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Ji Wang

Publications and source records attributed to Ji Wang.

At least 19 recordsLinked to original sources
arXiv2026

Rydberg Atomic Quantum Receivers for Wireless Communications: Two-Color vs. Three-Color Excitation

An efficient three-color (3C) laser excitation-based Rydberg atomic quantum receiver (RAQR) architecture is investigated for wireless communications, utilizing a five-level (5L) electronic transition mechanism. Specifically, the conventional two-color (2C) RAQR with the four-level (4L) excitation faces three fundamental obstacles: 1) high cost and engineering challenges due to the reliance on unstable short-wavelength lasers; 2) a fundamental sensitivity limit in thermal atoms caused by residual Doppler broadening; and 3) the inability to detect low-frequency bands due to the energy-level constraint of two-photon resonance. To address these challenges, this paper analyzes a 3C5L-RAQR architecture with all-red/infrared lasers, which not only solves the engineering cost issues but also enables effective Doppler cancellation and low-frequency detection by exploiting the three-photon resonance. Bridging atomic physics and communication theory, an end-to-end equivalent baseband signal model is derived. Furthermore, the performance of different RAQR architectures is evaluated in terms of sensitivity, achievable rate and spectrum access range. Moreover, we provide an exact numerical solution for practical RAQRs by employing the Liouvillian superoperator formalism. Numerical results demonstrate that the exhibited 3C5L-RAQR achieves superior sensitivity compared to the conventional 2C4L-RAQR and a classical antenna-based radio frequency receiver for weak-signal detection. Finally, the inherent sensitivity-rate trade-off is revealed, showing that the 3C5L-RAQR is more suitable for deployment in power-limited communication scenarios demanding broad spectrum access.

cs.IT↗
arXiv2026

The Science Potential of Characterizing Gas Giant Exoplanets with HWO

With the ability to directly image Earth-like exoplanets and search their atmospheres for biosignatures, the upcoming Habitable Worlds Observatory (HWO) will also collect high signal-to-noise ratio (S/N) reflected-light photometry and spectra of nearby gas giant exoplanets. Such high-quality data would allow novel investigations into gas giant atmospheric composition, formation, and kinematic properties, and could enable the detection of exomoons around these planets. We use the EXOSIMS direct imaging mission simulator to model HWO observations of Jupiter-radius gas giants at Earth-like and Jupiter-like instellations around the 164 stars in the ExEP target list. We find that HWO should be able to achieve S/N $\geq$ 5 broadband visible-light detections of gas giants in this instellation range within 5 minutes of integration. 10 hours of R=1000 near-IR spectroscopy with HWO should reveal water, methane, and ammonia absorption features in the atmospheres of Jupiter-like gas giants. HWO time-series photometry should exceed 1% flux precision in one hour for any Earth-instellation gas giants around ExEP stars, and for Jupiter-like gas giants at $d\leq$ 7 parsecs. Time-series light curves at this cadence and precision could, over tens of hours, reveal rotation-induced variability comparable to Jupiter's. Eclipses of Mars-sized exomoons may be detectable in high-cadence light curves of Jupiter sized planets in the habitable zones of ExEP stars at $d\leq$ 10 parsecs. For any hypothetical Earth-like exomoons with oxygen-rich atmospheres at $d\leq$ 7 parsecs from the Solar System, HWO might be able to detect the spectral signature of molecular oxygen amid the parent planet's photon noise in deep ($\sim$400 hour integration) spectroscopic HWO observations at R=1000. Such moons, if they exist, represent additional habitable worlds that HWO could investigate for biosignatures.

astro-ph.EP↗
arXiv2026

A Stellar-Type Dependence in the Rocky and Volatile Composition of Small Exoplanets

