal solution set isobtained using the Non-dominated Sorting Genetic Algorithm II (NSGA-II). Simulation results show that, under the same satellite deployment cost, the proposed LEO-NA Walker constellation improves the average number of visible satellites by 42.5% and 24.4%, and reduces the mean PDOP by 18.9% and 10.5% compared with representative Polar and optimized-LFC constellations, respectively, thereby enhancing service continuity and resource utilization efficiency. These results provide useful guidance for the design and deployment of LEO-NA constellations.

eess.SY↗

arXiv2026

JARVIS: An Evidence-Grounded Retrieval System for Interpretable Deceptive Reviews Adjudication

Deceptive reviews, refer to fabricated feedback designed to artificially manipulate the perceived quality of products. Within modern e-commerce ecosystems, these reviews remain a critical governance challenge. Despite advances in review-level and graph-based detection methods, two pivotal limitations remain: inadequate generalization and lack of interpretability. To address these challenges, we propose JARVIS, a framework providing Judgment via Augmented Retrieval and eVIdence graph Structures. Starting from the review to be evaluated, it retrieves semantically similar evidence via hybrid dense-sparse multimodal retrieval, expands relational signals through shared entities, and constructs a heterogeneous evidence graph. Large language model then performs evidence-grounded adjudication to produce interpretable risk assessments. Offline experiments demonstrate that JARVIS enhances performance on our constructed review dataset, achieving a precision increase from 0.953 to 0.988 and a recall boost from 0.830 to 0.901. In the production environment, our framework achieves a 27% increase in the recall volume and reduces manual inspection time by 75%. Furthermore, the adoption rate of the model-generated analysis reaches 96.4%.

cs.IR↗

arXiv2025

Single-cell identification with quantum-enhanced nuclear magnetic resonance

Identification of individual cells within heterogeneous populations is essential for biomedical research and clinical diagnostics. Conventional labeling-based sorting methods, such as fluorescence-activated cell sorting and magnetic-activated cell sorting, enable precise sorting when reliable markers are available. However, their applicability is limited in cells lacking defined markers or sensitive to labeling, as labeling can compromise cellular viability and function. We present a single-cell identification approach using quantum-enhanced NMR with diamond nitrogen-vacancy centers for label-free detection of intracellular proton ($^1$H) signals. Using this method, we distinguish two human tumor cell lines by their proton spin-lattice ($T_1$) relaxation times, which serve as a cell-intrinsic physicochemical signature. It lays the groundwork for label-free sorting applications in rare cell analysis, personalized medicine, and single-cell diagnostics.

quant-ph↗

arXiv2025

SHERLOCK: Towards Dynamic Knowledge Adaptation in LLM-enhanced E-commerce Risk Management

Effective e-commerce risk management requires in-depth case investigations to identify emerging fraud patterns in highly adversarial environments. However, manual investigation typically requires analyzing the associations and couplings among multi-source heterogeneous data, a labor-intensive process that limits efficiency. While Large Language Models (LLMs) show promise in automating these analyses, their deployment is hindered by the complexity of risk scenarios and the sparsity of long-tail domain knowledge. To address these challenges, we propose Sherlock, a framework that integrates structured domain knowledge with LLM-based reasoning through three core modules. First, we construct a domain Knowledge Base (KB) by distilling structured expertise from heterogeneous knowledge sources. Second, we design a two-stage retrieval-augmented generation strategy tailored for case investigation, which combines input contextual augmentation with a Reflect & Refine module to fully leverage the KB for improved analysis quality. Finally, we develop an integrated platform for operations and annotation to drive a self-evolving data flywheel. By combining real-time hotfixes through KB updates with periodic logic alignment via post-training, we facilitate continuous system evolution to counteract adversarial drifts. Online A/B tests at JD dot com demonstrate that Sherlock achieves an 82% Expert Acceptance Rate (EAR) and a 386.7% increase in daily investigation throughput. An additional 90-day evaluation shows that the flywheel successfully recovers from performance decay caused by changing tactics twice, raising the EAR ceiling by around 3.5% through autonomous model updates.

cs.IR↗

arXiv2024

Delay Performance Analysis of Delay-Deterministic Wireless Networks with Infinite and Finite Blocklength Transmission

In order to achieve stable and reliable industrial manufacturing, wireless networks must meet the stringent communication requirements of industrial automation, particularly the need for deterministic low latency communication. The limited wireless resources and time-varying fading channel contribute to the random fluctuations of transmission delay, making it challenging to realize delay-deterministic wireless networks. An open challenge in this context is to model delay determinism, also known as jitter, and analyze delay performance. In this paper, we model jitter as the variance of delay and conduct a comprehensive analysis of delay performance. Specifically, we consider two transmission regimes: infinite blocklength (IBL) and finite blocklength (FBL). In the IBL regime, the distribution of the transmission delay is analyzed, and the closed-form expressions for the average delay, jitter, and delay violation probability are derived. In the FBL regime, an upper bound on the transmission delay is first approximated at a high signalto-noise ratio. Based on this upper bound, the delay distribution, delay violation probability, average delay, and jitter are derived. Finally, simulation results are provided to validate the accuracy of the analysis and derivations. Additionally, the impact of system parameters on jitter is analyzed to gain further insights.

