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Jianguo Wang

Publications and source records attributed to Jianguo Wang.

At least 19 recordsLinked to original sources
arXiv2026

Aerodynamic Prior-Free Coordinated Trajectory Generation and Tracking Control for a Tail-Sitter UAV

This paper presents a coordinated trajectory generation and tracking control framework for a tail-sitter unmanned aerial vehicle (UAV), which does not require aerodynamic priors identified for a specific airframe while addressing the challenge of flight control under highly nonlinear aerodynamics across the full flight envelope. The core innovation lies in employing phase-specific aerodynamic modeling strategies for planning and tracking, tailored to their distinct functional characteristics, without requiring airframe-specific aerodynamic priors. Specifically, the phi-theory model under coordinated flight is employed to derive an analytic differential flatness mapping, and a simplified but locally accurate model is established for predictive control to enable real-time aerodynamic parameter estimation. The proposed framework is evaluated extensively through both simulation and challenging real-world flight tests under mild wind conditions, showing high-precision tracking and adaptability across the tested aerodynamic conditions. To the best of our knowledge, this is the first real-world demonstration of accurate trajectory tracking over tested flight regimes spanning the full envelope of a tail-sitter UAV without relying on aerodynamic identification campaigns. The source code of our framework is available at: https://github.com/SYSU-HILAB/AP-PnC.

cs.RO↗
arXiv2026

Git4Data: Database-Native Version Control for AI Agents

Large Language Model (LLM) agents increasingly explore many candidate states of relational data in parallel, each of which should remain isolated, reproducible, and auditable, preferably through the same SQL interface used for ordinary data work. Existing tools support this requirement only partially: source-code version control does not scale to large datasets, whereas relational databases manage large data efficiently but rarely expose native branching, comparison, and merging. We present Git4Data, a database-native version-control layer for agentic workflows. Git4Data treats a database as a repository and a table as a versioned object, exposing Git-style operations (snapshot/tag, branch, diff, and merge with explicit conflict-resolution policies) through SQL extensions. Implemented in MatrixOne, a cloud-native relational database, Git4Data leverages immutable object storage and MVCC to make the cost of these operations proportional to the size of the change rather than the size of the data. On the BranchBench agentic branching workloads, Git4Data outperforms DoltDB by up to an order of magnitude. Overall, we believe this work sheds light on how relational databases can better support AI agents through efficient versioning.

cs.DB↗
arXiv2026

The Reverse Big Push: Generative AI and Self-Fulfilling Automation

Generative AI relocates the fixed cost of automation. A model provider pays to train a frontier system, while a downstream firm rents capability by usage; the same firm must carry a continuing payroll to supply a human-augmented service. We study this asymmetry in a local service economy with household budgets and a market-clearing wage. Human augmentation earns a larger surplus from an additional customer, whereas automation has the lower break-even scale. Payroll supports demand across sectors. Wage adjustment works against this feedback but does not generally undo it: when the wage-income effect dominates the fall in the wage bill per retained worker, production modes are strategic complements. The economy can then possess both a high-demand human-augmented equilibrium and a low-demand automated equilibrium. The former is the local first best, even when flexible wages prevent a firm-profit ranking. With forward-looking firms and staggered revision opportunities, the same inherited employment structure can support an automation cascade or an augmentation recovery; the anticipated path of later adopters validates the first movers' choices. Under the regularity and boundary conditions of Frankel and Pauzner, a public aggregate shock selects a unique state-contingent path, while the vanishing-friction limit selects according to risk dominance. A transparent parameterization anchored to professional-services revenue-to-payroll ratios illustrates how high-autonomy uses can enter the coordination region and how wage adjustment compresses that region. Optimal policy combines the adoption wedge created by demand spillovers with a temporary bridge when the low state is locally self-sustaining.

