arXiv subjects

Ji Wang

Publications and source records attributed to Ji Wang.

At least 55 records · Page 3Linked to original sources

arXiv2026

Distinct Rotational Evolution of Giant Planets and Brown Dwarf Companions

We present a rotational velocity (vsini) survey of 32 stellar/substellar objects and giant planets using Keck/KPIC high-resolution spectroscopy, including 6 giant planets (2-7 M$_\mathrm{Jup}$) and 25 substellar/stellar companions (12-88 M$_\mathrm{Jup}$). Adding companions with spin measurements from the literature, we construct a curated spin sample for 43 benchmark stellar/substellar companions and giant planets and 54 free-floating brown dwarfs and planetary mass objects. We compare their spins, parameterized as fractional breakup velocities at 10 Myr, assuming constant angular momentum evolution. We find the first clear evidence that giant planets exhibit distinct spins versus low-mass brown dwarf companions (10 to 40 M$_\mathrm{Jup}$) at 4-4.5 $σ$ significance assuming inclinations aligned with their orbits, while under randomly oriented inclinations the significance is at 1.6-2.1 $σ$. Our findings hold when considering various assumptions about planets, and the mass ratio below 0.8% gives a clean cut for rotation between giant planets and brown dwarf companions. The higher fractional breakup velocities of planets can be interpreted as less angular momentum loss through circumplanetary disk braking during the planet formation phase. Brown dwarf companions exhibit evidence of slower rotation compared to isolated brown dwarfs, while planets and planetary mass objects show similar spins. Finally, our analysis of specific angular momentum versus age of 221 stellar/substellar objects below 0.1 M$_{\odot}$ with spin measurements in the literature indicates that the substellar objects of 5-40 M$_\mathrm{Jup}$ retain much higher angular momenta compared to stellar and substellar objects of 40-100 M$_\mathrm{Jup}$ after 10 Myr, when their initial angular momenta were set.

astro-ph.EP↗

arXiv2026

Wireless AI Evolution: From Statistical Learners to Electromagnetic-Guided Foundation Models

While initial applications of artificial intelligence (AI) in wireless communications over the past decade have demonstrated considerable potential using specialized models for targeted communication tasks, the revolutionary demands of sixth-generation (6G) networks for holographic communications, ubiquitous sensing, and native intelligence are propelling a necessary evolution towards AI-native wireless networks. The arrival of large AI models paves the way for the next phase of Wireless AI, driven by wireless foundation models (WFMs). In particular, pre-training on universal electromagnetic (EM) principles equips WFMs with the essential adaptability for a multitude of demanding 6G applications. However, existing large AI models face critical limitations, including pre-training strategies disconnected from EM-compliant constraints leading to physically inconsistent predictions, a lack of embedded understanding of wave propagation physics, and the inaccessibility of massive labeled datasets for comprehensive EM-aware training. To address these challenges, this article presents an electromagnetic information theory-guided self-supervised pre-training (EIT-SPT) framework designed to systematically inject EM physics into WFMs. The EIT-SPT framework aims to infuse WFMs with intrinsic EM knowledge, thereby enhancing their physical consistency, generalization capabilities across varied EM landscapes, and overall data efficiency. Building upon the proposed EIT-SPT framework, this article first elaborates on diverse potential applications in 6G scenarios of WFMs, then validates the efficacy of the proposed framework through illustrative case studies, and finally summarizes critical open research challenges and future directions for WFMs.

cs.IT↗

arXiv2026

Recent Advances in Near-Field Beam Training and Channel Estimation for XL-MIMO Systems

Extremely large-scale multiple-input multiple-output (XL-MIMO) is a key technology for next-generation wireless communication systems. By deploying significantly more antennas than conventional massive MIMO systems, XL-MIMO promises substantial improvements in spectral efficiency. However, due to the drastically increased array size, the conventional planar wave channel model is no longer accurate, necessitating a transition to a near-field spherical wave model. This shift challenges traditional beam training and channel estimation methods, which were designed for planar wave propagation. In this article, we present a comprehensive review of state-of-the-art beam training and channel estimation techniques for XL-MIMO systems. We analyze the fundamental principles, key methodologies, and recent advancements in this area, highlighting their respective strengths and limitations in addressing the challenges posed by the near-field propagation environment. Furthermore, we explore open research challenges that remain unresolved to provide valuable insights for researchers and engineers working toward the development of next-generation XL-MIMO communication systems.

