Showing 1–50 of 238 results for author: Jiang, Z

Multi-Agent Closed-Loop Reasoning for Organic Structure Elucidation from Multimodal Spectra

Authors: Bingsen Xue, Zhuojun Jiang, Jianhao Zhang, Mingcheng Gu, Yizhe Yuan, Yongtai Zhuo, Yifan Zhang, Li Wang, Ya Su, Yue Yuan, Jiang Liu, Xueqian Kong, Cheng Jin

Abstract: Following the molecular discovery and synthesis revolutions, scalable automated structure elucidation from routine spectroscopic data remains an outstanding challenge. Despite decades of computational efforts, no existing system achieved reliable reasoning over unseen spectra. Here, we propose MACROS, a multi-agent system automating structure elucidation by emulating expert iterative hypothesis-te… ▽ More Following the molecular discovery and synthesis revolutions, scalable automated structure elucidation from routine spectroscopic data remains an outstanding challenge. Despite decades of computational efforts, no existing system achieved reliable reasoning over unseen spectra. Here, we propose MACROS, a multi-agent system automating structure elucidation by emulating expert iterative hypothesis-testing. Trained on 100M simulated and 1.6M experimental spectra-molecule pairs, it natively supports arbitrary combinations of routine spectroscopic techniques. It achieves unprecedented zero-shot generalization to diverse real-world samples, correctly identifying synthetic compounds, natural products and metabolites above 500 Da with 1D NMR. Remarkably, MACROS spontaneously recovers textbook spectroscopic correlations from unassigned data and exhibits emergent chemical intuition such as a ring-first parsing preference, learning fundamental chemical principles rather than memorizing database patterns. MACROS augments chemists via collaboration to deliver sixfold faster, 40% more accurate elucidation. MACROS establishes a scalable foundation for fully automated structure elucidation, and catalyzes accelerated molecular discovery toward autonomous laboratories. △ Less

Submitted 12 August, 2026; originally announced August 2026.

Micro- and nanoscale focusing across the XUV range of the ASTRID2 light source with a capillary optic

Authors: Alfred J. H. Jones, Zhihao Jiang, Asger Petersen, Søren V. Hoffmann, Nykola C. Jones, Philip Hofmann, Jill A. Miwa, Søren Ulstrup

Abstract: Focusing of synchrotron light across extreme ultraviolet (XUV) and soft X-ray regimes is increasingly desired for photoemission-based techniques where reduced beam width gives access to smaller samples such as microscopic single crystals and functioning two-dimensional (2D) heterostructures and devices. Many existing focusing methods, however, are not able to take full advantage of the synchrotron… ▽ More Focusing of synchrotron light across extreme ultraviolet (XUV) and soft X-ray regimes is increasingly desired for photoemission-based techniques where reduced beam width gives access to smaller samples such as microscopic single crystals and functioning two-dimensional (2D) heterostructures and devices. Many existing focusing methods, however, are not able to take full advantage of the synchrotron beam due to limited photon energy range or low transmission. Modern capillary optics have enabled achromatic, high transmission focusing of XUV and X-ray light. Here, we present a detailed characterisation of such an achromatic capillary optic installed at the AU-SGM4 beamline for spatial- and angle-resolved photoemission spectroscopy (ARPES) experiments at the ASTRID2 light source. The transmission of the capillary as a function of photon energy is given, and the dependence of the beam width, position, and transmission are measured against the source size. Analysis of the far-field image of the beam allows for slope errors on the inner surface of the capillary to be overcome by selectively aperturing the beam, resulting in a minimum beam width of 900 nm measured in a photoemission geometry. △ Less

Submitted 13 August, 2026; originally announced August 2026.

Active Passivation Tunes Hotspot Locations in GaN Transistors with In Situ Thermal Mechanical Visualization

Authors: Yicheng Wei, Sihang Liu, Zimu Jiang, jinquan Zhang, Zifeng Huang, Han Yang, Yang He, Jin Wei, Zhe Cheng

Abstract: Efficient thermal dissipation has become critical in emerging electronic devices. However, most existing studies have primarily focused on engineering heat dissipation pathways, largely overlooking the intrinsic behavior of the heat source itself. We demonstrate an active passivation technology that proactively tunes hotspot locations in GaN transistors. By adjusting the active passivation layer l… ▽ More Efficient thermal dissipation has become critical in emerging electronic devices. However, most existing studies have primarily focused on engineering heat dissipation pathways, largely overlooking the intrinsic behavior of the heat source itself. We demonstrate an active passivation technology that proactively tunes hotspot locations in GaN transistors. By adjusting the active passivation layer length, the hotspot is shifted from the gate edge to the drain-side AP edge, establishing a clear one-to-one spatial correlation. In-situ thermal-mechanical visualization via micro-Raman thermography, combined with multi-physics electro-thermal-mechanical simulations, directly captures the spatial redistribution of both temperature and thermal stress profiles. Electrical analysis confirms that this hotspot migration is driven by the spatial shift of the peak electric field and localized Joule heating. This proactive heat-source tuning strategy provides critical design guidelines for power electronics. △ Less

Submitted 2 August, 2026; originally announced August 2026.

Transition-Aware Routing in Hybrid Hollow-Core/Single-Mode Fiber Networks: A Cost--Throughput Investigation

Authors: Md Ghulam Saber, Zhiping Jiang

Abstract: Incremental deployment of hollow-core fiber (HCF) in single-mode-fiber (SMF) networks introduces a routing tradeoff: reducing HCF-SMF transitions can improve physical-layer feasibility, but overly transition-averse routing incurs harmful path detours. We study this tradeoff using a common event-driven simulator that compares six protected routing schemes spanning fiber-blind, generalized signa… ▽ More Incremental deployment of hollow-core fiber (HCF) in single-mode-fiber (SMF) networks introduces a routing tradeoff: reducing HCF-SMF transitions can improve physical-layer feasibility, but overly transition-averse routing incurs harmful path detours. We study this tradeoff using a common event-driven simulator that compares six protected routing schemes spanning fiber-blind, generalized signal-to-noise ratio (GSNR)-aware, and explicitly transition-aware designs on hybrid HCF/SMF topologies. The model includes a per-transition GSNR penalty and an exploratory splice-failure availability term. Across six reference topologies, five HCF deployment fractions, and dynamic loads at 300 Erlang, the strongest transition minimizers, transition-penalty-aware routing (TPAR) and the GSNR/fiber-transition joint scheme (GFJ), halve the mean transition count at a 20-25% carried-traffic penalty. Among the intermediate designs, GSNR- maximal routing with transition-aware reranking (GMR-T) cuts transitions by approximately 22% relative to distance-adaptive routing and spectrum assignment (DA-RSA) at a 3% throughput cost, while bounded-detour TPAR (BD-TPAR) cuts transitions by approximately 11% at only a 1% cost. Deployment pattern also matters: contiguous HCF rollout lowers transitions by approximately 40% on average while improving carried traffic, reducing the benefit of aggressive transition-aware routing. These results support BD-TPAR as a practical default under fragmented deployment, GMR-T as a lower-complexity alternative, and TPAR or GFJ only where the external cost of transitions is high. △ Less

Submitted 15 July, 2026; originally announced July 2026.

Beyond Silica Assumptions: Optical Network Design in the Hollow-Core Era

Authors: Md Ghulam Saber, Zhiping Jiang

Abstract: Hollow-core fiber (HCF) is often presented as a modestly improved transmission medium that can be inserted into networks originally designed for solid-core silica. We argue instead that recent progress -- most notably the reported attenuation below 0.1 dBkm$^{-1}$, together with a broad low-loss window, reduced propagation delay, and extremely low optical nonlinearity -- makes it timely to reconsi… ▽ More Hollow-core fiber (HCF) is often presented as a modestly improved transmission medium that can be inserted into networks originally designed for solid-core silica. We argue instead that recent progress -- most notably the reported attenuation below 0.1 dBkm$^{-1}$, together with a broad low-loss window, reduced propagation delay, and extremely low optical nonlinearity -- makes it timely to reconsider which long-standing design conventions are fundamental to optical communication and which are specific to silica fiber. By reviewing implications at the physical-layer, transceiver, and network-architecture levels, we suggest that the most durable benefits of HCF may arise not from its use as a drop-in replacement, but from cross-layer co-design. We also outline the studies and experimental demonstrations needed to determine where such advantages are genuinely achievable. △ Less

Submitted 7 July, 2026; originally announced July 2026.

Journal ref: Photonics (MDPI) 2026

Calibration of systematic distortions in quantum emitter localization microscopy for deterministic nanophotonic fabrication

Authors: Chenxi Ma, Maximilian Heller, Timon Handrup, Yiteng Zhang, Tobias M. Krieger, Thomas Oberleitner, Zenghui Jiang, Xian Zheng, Eddy P. Rugeramigabo, Folke Dencker, Armando Rastelli, Fei Ding, Michael Zopf

Abstract: Quantum photonic technologies greatly benefit from quantum light emitters with high brightness, indistinguishability, and reliable polarization characteristics. Achieving optimal performance relies on the accurate localization of emitters and their deterministic integration into tailored photonic structures with nanometer-scale accuracy. Although marker-based photoluminescence imaging techniques c… ▽ More Quantum photonic technologies greatly benefit from quantum light emitters with high brightness, indistinguishability, and reliable polarization characteristics. Achieving optimal performance relies on the accurate localization of emitters and their deterministic integration into tailored photonic structures with nanometer-scale accuracy. Although marker-based photoluminescence imaging techniques can achieve statistical fitting uncertainties below 10 nm, the ultimate integration yield is often limited by uncorrected systematic distortions in custom cryo-optical setups that compromise metrological accuracy. Here, we present an in situ calibration protocol that uses lithographically defined gold nanodisk arrays as references to calibrate optical distortions with a Zernike vector-field model. On held-out validation patterns beyond the calibration dataset, this correction reduces the residual systematic bias to 5.3 nm with a 2D scatter of 24.6 nm across the analyzed field of view. Furthermore, we demonstrate that applying this correction to the deterministic fabrication of circular mesa structures around semiconductor quantum dots reduces the variance in emission polarization by 49%, indicating improved registration accuracy. This calibration strategy offers a practical route to high-yield deterministic integration of quantum emitters into scalable quantum photonic circuits. △ Less

Submitted 6 July, 2026; originally announced July 2026.

Binary Dipolar Condensates of Dysprosium Isotopes with Tunable Spatial Order

Authors: Shenshuang Nie, Zibin Jiang, Junrong Huang, Xiao Luo, Fucheng Qin, Kaiyue Wang, Mingyang Guo

Abstract: Dipolar quantum mixtures provide a route to many-body phases in which long-range anisotropic interactions couple with density, composition and spatial order. Here we realize a new quantum-degenerate dipolar mixture of $^{162}$Dy and $^{164}$Dy in a single-species-like apparatus. The mixture combines nearly matched single-particle Hamiltonians, tunable interactions and composition parameters, and i… ▽ More Dipolar quantum mixtures provide a route to many-body phases in which long-range anisotropic interactions couple with density, composition and spatial order. Here we realize a new quantum-degenerate dipolar mixture of $^{162}$Dy and $^{164}$Dy in a single-species-like apparatus. The mixture combines nearly matched single-particle Hamiltonians, tunable interactions and composition parameters, and isotope-resolved characterization. Tuning the interaction balance and relative composition reorganizes the coupled condensates from a miscible state into core--shell-like, side-by-side, and exchanged core--shell-like immiscible configurations. These results establish dysprosium isotope mixtures as a compact and versatile platform for multicomponent dipolar quantum matter, ranging from impurity physics to binary supersolidity. △ Less

Submitted 30 June, 2026; v1 submitted 25 June, 2026; originally announced June 2026.