econ.TH↗
arXiv2026

Building An Integrated Vector Database System in PostgreSQL

This paper presents PostgreSQL-V 2.0, a scalable integrated vector database system inside PostgreSQL. Existing PostgreSQL-based vector search systems such as pgvector embed vector indexes into PostgreSQL's page-oriented storage engine, incurring significant overhead that leads to a huge performance gap with specialized vector databases. In our earlier work, we introduced PostgreSQL-V 1.0, which addresses this issue by separating vector index structures from PostgreSQL's storage engine, enabling vector search performance close to that of native vector index libraries while preserving SQL compatibility. However, we find that PostgreSQL-V 1.0 has three limitations that matter for real-world workloads: it only supports a single connection (without concurrency), recovery time grows with index size, and physical replication is unsupported. We further present PostgreSQL-V 2.0, which closes all three gaps. PostgreSQL-V 2.0's concurrency support enables fully concurrent vector searches and updates across PostgreSQL's multi-process backends, delivering up to 36.4x the throughput of PostgreSQL-V 1.0 while serving 32 concurrent clients. PostgreSQL-V 2.0's fast crash recovery keeps cost independent of total index size, remaining near 20 ms while PostgreSQL-V 1.0's grows into seconds-scale. PostgreSQL-V 2.0's physical replication support extends physical replication to the decoupled index, preserving index consistency on standbys without burdening the primary node. Together, these advances make PostgreSQL-V 2.0 a fully concurrent, crash-resilient, and replication-ready vector database inside PostgreSQL.

cs.DB↗
arXiv2026

RVANNS: Mixed-Precision Indexing and Locality-Aware Graph Traversal on RISC-V

Approximate nearest neighbor search (ANNS) on CPUs is increasingly constrained by candidate-vector movement and decoding rather than peak arithmetic throughput. Although the RISC-V Vector Extension (RVV) provides vector-length-agnostic execution and LMUL-based register grouping, generic low-precision decoding still incurs conversion overhead, while irregular graph traversal generates scattered accesses that degrade cache locality and memory-level parallelism. We present RVANNS, an RVV-oriented ANNS engine that jointly optimizes vector representation and graph locality. Its Mixed-Precision Multi-Layer Index (MPMI) represents each vector with a dense 8-bit affine base and sparse FP16/FP32 residuals, fusing reconstruction with distance accumulation and aligning widening with LMUL-sized register groups. ROrder co-locates likely co-visited graph nodes and sorts remapped adjacency lists, transforming scattered payload probes into denser, predominantly forward-moving address streams. Integrated into Milvus, RVANNS achieves 3.39x and 4.94x speedups over scalar execution on real 128-bit and 256-bit RVV processors, respectively. Under controlled HNSW configurations, it improves throughput by 2.27--2.76x over RVV SIMD+FP32 and by 1.18--1.59x over the corresponding AVX-512 and SVE baselines. On Cohere10M, it further delivers 1.82--2.27x higher QPS/W than the evaluated GPU baselines.

cs.IR↗
arXiv2026

Plasma screening and configuration interaction effects induced large enhancement on L-shell photoionization cross sections and opacity

An opacity model that incorporates improved treatments of both plasma screening and configuration interaction (CI) effects is proposed, and a 25-30% enhancement on the iron L-shell opacity is predicted at solar interior temperatures. It is originated from the plasma screening induced 14-17% enhancement on the photoionization cross sections and the CI induced 10-20% enhancement on photoexcitation and photoionization cross sections for open L-shell ions. These explain the long-standing discrepancy between theoretical and experimental iron opacity [Nature 517, 56], and the relatively weaker enhancements on chromium and nickel opacity [Phys. Rev. Lett. 122, 235001] due to the sensitivity of these effects to the different L-shell electron population and plasma temperature/density. This letter provides the systematic interpretation of L-shell opacity measurements at solar interior temperatures, and advances the accurate simulation of opacity and radiative transport in high-energy-density plasma.