math.OC↗

arXiv2023

Sensing orbital hybridization of graphene-diamond interface with a single spin

Interfacial interactions are crucial in a variety of fields and can greatly affect the electric, magnetic, and chemical properties of materials. Among them, interface orbital hybridization plays a fundamental role in the properties of surface electrons such as dispersion, interaction, and ground states. Conventional measurements of electronic states at interfaces such as scanning tunneling microscopes are all based on electric interactions which, however, suffer from strong perturbation on these electrons. Here we unveil a new experimental detection of interface electrons based on the weak magnetic interactions between them and the nitrogen-vacancy (NV) center in diamond. With negligible perturbation on the interface electrons, their physical properties can be revealed by the NV spin coherence time. In our system, the interface interaction leads to significant decreases in both the density and coherence time of the electron spins at the diamond-graphene interface. Furthermore, together with electron spin resonance spectra and first-principle calculations, we can retrieve the effect of interface electron orbital hybridization. Our study opens a new pathway toward the microscopic probing of interfacial electronic states with weak magnetic interactions and provides a new avenue for future research on material interfaces.

quant-ph↗

arXiv2022

Sub-nanotesla Sensitivity at the Nanoscale with a Single Spin

High-sensitivity detection of microscopic magnetic field is essential in many fields. Good sensitivity and high spatial resolution are mutually contradictory in measurement, which is quantified by the energy resolution limit (ERL). Here we report that a sensitivity of 0.5 ${\bf{nT/\sqrt{Hz}}}$ at the nanoscale is achieved experimentally by using nitrogen-vacancy defects in diamond with depths of tens of nanometers. The achieved sensitivity is substantially enhanced by integrating with multiple quantum techniques, including real-time-feedback initialization, dynamical decoupling with shaped pulses, repetitive readout via quantum logic. Our magnetic sensors will shed new light on searching new physics beyond the standard model, investigating microscopic magnetic phenomena in condensed matters, and detection of life activities at the sub-cellular scale.

quant-ph↗

arXiv2022

99.92%-Fidelity CNOT Gates in Solids by Filtering Time-dependent and Quantum Noises

Inevitable interactions with the reservoir largely degrade the performance of non-local gates, which hinders practical quantum computation from coming into existence. Here we experimentally demonstrate a 99.920(7)\%-fidelity controlled-NOT gate by suppressing the complicated noise in a solid-state spin system at room temperature. We found that the fidelity limited at 99\% in previous works results from only considering static noise, and thus, in this work, time-dependent noise and quantum noise are also included. All noises are dynamically corrected by an exquisitely designed shaped pulse, giving the resulting error below $10^{-4}$. The residual gate error is mainly originated from the longitudinal relaxation and the waveform distortion that can both be further reduced technically. Our noise-resistant method is universal, and will benefit other solid-state spin systems.

quant-ph↗

arXiv2022

Temperature-dependent behaviors of single spin defects in solids determined with Hz-level precision

Revealing the properties of single spin defects in solids is essential for quantum applications based on solid-state systems. However, it is intractable to investigate the temperature-dependent properties of single defects, due to the low precision for single-defect measurements in contrast to defect ensembles. Here we report that the temperature dependence of the Hamiltonian parameters for single negatively charged nitrogen-vacancy (NV$^{-}$) centers in diamond is precisely measured, and the results find a reasonable agreement with first-principles calculations. Particularly, the hyperfine interactions with randomly distributed $^{13}$C nuclear spins are clearly observed to vary with temperature, and the relevant coefficients are measured with Hz-level precision. The temperature-dependent behaviors are attributed to both thermal expansion and lattice vibrations by first-principles calculations. Our results pave the way for taking nuclear spins as more stable thermometers at nanoscale. The methods developed here for high-precision measurements and first-principles calculations can be further extended to other solid-state spin defects.

quant-ph↗

arXiv2022

Observation of Floquet topological phases with large Chern numbers

One of the most intriguing advantage of Floquet engineering is to generate new phases with large topological invariants. In this work, we experimentally simulate a periodically quenched generalized Haldane model on an NV center in diamond, and observe its Floquet Chern insulator phases with Chern numbers $C=1,2,4$ by imaging the static and dynamic spin textures in momentum space. Our work reveals the power of Floquet driving in transforming system's topology and generating large Chern number phases. It further establishes a unique experimental scheme to detect Floquet topological phases in two and higher spatial dimensions.

quant-ph↗

arXiv2021

Beating the Standard Quantum Limit under Ambient Conditions with Solid-State Spins

Precision measurement plays a crucial role in all fields of science. The use of entangled sensors in quantum metrology improves the precision limit from the standard quantum limit (SQL) to the Heisenberg limit (HL). To date, most experiments beating the SQL are performed on the sensors which are well isolated under extreme conditions. However, it has not been realized in solid-state spin systems at ambient conditions, owing to its intrinsic complexity for the preparation and survival of pure and entangled quantum states. Here we show a full interferometer sequence beating the SQL by employing a hybrid multi-spin system, namely the nitrogen-vacancy (NV) defect in diamond. The interferometer sequence starts from a deterministic and joint initialization, undergoes entanglement and disentanglement of multiple spins, and ends up with projective measurement. In particular, the deterministic and joint initialization of NV negative state, NV electron spin, and two nuclear spins is realized at room temperature for the first time. By means of optimal control, non-local gates are implemented with an estimated fidelity above the threshold for fault-tolerant quantum computation. With these techniques combined, we achieve two-spin interference with a phase sensitivity of 1.79 \pm 0.06 dB beyond the SQL and three-spin 2.77 \pm 0.10 dB. Moreover, the deviations from the HL induced by experimental imperfections are completely accountable. The techniques used here are of fundamental importance for quantum sensing and computing, and naturally applicable to other solid-state spin systems.

quant-ph↗