We investigate the rocky and volatile composition of small exoplanets by modeling the population-level distribution of densities using a mixture framework that links interior structure models to observable quantities. We analyze three complementary samples spanning different stellar environments: the Luque \& Pallé M-dwarf sample, the DACE M-dwarf sample, and the DACE FGK sample. We consider a log-normal parameterization, which captures a characteristic core mass fraction (CMF) and the intrinsic dispersion to describe a single rocky population. The single rocky population inference suggests a higher CMF for small planets around FGK stars than those around M stars by $\sim$16\% (7-11 $σ$ depending on sample selection). We also consider a power-law parameterization, which probes clustering near compositional boundaries at CMF=0.32. The power-law parameterization provides an alternative interpretation: 89.9\% to 97.0\% of the planets around FGK stars are rocky whereas up to 61.6\% (ranging from 4.1\% to 61.6\%) of planets around M stars are rocky. In addition, we find that volatile mass fractions are highly concentrated. For example, to describe the DACE M-dwarf sample using a mixture of rocky, water-rich, and gas-rich planets, we find that more than 99.5\% gaseous planets have an atmospheric mass fraction (AMF) $\lesssim 0.01\%$, and more than 55.4\% (82.7\%) gaseous planets have a water mass fraction (WMF) $\lesssim 0.1\%$ ($\lesssim 1\%$). These results suggest that while volatile-bearing planets are common, their composition and prevalence depend strongly on stellar environment, and their volatile inventories are tightly constrained by formation and evolutionary processes.

astro-ph.EP↗
arXiv2026

Measuring Harmfulness of Computer-Using Agents

Computer-using agents (CUAs), which can autonomously control computers to perform multi-step actions, might pose significant safety risks if misused. However, existing benchmarks mainly evaluate LMs in chatbots or simple tool use. To more comprehensively evaluate CUAs' misuse risks, we introduce a new benchmark: CUAHarm. CUAHarm consists of 104 expert-written realistic misuse risks, such as disabling firewalls, leaking data, or installing backdoors. We provide a sandbox with rule-based verifiable rewards to measure CUAs' success rates in executing these tasks (e.g., whether the firewall is indeed disabled), beyond refusal rates. We evaluate frontier LMs including GPT-5, Claude 4 Sonnet, Gemini 2.5 Pro, Llama-3.3-70B, and Mistral Large 2. Even without jailbreaking prompts, these frontier LMs comply with executing these malicious tasks at a high success rate (e.g., 90% for Gemini 2.5 Pro). Furthermore, while newer models are safer in previous safety benchmarks, their misuse risks as CUAs become even higher, e.g., Gemini 2.5 Pro is riskier than Gemini 1.5 Pro. Additionally, while these LMs are robust to common malicious prompts (e.g., creating a bomb) when acting as chatbots, they could still act unsafely as CUAs. We further evaluate a leading agentic framework (UI-TARS-1.5) and find that while it improves performance, it also amplifies misuse risks. To mitigate the misuse risks of CUAs, we explore using LMs to monitor CUAs' actions. We find monitoring unsafe computer-using actions is significantly harder than monitoring conventional unsafe chatbot responses. While monitoring chain-of-thoughts leads to modest gains, the average monitoring accuracy is only 77%. A hierarchical summarization strategy improves performance by up to 13%, a promising direction though monitoring remains unreliable. CUAHarm is released at https://github.com/db-ol/CUAHarm to facilitate further research.

cs.CR↗
arXiv2026

On the Impact of Correlated Noise and Spectral Resolution on the Retrieval Analysis of the Habitable World Observatory

Finding signs of life elsewhere in the universe is the holy grail of the field of exoplanets. Future space missions such as the Habitable World Observatory (HWO) are under development to search for biosignatures in exoplanets. We investigate the impact of correlated noise and spectral resolution on the retrieved biosignature chemical abundances. At the nominal spectral resolving power R=140 for HWO, we show that in 40\% of the simulated runs the retrieved biosignature (H$_2$O and O$_2$) abundances are at least 1-$σ$ off the input ground truth. At R=1000, the 1-$σ$ inaccuracy rate drops to 10\%. We provide an empirical relationship between the retrieved biosignature abundance uncertainty and the amplitude of the correlated noise. As part of the mitigation plan to reduce the impact of correlated noise on retrieval accuracy at low spectral resolution, we investigate the synergy between the HWO and LIFE space missions that cover ultraviolet, optical, and thermal-infrared wavelengths. After considering clouds and their effect on planet albedo, we find that the two missions are complementary in that (1) more biosignatures (H$_2$O, CO$_2$, O$_2$, and O$_3$) are detectable with a broader wavelength coverage; (2) retrieval uncertainty improves with the joint HWO+LIFE data set; and (3) LIFE is more sensitive to the atmospheric temperature profile, surface pressure, and planet radius. This work provides evidence to support the choice of a medium resolution at R=1000 instead of R=140 for HWO and a quantitative relationship between the retrieved abundance uncertainty and the level of correlated noise at different spectral resolutions.