physics.atom-ph↗
arXiv2026

Causal Inference under Kink Bunching

Kinked policies change marginal incentives at a threshold, and agents respond by adjusting the assignment variable that determines their treatment. The bunching literature uses this response to estimate the elasticity of the assignment variable; policymakers often care about effects on other outcomes. We develop a framework for estimating causal effects of kinked policies on outcomes beyond the assignment variable when agents can fully manipulate it. Average effects are defined for two affected populations: bunchers, who locate at the kink, and shifters, who reduce their assignment values but remain above the threshold; shifter effects compare equal-mass intervals and require only rank invariance. Because a single kink identifies neither the counterfactual assignment density nor the counterfactual outcome function, identification is design-assisted: placebo groups and moving thresholds discipline the local shape of both objects, the focal group's unaffected observations pin down level and slope differences, and the restrictions are testable. Applying the framework to a kinked coinsurance schedule in China's medical insurance, we find that the loss of reimbursement above the annual cap sharply reduces outpatient visits, raises cost per visit, and shifts the composition of care toward hospitals -- effects that are invisible in a density-only bunching analysis.

econ.EM↗
arXiv2026

Radio and X-ray flux rebrightening six years after outburst in a partially-obscured extreme changing-look AGN

SDSS J1548+2208 is a unique partially-obscured nuclear transient that exhibits multiwavelength outbursts in mid-infrared, X-ray and radio. We present the results from multiwavelength photometric and spectroscopic follow-up observations with a time span of ~2500 days since its discovery. We find that the mid-infrared and X-ray emission (with a hard X-ray spectrum) are still in a high flux level relative to the pre-flare state, suggesting a sudden increased, and possibly long-sustained accreting activity from central black hole. This is supported by the slowly-evolving high-ionization coronal lines. The mid-infrared color turns blue slowly in the rising phase, which is distinct from stellar tidal disruption events (TDEs). All these properties point to the origin of outbursts from an extreme changing-look AGN and the scenario with a normal TDE seems disfavored. The radio spectral energy distribution (SED) in ~0.65-15 GHz is unusual, displaying a double-peak feature with distinct variability characteristics. In addition, we find evidence for the late-time radio rebrightening more than six years since the initial outburst, as well as a possibly new X-ray flare, though the significance for the latter is not high. The peculiar radio flux and SED evolution could be explained by a nascent outflow expanding into and shocking circumnuclear diffuse medium filled by denser clouds. In this case, SDSS J1548+2208 represents a rare changing-look AGN which can launch radio outflows. Continued multiwavelength observations are required to map the dust and gas distribution on pc-scales, providing new insights into the environmental properties that could regulate AGN changing-look phenomenon.

astro-ph.HE↗
arXiv2026

A Radio Changing-state Jet in the Narrow-line Seyfert 1 Galaxy J1105+1452

We report the discovery of a radio-quiet to radio-loud transition in the narrow-line Seyfert 1 galaxy J1105+1452. The source has undergone a long-term evolution from a radio-quiet state in the 1990s to a persistently radio-bright state after 2017. Post-2017 flux densities in the $0.8$-$7$ GHz range cluster between $32$ and $43$ mJy, whereas the $144$ MHz flux density is only $1.94 \pm 0.23$ mJy. This indicates strong low-frequency suppression from a compact, absorbed component. Modeling the radio spectral energy distribution with a synchrotron self-absorption model yields a turnover frequency $ν_{\rm p} = 0.48 \pm 0.03$ GHz and a peak flux density $S_{\rm p} = 38.9 \pm 4.7$ mJy. These parameters classify J1105+1452 as a megahertz peaked-spectrum source, consistent with the new episode of an early-stage compact jet. Under the assumption of equipartition, we derive an intrinsic physical radius $R \sim 0.68$ pc and an average apparent expansion velocity $β_{\rm app} \approx 0.64$. The observed brightness temperature $T_b \approx 6.0 \times 10^{11}$ K necessitates a Doppler factor $δ\approx 12$, implying a relativistic jet viewed at $θ\lesssim 5^\circ$. Despite the dramatic radio evolution, the X-ray spectrum remains stable and steep ($Γ\simeq 3.0$), suggesting that the X-ray emission remains dominated by the disk-corona, while the radio band has become jet-dominated. Our results identify J1105+1452 as a rare radio changing-state NLSy1, providing a unique laboratory for studying the birth and early evolution of relativistic jets at high Eddington ratios.