Comments: 11 pages, 4+4 figures

Protection Switching in Hybrid Hollow-Core and Single-Mode Fiber Networks: Challenges, Analysis, and Mitigation Strategies

Authors: Md Ghulam Saber, Zhiping Jiang

Abstract: Hollow-core fibers (HCF) are transitioning from laboratory curiosities to production-deployed infrastructure, with cloud providers operating thousands of kilometers of hollow-core links. As operators upgrade their networks, working and protection paths will inevitably traverse different fiber types, creating a class of protection switching challenges absent in homogeneous single-mode fiber network… ▽ More Hollow-core fibers (HCF) are transitioning from laboratory curiosities to production-deployed infrastructure, with cloud providers operating thousands of kilometers of hollow-core links. As operators upgrade their networks, working and protection paths will inevitably traverse different fiber types, creating a class of protection switching challenges absent in homogeneous single-mode fiber networks. This article provides a comprehensive overview of these challenges and presents a comparative analysis of protection switching under two architectures - 1+1 dedicated and shared backup path protection (SBPP) - in hybrid hollow-core and single-mode fiber networks. Using Monte Carlo simulation with random per-link fiber assignment across six reference topologies (1,602 node pairs), we quantify chromatic dispersion (CD) steps, generalized signal-to-noise ratio (GSNR) penalties, and modulation-format degradation for both architectures. At 50% HCF deployment mean CD steps range from 4,000 to 22,000 ps/nm, with GSNR penalties of 1.6-3.1 dB and 38-59% of node pairs requiring modulation downgrade under 1+1 protection. A complementary cross-fiber extreme analysis reveals that the two switching directions are fundamentally asymmetric: HCF-to-SMF switching doubles the CD step and inflicts about a 10 dB GSNR penalty while SMF-to-HCF switching delivers a negative GSNR penalty (the protection path is higher quality than the working path). SBPP shows up to 7% higher CD steps and 4 percentage points more downgrade in sparsely connected topologies due to its greedy shortest-first path selection. Capacity retention improves with HCF penetration for both architectures, reaching 85-99% at full HCF deployment. We present mitigation strategies including DSP pre-loading, spectral pre-equalization, and network planning guidelines, concluding that 1+1 dedicated protection is preferable to SBPP for hybrid deployments. △ Less

Submitted 22 June, 2026; originally announced June 2026.

System-Level Limits of Higher-Order QAM in Hollow-Core Fiber Systems

Authors: Md Ghulam Saber, Zhiping Jiang

Abstract: Hollow-core fiber (HCF) is widely expected to enable higher-order quadrature amplitude modulation (QAM) because of its near-vacuum Kerr nonlinearity and higher launch power. We develop a per-channel effective signal-to-noise ratio (SNR) budget that combines, in reciprocal form, optical-link impairments including amplified spontaneous emission, Kerr nonlinear interference (NLI), inter-modal interfe… ▽ More Hollow-core fiber (HCF) is widely expected to enable higher-order quadrature amplitude modulation (QAM) because of its near-vacuum Kerr nonlinearity and higher launch power. We develop a per-channel effective signal-to-noise ratio (SNR) budget that combines, in reciprocal form, optical-link impairments including amplified spontaneous emission, Kerr nonlinear interference (NLI), inter-modal interference (IMI), pigtail NLI, and CO2 gas absorption; a parameterized, symbol-rate-dependent transceiver back-to-back SNR ceiling determined by effective-number-of-bits at rate, analog bandwidth, and Tx/Rx nonlinearity; and the remaining transceiver and line impairments, including laser phase noise, equalization-enhanced phase noise, timing jitter, polarization-dependent loss, and amplifier gain ripple with filter narrowing, each expressed as an equivalent SNR floor. The central result, at a representative 64GBaud system with 75GHz channel spacing over 6THz, is that once HCF removes the fiber limits, the transceiver ceiling rather than the fiber sets the achievable modulation order: a roughly 25dB ceiling at 64GBaud makes 1024-QAM and above infeasible on either fiber, confining ultra-high-order QAM to low baud rates. HCF therefore provides its main advantage in reach and achievable baud rate at a given modulation order: at an IMI coefficient of kappa=-55dB/km, 256-QAM reach increases from about 45km to about 170km and 64-QAM reach from about 415km to about 2275km when moving from single-mode fiber to HCF. In the C-band, CO2 absorption lines are weak and sparse, so channels placed away from the lines follow the gas-free baseline, while only worst-case placements lose reach at long distances. In the L-band, the stronger absorption bands are denser than the channel bandwidth, making line avoidance spectrally costly, and a channel placed on a line loses one to two QAM orders. △ Less

Submitted 21 July, 2026; v1 submitted 22 June, 2026; originally announced June 2026.

Journal ref: Journal of Lightwave Technology, 2026

Hollow-Core Fiber in Direct-Detection Optical Networks: Technology Readiness, Deployment Drivers, and Adoption Outlook

Authors: Md Ghulam Saber, Zhiping Jiang

Abstract: This paper presents a comprehensive analysis of hollow-core fiber (HCF) for intensity-modulation and direct-detection (IMDD) optical networks, covering fiber-level physics, system-level performance, and deployment economics. We quantify the three principal advantages of anti-resonant HCF over standard single-mode fiber (SMF) for IMDD: (i) chromatic dispersion of 2-4 ps/(nm km) versus 17 ps/(nm km)… ▽ More This paper presents a comprehensive analysis of hollow-core fiber (HCF) for intensity-modulation and direct-detection (IMDD) optical networks, covering fiber-level physics, system-level performance, and deployment economics. We quantify the three principal advantages of anti-resonant HCF over standard single-mode fiber (SMF) for IMDD: (i) chromatic dispersion of 2-4 ps/(nm km) versus 17 ps/(nm km), which shifts the first dispersion-induced power-fading null from about 10 GHz to 20-28 GHz at 40 km, extending the dispersion-limited reach by 4-8x; (ii) a nonlinear coefficient approximately 1,000x lower than silica, permitting launch powers of +10 to +20 dBm and yielding 7-17 dB of additional link budget; and (iii) a group index near unity (ng about 1.003), reducing propagation latency by 31%. We further analyze inter-modal interference (IMI) as the dominant impairment for HCF-based IMDD. We show that differential modal attenuation (DMA) exceeding 12 dB/km suppresses IMI-induced crosstalk below the -30 dB multipath interference threshold required for PAM4. The reduced dispersion also lowers the required feed-forward equalizer (FFE) tap count by 3-6x, directly decreasing noise enhancement penalty and DSP complexity. A deployment cost model across five application scenarios - intra-data center, campus DCI, metro DCI, 5G fronthaul, and PON - reveals that fiber cable constitutes only 5-10% of outside-plant deployment cost, and that coherent transceiver avoidance savings of $1000 to $2000 per transceiver can offset the current HCF premium at metro distances. We provide a technology adoption roadmap indicating that HCF is economically justified now for intra-DC and campus DCI, with metro DCI following in 2027-2030 as manufacturing costs continue to decline. △ Less

Submitted 22 June, 2026; originally announced June 2026.

Journal ref: IEEE Network, 2026

Isometrization of Tensor Network States via Gauge Propagation

Authors: Zhiyu Jiang, Hiroshi Ueda

Abstract: We introduce a gauge-propagation approach for approximately converting generic tensor-network states into an isometric tensor-network form with a prescribed orthogonality center. In one dimension, this propagation is exact because the non-isometric factor produced by a QR or singular-value decomposition is supported on a single virtual bond. In higher-dimensional networks, however, a local step ca… ▽ More We introduce a gauge-propagation approach for approximately converting generic tensor-network states into an isometric tensor-network form with a prescribed orthogonality center. In one dimension, this propagation is exact because the non-isometric factor produced by a QR or singular-value decomposition is supported on a single virtual bond. In higher-dimensional networks, however, a local step can have several outgoing directions, and the residual factor is generally not separable into independent single-bond contributions. We address this local obstruction by approximating a local tensor, or a contracted local cluster, by structured terms consisting of an isometric factor multiplied by a tensor product of output-leg factors. The isometric factor is retained at the current site or cluster, while the output-leg factors are absorbed into neighboring tensors along the propagation directions. This construction applies to general local input-output partitions for which the input-side dimension is no smaller than the output-side dimension and provides a local truncation criterion for gauge propagation. Benchmarks on random tensors show that the proposed decomposition is effective in the low-term regime and that the residual decreases for larger local clusters. For the loop-gas tensor representation of the Kitaev spin liquid, two structured terms reduce the local residual to numerical precision, and the same cluster refinement further lowers the leading-term truncation error and reduces error accumulation during gauge propagation on a finite honeycomb network. These results identify a propagation-compatible local decomposition as a useful building block for approximate isometrization and as a potential initializer or preconditioner for variational isoTNS algorithms. △ Less

Submitted 19 August, 2026; v1 submitted 21 June, 2026; originally announced June 2026.

Comments: 17 pages, 6 figures, 1 table

Empowering Polymeric Materials Discovery by Artificial Intelligence

Authors: Chenyao Ma, Linda Zhang, Yuheng Chen, Wei Du, Shangwen Fang, Zihao Jiang, Chuanyu Liu, Xinyu Ma, Rui Su, Gang Wang, Muyao Yu, Dong Zhong, Jie Zhu, Weibo Gong, Huan Gu, Limin Li, Chen Shen, Rui Wu, Zhenghao Wu, Kan Xu, Min Zhou, Donglin He, Xiayun Huang, Shan Jiang, Pengfei Ou , et al. (7 additional authors not shown)

Abstract: Polymeric materials underpin modern technologies spanning energy storage, microelectronics, healthcare and sustainable manufacturing. Yet their rational design remains exceptionally challenging because material performance emerges from complex interactions among molecular composition, chain architecture, processing history and hierarchical structural evolution across multiple length and time scale… ▽ More Polymeric materials underpin modern technologies spanning energy storage, microelectronics, healthcare and sustainable manufacturing. Yet their rational design remains exceptionally challenging because material performance emerges from complex interactions among molecular composition, chain architecture, processing history and hierarchical structural evolution across multiple length and time scales. Consequently, polymer research has long relied on labor-intensive experimentation and fragmented modeling approaches, limiting both mechanistic understanding and innovation efficiency. Recent advances in data infrastructure, machine learning, large artificial intelligence (AI) models and laboratory automation are beginning to reshape this landscape. Rather than functioning as isolated tools, polymer databases, predictive models, AI agents and automated laboratories are increasingly converging into interconnected discovery ecosystems. As a result, the central challenge is shifting from improving predictive accuracy alone to enabling reliable decision-making, adaptive learning and seamless integration across computation, experimentation and scientific reasoning. We argue that polymer science is entering an era of autonomous discovery, in which data, simulation, reasoning and experimentation operate within self-improving feedback loops that continuously generate hypotheses, design materials, execute experiments and refine predictive models. By unifying molecular design, process optimization, experimental validation and industrial translation, such autonomous ecosystems establish a more predictive, reproducible and scalable paradigm for polymer innovation, fundamentally transforming how polymer research is conducted. △ Less

Submitted 16 August, 2026; v1 submitted 18 June, 2026; originally announced June 2026.