cs.IT↗

arXiv2026

AutoEP: LLMs-Driven Automation of Hyperparameter Evolution for Metaheuristic Algorithms

Dynamically configuring algorithm hyperparameters is a fundamental challenge in computational intelligence. While learning-based methods offer automation, they suffer from prohibitive sample complexity and poor generalization. We introduce AutoEP, a novel framework that bypasses training entirely by leveraging Large Language Models (LLMs) as zero-shot reasoning engines for algorithm control. AutoEP's core innovation lies in a tight synergy between two components: (1) an online Exploratory Landscape Analysis (ELA) module that provides real-time, quantitative feedback on the search dynamics, and (2) a multi-LLM reasoning chain that interprets this feedback to generate adaptive hyperparameter strategies. This approach grounds high-level reasoning in empirical data, mitigating hallucination. Evaluated on three distinct metaheuristics across diverse combinatorial optimization benchmarks, AutoEP consistently outperforms state-of-the-art tuners, including neural evolution and other LLM-based methods. Notably, our framework enables open-source models like Qwen3-30B to match the performance of GPT-4, demonstrating a powerful and accessible new paradigm for automated hyperparameter design. Our code is available at https://github.com/YiZheZhang12/AutoEP.

cs.AI↗

arXiv2026

Rotatable Antenna Assisted Mobile Edge Computing

This paper investigates a rotatable antenna (RA) assisted mobile edge computing (MEC) network, where multiple users offload their computation tasks to an edge server equipped with an RA array under a time-division multiple access protocol. To maximize the weighted sum computation rate, we formulate a joint optimization problem over the RA rotation angles, time-slot allocation, transmit power, and local CPU frequencies. Due to the non-convex nature of the formulated problem, a scenario-adaptive hybrid optimization algorithm is proposed. Specifically, for the dynamic rotating scenario, where RAs can flexibly reorient within each time slot, we derive closed-form optimal antenna pointing vectors to enable a low-complexity sequential solution. In contrast, for the static rotating scenario where RAs maintain a unified orientation, we develop an alternating optimization framework, where the non-convex RA rotation constraints are handled using successive convex approximation iteratively with the resource allocation. Simulation results demonstrate that the proposed RA assisted MEC network significantly outperforms conventional fixed-antenna MEC networks. Owing to the additional spatial degrees of freedom introduced by mechanical rotation, the flexibility of RAs effectively mitigates the severe beam misalignment inherent in fixed-antenna systems, particularly under high antenna directivity.

cs.IT↗

arXiv2026

Rapid Boundary Stabilization of Two-Dimensional Elastic Plates with In-Domain Aeroelastic Instabilities

Motivated by active wing flutter suppression in high-Mach-number flight, this paper presents a rapid boundary stabilization strategy for a two-dimensional PDE-modeled elastic plate with in-domain instabilities, where the exponential stability is achieved with a decay rate that can be arbitrarily assigned by the users. First, the aeroelastic system is modeled as two-dimensional coupled wave PDEs with internal anti-damping terms, derived by Piston theory and Hamilton's principle. Using Fourier series expansion, the 2-D problem is decomposed into a large-scale 1-D system, based on which full-state boundary feedback control is designed via PDE backstepping transformation. To enable output-feedback implementation, a state observer is further designed to estimate the distributed states over the two-dimensional spatial domain using the available boundary measurements. Through Lyapunov analysis, the exponential stability of the 2-D elastic plate PDE under the proposed boundary control is established with a designer-tunable decay rate. Numerical simulations verify the effectiveness of the control strategy in suppressing flow-induced vibrations in a 2-D elastic plate.

eess.SY↗

arXiv2026

Possible stratospheric emission in the warm Neptune GJ 436 b from high-resolution spectroscopy

We present high spectral resolution $L$ band (2.91--3.85 $μ$m) observations of the warm Neptune GJ 436 b from Keck II/KPIC. KPIC's single-mode fiber feed reduces the $L$ band sky background by a factor of 100, significantly improving sensitivity compared to a seeing-limited spectrometer and enabling a tentative ($\rm SNR = 3-4$) cross-correlation detection of GJ 436 b with a thermally inverted atmospheric model. In contrast with recent results from $JWST$ and high-resolution transmission spectroscopy, our retrieval analysis prefers the presence of H$_2$O, and possibly CH$_4$, molecular features in emission. The broad-band continuum flux associated with the maximum-likelihood model is substantially higher than expected based on both the $\sim670\rm\ K$ equilibrium temperature of GJ 436 b and previous results from low-resolution spectroscopy. We demonstrate that the loss of continuum information during the processing of high-resolution spectra makes our analysis effectively insensitive to the absolute continuum level of the planet, and that scaling the maximum-likelihood model to match the broad-band flux measured from low-resolution observations of GJ 436 b results in a detection of similar strength in cross-correlation. These results could be explained by a thermal inversion arising above a haze layer in the upper atmosphere of \gjb. Further observations, ideally post-eclipse in order to break the $K_p - Δv_{sys}$ degeneracy, are needed to clarify this possible detection. This work demonstrates the potential of $L$ band high-resolution spectroscopy for characterizing significantly smaller and cooler exoplanets compared with hot Jupiters.