astro-ph.HE↗
arXiv2026

WAter: A Workload-Adaptive Knob Tuning System based on Workload Compression

Selecting appropriate values for the configurable parameters of Database Management Systems (DBMS) to improve performance is a significant challenge. Recent machine learning (ML)-based tuning systems have shown strong potential, but their practical adoption is often limited by the high tuning cost. This cost arises from two main factors: (1) the system needs to evaluate a large number of configurations to identify a satisfactory one, and (2) for each configuration, the system must execute the entire target workload on the DBMS, which is both time-consuming. Existing studies have primarily addressed the first factor by improving sample efficiency, that is, by reducing the number of configurations evaluated. However, the second factor, improving runtime efficiency by reducing the time required for each evaluation, has received limited attention and remains an underexplored direction. We develop WAter, a runtime-efficient and workload-adaptive tuning system that finds near-optimal configurations at a fraction of the tuning cost compared with state-of-the-art methods. We divide the tuning process into multiple time slices and evaluate only a small subset of queries from the workload in each slice. Different subsets are evaluated across slices, and a runtime profile is used to dynamically identify more representative subsets for evaluation in subsequent slices. At the end of each time slice, the most promising configurations are evaluated on the original workload to measure their actual performance. Evaluations demonstrate that WAter identifies the best-performing configurations with up to 73.5% less tuning time and achieves up to 16.2% higher performance than the best-performing alternative.

cs.DB↗
arXiv2026

Dielectric response and structural properties of finite-temperature electron liquids

The dielectric response and structural properties of finite-temperature electron liquids are central to accurately describing the physical behavior of electronic systems. This study presents a robust analytical model for the static structure factor of the uniform electron gas, combining physically motivated form for the static structure factor with constraints derived from high-accuracy path integral Monte Carlo simulations. The model accurately reproduces key features of the static structure factor across a broad range of temperatures and densities. Using this static structure factor, the density response function is directly evaluated, enabling a self-consistent definition of the static local field correction. As practical applications, the model is employed to investigate the low-velocity stopping power and the electron-ion friction coefficient. Results derived for the friction coefficient show good agreement with simulation data at moderate coupling and degeneracy. The proposed approach provides a computationally efficient and reliable method for characterizing the static response properties of correlated electron systems, facilitating improved simulations of energy deposition and ionic transport in warm dense matter and other strongly coupled quantum plasmas.

physics.plasm-ph↗
arXiv2026

O^3-LSM: Maximizing Disaggregated LSM Write Performance via Three-Layer Offloading

Log-Structured Merge-tree-based Key-Value Stores (LSM-KVS) have been optimized and redesigned for disaggregated storage via techniques such as compaction offloading to reduce the network I/Os between compute and storage. However, the constrained memory space and slow flush at the compute node severely limit the overall write throughput of existing optimizations. In this paper, we propose O3-LSM, a fundamental new LSM-KVS architecture, that leverages the shared Disaggregated Memory (DM) to support a three-layer offloading, i.e., memtable Offloading, flush Offloading, and the existing compaction Offloading. Compared to the existing disaggregated LSM-KVS with compaction offloading only, O3-LSM maximizes the write performance by addressing the above issues. O3-LSM first leverages a novel DM-Optimized Memtable to achieve dynamic memtable offloading, which extends the write buffer while enabling fast, asynchronous, and parallel memtable transmission. Second, we propose Collaborative Flush Offloading that decouples the flush control plane from execution and supports memtable flush offloading at any node with dedicated scheduling and global optimizations. Third, O3-LSM is further improved with the Shard-Level Optimization, which partitions the memtable into shards based on disjoint key-ranges that can be transferred and flushed independently, unlocking parallelism across shards. Besides, to mitigate slow lookups in the disaggregated setting, O3-LSM also employs an adaptive Cache-Enhanced Read Delegation mechanism to combine a compact local cache with DM-assisted memtable delegated read. Our evaluation shows that O3-LSM achieves up to 4.5X write, 5.2X range query, and 1.8X point lookup throughput improvement, and up to 76% P99 latency reduction compared with Disaggregated-RocksDB, CaaS-LSM, and Nova-LSM.