Layer-Resolved Nonlinear Optics in Finite-Thickness Two-Dimensional Systems

Authors: Liangting Ye, Chengzhi Wu, Zeyu Jiang, Bing Huang

Abstract: Nonlinear optical (NLO) responses in two-dimensional quantum-confined systems are typically described within bulk-based frameworks as macroscopic spatial averages. In finite-thickness van der Waals multilayers directly relevant to nanoscale devices, this picture substantially breaks down. Here, we establish a general symmetry-based framework for classifying second-order NLO responses in multilayer… ▽ More Nonlinear optical (NLO) responses in two-dimensional quantum-confined systems are typically described within bulk-based frameworks as macroscopic spatial averages. In finite-thickness van der Waals multilayers directly relevant to nanoscale devices, this picture substantially breaks down. Here, we establish a general symmetry-based framework for classifying second-order NLO responses in multilayers. We reveal a layer-resolved organization into skin, weak-skin, and hidden effects governed by local symmetry and stacking order. First-principles calculations for both nonmagnetic and spin-polarized systems confirm our predictions, demonstrating that stacking alone suffices to dramatically reshape both the spatial pattern and magnitude of the NLO response, a phenomenon not explainable within standard bulk theory. Our results establish stacking geometry as an effective knob for engineering surface-selective NLO responses in layered materials. △ Less

Submitted 1 June, 2026; originally announced June 2026.

Comments: 9 pages, 5 figures

Prebiotic magnetite enables chirality-magnetic surface feedback

Authors: Jose A. P. M. Devienne, Ziwei Liu, Clancy Z. Jiang, Nicholas J. Tosca, Thomas Ginnis, Dimitar D. Sasselov, Richard J. Harrison, S. Furkan Ozturk

Abstract: The emergence of biomolecular homochirality requires both an initial symmetry-breaking event and a mechanism to amplify and preserve a chiral imbalance. Magnetic minerals have been shown to function as chiral agents through the chiral-induced spin selectivity (CISS) effect and may have enabled homochirality on early Earth, yet the magnetic properties of magnetite formed under realistic prebiotic c… ▽ More The emergence of biomolecular homochirality requires both an initial symmetry-breaking event and a mechanism to amplify and preserve a chiral imbalance. Magnetic minerals have been shown to function as chiral agents through the chiral-induced spin selectivity (CISS) effect and may have enabled homochirality on early Earth, yet the magnetic properties of magnetite formed under realistic prebiotic conditions remain unexplored. Here we show that magnetite synthesized through two geochemically plausible pathways - UV-driven photo-oxidation and nitrite-mediated oxidation of Fe(II) - produces particles dominated by single-vortex and multi-vortex magnetic domain states. Magnetic measurements and electron microscopy confirm that these populations differ markedly from the nano-fabricated thin-film substrates conventionally used in previous CISS experiments. Using 3D micromagnetic simulations, we demonstrate that single-domain and vortex-state grains undergo irreversible, exchange-driven re-magnetization when interacting with spin-polarized homochiral compounds. This magnetic irreversibility provides a robust mechanism for storing and reinforcing weak chiral bias, suggesting that prebiotic magnetite could have contributed to the emergence and stabilization of persistent chiral bias on the early Earth. △ Less

Submitted 19 May, 2026; originally announced May 2026.

Programmable cavity-enhanced telecom quantum memory in thin-film lithium niobate

Authors: Chengdong Yang, Hanwen Guo, Yu-Yang An, Qian He, Chi Lu, Ziheng Jiang, Yan-Qing Lu, Shining Zhu, Xiao-Song Ma

Abstract: Spectrally multiplexed telecom quantum networks require quantum memories combining efficient storage with programmable frequency addressing. An integrated implementation should therefore unite a native telecom transition, efficient storage, and fast on-chip spectral control. Here we demonstrate a cavity-enhanced memory in an isotopically purified $^{167}\mathrm{Er}^{3+}$-doped thin-film lithium ni… ▽ More Spectrally multiplexed telecom quantum networks require quantum memories combining efficient storage with programmable frequency addressing. An integrated implementation should therefore unite a native telecom transition, efficient storage, and fast on-chip spectral control. Here we demonstrate a cavity-enhanced memory in an isotopically purified $^{167}\mathrm{Er}^{3+}$-doped thin-film lithium niobate microring. Long-lived hyperfine shelving states enable persistent, high-contrast atomic frequency comb preparation with a single-component lifetime of $277.6(52.6)$~s, while cavity impedance matching yields $23.3(5)\%$ on-chip efficiency for 100-ns storage. The intrinsic electro-optic response enables frequency-selective storage and routing at rates up to 20~MHz. We further store and retrieve time-energy-entangled telecom photons, violating an entanglement-witness bound by more than 11 standard deviations. Our results establish erbium-doped thin-film lithium niobate as a programmable light--matter interface for spectrally multiplexed quantum networks. △ Less

Submitted 15 July, 2026; v1 submitted 14 May, 2026; originally announced May 2026.

Comments: 29 pages, 24 figures

Revealing dynamics of non-autonomous complex systems from data

Authors: Chengzuo Zhuge, Zheng Jiang, Zhefan Xu, Wei Chen

Abstract: Discovering governing equations from data is crucial for understanding complex systems in many diverse fields from science to engineering. Yet, there still is a lack of versatile computational toolbox to deal with this long standing challenge due to the inherent non-autonomicity and unknowability of the underlying dynamics. Here, we introduce a data-driven approach for inferring non-autonomous dyn… ▽ More Discovering governing equations from data is crucial for understanding complex systems in many diverse fields from science to engineering. Yet, there still is a lack of versatile computational toolbox to deal with this long standing challenge due to the inherent non-autonomicity and unknowability of the underlying dynamics. Here, we introduce a data-driven approach for inferring non-autonomous dynamical equations by identifying an optimal set of basis functions within the model space, enabling the reconstruction of complex systems behavior under simplified prior specifications. Our method demonstrates effectiveness in equation discovery on canonical synthetic systems such as cusp bifurcation and coupled Kuramoto oscillators. Furthermore, we extend the application of this approach to leaf cellular energy, unmanned aerial vehicle navigation, chick-heart aggregates, and marine fish community under simple basis function libraries. Leveraging the inferred equations, we accurately predict the evolution of these empirical systems and further uncover their governing laws. Our approach offers a novel paradigm to reveal the underlying dynamics of a wide range of real-world systems. △ Less

Submitted 10 May, 2026; originally announced May 2026.

Stable Charge Collection and Sub-45 ps Time Resolution in a 4H-SiC PIN Detector Irradiated With Low Fluence 16.5 MeV/u Ta Ions

Authors: Jingxuan He, Congcong Wang, Yi Zhan, Zhenyu Jiang, Xiyuan Zhang, Xin Shi

Abstract: A silicon carbide PIN detector was fabricated and its radiation tolerance under Ta heavy ion irradiation of 2370 MeV was evaluated. Its electrical properties, charge collection performance and time resolution of $β$-particles ($^{90}$Sr) are reported. The leakage currents for unirradiated and irradiated 4H-SiC PIN detectors are $1.47 \times 10^{-10}$~A @ 300 V and 1.49~$\times$ 10$^{-10}$A@ 300 V.… ▽ More A silicon carbide PIN detector was fabricated and its radiation tolerance under Ta heavy ion irradiation of 2370 MeV was evaluated. Its electrical properties, charge collection performance and time resolution of $β$-particles ($^{90}$Sr) are reported. The leakage currents for unirradiated and irradiated 4H-SiC PIN detectors are $1.47 \times 10^{-10}$~A @ 300 V and 1.49~$\times$ 10$^{-10}$A@ 300 V. The effective doping concentrations for unirradiated and irradiated 4H-SiC PIN detectors are $6.23\times 10^{13}$~cm$^{-3}$ and $6.13\times 10^{13}$~cm$^{-3}$. The irradiated detector exhibits good electrical performance and stable device architecture. The 4H-SiC PIN detector exhibits a charge collection efficiency (CCE) of 99.24\% under Ta Heavy Ion Irradiation. The time resolutions of the detector before and after irradiation are 40 ps and 45 ps, respectively. Experimental results indicate that the CCE and time resolution performance exhibit good stability before and after irradiation. These results demonstrate stable performance under Ta heavy ion irradiation, highlighting the detectors potential for radiation-hard applications in high-energy physics, space missions, and nuclear reactor monitoring. △ Less

Submitted 13 May, 2026; originally announced May 2026.

Development of embedded target detection system based on FPGA and YOLOv3-Tiny

Authors: Zihan Jiang, Fanghao Liu, Huawei Wang, Mamataziz Mattohti, Xiangquan Chen, Jingfu Guo, Xiaotian Wu, Yongjun Dong

Abstract: Computational complexity and storage requirements are crucial factors influencing the performance and efficiency of convolutional neural networks (CNNs) in resource-constrained environments. This paper presents a high-performance embedded target detection system based on FPGA and YOLOv3-Tiny, specifically designed for embedded artificial intelligence applications. By integrating lightweight CNN op… ▽ More Computational complexity and storage requirements are crucial factors influencing the performance and efficiency of convolutional neural networks (CNNs) in resource-constrained environments. This paper presents a high-performance embedded target detection system based on FPGA and YOLOv3-Tiny, specifically designed for embedded artificial intelligence applications. By integrating lightweight CNN optimization techniques with hardware accelerator design, significant improvements are made in both computational efficiency and resource utilization. Key optimizations, including low-bit quantization, batch normalization fusion, and table lookup mapping, reduce model parameters and computational complexity. Additionally, an FPGA hardware accelerator with a pipelined architecture is developed to enhance the efficiency of convolution operations while minimizing off-chip data transmission through modular design and on-chip cache optimization. On the ZYNQ-XC7Z035 platform, the system achieves an inference latency of 0.211 seconds, outperforming comparable designs by 75.58% in speed. The system achieves an power efficiency of 10.11 GOPS/W, surpassing comparable designs by at least 29.45%. Furthermore, hardware resource utilization is reduced by up to 51.94% compared to similar systems. This study offers innovative design methodologies and practical application examples for the efficient deployment of deep learning models on embedded platforms. △ Less

Submitted 7 May, 2026; originally announced May 2026.

