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Heng Wang

Publications and source records attributed to Heng Wang.

At least 55 records · Page 3Linked to original sources
arXiv2026

Bipolar-doped superconducting infinite-layer cuprates

Distilling the intrinsic physics of the superconducting CuO2 plane from the complexities of charge-reservoir layers is a defining challenge in high-temperature superconductivity. While superconducting electron-doped infinite-layer cuprates have been synthesized, controllable and uniform hole doping has long remained elusive despite exploratory attempts, limiting spectroscopic insights. Here, we realize bipolar doping across infinite-layer (Sr,Eu)CuO2 and (Ca,Li)CuO2+δ single-crystalline thin films, mapping the electronic phase diagram. Both electron- and hole-doped films show pronounced electrical resistance anisotropy, indicating the quasi-two-dimensional nature of the CuO2 planes. Angle-resolved photoemission spectroscopy across electron- and hole-doped regimes reveals persistent antiferromagnetic band folding coexisting with superconductivity. Remarkably, at a hole doping ~0.07 determined by Luttinger volume, the antiferromagnetic folding emerges from Fermi arcs within the film's single Fermi surface, with the onset superconducting transition temperature exceeding 60 K. These findings redefine the interplay between magnetic order and superconductivity and establish a definitive platform to investigate the intrinsic mechanism of high-temperature superconducting cuprates.

cond-mat.supr-con↗
arXiv2026

ChannelAgent-Empowered Electromagnetic Space World Model: A Case Study on Agent-Driven Channel Generation for 6G AI-Native Air Interface

As sixth-generation (6G) wireless networks evolve toward increasingly heterogeneous scenarios, tasks, and service requirements, conventional artificial intelligence (AI) models remain limited in task-aware decision-making and autonomous adaptation. To address this issue, this paper first proposes a ChannelAgent-empowered electromagnetic space world model, in which wireless intelligence is organized into a closed-loop process consisting of multi-modal sensing, ChannelAgent as the intelligent core, and execution with feedback update. As a case study, agent-driven channel generation is instantiated through path loss prediction. Specifically, a task-oriented intelligent feature selection mechanism is designed by integrating reinforcement-learning-inspired policy adaptation with evolutionary search, enabling the agent to iteratively derive compact and task-suitable feature subsets according to the current scenario and performance feedback. Simulation results demonstrate superior performance in both single-scenario and multi-scenario tasks, highlighting the potential of the proposed model for autonomous, adaptive, task-oriented, and closed-loop wireless intelligence.

eess.SP↗
arXiv2026

Magnetic-field-tunable cyclotron hyperbolic polaritons

Hyperbolic polaritons are conventionally associated with structural anisotropy or phononic Reststrahlen bands. Here, we predict a new class of hyperbolic polaritons arising from magnetic-field-induced cyclotron motion of charge carriers. When a perpendicular magnetic field is applied to high-mobility semimetals, the cyclotron response drives the in-plane dielectric function from metallic- to insulating-like below the cyclotron resonance frequency, while the out-of-plane response remains metallic. This anisotropy creates a hyperbolic dielectric environment that supports field-tunable hyperbolic polaritons. We develop a comprehensive theoretical framework incorporating coupling to other collective excitations and show that these modes can be directly visualized in real space via terahertz near-field nanoscopy. Our work identifies cyclotron motion as a new route to hyperbolic polaritons and establishes a versatile platform for magnetically programmable nanophotonics.

cond-mat.mes-hall↗
arXiv2026

Field re-entrant superconductivity in Eu-doped infinite-layer nickelates

Intertwined superconducting and magnetic orders may give rise to exotic quantum phases, including field-induced and re-entrant superconductivity. However, such magnetism-enhanced superconductivity has remained elusive in superconductors with higher transition temperatures. While infinite-layer nickelates represent a new class of unconventional superconductors, the impact of rare-earth magnetism on superconducting properties remains largely unexplored. Here, we show that Eu-doped infinite-layer nickelate Sm$_{0.95-x}$Ca$_{0.05}$Eu$_x$NiO$_2$ exhibits a magnetic-field-induced re-entrant superconducting phase in the Eu-rich over-doped regime. Zero-resistance transport and high-field diamagnetic screening confirm the superconducting nature of this phase, which emerges after the initial suppression of low-field superconductivity and remains robust across a broad range of temperatures, fields and field orientations. In the same doping range, we observe nonlinear Hall transport and hysteretic magnetoresistance, indicating the unconventional nature of the re-entrant behaviour. While partially consistent with a compensation mechanism between the Eu-derived exchange field and the applied field, our data reveal pronounced deviations from this model at the highest-doping levels. Our findings establish infinite-layer nickelates as a fertile platform for exploring magnetically driven high-field superconductivity in strongly correlated oxides.