astro-ph.EP↗

arXiv2026

Data-Driven Safe Output Regulation of Strict-Feedback Linear Systems with Input Delay

This paper develops a data-driven safe control framework for linear systems possessing a known strict-feedback structure, but with most plant parameters, external disturbances, and input delay being unknown. By leveraging Koopman operator theory, we utilize Krylov dynamic mode decomposition (DMD) to extract the system dynamics from measured data, enabling the reconstruction of the system and disturbance matrices. Concurrently, the batch least-squares identification (BaLSI) method is employed to identify other unknown parameters in the input channel. Using control barrier functions (CBFs) and backstepping, we first develop a full-state safe controller. Based on this, we build an output-feedback controller by performing system identification using only the output data and actuation signals as well as constructing an observer to estimate the unmeasured plant states. The proposed approach achieves: 1) finite-time identification of a substantial set of unknown system quantities, and 2) exponential convergence of the output state (the state furthest from the control input) to a reference trajectory while rigorously ensuring safety constraints. The effectiveness of the proposed method is demonstrated through a safe vehicle platooning application.

eess.SY↗

arXiv2026

Fluid Antenna Systems under Channel Uncertainty and Hardware Impairments: Trends, Challenges, and Future Research Directions

Fluid antenna systems (FAS) have recently emerged as a promising paradigm for achieving spatially reconfigurable, compact, and energy-efficient wireless communications in beyond fifth-generation (B5G) and sixth-generation (6G) networks. By dynamically repositioning a liquid-based radiating element within a confined physical structure, FAS can exploit spatial diversity without relying on multiple fixed antenna elements. This spatial mobility provides a new degree of freedom for mitigating channel fading and interference, while maintaining low hardware complexity and power consumption. However, the performance of FAS in realistic deployments is strongly affected by channel uncertainty, hardware nonidealities, and mechanical constraints, all of which can substantially deviate from idealized analytical assumptions. This paper presents a comprehensive survey of the operation and design of FAS under such practical considerations. Key aspects include the characterization of spatio-temporal channel uncertainty, analysis of hardware and mechanical impairments such as RF nonlinearity, port coupling, and fluid response delay, as well as the exploration of robust design and learning-based control strategies to enhance system reliability. Finally, open research directions are identified, aiming to guide future developments toward robust, adaptive, and cross-domain FAS design for next-generation wireless networks.

eess.SP↗

arXiv2026

S$^2$F: Principled Hybrid Testing With Fuzzing, Symbolic Execution, and Sampling

Hybrid testing that integrates fuzzing, symbolic execution, and sampling has demonstrated superior testing efficiency compared to individual techniques. However, the state-of-the-art (SOTA) hybrid testing tools do not fully exploit the capabilities of symbolic execution and sampling in two key aspects. First, the SOTA hybrid testing tools employ tailored symbolic execution engines that tend to over-prune branches, leading to considerable time wasted waiting for seeds from the fuzzer and missing opportunities to discover crashes. Second, existing methods do not apply sampling to the appropriate branches and therefore cannot utilize the full capability of sampling. To address these two limitations, we propose a novel hybrid testing architecture that combines the precision of conventional symbolic execution with the scalability of tailored symbolic execution engines. Based on this architecture, we propose several principles for combining fuzzing, symbolic execution, and sampling. We implement our method in a hybrid testing tool S$^2$F. To evaluate its effectiveness, we conduct extensive experiments on 15 real-world programs. Experimental results demonstrate that S$^2$F outperforms the SOTA tool, achieving an average improvement of 6.14% in edge coverage and 32.6% in discovered crashes. Notably, our tool uncovers three previously unknown crashes in real-world programs.

cs.SE↗

arXiv2026

Multi-Agent Collaborative Reward Design for Enhancing Reasoning in Reinforcement Learning