Stability of Charge Collection Efficiency in a Novel Graphene-Optimized Silicon Carbide Detector Under 160 keV X-Ray Irradiation

Authors: Yingjie Huang, Congcong Wang, Jingxuan He, Yi Zhan, Zhenyu Jiang, Xiyuan Zhang, Xin Shi

Abstract: A novel graphene-optimized silicon carbide PIN detector was fabricated. Its electrical properties, charge collection performance and signal rise time were evaluated under non-irradiated conditions and under X-ray irradiation with an energy of 160 keV at doses of 0.1 MGy and 1 MGy. The leakage currents of the detectors under non-irradiated, 0.1 MGy, and 1 MGy irradiation conditions are approximatel… ▽ More A novel graphene-optimized silicon carbide PIN detector was fabricated. Its electrical properties, charge collection performance and signal rise time were evaluated under non-irradiated conditions and under X-ray irradiation with an energy of 160 keV at doses of 0.1 MGy and 1 MGy. The leakage currents of the detectors under non-irradiated, 0.1 MGy, and 1 MGy irradiation conditions are approximately 1.45e-10 A, 1.51e-10 A, and 1.57e-10 A, respectively. The effective doping concentration of the detector is approximately 8.08e13 cm^-3 before and after irradiation, with no significant change. The rise times of the signals from alpha particles signal detected by the detector under unirradiated, 0.1 MGy, and 1 MGy X-ray irradiation conditions are 336 ps, 368 ps, and 387 ps, respectively. The rise times of the beta particles signal detected by the detector under unirradiated, 0.1 MGy, and 1 MGy X-ray irradiation conditions are 342 ps, 375 ps, and 398 ps, respectively. After 0.1 MGy and 1 MGy X-ray irradiation, the charge collection efficiencies (CCEs) of the detector for alpha particles are 97.2% and 90.0%, respectively; for beta particles, they are 100.0% and 97.0%, respectively. Experiments confirm that 160 keV X-ray irradiation may not cause significant displacement damage in the 4H-SiC, and the minor performance degradation may be attributed to ionization induced changes in the graphene electrode. The detector exhibits excellent charge collection performance and fast time response. These results demonstrate stable performance under extreme X-ray exposure, highlighting the detector's potential for radiation-hard applications in high-energy physics, space missions, and nuclear reactor monitoring. △ Less

Submitted 6 May, 2026; originally announced May 2026.

A Continuous-Time Ensemble Kalman-Bucy Smoother for Causal Inference and Model Discovery

Authors: Zhang Jiang, Marios Andreou, Sebastian Reich, Nan Chen

Abstract: Data assimilation (DA) integrates observational information with model predictions to improve state estimation in complex systems. While filtering provides the basis for online forecasts by using only past and present observations, it can exhibit delays and biases when the underlying dynamics evolve rapidly or undergo regime transitions. Smoothing, which additionally incorporates future observatio… ▽ More Data assimilation (DA) integrates observational information with model predictions to improve state estimation in complex systems. While filtering provides the basis for online forecasts by using only past and present observations, it can exhibit delays and biases when the underlying dynamics evolve rapidly or undergo regime transitions. Smoothing, which additionally incorporates future observations, provides a natural pipeline for hindcasting and reanalysis that yields an uncertainty reduction beyond the filter. This paper introduces an ensemble Kalman-Bucy smoother (EnKBS) for continuous-time DA of nonlinear dynamical systems, where the smoother's conditional distributions are reconstructed using ensemble moments. The result is a derivative-free framework that does not require explicit computation of tangent-linear or adjoint models, which converges to the exact smoother solution at the infinite-ensemble limit for a wide class of complex systems. Incorporating standard regularization techniques for high-dimensional systems, such as covariance localization and inflation, the skill of the EnKBS is demonstrated in various important scientific problems. By integrating future observations, which reveal the underlying causal mechanisms for retrospective state updates, the EnKBS is used for Bayesian-based inference of causal relationships and their temporal influence range in a dyadic trigger-feedback model and the development of a causality-driven iterative learning algorithm that identifies the structure and recovers the hidden parameters of a nonlinear reduced-order model mimicking midlatitude atmospheric circulation. Notably, both tasks remain effective with an ensemble size of $O(10)$ under partial observations, suggesting that EnKBS can support the instantaneous discovery of high-dimensional complex systems over time. △ Less

Submitted 3 May, 2026; v1 submitted 27 April, 2026; originally announced April 2026.

Comments: 31 pages, 11 figures. Corresponding author: Nan Chen (chennan@math.wisc.edu)

MSC Class: 93E14; 93E11; 65C35; 62F15; 62M20

Polymeric Solvents Control Swelling-Induced Surface Creasing

Authors: Zechao Jiang, Zhaoyu Ding, Shaohua Yang, Ye Xu, Dongshi Guan, Abdelhamid Maali, Joshua D Mcgraw, Thomas Salez, Zaicheng Zhang, Xingkun Man

Abstract: Surface creasing in swelling polymer gels is commonly attributed to compressive strain or interlayer mismatch, yet its general control remains unclear. Here we show that solvent polymerization degree $N_{\rm s}$ provides an independent control parameter for crease onset in surface-bound polydimethylsiloxane gels swollen by silicone oils. Despite nearly identical swelling kinetics and through-thick… ▽ More Surface creasing in swelling polymer gels is commonly attributed to compressive strain or interlayer mismatch, yet its general control remains unclear. Here we show that solvent polymerization degree $N_{\rm s}$ provides an independent control parameter for crease onset in surface-bound polydimethylsiloxane gels swollen by silicone oils. Despite nearly identical swelling kinetics and through-thickness solvent concentration profiles, we observe a transition from creased to stable surfaces with increasing $N_{\rm s}$. A theory coupling swelling thermodynamics and mechanical stability reveals that polymeric solvents reduce the mixing entropy and thereby modify the osmotic pressure, allowing $N_{\rm s}$ to tune separately the equilibrium swelling and the crease threshold. This framework captures the stability boundary across solvent polymerization degree and network elasticity. These results identify polymeric solvents as active thermodynamic-mechanical regulators of swelling-induced surface. △ Less

Submitted 22 April, 2026; originally announced April 2026.

Stability of Charge Collection Efficiency and Time Resolution in a Novel Ultra-fast Graphene-Optimized Silicon Carbide Detector Under X-ray Irradiation

Authors: Zhenyu Jiang, Congcong Wang, Jingxuan He, Yi Zhan, Yingjie Huang, Xiyuan Zhang, Xin Shi

Abstract: A graphene-optimized silicon carbide PIN detector was fabricated and its radiation tolerance under X-ray irradiation of 160 keV was evaluated. Its electrical properties, charge collection performance and time resolution of beta-particles (90Sr) are reported. After 1 MGy irradiation, the detector maintains an ultralow leakage current of approximately 2.2e-10 A @ 300 V and the C-V characteristics ar… ▽ More A graphene-optimized silicon carbide PIN detector was fabricated and its radiation tolerance under X-ray irradiation of 160 keV was evaluated. Its electrical properties, charge collection performance and time resolution of beta-particles (90Sr) are reported. After 1 MGy irradiation, the detector maintains an ultralow leakage current of approximately 2.2e-10 A @ 300 V and the C-V characteristics are basically consistent with full depletion at 120V. The time resolution of the graphene-optimized silicon carbide detector is 58.0 ps. The time resolution is comparable to that of state-of-the-art 4H-SiC low-gain avalanche detectors (LGADs). The G/RE 4H-SiC PIN detector exhibits outstanding time resolution performance. Compared with the time resolution of the RE 4H-SiC PIN detector, the time resolution of the G/RE 4H-SiC PIN detector has decreased by 39.6%. This demonstrates the significance of the graphene electrode design. The graphene detector exhibits a charge collection efficiency (CCE) of 99.24% after X-ray irradiation, along with excellent stability. The graphene-optimized silicon carbide detector maintains good timing resolution: 58.0ps before and 64.0ps after X-ray irradiation. Experimental results indicate that the CCE and time resolution performance exhibit good stability before and after irradiation. These results demonstrate stable performance under extreme X-ray exposure, highlighting the detectors potential for radiation-hard applications in high-energy physics, space missions, and nuclear reactor monitoring. △ Less

Submitted 22 April, 2026; originally announced April 2026.

Nonuniform Iterative Phasing Framework and Sampling Requirements for 3D Dynamical Inversion from Coherent Surface Scattering Imaging

Authors: Jeffrey J. Donatelli, Miaoqi Chu, Zixi Hu, Zhang Jiang, Nicholas Schwarz, Jin Wang, James A. Sethian

Abstract: Coherent surface scattering imaging (CSSI) is an emerging experimental technique uniquely suited to probing the structure of thin nanostructures. In these experiments, a specimen is placed on a substrate, and a series of X-ray diffraction patterns is collected at grazing incidence angles as the specimen is rotated. However, reconstructing the specimen's 3D structure from the data is challenging du… ▽ More Coherent surface scattering imaging (CSSI) is an emerging experimental technique uniquely suited to probing the structure of thin nanostructures. In these experiments, a specimen is placed on a substrate, and a series of X-ray diffraction patterns is collected at grazing incidence angles as the specimen is rotated. However, reconstructing the specimen's 3D structure from the data is challenging due to dynamical scattering effects induced by the experimental geometry and the lack of direct phase measurements. Specifically, the data involves nonuniformly sampled Fourier-transform values of the specimen density, and failure to effectively address this nonuniformity can lead to errors or degraded performance. Here we introduce a mathematical inversion framework that combines iterative-projection-based phasing techniques with new fast nonuniform Fourier inversion methods to efficiently reconstruct isolated 3D structures from their CSSI rotation-series data. We also analyze the theoretical properties of CSSI reconstruction to derive requirements on experimental parameters and characterize solution uniqueness. We validate our approach using CSSI data simulated from a conical Siemens star and a porous medium, demonstrating that high-resolution 3D structures can be reconstructed even in the presence of significant dynamical scattering, from data collected at as few as one or two incident angles. More broadly, the presented nonuniform reconstruction framework provides a foundation for solving challenging generalizations of the phase problem in which measurements involve nonlinear combinations of nonuniformly sampled Fourier values. △ Less

Submitted 20 April, 2026; originally announced April 2026.

Comments: Main text: 47 pages, 31 figures. Supplemental material: 22 pages, 3 figures

Nonlinear atomic tunnelling boosted by bright squeezed vacuum

Authors: Zhejun Jiang, Shengzhe Pan, Jianqi Chen, Mingyu Zhu, Chenhao Zhao, Yiwen Wang, Ru Zhang, Jianshi Lu, Lulu Han, Suwen Xiong, Dian Wu, Wenxue Li, Shicheng Jiang, Hongcheng Ni, Jian Wu

Abstract: Nonlinear optical processes, mediated by multiphoton interactions rather than single-photon response, are routinely exploited to enable a range of light-based functionalities in devices and applications. Nonlinear effects are enhanced through higher intensity fields, which is a limiting strategy owing to potential radiation damage. An alternative strategy relies on the fluctuation redistribution t… ▽ More Nonlinear optical processes, mediated by multiphoton interactions rather than single-photon response, are routinely exploited to enable a range of light-based functionalities in devices and applications. Nonlinear effects are enhanced through higher intensity fields, which is a limiting strategy owing to potential radiation damage. An alternative strategy relies on the fluctuation redistribution typical of quantum light, but experimental demonstrations at the most fundamental level have been limited. Here we report experimental nonlinear tunnelling ionization of isolated atoms, a pivotal nonlinear process that drives high-harmonic generation and forms the basis of attosecond science, boosted by quantum light -- bright squeezed vacuum (BSV). A BSV light with an average pulse energy of 300 nJ achieves an effective intensity equivalent to that of a coherent light with 7.1 {\textmu}J, demonstrating a more than 20-fold quantum boost in nonlinear effect from BSV light. This boost is revealed by matching the peaks of the photoelectron momentum spectra produced by the BSV and coherent light using angular streaking. Furthermore, we demonstrate control of the effective intensity of the BSV by tuning the correlation function at fixed average pulse energy, establishing a robust method to tailor nonlinear processes via quantum statistics rather than classical intensity scaling. These findings may facilitate the development of quantum-controlled strong-field dynamics using tailored quantum light sources. △ Less

Submitted 20 May, 2026; v1 submitted 7 April, 2026; originally announced April 2026.