cond-mat.supr-con↗
arXiv2026

$3d_{z^2}$ orbital delocalization and magnetic collapse in superconducting (La,Pr)$_3$Ni$_2$O$_{7-δ}$ films

The recent discovery of Ruddlesden--Popper (RP) nickelate thin-film superconductors has opened a new frontier in unconventional superconductivity. Its realization requires both compressive epitaxial strain and highly oxidative growth conditions, yet the microscopic pathway from the parent phase to the superconducting phase remains elusive. Here, X-ray absorption spectra and resonant inelastic X-ray scattering are employed to track this evolution by independently tuning strain and oxygen content in (La,Pr)$_3$Ni$_2$O$_{7-δ}$ thin films. We uncover a remarkable two-step narrative. First, signatures of delocalization emerge in the same way upon two independent tunings: Spectral weight transfers from a ''Upper Hubbard''-like peak to the hole-like peak associated with O $2p_z$ state, and in parallel, the initially localized Ni $3d_{z^2}$ orbital becomes more itinerant followed by the broadening and weakening of $dd$ orbital excitations. Second, as itinerancy increases, long-range spin-density-wave (SDW) order is suppressed in both intensity and correlation length, indicating direct competition with superconductivity. Yet, short-range magnons persist: they become damped but their bandwidth stays unchanged. Our results paint a coherent picture that both strain and oxygenation drive the RP bilayer nickelates towards the superconducting instability, where the O $2p_z$ and Ni $3d_{z^2}$ orbitals become delocalized. Concomitantly, the long-range magnetic order loses coherence and gets suppressed. These findings establish an orbital-selective route to RP nickelate superconductivity, in which the delocalization of the $2p_z$ and $3d_{z^2}$ orbitals and the robust short-range magnons upon the melting of SDW order are prerequisites, providing strong constraints for theory and the roadmap for designing nickelate superconductors.

cond-mat.supr-con↗
arXiv2026

Electronic structures across superconductor-insulator transition in Ruddlesden-Popper bilayer nickelate films

High-transition-temperature ($T_{C}$) superconductivity is recently discovered in Ruddlesden-Popper (RP) nickelate films with extraordinarily strong oxidation. While investigating phase diagrams is essential for uncovering the superconducting mechanism, the oxygen-tuned superconductor-insulator transition (SIT) in RP nickelates differs fundamentally from that in cuprates or iron-based systems. Here, we unveil the evolution of electronic structure in RP bilayer nickelate thin films across the SIT, combining angle-resolved photoemission spectroscopy (ARPES) and X-ray absorption spectroscopy (XAS) for both occupied and unoccupied states. In the superconducting state, a coherent quasiparticle band near Fermi level ($E_{F}$) coexists with an incoherent waterfall feature at high energy, paralleling that in cuprates. Approaching the insulating state with oxygen deficiency, the spectral weight of the occupied coherent quasiparticle band is gradually suppressed, accompanied by pronounced density of states redistribution and orbital reconfiguration in unoccupied states. These results reveal the electronic origin of the SIT in the phase diagram, which transcends carrier doping effects and oxygen vacancy states. Our findings point to a decisive role of oxygen in shaping the essential electronic landscape of RP bilayer nickelates, offering crucial insights into the superconducting mechanism.

cond-mat.supr-con↗
arXiv2026

Superconductivity and Electronic Structures of Nickelate Thin Film Superstructures