We present CRM (Multi-Agent Collaborative Reward Model), a framework that replaces a single black-box reward model with a coordinated team of specialist evaluators to improve robustness and interpretability in RLHF. Conventional reward models struggle to jointly optimize multiple, sometimes conflicting, preference dimensions (e.g., factuality, helpfulness, safety) and offer limited transparency into why a score is assigned. CRM addresses these issues by decomposing preference evaluation into domain-specific agents that each produce partial signals, alongside global evaluators such as ranker-based and embedding-similarity rewards. A centralized aggregator fuses these signals at each timestep, balancing factors like step-wise correctness, multi-agent agreement, and repetition penalties, yielding a single training reward compatible with standard RL pipelines. The policy is optimized with advantage-based updates (e.g., GAE), while a value model regresses to the aggregated reward, enabling multi-perspective reward shaping without requiring additional human annotations beyond those used to train the evaluators. To support training and assessment, we introduce rewardBench, a benchmark and training suite aligned with the collaborative structure of CRM. Together, CRM and rewardBench provide a practical, modular path to more transparent reward modeling and more stable optimization.

cs.AI↗

arXiv2025

Dynamical Architectures of S-type Transiting Planets in Binaries II: A Dichotomy in Orbital Alignment of Small Planets in Close Binary Systems

Stellar multiplicity plays a crucial role in shaping planet formation and dynamical evolution. We present a survey of 54 TESS Objects of Interest (TOIs) within 300 pc that exhibit significant Hipparcos-Gaia astrometric accelerations. We identified 35 TOIs with stellar companions at projected separations between $0.1^{\prime\prime}$ to $2^{\prime\prime}$ (or $10-200$ AU). We also identified 12 TOIs that could host planetary-mass or brown dwarf companions, including 6 that are newly discovered. Furthermore, we perform three-dimensional orbital characterization for 12 binaries hosting confirmed planets or planet candidates, allowing us to constrain the line-of-sight mutual inclination, $ΔI_{\mathrm{los}}$, between the planetary and binary orbits. Combining our sample with previous measurements, we apply Bayesian hierarchical analysis to a total of 26 binary systems with S-type transiting planets ($r_p<5R_{\oplus}$). Specifically, we fit the $ΔI_{\mathrm{los}}$ distribution with both single (Rayleigh) and mixture models (two-component Rayleigh and Rayleigh-isotropic mixture). We find the mixture models are strongly favored ($\log Z\gtrsim13.9$, or $\approx$5$σ$), indicating the observed planet-binary $ΔI_{\mathrm{los}}$ values likely originate from two underlying populations: one nearly aligned ($σ_1 = 2^{\circ}.4^{+0.7}_{-0.9}$) and one with more scattered mutual inclinations ($σ_2 = 23^{\circ}.6^{+8.8}_{-7.1}$). Alternatively, the misaligned systems can be equally well described by an isotropic distribution of inclinations. This observed dichotomy likely reflects different dynamical histories. Notably, the misaligned population only emerges in systems with stellar periastron distances $>40$ AU while systems with close-in or eccentric stellar companions (periastron distances $<40$ AU) preserve planet-binary alignment.

astro-ph.EP↗

arXiv2025

Surveying Ultra-hot Jupiters using Phase Curves with $\textit{Twinkle}$

Due to their high equilibrium temperatures ($T_{eq}$ $>$ 2000 K), ultra-hot Jupiters (UHJs) are the best characterized exoplanets to date. However, many questions about their formation, evolution, and atmospheres remain unanswered. Phase curve observations can reveal answers to these questions by constraining multiple atmospheric properties including circulation, albedo, and chemistry. To this end, we simulate and forecast a survey of UHJ atmospheres via phase curve observations with the upcoming $\textit{Twinkle}$ mission. $\textit{Twinkle}$ is a spectroscopic satellite covering 0.5--4.5 micron with a spectral resolving power of R $\sim$ 50--70. Using a physically motivated model, we simulate white-light photometric phase curve observations for 14 UHJs in $\textit{Twinkle's}$ field of regard. We project that $\textit{Twinkle}$ will be able to detect all phase curve signals in our survey. Additionally, we simulate spectroscopic phase curves for the UHJ, WASP-189b. From our simulated spectroscopic phase curves, we generate mock phase-resolved emission spectra. Previously detected UHJ molecules (e.g. H$_2$O, CO and CO$_2$) produce notable features in the resulting spectra, allowing for detailed atmospheric characterization to study the 3D structure of UHJ atmospheric chemistry and dynamics. For planets with hotspot phase offsets, $\textit{Twinkle}$ will be capable of detecting them both in the optical and infrared wavelength ranges. This future survey would represent the first UHJ phase curve survey with simultaneous coverage in optical and infrared wavelengths and will provide new constraints and reveal intriguing trends in these extreme environments.