Journal ref: Nature (2026)

Topographic Modulation of Martian Near-Surface Winds: Insights from Perseverance Measurements and CFD Modeling in Jezero Crater

Authors: Yuhang Liu, Lei Zhang, Zhihao Shen, Peng Cao, Zhao Jiang, Jing Li, Jinhai Zhang

Abstract: Near-surface wind fields on Mars are profoundly modulated by complex topography, yet fine-scale wind field characteristics remain poorly resolved for key geomorphological units such as deltas, valleys, and impact craters, due to the spatial constraints of lander-based wind observations. To address this, we identified three dominant wind directions using measured near-surface wind data from the Per… ▽ More Near-surface wind fields on Mars are profoundly modulated by complex topography, yet fine-scale wind field characteristics remain poorly resolved for key geomorphological units such as deltas, valleys, and impact craters, due to the spatial constraints of lander-based wind observations. To address this, we identified three dominant wind directions using measured near-surface wind data from the Perseverance rover at Jezero Crater and then integrated in-situ wind measurements with high-resolution numerical modeling. We established a high-resolution three-dimensional (3D) terrain model encompassing key local geomorphic units, including the delta, an impact crater, and nearby mesas, and performed Computational Fluid Dynamics (CFD) simulations under the above-mentioned three dominant wind directions. The results reveal a robust coupling mechanism between local topography and near-surface wind field structures. We demonstrate that wind speed is significantly enhanced over windward slopes but evidently attenuated within depressions and crater floors. Crucially, significant wind direction deflection angles were particularly evident in areas characterized by steeper slopes. For instance, wind flow exhibited a symmetrical deflection pattern along the opposing inner walls of the modeled impact crater, but stabilizing on the crater floor. Spatial comparisons indicate that wind deflection is most pronounced over steeper slopes, while sector-based distributions within the impact crater reveal a consistent symmetry between opposing wall and floor regions. These findings offer new and critical insights into the intimate connection between Martian surface aeolian erosion/deposition processes and local topographic evolution, which is vital for interpreting the sedimentary history of Jezero Crater. △ Less

Submitted 2 April, 2026; originally announced April 2026.

Time Resolution of a Novel Ultra-fast Graphene-Optimized 4H-SiC PIN

Authors: Suyu Xiao, Hui Liang, Congcong Wang, Zhenyu Jiang, Lin Zhu

Abstract: Silicon carbide detectors exhibit good detection performance such as fast time resolution, high radiation tolerances, high breakdown voltage and low temperature sensitivity and have been studied for detection applications. Meanwhile, transient current technique (TCT) is a direct and effective method to evaluate the time resolution of semiconductor detectors. Conventional metal electrodes for TCT t… ▽ More Silicon carbide detectors exhibit good detection performance such as fast time resolution, high radiation tolerances, high breakdown voltage and low temperature sensitivity and have been studied for detection applications. Meanwhile, transient current technique (TCT) is a direct and effective method to evaluate the time resolution of semiconductor detectors. Conventional metal electrodes for TCT testing employ window structures, which lead to non-uniform electric field distribution and deteriorated time resolution. Graphene features high optical transmittance, ultrahigh carrier mobility, and excellent radiation resistance, making it an ideal transparent electrode material for semiconductor detectors. In this work, a graphene-optimized ring electrode (G/RE) 4H-SiC PIN detector and a reference ring electrode (RE) 4H-SiC PIN detector are fabricated. TCT measurements demonstrate that graphene integration improves the time resolution consistency, reducing the time resolution from 38 ps (reference RE detector) to 21 ps (G/RE detector) at the maximum scanning distance, while also achieving effective noise suppression. The graphene integration improves the stability of time resolution by 87% compared to the reference detector. Notably, the achieved time resolution of 21 ps is comparable to that of state-of-the-art 4H-SiC low-gain avalanche detectors (LGADs), which typically exhibit time resolutions better than 35 ps under single minimum ionizing particle (MIP) equivalent injection conditions, further validating the effectiveness of graphene-based electrode design. △ Less

Submitted 28 March, 2026; originally announced March 2026.

Pearcey-Inspired Quartic Wavefront Shaping for Obstructed Near-Field Multi-User Communications

Authors: Yifeng Qin, Jing Chen, Zhi Hao Jiang

Abstract: Radiative near-field (RNF) beamforming is vulnerable to blockages that disrupt Fresnel zones. This letter proposes an obstruction-unaware wavefront shaping strategy inspired by catastrophe optics. By superimposing a calibrated quartic phase, we generate a Pearcey-like wave packet that exhibits structural stability against perturbations. We establish a fair comparison protocol where the quartic bea… ▽ More Radiative near-field (RNF) beamforming is vulnerable to blockages that disrupt Fresnel zones. This letter proposes an obstruction-unaware wavefront shaping strategy inspired by catastrophe optics. By superimposing a calibrated quartic phase, we generate a Pearcey-like wave packet that exhibits structural stability against perturbations. We establish a fair comparison protocol where the quartic beam is calibrated in free space to avoid exploiting obstruction knowledge. Numerical results demonstrate up to 8.5~dB SINR gain over conventional focusing for multi-user scenarios near the depth-of-focus limit. Crucially, this gain stems from improved channel conditioning under partial blockage, which mitigates the severe noise amplification inherent to zero-forcing precoding. △ Less

Submitted 4 March, 2026; originally announced March 2026.

Random batch sum-of-Gaussians method for molecular dynamics simulation of particle systems in the NPT ensemble

Authors: Zhen Jiang, Jiuyang Liang, Qi Zhou

Abstract: In this work, we develop a random batch sum-of-Gaussians (RBSOG) method for molecular dynamics simulations of charged systems in the isothermal-isobaric (NPT) ensemble. We introduce an SOG splitting of the pressure-related $1/r^3$ kernel, yielding a smooth short-/long-range decomposition for instantaneous pressure evaluation. The long-range part is treated in Fourier space by random-batch importan… ▽ More In this work, we develop a random batch sum-of-Gaussians (RBSOG) method for molecular dynamics simulations of charged systems in the isothermal-isobaric (NPT) ensemble. We introduce an SOG splitting of the pressure-related $1/r^3$ kernel, yielding a smooth short-/long-range decomposition for instantaneous pressure evaluation. The long-range part is treated in Fourier space by random-batch importance sampling. Because the radial and non-radial pressure components favor different proposals, direct sampling either increases structure-factor evaluations and communication or leads to substantial variance inflation. To address this tradeoff, we introduce a measure-recalibration strategy that reuses Fourier modes drawn from the radial proposal and corrects them for the non-radial target, producing an unbiased pressure estimator with significantly reduced variance and negligible extra cost. The resulting method mitigates pressure artifacts caused by cutoff discontinuities in traditional Ewald-based treatments while preserving near-optimal $O(N)$ complexity. We provide theoretical evidence on pressure decomposition error, consistency of stochastic approximation, and convergence of RBSOG-based MD. Numerical experiments on bulk water, LiTFSI ionic liquids, and DPPC membranes show that RBSOG accurately reproduces key structural and dynamical observables with small batch sizes ($P\sim 100$). In large-scale benchmarks up to $10^7$ atoms on $2048$ CPU cores, RBSOG achieves about an order-of-magnitude speedup over particle-particle particle-mesh in electrostatic calculations for NPT simulations, together with a consistent $4\times$ variance reduction relative to random batch Ewald and excellent weak/strong scalability. Overall, RBSOG provides a practical and scalable route to reduce time-to-solution and communication cost in large-scale NPT simulations. △ Less

Submitted 26 February, 2026; originally announced February 2026.

Comments: 29 pages, 8 pages

MSC Class: 82M37; 65C35; 65T50; 65Y20

Omnidirectional wave energy gimbal-based electromagnetic generator

Authors: Zhichao Jiang, Shunchao Jiang

Abstract: Wave energy, as a renewable energy source, is widely distributed and possesses substantial reserves. However, many existing wave energy harvesters exhibit motion constraints under irregular wave conditions, which limits their energy conversion efficiency. In this study, an omnidirectional wave energy gimbal-based electromagnetic generator (OWG-EMG) is proposed to achieve stable power generation un… ▽ More Wave energy, as a renewable energy source, is widely distributed and possesses substantial reserves. However, many existing wave energy harvesters exhibit motion constraints under irregular wave conditions, which limits their energy conversion efficiency. In this study, an omnidirectional wave energy gimbal-based electromagnetic generator (OWG-EMG) is proposed to achieve stable power generation under irregular wave motions. By integrating a three-axis gimbal mechanism with an inertial mass regulator, the proposed harvester effectively converts complex and varying wave-induced motions into relative rotational motion between gimbal frames. A planetary gear transmission is further employed to increase the rotational speed of the electromagnetic generator, enabling efficient omnidirectional wave energy harvesting. Experimental results demonstrate that the device delivers an average output power of up to 0.24 W at a frequency of 1 Hz, corresponding to an average power density of 40 W/m3. Importantly, in addition to its high energy conversion efficiency, the proposed device offers notable advantages including low cost, structural simplicity, and high reliability, highlighting its significant potential for applications in ocean energy harvesting and utilization. △ Less

Submitted 24 February, 2026; originally announced February 2026.

g4chargeit: Geant4-based kinetic Monte Carlo simulations of charging in dielectric materials

Authors: Kush P. Gandhi, Advik D. Vira, William M. Farrell, Nikolai Simonov, Alvaro Romero-Calvo, Thomas M. Orlando, Phillip N. First, Zhigang Jiang

Abstract: We present g4chargeit, a kinetic Monte Carlo framework built on Geant4 for self-consistent simulation of time-dependent electrostatic charging in dielectric materials. The model explicitly incorporates stochastic particle transport and scattering processes using validated Geant4 cross-sections, while self-consistently evolving the electric potential and field. As a representative application, we… ▽ More We present g4chargeit, a kinetic Monte Carlo framework built on Geant4 for self-consistent simulation of time-dependent electrostatic charging in dielectric materials. The model explicitly incorporates stochastic particle transport and scattering processes using validated Geant4 cross-sections, while self-consistently evolving the electric potential and field. As a representative application, we simulate the charging of regolith grains under average dayside conditions on the Moon. The surface of the Moon, in addition to other airless planetary bodies, are regularly exposed to solar ultraviolet photons and solar-wind plasma, creating a radiation environment in which electrostatic interactions among regolith grains become significant. Until now, simulations of regolith charging have often relied on analytical approximations that oversimplify grain geometry and interaction mechanisms. Our Geant4-based simulations reveal charge accumulation within intergrain micro-cavities, leading to repulsive electrostatic forces consistent with experimental observations. The framework establishes a multiscale approach that links microscopic scattering events to the continuity equation of surface charge density and to the formation of macroscopic surface charge patches in complex grain geometries. Although demonstrated here for planetary regolith, the method is general and applicable to a broad range of dielectric charging problems. The code is openly available at https://github.com/kgandhi63/g4chargeit.git. △ Less

Submitted 19 February, 2026; originally announced February 2026.