astro-ph.EP↗
arXiv2026

IncSFS: Incremental Full-Sparse Flow-Sensitive Pointer Analysis for C/C++

Pointer analysis is a fundamental technique for compiler optimization and program analysis. Flow-sensitive pointer analysis provides high precision but is difficult to scale to large projects. Tailored for rapid iteration scenarios where software evolves continuously, we introduce IncSFS, the first incremental full-sparse flow-sensitive pointer analysis algorithm for C/C++ programs. IncSFS first transforms the value-flow graph into a constraint graph and performs strongly connected component detection to ensure precision. It then propagates increases and decreases in points-to sets in an interleaved manner, supporting code deletion and insertion within a single analysis pass. IncSFS is guaranteed to terminate and compute the least fixed point when the points-to relation remains object-acyclic during analysis. Experiments on six large-scale real-world projects show that IncSFS is precise and efficient, achieving average speedups of 9.60x over full flow-sensitive pointer analysis and 5.84x over the traditional reset-recompute approach. It also improves efficiency by 15.8% over state-of-the-art incremental pointer analysis algorithms that propagate points-to-set changes.

cs.PL↗
arXiv2026

Safe Output Regulation of Coupled Hyperbolic PDE-ODE Systems

This paper presents a safe output regulation control strategy for a class of systems modeled by a coupled $2\times 2$ hyperbolic PDE-ODE structure, subject to fully distributed disturbances throughout the system. A state-feedback controller is developed by the nonovershooting backstepping method to simultaneously achieve output regulation and enforce safety constraints on the regulated output that is the state furthest from the control input. To handle unmeasurable states and external disturbances, an extended observer is designed. Explicit bounds on the estimation errors are derived and used to construct a robust safe regulator that accounts for the uncertainties. The proposed control scheme guarantees that: 1) If the regulated output is initially within the safe region, it remains there; otherwise, it will be rescued to the safety region within a prescribed time; 2) The output tracking error converges to zero; 3) The observer accurately estimates both the distributed states and external disturbances, with estimation errors converging to zero exponentially; 4) All signals in the closed-loop system remain bounded. The effectiveness of the proposed method is demonstrated through a UAV delivery scenario with a cable-suspended payload, where the payload is regulated to track a desired reference while avoiding collisions with barriers.

eess.SY↗
arXiv2026

Modeling the Dynamics and Thermochemistry for the Outer Atmospheres of the Ultra-hot Jupiter WASP-121b

We present three-dimensional simulations of the ultra-hot Jupiter (UHJ) WASP-121b from the planetary surface to extended outflows, coupling hydrodynamics with consistent non-equilibrium thermochemistry, ray-tracing radiative transfer, and hydrodynamics using the GPU-accelerated Kratos framework. The fiducial model exhibits several atmospheric layers, including the lower atmospheres controlled by day-night circulation, and transonic photoevaporative outflows at higher altitudes shaped into two spiral arms by the stellar gravity and orbital motion effects. Different species could trace different regions: Fe probes rotation-dominated inner layers, Na maps dense spiral arms where recombination balances photoionization, and H$α$ and He 10830 A features trace progressively more extended, ionized gas. With spiral arm velocities reaching ~ 40 km/s projected along the line of sight, this morphology naturally reproduces the velocity pattern of observed high-velocity Na and H$α$ absorption features without requiring significant super-rotation jet streams, although the absolute absorption amplitudes could carry uncertainties from stellar UV luminosity and trace elemental abundances. Parametric studies reveal complex dependencies on stellar irradiation: enhanced FUV intensifies outflows and extends spiral arms spatially and kinematically, while EUV and X-ray expands spiral structures into attenuated, ionized regions. Stellar wind confinement compresses the dayside outflow and enhances metastable helium absorption. This work demonstrates that current and future transmission spectral observations that probe multiple species can provide important constraints on astrophysical environments of UHJs by comparing state-of-the-art simulations.

astro-ph.EP↗
arXiv2026

LimICE: Integrating LLM into ICE Framework for Efficient Loop Invariant Inference