Ruddlesden-Popper (RP) nickelates have emerged as a crucial platform for exploring the mechanisms of high-temperature superconductivity. However, the Fermi surface topology required for superconductivity remains elusive. Here, beyond the superconducting pure bilayer (2222) phase, we report the thin film growth and ambient-pressure superconductivity of monolayer-bilayer (1212) and bilayer-trilayer (2323) superstructures, together with the absence of superconductivity in monolayer-trilayer (1313) superstructure, under identical compressive epitaxial strain. The onset superconducting transition temperatures range from 46 to 50 K, exceeding the McMillan limit. Angle-resolved photoemission spectroscopy reveals key Fermi surface differences in these atomically-engineered structures. In superconducting 1212 and 2222 films, a dispersive hole-like band ($γ^{\mathrm{II}}$) forms an underlying Fermi pocket, surrounding the Brillouin zone corner. In contrast, the top of the flat band ($γ^{\mathrm{III}}$) is observed ~70 meV below $E_\text{F}$ in the non-superconducting 1313 films. Particularly, the superconducting 2323 films host both $γ^{\mathrm{II}}$ and $γ^{\mathrm{III}}$ bands. The polarization dependence of the $γ$ bands reveals their Ni $d_{z^2}$ origin. Our findings expand the family of ambient-pressure nickelate superconductors and establish a connection between structural configuration, electronic structure, and the emergence of superconductivity in nickelates.

cond-mat.supr-con↗
arXiv2026

Three-Dimensional Electronic Structures in Superconducting Ruddlesden-Popper Bilayer Nickelate Films

Beyond the quasi-two-dimensional (2D) paradigm of cuprates, the role of the third dimension of the Ruddlesden-Popper bilayer nickelates is essential to decoding their superconducting mechanism. Here, using angle-resolved photoemission spectroscopy (ARPES) with varied photon energies, we systematically investigate the electronic band structures in three dimensions for superconducting (La,Pr,Sm)$_3$Ni$_2$O$_7$/SrLaAlO$_4$ thin films (superconducting onset temperature $T_c^{\text{onset}} \sim 48$ K) transferred via a cryogenic ultra-high vacuum suitcase. We reveal an orbital-dependent dimensionality: while the $d{x^2-y^2}$-dominant bands exhibit a quasi-2D character, the $d{z^2}$-dominant band displays a finite $k_z$ dispersion. Finite energy gaps are identified on all observed bands across multiple high-symmetry directions. Systematic temperature-dependent analysis characterizes the superconducting nature of the gap on the $d{z^2}$-derived band, revealing a large gap $Δ\sim 18$ meV and a ratio $2Δ/k_BT_c\sim 8$ exceeding the weak-coupling BCS limit. The suppression of spectral weight near the Fermi level persists above the superconducting transition temperature. Ubiquitous waterfall-like spectral features evidence the presence of electron interactions. These results underscore the role of the $d_{z^2}$ orbital and correlations, placing constraints on theoretical models for nickelate superconductivity.

cond-mat.supr-con↗
arXiv2026

Finding Quasars behind the Galactic Plane. IV. Candidate Selection from Chandra with Random Forest

Quasar samples remain severely incomplete at low Galactic latitudes because of strong extinction and source confusion. We conduct a systematic search for quasars behind the Galactic plane using X-ray sources from the Chandra Source Catalog (CSC 2.1), combined with optical data from Gaia DR3 and mid-infrared data from CatWISE2020. Using spectroscopically confirmed quasars and stellar-type objects from data sets including DESI, SDSS, and LAMOST, we apply a Random Forest classifier to identify quasar candidates, with stellar contaminants suppressed using Gaia proper-motion constraints. Photometric redshifts are estimated for the candidates using a Random Forest regression model. Applying this framework to previously unclassified CSC sources, we identify 7570 quasar candidates, including 1060 Galactic Plane Quasar (GPQ) candidates at |b|<20°, of which 551 are high-confidence candidates. Relative to the previously known GPQ sample, our selected GPQs reach lower optical and X-ray fluxes, improving sensitivity to low-flux GPQs. In addition, both the GPQ candidates and known GPQs display harder X-ray spectra than the all-sky quasar sample, consistent with increased absorption through the Galactic plane. Pilot spectroscopy confirms two high-confidence GPQ candidates as quasars at spectroscopic redshifts of z=1.2582 and z=1.1313, and further spectroscopic follow-up of the GPQ sample is underway. This work substantially improves the census of GPQs and provides a valuable target sample for future spectroscopic follow-up, enabling the use of GPQs to refine the reference frames for astrometry and probe the Milky Way interstellar and circumgalactic media with the absorption features of GPQs.