Ultrasound-Guided Real-Time Spinal Motion Visualization for Spinal Instability Assessment

Authors: Feng Li, Yuan Bi, Tianyu Song, Zhongliang Jiang, Nassir Navab

Abstract: Purpose: Spinal instability is a widespread condition that causes pain, fatigue, and restricted mobility, profoundly affecting patients' quality of life. In clinical practice, the gold standard for diagnosis is dynamic X-ray imaging. However, X-ray provides only 2D motion information, while 3D modalities such as computed tomography (CT) or cone beam computed tomography (CBCT) cannot efficiently ca… ▽ More Purpose: Spinal instability is a widespread condition that causes pain, fatigue, and restricted mobility, profoundly affecting patients' quality of life. In clinical practice, the gold standard for diagnosis is dynamic X-ray imaging. However, X-ray provides only 2D motion information, while 3D modalities such as computed tomography (CT) or cone beam computed tomography (CBCT) cannot efficiently capture motion. Therefore, there is a need for a system capable of visualizing real-time 3D spinal motion while minimizing radiation exposure. Methods: We propose ultrasound as an auxiliary modality for 3D spine visualization. Due to acoustic limitations, ultrasound captures only the superficial spinal surface. Therefore, the partially compounded ultrasound volume is registered to preoperative 3D imaging. In this study, CBCT provides the neutral spine configuration, while robotic ultrasound acquisition is performed at maximal spinal bending. A kinematic model is applied to the CBCT-derived spine model for coarse registration, followed by ICP for fine registration, with kinematic parameters optimized based on the registration results. Real-time ultrasound motion tracking is then used to estimate continuous 3D spinal motion by interpolating between the neutral and maximally bent states. Results: The pipeline was evaluated on a bendable 3D-printed lumbar spine phantom. The registration error was $1.941 \pm 0.199$ mm and the interpolated spinal motion error was $2.01 \pm 0.309$ mm (median). Conclusion: The proposed robotic ultrasound framework enables radiation-reduced, real-time 3D visualization of spinal motion, offering a promising 3D alternative to conventional dynamic X-ray imaging for assessing spinal instability. △ Less

Submitted 13 February, 2026; originally announced February 2026.

Social Catalysts, Not Moral Agents: The Illusion of Alignment in LLM Societies

Authors: Yueqing Hu, Yixuan Jiang, Zehua Jiang, Xiao Wen, Tianhong Wang

Abstract: The rapid evolution of Large Language Models (LLMs) has led to the emergence of Multi-Agent Systems where collective cooperation is often threatened by the "Tragedy of the Commons." This study investigates the effectiveness of Anchoring Agents--pre-programmed altruistic entities--in fostering cooperation within a Public Goods Game (PGG). Using a full factorial design across three state-of-the-art… ▽ More The rapid evolution of Large Language Models (LLMs) has led to the emergence of Multi-Agent Systems where collective cooperation is often threatened by the "Tragedy of the Commons." This study investigates the effectiveness of Anchoring Agents--pre-programmed altruistic entities--in fostering cooperation within a Public Goods Game (PGG). Using a full factorial design across three state-of-the-art LLMs, we analyzed both behavioral outcomes and internal reasoning chains. While Anchoring Agents successfully boosted local cooperation rates, cognitive decomposition and transfer tests revealed that this effect was driven by strategic compliance and cognitive offloading rather than genuine norm internalization. Notably, most agents reverted to self-interest in new environments, and advanced models like GPT-4.1 exhibited a "Chameleon Effect," masking strategic defection under public scrutiny. These findings highlight a critical gap between behavioral modification and authentic value alignment in artificial societies. △ Less

Submitted 1 February, 2026; originally announced February 2026.

Comments: 7 pages, 5 figures

Suspended thin-film lithium niobate modulator for broadband mid-infrared light modulation and frequency comb generation

Authors: Chun-Ho Lee, Xinyi Ren, Xinzhou Su, Wonho Lee, Zile Jiang, Yue Yu, Huibin Zhou, Yue Zuo, Shaoyuan Ou, Reshma Kopparapu, Adam T. Heiniger, Moshe Tur, Alan E. Willner, Zaijun Chen, Mengjie Yu

Abstract: The mid-infrared (MIR) spectral regime is central to applications including remote sensing, precision spectroscopy, higher harmonic generation, and free-space optical communication. However, coherent and broadband MIR modulation remains challenging owing to high optical loss, limited bandwidth, and large drive voltages in existing platforms. Here, we overcome these challenges by deploying a suspen… ▽ More The mid-infrared (MIR) spectral regime is central to applications including remote sensing, precision spectroscopy, higher harmonic generation, and free-space optical communication. However, coherent and broadband MIR modulation remains challenging owing to high optical loss, limited bandwidth, and large drive voltages in existing platforms. Here, we overcome these challenges by deploying a suspended thin-film lithium-niobate (TFLN) based electro-optic (EO) platform co-designed with high-performance traveling-wave microwave (MW) electrodes. We demonstrate a record-low Vpi,DC of 2.3 to 4.3 V over a broadband MIR bandwidth from 2.4 to 3.6 um, and a 2.7 dB EO bandwidth of 40 GHz (extracted 3 dB bandwidth of 50 GHz), yielding a figure of merit of 17.4 GHz/V, more than an order of magnitude higher than the state of the art. We demonstrate, for the first time, high-frequency Vpi,MW of 4.5 to 6.5 V in the 25 to 35 GHz range, and frequency-agile MIR EO frequency comb generation with a 10 dB optical bandwidth over 0.8 THz using a suspended phase modulator of 4 cm active modulation length. We further validate the platform in a free-space optical communication link. Our results establish a monolithic MIR photonic platform capable of powerful EO modulation and spectral synthesis, and represent a significant step toward reconfigurable MIR sensing and communication systems on chip. △ Less

Submitted 24 January, 2026; originally announced January 2026.

Temporal Beam Self-Cleaning in Second-Harmonic Generation

Authors: Siyu Chen, Jun Ye, Lei Du, Wenwen Cheng, Jiangming Xu, Rongtao Su, Pu Zhou, Zongfu Jiang

Abstract: The spatial-temporal beam quality of laser sources is crucial for applications such as nonlinear spectroscopy and master oscillator power amplification systems. However, the temporal stability remains challenged by issues like line-width broadening and high-power demand in efforts to improve it. In this work, we investigate the effect of the second-harmonic generation process on the laser characte… ▽ More The spatial-temporal beam quality of laser sources is crucial for applications such as nonlinear spectroscopy and master oscillator power amplification systems. However, the temporal stability remains challenged by issues like line-width broadening and high-power demand in efforts to improve it. In this work, we investigate the effect of the second-harmonic generation process on the laser characteristics under three longitudinal mode regimes: single-longitudinal-mode, dual-longitudinal-mode, and multi-longitudinal-mode. The results demonstrate that the second-harmonic generation process effectively stabilizes the temporal characteristics of the laser and enhances its correlation, leading to a temporally clean output beam. The physical mechanism of the observed temporal stabilization effect can be attributed to a high-peak-pulse attenuation effect, jointly induced by nonuniform longitudinal-mode depletion and phase preservation in the residual fundamental wave. Statistical analysis indicates that at the maximum fundamental-wave power in the multi-longitudinal-mode regime, the standard deviation and peak-to-valley values derived from the normalized temporal profile decrease from 0.6122 and 5.6846 for the fundamental wave to 0.189 and 0.8847 for the residual fundamental wave. Meanwhile, the background level of the intensity auto-correlation function rises from ~0.72 to ~0.96, revealing its evolution toward a more coherent state. To the best of our knowledge, this research presents the first demonstration of laser temporal stabilization and correlation enhancement via second-harmonic generation. It not only deepens the comprehension of second-harmonic generation mechanisms, but also opens up a new avenue for realizing temporal beam self-cleaning of light. △ Less

Submitted 17 January, 2026; originally announced January 2026.

Airy Beamforming for Radiative Near-Field MU-XL-MIMO: Overcoming Half-Space Blockage

Authors: Yifeng Qin, Jing Chen, Zhi Hao Jiang, Zhi Ning Chen, Yongming Huang, Lingyang Song

Abstract: The move to next-generation wireless communications with extremely large-scale antenna arrays (ELAAs) brings the communications into the radiative near-field (RNF) region, where distance-aware focusing is feasible. However, high-frequency RNF links are highly vulnerable to blockage in indoor environments dominated by half-space obstacles (walls, corners) that create knife-edge shadows. Conventiona… ▽ More The move to next-generation wireless communications with extremely large-scale antenna arrays (ELAAs) brings the communications into the radiative near-field (RNF) region, where distance-aware focusing is feasible. However, high-frequency RNF links are highly vulnerable to blockage in indoor environments dominated by half-space obstacles (walls, corners) that create knife-edge shadows. Conventional near-field focused beams offer high gain in line-of-sight (LoS) scenarios but suffer from severe energy truncation and effective-rank collapse in shadowed regions, often necessitating the deployment of auxiliary hardware such as Reconfigurable Intelligent Surfaces (RIS) to restore connectivity. We propose a beamforming strategy that exploits the auto-bending property of Airy beams to mitigate half-space blockage without additional hardware. The Airy beam is designed to ``ride'' the diffraction edge, accelerating its main lobe into the shadow to restore connectivity. Our contributions are threefold: (i) a Green's function-based RNF multi-user channel model that analytically reveals singular-value collapse behind knife-edge obstacles; (ii) an Airy analog beamforming scheme that optimizes the bending trajectory to recover the effective channel rank; and (iii) an Airy null-steering method that aligns oscillatory nulls with bright-region users to suppress interference in mixed shadow/bright scenarios. Simulations show that the proposed edge-riding Airy strategy achieves a Signal-to-Noise Ratio (SNR) improvement of over 20 dB and restores full-rank connectivity in shadowed links compared to conventional RNF focusing, virtually eliminating outage in geometric shadows and increasing multi-user spectral efficiency by approximately 35\% under typical indoor ELAA configurations. These results demonstrate robust RNF multi-user access in half-space blockage scenarios without relying on RIS. △ Less

Submitted 24 January, 2026; v1 submitted 13 January, 2026; originally announced January 2026.

PIDT: Physics-Informed Digital Twin for Optical Fiber Parameter Estimation

Authors: Zicong Jiang, Magnus Karlsson, Erik Agrell, Christian Häger

Abstract: We propose physics-informed digital twin (PIDT): a fiber parameter estimation approach that combines a parameterized split-step method with a physics-informed loss. PIDT improves accuracy and convergence speed with lower complexity compared to previous neural operators. We propose physics-informed digital twin (PIDT): a fiber parameter estimation approach that combines a parameterized split-step method with a physics-informed loss. PIDT improves accuracy and convergence speed with lower complexity compared to previous neural operators. △ Less

Submitted 12 January, 2026; originally announced January 2026.