Loop invariant synthesis is a fundamental problem in program verification, yet the inherent undecidability makes it highly challenging. Recent studies have increasingly employed various machine learning techniques to generate loop invariants. However, most of these methods adopt a monolithic approach. Due to the inability to strictly constrain the learning process, learning-based methods struggle to simultaneously consider all necessary conditions and generate complete invariants when tackling complex problems. In fact, a loop invariant is often an ordered sequence of lemmas, rather than a single invariant formula. This motivates us to propose Incremental ICE, a novel learning framework for incremental synthesis. Our framework integrates the incremental philosophy of IC3 into the general invariant learning framework ICE. By defining a lemma-specific learning objective and introducing a counterexample filtering mechanism, we can achieve sound incremental learning. Under this framework, we instantiate a loop invariant synthesis tool, LimICE, which leverages LLMs to generate the ordered sequence of lemmas and incorporates ICE-DT as a fallback mechanism to complement the lemma sequence. Experiments on 367 linear benchmarks and 50 nonlinear benchmarks demonstrate the effectiveness of the proposed approach. LimICE solves 349 (out of 367) linear problems on an average of 15.2 seconds and 47 (out of 50) nonlinear problems on an average of 8.8 seconds. Compared to the state-of-the-art LLM-based baseline, our approach solves 12-24% more instances while running 36-63% faster across linear and nonlinear benchmarks. LimICE also consistently outperforms strong non-LLM baselines and solves at least 86 and 27 additional instances on the linear and nonlinear benchmarks, respectively.

cs.SE↗
arXiv2026

Commissioning and on-sky performance verification of iLocater

iLocater is a high-resolution near-infrared extreme precision radial velocity (EPRV) spectrograph that was deployed to the Large Binocular Telescope (LBT) in June 2026. iLocater operates over $λ=966-1312$ nm with a median resolving power of $R=205,000$ as measured in the laboratory. We present the commissioning and initial on-sky verification program using solar and night-time observations at the LBT. First light was achieved on 27 June 2026, and nearly 150 on-sky spectra have now been recorded. Observations include single stars ranging in spectral type from B5 to M6. iLocater uses the LBT AO system, and we have demonstrated its ability to obtain spatially resolved spectra of close ($θ< 1''$) binary stars.

astro-ph.IM↗
arXiv2026

Toward Anthropomorphic Dialogue: A Closed-Loop Framework for Human-Like Chat Generation, Evaluation, and Preference Alignment

Human-like private chat requires more than fluent response generation: a system must preserve persona, relationship, memory, bounded knowledge, medium-specific timing, and a coherent multi-turn arc. We present AnthroDial, a closed-loop framework that formulates anthropomorphic dialogue as a joint problem of system architecture, executable evaluation, and diagnostic alignment. It combines (1) a role-conditioned scheduled dialogue runtime with persona and scenario cards, long-term memory, virtual time, and single-draft message decisions; (2) an executable benchmark with an L0 validity gate, five per-turn dimensions, and five dialogue-level dimensions; and (3) a post-training pipeline that filters 16,436 scheduled-decision examples for SFT and applies GRPO with a cognitive-diagnostic, ZPD-aware reward. The reward maintains Kalman-filtered capability estimates for each behavioral dimension, upweights dimensions with larger capability deficits, and uses rollout scores as task-level ZPD matches to focus optimization on learnable weak skills. On a benchmark with 55 personas, 50 scenarios, 50 persona-scenario bindings, and 100 role-conditioned cases per model, we evaluate 16 systems spanning frontier baselines, open models, thinking/no-think variants, and SFT/RL ablations. The strongest non-trained baseline reaches 32.00% strict ACC, while Qwen3.6-27B-SFT+RL reaches 39.00% strict ACC and a 98.5 overall score. In the 9B no-think setting, SFT and RL improve strict ACC from 0.00% to 13.00% and 18.37%. These results show that anthropomorphic dialogue benefits when generation, evaluation, and reward shaping share the same behavioral dimensions.

cs.AI↗
arXiv2026

Fly0: Persistent Metric Anchoring for Zero-Shot Aerial Vision-Language Navigation