astro-ph.EP↗

arXiv2025

Chemical and Isotopic Homogeneity Between the L Dwarf CD-35 2722 B and its Early M Host Star

CD-35 2722 B is an L dwarf companion to the nearby, $\sim 50-200$ Myr old M1 dwarf CD-35 2722 A. We present a detailed analysis of both objects using high-resolution ($R \sim 35,000$) $K$ band spectroscopy from the Keck Planet Imager and Characterizer (KPIC) combined with archival photometry. With a mass of $30^{+5}_{-4} M_{\mathrm{Jup}}$ (planet-to-host mass ratio 0.05) and projected separation of $67\pm4$ AU from its host, CD-35 2722 B likely formed via gravitational instability. We explore whether the chemical composition of the system tells a similar story. Accounting for systematic uncertainties, we find $\mathrm{[M/H]}=-0.16^{+0.03}_{-0.02} \mathrm{(stat)} \pm 0.25 \mathrm{(sys)}$ dex and $^{12}\mathrm{C}/^{13}\mathrm{C}=132^{+20}_{-14}$ for the host, and $\mathrm{[M/H]}=0.27^{+0.07}_{-0.06} (\mathrm{stat}) \pm 0.12 (\mathrm{sys})$ dex, $^{12}\mathrm{CO}/^{13}\mathrm{CO}=159^{+33}_{-24} \mathrm{(stat)}^{+40}_{-33} \mathrm{(sys)}$, and $\mathrm{C/O} = 0.55 \pm 0.01 (\mathrm{stat}) \pm 0.04 (\mathrm{sys})$ for the companion. The chemical compositions for the brown dwarf and host star agree within the $1.5σ$ level, supporting a scenario where CD-35 2722 B formed via gravitational instability. We do not find evidence for clouds on CD-35 2722 B despite it being a photometrically red mid-L dwarf and thus expected to be quite cloudy. We retrieve a temperature structure which is more isothermal than models and investigate its impact on our measurements, finding that constraining the temperature structure to self-consistent models does not significantly impact our retrieved chemical properties. Our observations highlight the need for data from complementary wavelength ranges to verify the presence of aerosols in likely cloudy L dwarfs.

astro-ph.EP↗

arXiv2025

PEPSI Investigation, Retrieval, and Atlas of Numerous Giant Atmospheres (PIRANGA). II. Phase-Resolved Cross-Correlation Transmission Spectroscopy of KELT-20b

KELT-20b is a well-studied ($T_{\text{eq}}=2262$ K) ultra hot Jupiter, but its multidimensional atmospheric structure remains unconstrained. We performed high-resolution cross-correlation transmission spectroscopy (HRCCTS) on a single transit time series of KELT-20b, observed with PEPSI on the LBT. Upon combining nineteen in-transit exposures, we detect Fe I $(11.9σ)$ and Fe II $(23.7σ)$ and tentatively detect Na I $(3.4σ)$ and Cr I $(3.3σ)$. The full-transit velocity offsets of the strongest absorbers are $ΔV_{\text{Fe I}} = -1.0 \pm 0.7$ km s$^{-1}$ and $ΔV_{\text{Fe II}}= 0.0\pm 0.5$ km s$^{-1}$, which are mostly inconsistent with previously published values for KELT-20b, although the previous measurements are mostly inconsistent with each other. By correcting for discrepant systemic velocity solutions of up to $1.7$ km s$^{-1}$ between studies, our Fe II offset becomes consistent with previous measurements ($\leq 1.7σ$), while Fe I remains significantly less blueshifted than in earlier studies ($ \geq 2.2-4.5σ$). We propose a set of detection criteria to improve future reproducibility in HRCCTS work. Phase-resolving the Fe I and Fe II absorption signatures into eight orbital phase bins reveals distinct dynamical regimes: Fe II exhibits a strong phase-dependent blueshift from ingress to egress along with significant limb asymmetry, while Fe I shows weaker signals and a more modest blueshift with phase. These patterns indicate day-to-night winds and suggest scale height differences are a significant driver of limb asymmetry in KELT-20b.