Comments: The paper will be appeared in Optical Fiber Communications Conference and Exhibition (OFC) 2026

Turbulence enhancement of a fan array wind generator using geometric texturing and optimization-based control

Authors: Gengshou Cao, Tamir Shaqarin, Zhutao Jiang, Yutong Liu, Yiqing Li, Nan Gao, Xiaozhou He, Bernd R. Noack

Abstract: Fan array wind generators (FAWG) are designed to generate a rich set of turbulent flows reminiscent of those found in natural environments. In this study, we experimentally investigate a square FAWG consisting of 10x10 individually controllable fans with 4 cm width and a maximum velocity of 17 m/s. The goal is to maximize the turbulence intensity in the test region. Two approaches for fan operatio… ▽ More Fan array wind generators (FAWG) are designed to generate a rich set of turbulent flows reminiscent of those found in natural environments. In this study, we experimentally investigate a square FAWG consisting of 10x10 individually controllable fans with 4 cm width and a maximum velocity of 17 m/s. The goal is to maximize the turbulence intensity in the test region. Two approaches for fan operation are investigated: first, geometric texturing of the duty cycle distribution, and second, maximization of the turbulence intensity at selected hot-wire sensors with particle-swarm optimization. We find that geometric texturing (specifically a checkerboard pattern) yields a robust, uniform turbulence field (Tu ~ 0.14) driven by jet interactions. Conversely, particle swarm optimization achieves higher local turbulence (Tu ~ 0.28) but significantly sacrifices spatial uniformity. This study underscores the trade-off between local maximization and global uniformity in active turbulence generation. △ Less

Submitted 16 December, 2025; originally announced December 2025.

Fast and Robust T1 Mapping Based on a 3D Dual-Echo UTE Sequence (PETALUTE) for SPION Biodistribution Assessment

Authors: Zhen Jiang, Stephen Sawiak, Alexandra Lipka, Xin Shen, Uzay Emir, Ali Özen, Mark Chiew, Justin Geise, Joseph Speth, Deng-Yuan Chang, Jessica Veenstra, Mitchell Gabalski, Luis Solorio, Gregory Tamer Jr., Matthew Scarpelli

Abstract: Superparamagnetic iron oxide nanoparticles (SPIONs) such as ferumoxytol are promising theranostic agents detectable with MRI. Relaxation time mapping offers reproducible, quantitative biomarkers of SPION distribution, but conventional methods suffer from susceptibility artifacts, long echo times, and extended scan durations, limiting accurate quantification. This study developed a fast, B1-correct… ▽ More Superparamagnetic iron oxide nanoparticles (SPIONs) such as ferumoxytol are promising theranostic agents detectable with MRI. Relaxation time mapping offers reproducible, quantitative biomarkers of SPION distribution, but conventional methods suffer from susceptibility artifacts, long echo times, and extended scan durations, limiting accurate quantification. This study developed a fast, B1-corrected T1-mapping protocol using PETALUTE, a 3D dual-echo ultrashort-echo MRI sequence with a rosette k-space trajectory and variable flip-angle acquisition for quantitative ferumoxytol imaging. Agarose phantoms containing 0-5000 ppm ferumoxytol were scanned at 7T with PETALUTE and vendor-supplied RARE-VTR. PETALUTE T1 maps were derived from two flip angles (4 deg and 20 deg), and mean R1 values were correlated with ferumoxytol concentration. For in vivo feasibility, mice bearing 4T1 mammary and flank tumors were scanned 24 h post-injection (ferumoxytol: n=2, 40 mg/kg; control: n=1). Regions of interest in muscle and tumors were analyzed to compare T1 and R1 values obtained with both methods. PETALUTE produced positive contrast for all phantom concentrations except 5000 ppm, whereas RARE-VTR did not. PETALUTE demonstrated a significant linear correlation between R1 and ferumoxytol concentration (R=0.975, p<0.01), in contrast to RARE-VTR (R=0.672, p=0.144). In vivo, PETALUTE enabled high-resolution, whole-abdominal imaging in 4 min 19 s. Ferumoxytol-injected mice showed T1 shortening in flank tumors, consistent with iron uptake, and PETALUTE revealed elevated T1 value with preserved T2*-weighted signal in one mammary tumor. PETALUTE-based T1 mapping provides fast, quantitative, positive-contrast ferumoxytol imaging with greater spatial coverage and a wider usable concentration range than conventional RARE-VTR. △ Less

Submitted 5 December, 2025; originally announced December 2025.

EWE: An Agentic Framework for Extreme Weather Analysis

Authors: Zhe Jiang, Jiong Wang, Xiaoyu Yue, Zijie Guo, Wenlong Zhang, Fenghua Ling, Wanli Ouyang, Lei Bai

Abstract: Extreme weather events pose escalating risks to global society, underscoring the urgent need to unravel their underlying physical mechanisms. Yet the prevailing expert-driven, labor-intensive diagnostic paradigm has created a critical analytical bottleneck, stalling scientific progress. While AI for Earth Science has achieved notable advances in prediction, the equally essential challenge of autom… ▽ More Extreme weather events pose escalating risks to global society, underscoring the urgent need to unravel their underlying physical mechanisms. Yet the prevailing expert-driven, labor-intensive diagnostic paradigm has created a critical analytical bottleneck, stalling scientific progress. While AI for Earth Science has achieved notable advances in prediction, the equally essential challenge of automated diagnostic reasoning remains largely unexplored. We present the Extreme Weather Expert (EWE), the first intelligent agent framework dedicated to this task. EWE emulates expert workflows through knowledge-guided planning, closed-loop reasoning, and a domain-tailored meteorological toolkit. It autonomously produces and interprets multimodal visualizations from raw meteorological data, enabling comprehensive diagnostic analyses. To catalyze progress, we introduce the first benchmark for this emerging field, comprising a curated dataset of 103 high-impact events and a novel step-wise evaluation metric. EWE marks a step toward automated scientific discovery and offers the potential to democratize expertise and intellectual resources, particularly for developing nations vulnerable to extreme weather. △ Less

Submitted 26 November, 2025; originally announced November 2025.

Near-Field Topology-Optimized Superchiral Metasurfaces for Enhanced Chiral Sensing

Authors: Zhongjun Jiang, Soyaib Sohag, You Zhou

Abstract: The detection and discrimination of molecular chirality are essential for advancing pharmaceutical and biological applications. While nanophotonic platforms offer a route to enhance chiral light-matter interactions, existing device concepts for chiral sensing remain heuristic, resulting in limited chiral enhancement and control over chiral hotspot placement within nanostructures. Here, we introduc… ▽ More The detection and discrimination of molecular chirality are essential for advancing pharmaceutical and biological applications. While nanophotonic platforms offer a route to enhance chiral light-matter interactions, existing device concepts for chiral sensing remain heuristic, resulting in limited chiral enhancement and control over chiral hotspot placement within nanostructures. Here, we introduce an inverse-design framework that directly optimizes superchiral near fields in photonic nanostructures and demonstrate its powerful opportunities for enantioselective analysis. We first show that freeform achiral metasurfaces can be optimized to achieve an 800-fold chiral density enhancement, with fully customizable chiral hotspot placement for direct molecular interaction. We further demonstrate ultrasensitive detection of chiral analytes and achieve a 116-fold increase in detection sensitivity over the native enantiomeric response. Lastly, we extend our platform to determine chiral-molecule concentration and resolve enantiomeric excess in chiral mixtures. Our framework offers a generic route to enabling nanophotonic platforms for detecting chiral compounds and can be integrated with a broad range of spin-based photonic materials for applications in valleytronics, chiral emission control, and topological photonics. △ Less

Submitted 19 November, 2025; originally announced November 2025.

Comments: 17 pages, 4 figures

Socrates-Mol: Self-Oriented Cognitive Reasoning through Autonomous Trial-and-Error with Empirical-Bayesian Screening for Molecules

Authors: Xiangru Wang, Zekun Jiang, Heng Yang, Cheng Tan, Xingying Lan, Chunming Xu, Tianhang Zhou

Abstract: Molecular property prediction is fundamental to chemical engineering applications such as solvent screening. We present Socrates-Mol, a framework that transforms language models into empirical Bayesian reasoners through context engineering, addressing cold start problems without model fine-tuning. The system implements a reflective-prediction cycle where initial outputs serve as priors, retrieved… ▽ More Molecular property prediction is fundamental to chemical engineering applications such as solvent screening. We present Socrates-Mol, a framework that transforms language models into empirical Bayesian reasoners through context engineering, addressing cold start problems without model fine-tuning. The system implements a reflective-prediction cycle where initial outputs serve as priors, retrieved molecular cases provide evidence, and refined predictions form posteriors, extracting reusable chemical rules from sparse data. We introduce ranking tasks aligned with industrial screening priorities and employ cross-model self-consistency across five language models to reduce variance. Experiments on amine solvent LogP prediction reveal task-dependent patterns: regression achieves 72% MAE reduction and 112% R-squared improvement through self-consistency, while ranking tasks show limited gains due to systematic multi-model biases. The framework reduces deployment costs by over 70% compared to full fine-tuning, providing a scalable solution for molecular property prediction while elucidating the task-adaptive nature of self-consistency mechanisms. △ Less

Submitted 14 November, 2025; originally announced November 2025.

SSTODE: Ocean-Atmosphere Physics-Informed Neural ODEs for Sea Surface Temperature Prediction

Authors: Zheng Jiang, Wei Wang, Gaowei Zhang, Yi Wang

Abstract: Sea Surface Temperature (SST) is crucial for understanding upper-ocean thermal dynamics and ocean-atmosphere interactions, which have profound economic and social impacts. While data-driven models show promise in SST prediction, their black-box nature often limits interpretability and overlooks key physical processes. Recently, physics-informed neural networks have been gaining momentum but strugg… ▽ More Sea Surface Temperature (SST) is crucial for understanding upper-ocean thermal dynamics and ocean-atmosphere interactions, which have profound economic and social impacts. While data-driven models show promise in SST prediction, their black-box nature often limits interpretability and overlooks key physical processes. Recently, physics-informed neural networks have been gaining momentum but struggle with complex ocean-atmosphere dynamics due to 1) inadequate characterization of seawater movement (e.g., coastal upwelling) and 2) insufficient integration of external SST drivers (e.g., turbulent heat fluxes). To address these challenges, we propose SSTODE, a physics-informed Neural Ordinary Differential Equations (Neural ODEs) framework for SST prediction. First, we derive ODEs from fluid transport principles, incorporating both advection and diffusion to model ocean spatiotemporal dynamics. Through variational optimization, we recover a latent velocity field that explicitly governs the temporal dynamics of SST. Building upon ODE, we introduce an Energy Exchanges Integrator (EEI)-inspired by ocean heat budget equations-to account for external forcing factors. Thus, the variations in the components of these factors provide deeper insights into SST dynamics. Extensive experiments demonstrate that SSTODE achieves state-of-the-art performances in global and regional SST forecasting benchmarks. Furthermore, SSTODE visually reveals the impact of advection dynamics, thermal diffusion patterns, and diurnal heating-cooling cycles on SST evolution. These findings demonstrate the model's interpretability and physical consistency. △ Less

Submitted 6 November, 2025; originally announced November 2025.

Comments: To be published in the Proceedings of AAAI-AISI 2026

A Calibration Method for Indirect Time-of-Flight Cameras to Eliminate Internal Scattering Interference

Authors: Yansong Du, Jingtong Yao, Yuting Zhou, Feiyu Jiao, Zhaoxiang Jiang, Xun Guan

Abstract: In-camera light scattering is a typical form of non-systematic interference in indirect Time-of-Flight (iToF) cameras, primarily caused by multiple reflections and optical path variations within the camera body. This effect can significantly reduce the accuracy of background depth measurements. To address this issue, this paper proposes a calibration-based model derived from real measurement data,… ▽ More In-camera light scattering is a typical form of non-systematic interference in indirect Time-of-Flight (iToF) cameras, primarily caused by multiple reflections and optical path variations within the camera body. This effect can significantly reduce the accuracy of background depth measurements. To address this issue, this paper proposes a calibration-based model derived from real measurement data, introducing three physically interpretable calibration parameters: a normal-exposure amplitude influence coefficient, an overexposure amplitude influence coefficient, and a scattering phase shift coefficient. These parameters are used to describe the effects of foreground size, exposure conditions, and optical path differences on scattering interference. Experimental results show that the depth values calculated using the calibrated parameters can effectively compensate for scattering-induced errors, significantly improving background depth recovery in scenarios with complex foreground geometries and varying illumination conditions. This approach provides a practical, low-cost solution for iToF systems, requiring no complex hardware modifications, and can substantially enhance measurement accuracy and robustness across a wide range of real-world applications. △ Less

Submitted 21 October, 2025; originally announced November 2025.