astro-ph.GA↗
arXiv2026

Superconductivity onset above 60 K in ambient-pressure nickelate films

Ambient-pressure superconductivity in nickelates has been capped at an onset transition temperature ($T_{c}^{onset}$) of ~50 K, a value that remains lower than the cuprate (~133 K) and iron-based (~55 K) counterparts, despite the promise shown under high pressure. Here, we report ambient-pressure superconductivity onset at ~63 K in epitaxial (La,Pr)3Ni2O7 thin films grown under compressive strain on SrLaAlO4 substrates. This $T_{c}$ leap is enabled by pushing our gigantic-oxidative atomic-layer-by-layer epitaxy (GAE) method into an extreme non-equilibrium growth regime. It simultaneously enhances kinetics via higher temperatures and achieves full oxygenation in situ without post-annealing. Synchrotron X-ray diffraction and scanning transmission electron microscopy confirm that this approach yields films of large-scale crystalline purity, overcoming the inherent metastability of the strained superconducting phase. Transport measurements reveal a zero-resistance temperature ($T_{c}^{zero}$) reaching ~37 K, while mutual inductance measurements demonstrate a robust diamagnetic transition starting at ~23 K. These films exhibit a systematic evolution in their normal-state resistivity-temperature curve: the power-law exponent $α$ evolves from Fermi-liquid-like ($α$ ~2) at lower $T_{c}^{onset}$ to strange-metal-like ($α$ ~1) in higher $T_{c}^{onset}$ samples, directly linking the enhanced superconductivity to non-Fermi liquid behavior. Mapping the vortex melting phase diagram by the mutual inductance technique further reveals 2D melting limit suppressed to near zero, which demonstrates significantly stronger interlayer coupling than that of cuprates. These results identify the nickelates as an ambient-pressure strange-metal high-temperature superconductors with strong interlayer coupling.

cond-mat.supr-con↗
arXiv2026

Adaptation of Agentic AI: A Survey of Post-Training, Memory, and Skills

Large language model (LLM) agents are moving beyond prompting alone. ChatGPT marked the rise of general-purpose LLM assistants, DeepSeek showed that on-policy reinforcement learning with verifiable rewards can improve reasoning and tool use, and OpenClaw highlights a newer direction in which agents accumulate persistent memory and reusable skills. Yet the research landscape remains fragmented across post-training, retrieval, memory, and skill systems. This survey studies these developments under a single notion of \emph{adaptation}: improving an agent, its tools, or their interaction after pretraining. We organize the field with a four-paradigm framework spanning agent adaptation and tool adaptation. On the agent side, A1 (tool-execution-signaled) and A2 (agent-output-signaled) improve the agent itself through supervised fine-tuning, preference optimization, and reinforcement learning with verifiable rewards. On the tool side, T1 (agent-agnostic) provides reusable pre-trained modules any agent can call, while T2 (agent-supervised) uses the agent's outputs to train memory systems, skill libraries, or lightweight subagents. Using this framework, we review post-training methods, adaptive memory architectures, and agent skills; compare their trade-offs in cost, flexibility, and generalization; and summarize evaluation practices across deep research, software development, computer use, and drug discovery. We conclude by outlining open problems in agent-tool co-adaptation, continual learning, safety, and efficient deployment.

cs.AI↗
arXiv2026

MagRobot:An Open Simulator for Magnetically Navigated Robots

Magnetic navigation systems, including magnetic tracking systems and magnetic actuation systems, have shown great potential for occlusion-free localization and remote control of intracorporeal medical devices and robots in minimally invasive medicine, such as capsule endoscopy and cardiovascular intervention. However, the design of magnetically navigated robots remains heavily reliant on experimental prototyping, which is time-consuming and costly. Furthermore, there is a lack of a consistent experimental environment to compare and benchmark the hardware and algorithms across different magnetic navigation systems. To address these challenges, we propose the first universal open-source simulation platform to facilitate research, design and benchmarking of magnetically navigated robots. Our simulator features an intuitive graphical user interface that enables the user to efficiently design, visualize, and analyze magnetic navigation systems for both rigid and soft robots. The proposed simulator is versatile, which can simulate both magnetic actuation and magnetic tracking tasks in diverse medical applications that involve deformable anatomies. The proposed simulator provides an open development environment, where the user can load third-party anatomical models and customize both hardware and algorithms of magnetic navigation systems. The fidelity of the simulator is validated using both phantom and ex vivo experiments of magnetic navigation of a continuum robot and a capsule robot with diverse magnetic actuation setups. Three use cases of the simulator, i.e., bronchoscopy, endovascular intervention, and gastrointestinal endoscopy, are implemented to demonstrate the functionality of the simulator. It is shown that the configuration and algorithms of magnetic navigation systems can be flexibly designed and optimized for better performance using the simulator.