astro-ph.EP↗

arXiv2025

PEPSI Investigation, Retrieval, and Atlas of Numerous Giant Atmospheres (PIRANGA). IV. High-Resolution Phased-Resolved Spectroscopy of The Ultra Hot Jupiter KELT-20 b

We present five datasets of high-resolution optical emission spectra of the ultra-hot Jupiter KELT-20 b with the PEPSI spectrograph. Using a Bayesian retrieval framework, we constrain its dayside pressure-temperature profile and abundances of Fe, Ni, and Ca, providing the first measurements for Ni and Ca for KELT-20 b in emission. We retrieve the pre- and post-eclipse datasets separately (corresponding to the evening and morning sides, respectively), and compare the constraints on their thermal structures and chemical abundances. We constrain lower abundances in the pre-eclipse datasets compared to the post-eclipse datasets. We interpret these results with an equilibrium chemistry model which suggests ~10-30x supersolar refractory abundances. Due to the well-known degeneracy between absolute abundances and continuum opacities, the abundance ratios are more precise probes of the planetary abundances. Therefore we measure the abundance ratios [Ni/Fe] and [Ca/Fe] across these datasets and find they agree within 1-sigma. We constrain [Ni/Fe] to be consistent with solar within 2-sigma, and [Ca/Fe] to be 0.001-0.01x solar, not accounting for ionization. We compare these abundance ratios with literature results for KELT-20 b in transmission, and find they agree within 2-sigma, suggesting that even though the abundances vary significantly as a function of phase, the abundance ratios of these species remain relatively constant. We find a ~100 K difference in temperature at the top of the thermal inversion, suggesting a hotter evening side than morning side and underscoring the importance of considering 3D effects when studying ultra-hot Jupiters.

astro-ph.EP↗

arXiv2025

Origins of Mercury's Big Heart of Iron: Exploring Pathways to Form High Core Mass Fraction (CMF) Planets via N-body Simulations

Mercury's core mass fraction (CMF) is ~0.7, more than double that of the other rocky planets in the solar system, which have CMFs of ~0.3. The origin of Mercury's large, iron-rich core remains unknown. Adding to this mystery, an elusive population of "Exo-Mercuries" with high densities is emerging. Therefore, understanding the formation of Mercury and its exoplanetary analogs is essential to developing a comprehensive planet formation theory. Two hypotheses have been proposed to explain the high CMF of Mercury: (1) giant impacts during the latest stages of planet formation strip away mantle layers, leaving Mercury with a large core; and (2) earlier-stage iron enrichment of planetesimals closer to the Sun leads to the formation of an iron-rich planet. In this work, we conduct N-body simulations to test these two possibilities. Our simulations are focused on the solar system, however, we aim to provide a framework that can later be applied to the formation of high-CMF exoplanets. To investigate the giant impact scenario, we employ uniform initial CMF distributions. To address the other hypothesis, we use a step function with higher CMFs in the inner region. For a uniform initial CMF distribution, our results indicate that although erosive impacts produce iron-rich particles, without mechanisms that deplete stripped mantle material, these particles merge with lower-CMF objects and do not lead to Mercury's elevated CMF. However, a step function initial CMF distribution leads to the formation of a high-CMF planet alongside Earth-like planets, resembling the architecture of the terrestrial solar system.

astro-ph.EP↗

arXiv2025

Sum Rate Maximization for NOMA-Assisted Uplink Pinching-Antenna Systems

In this paper, we investigate an uplink communication scenario in which multiple users communicate with an access point (AP) employing non-orthogonal multiple access (NOMA). A pinching antenna, which can be activated at an arbitrary point along a dielectric waveguide, is deployed at the AP to dynamically reconfigure user channels. The objective is to maximize the system sum rate by jointly optimizing the pinching-antenna's position and the users' transmit powers. Two scenarios are considered: one without quality-of-service (QoS) guarantees, and the other with QoS guarantees. In the former case, users transmit at full power, and the antenna position is determined using the particle swarm optimization (PSO) algorithm. In the latter, an alternating optimization approach is adopted, where a low-complexity solution is derived for power allocation, and a modified PSO algorithm is applied to optimize the antenna position. Numerical results show that the proposed pinching-antenna-assisted system significantly improves the sum rate compared to the conventional fixed-antenna architecture. Furthermore, the NOMA-based approach consistently outperforms its TDMA-based counterpart. Finally, the proposed PSO-based method achieves near-optimal performance, particularly when the QoS constraints are moderate.

cs.IT↗