cs.DB↗
arXiv2026

GraphLake: A Purpose-Built Graph Compute Engine for Lakehouse

In this paper, we introduce GraphLake, a purpose-built graph compute engine for Lakehouse. GraphLake is built on top of the commercial graph database TigerGraph. It maps Lakehouse tables to vertex and edge types in a labeled property graph and supports graph analytics over Lakehouse tables using GSQL. To minimize startup time, it loads only the graph topology. Furthermore, it introduces a series of techniques to ensure query efficiency over Lakehouse tables, including a graph-aware caching mechanism and two Lakehouse-optimized parallel primitives. Extensive experiments demonstrate that GraphLake significantly outperforms PuppyGraph, the current state-of-the-art graph compute engine for Lakehouse, by achieving both lower startup and query time.

cs.DB↗
arXiv2026

Multiple charge transfer driven complex reaction dynamics: covalent bonding meets van der Waals interactions

Ultrafast charge transfer (CT) processes redistribute electronic charge within and between molecular units and play a central role in many physical, chemical, and biological phenomena. However, the microscopic pathways of multiple CT events, including the coupled structural evolution and energy redistribution, are challenging to disentangle experimentally in complex systems. To obtain controlled insight into such dynamics, well-defined properties are required. Here, we investigate the N2Ar dimer, which combines a covalent bond with a weak van der Waals interaction, using site-selective synchrotron photoionization and coincident detection of electrons and ions. Combined with ab initio calculations, this approach enables step-by-step tracking of ultrafast CT and fragmentation dynamics. We find that the dimer's structural evolution triggers a second CT event, opening complex reaction pathways in which electrons are transferred back and forth between Ar and N2, through two nonadiabatic transitions involving conical intersections. These results demonstrate that sequential multiple CT-induced transitions, even in a simple dimer, provide controlled insight into nonadiabatic reaction mechanisms relevant to complex systems.

physics.chem-ph↗
arXiv2026

Dust-obscured radio-emitting tidal disruption event coincident with a high-energy neutrino event

Despite the growing number of high-energy neutrinos (TeV-PeV) detected by IceCube, their astrophysical origins remain largely unidentified. Recent observations have linked a few tidal disruption events (TDEs) to the production of high-energy neutrino emission, all of which display dust-reprocessed infrared flares, indicating a dust- and gas-rich environment. By cross-matching the neutrino events and a sample of mid-infrared outbursts in nearby galaxies with transient radio flares, we uncover an optically obscured TDE candidate, SDSS J151345.75 $+$ 311125.2, which shows both spatial and temporal coincidence with the sub-PeV neutrino event IC170514B. Using a standard equipartition analysis of the synchrotron spectral evolution spanning 605 days post mid-infrared discovery, we find a little evolution in the radio-emitting region, with a kinetic energy up to $10^{51}$ erg, depending on the outflow geometry and shock acceleration efficiency assumed. High-resolution European VLBI Network imaging reveals a compact radio emission that is unresolved at a scale of $<$ 2.1 pc, with a brightness temperature of $T_b>5\times10^6$ K, suggesting that the observed late-time radio emission might originate from the interaction between a decelerating outflow and a dense circumnuclear medium. If the association is genuine, the neutrino production is possibly related to the acceleration of protons through pp collisions during the outflow expanding process, implying that the outflow-cloud interaction could provide a physical site with a high-density environment for producing the sub-PeV neutrinos. Such a scenario can be tested with future identifications of radio transients coincident with high-energy neutrinos.