cs.RO↗
arXiv2026

Time-reversal symmetry breaking superconductivity with electronic glass in nickelate (La, Pr, Sm)3Ni2O7 films

The discovery of Ruddlesden-Popper (R-P) nickelate superconductors under high pressure heralds a new chapter of high-transition temperature (high-Tc) superconductivity. Recently, ambient-pressure superconductivity is achieved in R-P bilayer nickelate thin films through epitaxial compressive strain, unlocking the potential for understanding the nature of the unconventional superconductivity. Here, through electrical transport study, we report the discovery of time-reversal symmetry (TRS) breaking superconductivity with electronic glass in bilayer nickelate (La, Pr, Sm)3Ni2O7 films. It emerges in the lower-temperature regime of superconducting transition to the zero-resistance state, and is captured by three remarkable characteristics: 1. Unconventional magnetoresistance hysteresis, the direct evidence of TRS breaking, which is robust under different magnetic field orientations and differs fundamentally from trapped vortices or long-range-ordered magnetism. Successive oxygen reductions simultaneously weaken both the superconductivity and hysteresis, revealing their mutual connections to selective electronic orbitals. 2. Magnetic field history-dependence and zero-field non-reciprocity in the current-voltage responses, further substantiating the intrinsic and spontaneous TRS breaking. 3. Logarithmically slow resistance relaxations upon the removal of magnetic field, the hallmarks of glassy dynamics. Distinguished by the striking magnetic field history- and time-dependent properties, our findings uncover an unprecedented superconducting state in the nickelate superconductors, providing phenomenological and conceptual advances for future research on high-Tc superconductivity.

cond-mat.supr-con↗
arXiv2026

Preparation and optimization of high-temperature superconducting Ruddlesden-Popper nickelate thin films

The discovery of ambient-pressure nickelate high-temperature superconductivity provides a new platform for probing the underlying superconducting mechanisms. However, the thermodynamic metastability of Ruddlesden-Popper nickelates Lnn+1NinO3n+1 (Ln = lanthanide) presents significant challenges in achieving precise control over their structure and oxygen stoichiometry. This study establishes a systematic approach for growing phase-pure, high-quality Ln3Ni2O7 thin films on LaAlO3 and SrLaAlO4 substrates using gigantic-oxidative atomic-layer-by-layer epitaxy. The films grown under an ultrastrong oxidizing ozone atmosphere are superconducting without further post annealing. Specifically, the optimal Ln3Ni2O7/SrLaAlO4 superconducting film exhibits an onset transition temperature (Tc,onset) of 50 K. Four critical factors governing the crystalline quality and superconducting properties of Ln3Ni2O7 films are identified: 1) precise cation stoichiometric control suppresses secondary phase formation; 2) complete atomic layer-by-layer coverage coupled with 3) optimized interface reconstruction minimizes stacking faults; 4) accurate oxygen content regulation is essential for achieving a single superconducting transition and high Tc,onset. These findings provide valuable insights for the layer-by-layer epitaxy growth of diverse oxide high-temperature superconducting films.

cond-mat.supr-con↗
arXiv2026

Improving Implicit Discourse Relation Recognition with Natural Language Explanations from LLMs

Implicit Discourse Relation Recognition (IDRR) remains a challenging task due to the requirement for deep semantic understanding in the absence of explicit discourse markers. A further limitation is that existing methods only predict relations without providing any supporting explanations. Recent advances in large language models (LLMs) have shown strong reasoning capabilities in both deep language understanding and natural language explanation generation. In this work, we propose a simple yet effective approach to distill the reasoning capabilities of LLMs into lightweight IDRR models to improve both performance and interpretability. Specifically, we first prompt an LLM to generate explanations for each training instance conditioned on its gold label. Then, we introduce a novel classification-generation framework that jointly performs relation prediction and explanation generation, and train it with the additional supervision of LLM-generated explanations. Our framework is plug-and-play, enabling easy integration with most existing IDRR models. Experimental results on PDTB demonstrate that our approach significantly improves IDRR performance, while human evaluation further confirms that the generated explanations enhance model interpretability. Furthermore, we validate the generality of our approach on sentiment classification and natural language inference