Current Visual-Language Navigation (VLN) methodologies face a trade-off between semantic understanding and control precision. While Multimodal Large Language Models (MLLMs) offer superior reasoning, deploying them as low-level controllers leads to high latency, trajectory oscillations, and poor generalization due to weak geometric grounding. To address these limitations, we propose Fly0, a framework that decouples semantic reasoning from geometric planning. The proposed method operates through a three-stage pipeline: (1) an MLLM-driven module for grounding natural language instructions into 2D pixel coordinates; (2) a geometric projection module that utilizes depth data to localize targets in 3D space; and (3) a geometric planner that generates collision-free trajectories. This mechanism enables robust navigation even when visual contact is lost. By eliminating the need for continuous inference, Fly0 reduces computational overhead and improves system stability. Extensive experiments in simulation and real-world environments demonstrate that Fly0 outperforms state-of-the-art baselines, improving the Success Rate by over 20\% and reducing Navigation Error (NE) by approximately 50\% in unstructured environments. Our code is available at https://github.com/xuzhenxing1/Fly0.

cs.RO↗
arXiv2026

Rethinking Efficiency in Neural Combinatorial Optimization: Batched Preference Optimization with Mamba

We study efficiency as a first-class objective in Neural Combinatorial Optimization (NCO) and present ECO, an efficient learning framework that combines batched preference optimization with a Mamba backbone. Instead of tightly interleaving every policy update with on-policy rollouts, ECO decouples trajectory generation from gradient updates through two stages: supervised warm-up on pre-computed solutions and iterative Direct Preference Optimization (DPO) on batched candidate sets generated by the current policy. We pair this learning pipeline with a mixed Mamba encoder-decoder that reduces memory growth on long sequences and improves hardware utilization. A local-search-guided bootstrapping strategy is further used during training to widen preference margins and stabilize iterative improvement. Importantly, local search is only used to construct stronger preference pairs during training and is never invoked at inference time. On TSP and CVRP, ECO achieves the strongest overall performance among the compared neural baselines while also delivering clear advantages in memory usage and throughput. We provide additional analysis on memory scaling, throughput, and the contribution of each design component.

cs.LG↗
arXiv2026

Benchmark Brown Dwarf Systems I: Chemical Abundance Analysis of FGK Stars with Wide-Separation Brown Dwarf Companions Using PEPSI

We present results from a spectroscopic survey of 32 FGK stars hosting brown dwarfs, using high-resolution optical spectra (R = 130,000 and 50,000) obtained with the PEPSI spectrograph on the Large Binocular Telescope. The primary goal of this survey is to determine precise stellar parameters and abundances for 11 elements (C, O, Mg, Si, Ca, Al, Ti, Fe, Y, S, and N) in these systems. We employ spectral synthesis within the BACCHUS framework to derive precise stellar properties and elemental abundance ratios. For our average S/N $>$ 200 data, we achieve a typical error of 42 K in T$_\mathrm{eff}$ and $\sim$0.03 dex for [Fe/H]. We observe a significant dispersion from a solar C/O ratio among the sample of brown dwarf host stars that host primarily wide-orbit brown dwarfs. Using established theoretical chemical frameworks, we discuss the implications of the observed Mg/Si and Ca/Al ratios for cloud properties in the brown dwarf companions. Finally, we evaluate the applicability of the [Y/Mg] stellar clock for our sample and discuss the broader implications of our results. This work provides a timely and uniform abundance analysis of host stars, supporting extended wavelength brown dwarf observations in the era of JWST.

astro-ph.SR↗
arXiv2026

CABTO: Context-Aware Behavior Tree Grounding for Robot Manipulation

Behavior Trees (BTs) offer a powerful paradigm for designing modular and reactive robot controllers. BT planning, an emerging field, provides theoretical guarantees for the automated generation of reliable BTs. However, BT planning typically assumes that a well-designed BT system is already grounded -- comprising high-level action models and low-level control policies -- which often requires extensive expert knowledge and manual effort. In this paper, we formalize the BT Grounding problem: the automated construction of a complete and consistent BT system. We analyze its complexity and introduce CABTO (Context-Aware Behavior Tree grOunding), the first framework to efficiently solve this challenge. CABTO leverages pre-trained Large Models (LMs) to heuristically search the space of action models and control policies, guided by contextual feedback from BT planners and environmental observations. Experiments spanning seven task sets across three distinct robotic manipulation scenarios demonstrate CABTO's effectiveness and efficiency in generating complete and consistent behavior tree systems.