astro-ph.HE↗
arXiv2026

QUITE: A Query Rewrite System Beyond Rules with LLM Agents

Query rewrite transforms SQL queries into semantically equivalent forms that run more efficiently. Existing approaches mainly rely on predefined rewrite rules, but they handle a limited subset of queries and can cause performance regressions. This limitation stems from three challenges of rule-based query rewrite: (1) it is hard to discover and verify new rules, (2) fixed rewrite rules do not generalize to new query patterns, and (3) some rewrite techniques cannot be expressed as fixed rules. Motivated by the fact that human experts exhibit significantly better rewrite ability but suffer from scalability, and Large Language Models (LLMs) have demonstrated nearly human-level semantic and reasoning abilities, we propose a new approach of using LLMs to rewrite SQL queries beyond rules. Due to the hallucination problems in LLMs, directly applying LLMs often leads to nonequivalent and suboptimal queries. To address this issue, we propose QUITE (query rewrite), a training-free and feedback-aware system based on LLM agents that rewrites SQL queries into semantically equivalent forms with significantly better performance, covering a broader range of query patterns and rewrite strategies compared to rule-based methods. Firstly, we design a multi-agent framework controlled by a finite state machine (FSM) to equip LLMs with the ability to use external tools and enhance the rewrite process with real-time database feedback. Secondly, we develop a rewrite middleware to enhance the ability of LLMs to generate optimized query equivalents. Finally, we employ a novel hint injection technique to improve execution plans for rewritten queries. Extensive experiments show that QUITE reduces query execution time by up to 35.8% over state-of-the-art approaches and produces 24.1% more rewrites than prior methods, covering query cases that earlier systems did not handle.

cs.DB↗
arXiv2025

MCI: Multi-Channel Imager on the Chinese Space Station Survey Telescope

The Multi-Channel Imager (MCI) is a powerful near-ultraviolet (NUV) and visible imager onboard the Chinese Space Station Survey Telescope (CSST). The MCI provides three imaging channels, which are the NUV channel, the Blue channel and the Red channel, with the wavelength range of 255-430 nm, 430-700 nm, and 700-1000 nm, respectively. MCI's three channels can target the same field simultaneously, which is unique compared to other imagers onboard the Hubble Space Telescope (HST) or the James Webb Space Telescope (JWST). Each channel employs a CCD focal plane of 9216 x 9232 pixels and $\sim$7\arcmin.5 x 7\arcmin.5 field of view (FOV), which are about $\gtrsim 4$ times greater than the FOVs of HST imagers. The MCI's three channels feature unprecedented sensitivities and field of views complement the NUV and visible capabilities of the CSST for high-precision photometry and weak-signal detection, which would help build a new standard-star system and the deepest UV-Optical exposures for CSST. Rich filter sets of MCI would help explore other sciences such as local emission line mapping, high-z Ly$α$ emitters searching, etc. Here we present key design features, results of current ground tests, and suggested observing strategies of the MCI.

astro-ph.IM↗
arXiv2025

The Impact of ${}^{12} \mathrm{C}(α, γ)^{16} \mathrm{O}$ Reaction on the Evolution of He Stars

The ${}^{12} \mathrm{C}(α, γ)^{16} \mathrm{O}$ reaction is one of the most important reactions in the evolution of massive stars, yet its rate is still highly uncertain. In this work, we investigated how variations in the ${}^{12} \mathrm{C}(α, γ)^{16} \mathrm{O}$ reaction rate affect the evolution of a 14 $\rm M_{\odot}$ He star using the MESA code. Our simulations indicate that the ${}^{12} \mathrm{C}(α, γ)^{16} \mathrm{O}$ reaction rate determines the conditions for C burning, affecting its explodability. As the reaction rate increases, central C-burning becomes neutrino-dominated, transitioning from the convective to the radiative regime. This leads to higher compactness and a larger iron core, indicating a more compact pre-SN core structure that is difficult to explode. Conversely, lower reaction rates shorten the C-burning lifetime and trigger earlier central Ne ignition, which counteracts core contraction. This results in reduced compactness and iron core mass. We also found that variations in reaction rates shift the location of the last C-burning shell. When this shell exceeds the mass coordinate used for compactness evaluation, the overall compactness increases significantly. Although the Si- and O-burning convective shells decrease compactness, the overall increase remains unaffected. This work suggests that the ${}^{12} \mathrm{C}(α, γ)^{16} \mathrm{O}$ reaction play an important role in the pre-SN core structure and potentially impact the explodability of massive He stars.

astro-ph.SR↗