cs.CL↗
arXiv2026

World Simulation with Video Foundation Models for Physical AI

We introduce [Cosmos-Predict2.5], the latest generation of the Cosmos World Foundation Models for Physical AI. Built on a flow-based architecture, [Cosmos-Predict2.5] unifies Text2World, Image2World, and Video2World generation in a single model and leverages [Cosmos-Reason1], a Physical AI vision-language model, to provide richer text grounding and finer control of world simulation. Trained on 200M curated video clips and refined with reinforcement learning-based post-training, [Cosmos-Predict2.5] achieves substantial improvements over [Cosmos-Predict1] in video quality and instruction alignment, with models released at 2B and 14B scales. These capabilities enable more reliable synthetic data generation, policy evaluation, and closed-loop simulation for robotics and autonomous systems. We further extend the family with [Cosmos-Transfer2.5], a control-net style framework for Sim2Real and Real2Real world translation. Despite being 3.5$\times$ smaller than [Cosmos-Transfer1], it delivers higher fidelity and robust long-horizon video generation. Together, these advances establish [Cosmos-Predict2.5] and [Cosmos-Transfer2.5] as versatile tools for scaling embodied intelligence. To accelerate research and deployment in Physical AI, we release source code, pretrained checkpoints, and curated benchmarks under the NVIDIA Open Model License at https://github.com/nvidia-cosmos/cosmos-predict2.5 and https://github.com/nvidia-cosmos/cosmos-transfer2.5. We hope these open resources lower the barrier to adoption and foster innovation in building the next generation of embodied intelligence.

cs.CV↗
arXiv2026

Step 3.5 Flash: Open Frontier-Level Intelligence with 11B Active Parameters

We introduce Step 3.5 Flash, a sparse Mixture-of-Experts (MoE) model that bridges frontier-level agentic intelligence and computational efficiency. We focus on what matters most when building agents: sharp reasoning and fast, reliable execution. Step 3.5 Flash pairs a 196B-parameter foundation with 11B active parameters for efficient inference. It is optimized with interleaved 3:1 sliding-window/full attention and Multi-Token Prediction (MTP-3) to reduce the latency and cost of multi-round agentic interactions. To reach frontier-level intelligence, we design a scalable reinforcement learning framework that combines verifiable signals with preference feedback, while remaining stable under large-scale off-policy training, enabling consistent self-improvement across mathematics, code, and tool use. Step 3.5 Flash demonstrates strong performance across agent, coding, and math tasks, achieving 85.4% on IMO-AnswerBench, 86.4% on LiveCodeBench-v6 (2024.08-2025.05), 88.2% on tau2-Bench, 69.0% on BrowseComp (with context management), and 51.0% on Terminal-Bench 2.0, comparable to frontier models such as GPT-5.2 xHigh and Gemini 3.0 Pro. By redefining the efficiency frontier, Step 3.5 Flash provides a high-density foundation for deploying sophisticated agents in real-world industrial environments.

cs.CL↗
arXiv2026

Bosonic phases across the superconductor-insulator transition in infinite-layer samarium nickelate

Superconductivity arises from the global phase coherence of Cooper pairs. Modulation of phase coherence leads to quantum phase transitions, serving as an important tool for studying unconventional superconductivity. Here, we demonstrate bosonic phases across the superconductor-insulator transition in infinite-layer nickelate superconducting films by the control of spatially periodic network patterns. Magnetoresistance oscillations with a periodicity of h/2e provide direct evidence of 2e Cooper pairing in nickelates. The phase transition is predominantly driven by enhanced superconducting fluctuations, and Cooper pairs are involved in charge transport across the transition. Notably, we observe two types of anomalous metallic phases, emerging respectively at finite magnetic fields and down to zero magnetic field. They can be characterized by bosonic excitations, suggesting the dynamic roles of vortices in the ground states. Our work establishes nickelates as a key platform for investigating the rich landscape of bosonic phases controlled via the phase coherence of Cooper pairs.

cond-mat.supr-con↗