cs.RO↗
arXiv2026

Atmospheric characterization of six ultra-hot Jupiters from $K$-band high-resolution spectroscopy

We present new Keck/KPIC high-resolution spectroscopic detections of three ultra-hot Jupiters (UHJs) in the $K$ band: WASP-189b ($\rm SNR = 7.2$), MASCARA-1b ($\rm SNR = 8.6$), and TOI-1518b ($\rm SNR = 7.1$), as well as a tentative detection of KELT-9b ($\rm SNR = 5.0$). We perform a uniform set of atmospheric retrieval analysis on these objects, as well as previously reported KPIC observations of WASP-33b ($\rm SNR = 11.2$) and KELT-20b ($\rm SNR = 10.5$), We perform atmospheric retrievals for the pressure-temperature ($P-T$) profile, orbital velocity parameters, $v\sin i$, and abundances of CO, H$_2$O, OH, and Fe, with parameterized mixing profiles to account for the expected vertical abundance variations of H$_2$O and OH. We also perform a set of retrievals assuming chemical equilibrium, which are generally in good agreement with the free retrievals. Except for \knb, the retrieved spectra are dominated by CO emission features, with additional weak H$_2$O or OH features consistent with thermal dissociation of H$_2$O. \knb, which is significantly hotter, appears to have very weak molecular features. Dissociation limits our ability to reliably constrain H$_2$O or OH abundances from $K$ band data alone, resulting in poor constraints on the C/O ratio. For all objects, the atmospheric abundances from detected carbon and oxygen species are $1-10\times$ solar. These results highlight the importance of wide spectral coverage for high-resolution retrievals. Additional observations to expand phase and wavelength coverage are needed to better constrain oxygen species and possible spatial inhomogeneities from dissociation.

astro-ph.EP↗
arXiv2026

FedUP: One-Shot Federated Unlearning via Centroid-Guided Plug-in Filters

Federated unlearning (FU) is critical for complying with legal mandates like the right to be forgotten in decentralized systems, yet current methods face a persistent dilemma between non-target knowledge loss and high request latency. To resolve these issues, we propose FedUP, a one-shot federated unlearning framework utilizing lightweight pluggable filters that act as a "knowledge funnel" to screen out target data while preserving original model performance. By freezing original model parameters and training filters at the server side using differentially private (DP)-protected class centroid samples, FedUP bypasses the need for multi-round client-server communication and complex retraining, reducing unlearning latency from minutes to mere seconds. Additionally, the framework's pluggable architecture ensures inherent reversibility, enabling the seamless restoration of forgotten knowledge by simply removing the filters. Extensive experiments on diverse image and text tasks demonstrate that FedUP effectively reduces non-target knowledge loss and achieves superior unlearning precision and efficiency across various scenarios. Code is available at: https://github.com/suows/FedUP-code.

cs.LG↗
arXiv2026

Characterizing Earth analogs may require a moderate or high-resolution spectrograph

A primary goal of the Habitable Worlds Observatory (HWO) is to detect and measure the abundance of biosignature molecules, such as water (H2O) and oxygen (O2), in the atmosphere of Earth analogs. This is expected to require deep spectroscopic observations lasting hundreds of hours per planet. In this context, it is essential to optimize the spectral resolution of the spectrograph to both maximize the number of planets that can be studied over the lifetime of the mission, and also to reduce the risks of false detections. The purpose of this work is to provide a framework to explore the spectral resolution design trade-space for HWO. This framework must be valid and comparable across all spectral resolutions from low (R<100) to high resolutions (R>10,000), and account for the spectral correlation of the residual starlight (i.e., speckle noise chromaticity). Leveraging the concept of "template matching", we develop a simulation toolkit based on the Python package EXOSIMS to compute the detection significance of planets and molecules. We then simulate observations of Earth analogs around 164 stars using representative mission parameters to explore the effects of the detector noise and the correlated speckle noise floor. Our findings suggest that a moderate or high resolution spectrograph (R>1,000) will provide higher sensitivity to critical molecules compared to a low resolution spectroscopy mode (e.g., R~140). The correlated speckle noise may also entirely suppress our ability to detect bio-signatures at low spectral resolutions. We conclude that a more comprehensive study combined with detailed models of its stability, and other sources of correlated noise, is necessary to fully explore the trade space of spectral resolution and detectability of key species.

astro-ph.IM↗