Comments: 20 pages, 11 figures

Non-Diffracting Beams for Near-Field Millimeter-Wave Communications: Advantage Regimes Under Aperture and Blockage Constraints

Authors: Yifeng Qin, Jing Chen, Zhi Hao Jiang, Zhining Chen, Yongming Huang

Abstract: Near-field blockage changes the beam-design objective in millimeter-wave links: maximizing the unblocked on-axis gain does not necessarily maximize blocked-link performance. This paper studies when phase-only, aperture-constrained non-diffracting (ND) beams provide a blocked-link advantage over equal-aperture, equal-power conventional reference beams. We develop a unified annular-spectrum framewor… ▽ More Near-field blockage changes the beam-design objective in millimeter-wave links: maximizing the unblocked on-axis gain does not necessarily maximize blocked-link performance. This paper studies when phase-only, aperture-constrained non-diffracting (ND) beams provide a blocked-link advantage over equal-aperture, equal-power conventional reference beams. We develop a unified annular-spectrum framework that generates isotropic Bessel-like and anisotropic Mathieu-like beams under discrete phased-array constraints, and a geometry-aware analysis centered on three propagation landmarks: the peak-intensity distance, the crossover distance, and an effective post-blockage recovery distance. Their relationship yields a recovery-before-crossover condition linking blockage size, depth, cone angle, and usable ND range, and motivates a blocked-link gain ratio that maps directly onto an achievable-rate gap at every operating SNR. The analysis also explains why anisotropic Mathieu-like beams can outperform isotropic ones under direction-dependent blockage. Monte Carlo simulations verify the predicted advantage regimes, an auxiliary comparison against a near-field focusing baseline confirms that the advantage persists against an unblocked-optimal array, and sensitivity studies over cone-angle choice and partial-transmission blockers show that the opaque-screen picture is a conservative reading of the underlying physics. The results identify Bessel-like and Mathieu-like beams as practical candidates for blockage-resilient near-field communications. △ Less

Submitted 20 April, 2026; v1 submitted 16 October, 2025; originally announced October 2025.

Spatiotemporal Raman Probing of Molecular Transport in sub-2-nm Plasmonic Quasi-2D Nanochannels

Authors: Haoran Liu, Zihe Jiang, Zhiwei Hu, Banghuan Zhang, Tao He, Xiaohui Dong, Chaowei Sun, Jun Tian, Wei Jiang, Huatian Hu, Wen Chen, Hongxing Xu

Abstract: Capturing molecular dynamics in nanoconfined channels with high spatiotemporal resolution is a key challenge in nanoscience, crucial for advancing catalysis, energy conversion, and molecular sensing. Bottom-up ultrathin plasmonic nanogaps, such as nanoparticle-on-mirror (NPoM) structures, are ideal for ultrasensitive probing due to their extreme light confinement, but their perceived sealed geomet… ▽ More Capturing molecular dynamics in nanoconfined channels with high spatiotemporal resolution is a key challenge in nanoscience, crucial for advancing catalysis, energy conversion, and molecular sensing. Bottom-up ultrathin plasmonic nanogaps, such as nanoparticle-on-mirror (NPoM) structures, are ideal for ultrasensitive probing due to their extreme light confinement, but their perceived sealed geometry has cast doubt on the existence of accessible transport pathways. Here, counterintuitively, we demonstrate that ubiquitous ligand-capped NPoM-type nanogaps can form a natural quasi-two-dimensional nanochannel, supporting molecular transport over unprecedented length scales ($\gtrsim5$ $μ$m) with an extreme aspect ratio ($>10^3$). Using wavelength-multiplexed Raman spectroscopy, we resolve the underlying centripetal infiltration pathway with a spatial resolving power of $\sim$20 nm. This redefines the NPoM architecture as a sensitive, \textit{in-situ}, all-in-one "transport-and-probe" platform, enabling real-time, reusable monitoring of analyte with $\sim$10$^{-11}$ M. This work establishes a versatile new platform for advancing super-resolved \textit{in-situ} molecular sensing, nanoscale physicochemical studies, and on-chip nanophotofluidics. △ Less

Submitted 30 September, 2025; originally announced September 2025.

A FFT-based GMRES for fast solving of Poisson equation in concatenated geometry

Authors: Zichao Jiang, Jiacheng Lian, Zhuolin Wang

Abstract: Fast Fourier Transform (FFT)-based solvers for the Poisson equation are highly efficient, exhibiting $O(N\log N)$ computational complexity and excellent parallelism. However, their application is typically restricted to simple, regular geometries due to the separability requirement of the underlying discrete operators. This paper introduces a novel domain decomposition method that extends the appl… ▽ More Fast Fourier Transform (FFT)-based solvers for the Poisson equation are highly efficient, exhibiting $O(N\log N)$ computational complexity and excellent parallelism. However, their application is typically restricted to simple, regular geometries due to the separability requirement of the underlying discrete operators. This paper introduces a novel domain decomposition method that extends the applicability of FFT-based solvers to complex composite domains geometries constructed from multiple sub-regions. The method transforms the global problem into a system of sub-problems coupled through Schur complements at the interfaces. A key challenge is that the Schur complement disrupts the matrix structure required for direct FFT-based inversion. To overcome this, we develop a FFT-based preconditioner to accelerate the Generalized Minimal Residual (GMRES) method for the interface system. The central innovation is a novel preconditioner based on the inverse of the block operator without the Schur complement, which can be applied efficiently using the FFT-based solver. The resulting preconditioned iteration retains an optimal complexity for each step. Numerical experiments on a cross-shaped domain demonstrate that the proposed solver achieves the expected second-order accuracy of the underlying finite difference scheme. Furthermore, it exhibits significantly improved computational performance compared to a classic sparse GMRES solver based on Eigen libeary. For a problem with $10^5$ grid points, our method achieves a speedup of over 40 times. △ Less

Submitted 27 September, 2025; originally announced September 2025.

Flow reorganization and transport enhancement in two-dimensional horizontal convection near a density extremum

Authors: Zhiyang Cai, Shengqi Zhang, Kaizhen Shi, Zhouxin Jiang, Shijun Liao

Abstract: Horizontal convection serves as a canonical model for geophysical and industrial flows. While the Oberbeck-Boussinesq approximation is well established, the impact of a nonlinear equation of state, specifically the density extremum of water near $4^\circ\mathrm{C}$, remains underexplored. Here we investigate this effect using two-dimensional direct numerical simulations over the Rayleigh number ra… ▽ More Horizontal convection serves as a canonical model for geophysical and industrial flows. While the Oberbeck-Boussinesq approximation is well established, the impact of a nonlinear equation of state, specifically the density extremum of water near $4^\circ\mathrm{C}$, remains underexplored. Here we investigate this effect using two-dimensional direct numerical simulations over the Rayleigh number range $10^6 \le Ra \le 5\times 10^{10}$. We examine four configurations, contrasting extremum (EXT) and monotonic (MON) buoyancy boundary conditions against linear (LENT) and nonlinear (NELT) equations of state. Our results reveal that the EXT-NELT case undergoes a pronounced reorganization of the large-scale flow, evolving from a bicellular structure to a single-roll circulation driven by central `mixing plumes'. This reorganization manifests as transitional anomalies in the $Re$ scaling, while the emergence of full-depth plumes alters the heat transport mechanism. Consequently, distinct from the Rossby scaling ($Nu \sim Ra^{1/5}$) observed in the reference cases, the EXT-NELT case exhibits an enhanced heat transport scaling ranging from $Nu \sim Ra^{1/4}$ to $Nu \sim Ra^{1/3}$. To interpret this behaviour, we examine the total energy budget and identify an additional potential-energy transfer term, \(Φ_{i2}\), arising from the nonlinear equation of state. The scaling argument suggests that the magnitude of this contribution is controlled by the characteristic plume height ($\hat{z}$). Specifically, when plumes penetrate the entire cavity depth ($\hat{z} \sim H$), as observed in the EXT-NELT case, the global kinetic energy dissipation is no longer described by the standard OB HC energy closure alone. The resulting model captures the main trends of the numerical data and provides a possible energy budget interpretation of the enhanced transport observed in this two-dimensional configuration. △ Less

Submitted 17 June, 2026; v1 submitted 17 August, 2025; originally announced August 2025.

Numerical Study of Oblique Detonation Initiation Assisted by Local Energy Deposition

Authors: Ziqi Jiang, Zongnan Chen, Lisong Shi, Zijian Zhang, Jiaao Hao, Chih-yung Wen

Abstract: Reliable initiation of oblique detonation waves (ODWs) is crucial for the stable operation of oblique detonation engines (ODEs), especially under flight conditions of low Mach numbers and/or high altitudes. In this case, conventional initiation approaches relying solely on a fixed-angle wedge may engender risks of initiation failure, which necessitates extra initiation assistance measures. In this… ▽ More Reliable initiation of oblique detonation waves (ODWs) is crucial for the stable operation of oblique detonation engines (ODEs), especially under flight conditions of low Mach numbers and/or high altitudes. In this case, conventional initiation approaches relying solely on a fixed-angle wedge may engender risks of initiation failure, which necessitates extra initiation assistance measures. In this study, ODW initiation over a finite wedge with local energy deposition is numerically investigated to assess the thermal effects of plasma-based initiation assistance techniques. Particular emphasis is put on the effects of forms and magnitudes of energy deposition on initiation modes and flow field structures of ODWs. The results demonstrate that on-wedge initiation of ODWs fails at a low Mach number without any energy depositions. In contrast, both continuous and pulsatile local energy depositions can effectively initiate ODWs, leading to sustainable detonation on the finite wedge. As continuous energy deposition power or pulsatile single pulse energy increases, several key detonation initiation modes emerge sequentially. Analysis of the spatiotemporal evolution of the primary wave structures under single-pulse energy deposition reveals the minimum pulse repetition frequency required for sustainable on-wedge detonation, which is subsequently verified through multi-pulse energy deposition simulations. Nevertheless, it is found that sustainable on-wedge detonation can be achieved by pulsatile energy deposition with an average power consumption of less than 10% of that required for continuous energy deposition while maintaining a same initiation length, suggesting that the pulsatile one is an efficient way of energy deposition for initiation assistance of ODWs on finite wedges under extreme flight conditions. △ Less

Submitted 12 August, 2025; originally announced August 2025.

Comments: 34 pages, 26 figures

Quantitative Benchmarking of Remote Excitation in Plasmonic Sensing with Enhanced Signal-to-Noise Ratio

Authors: Tao He, Haoran Liu, Zihe Jiang, Zhiwei Hu, Banghuan Zhang, Xiaohui Dong, Chaowei Sun, Wei Jiang, Jiawei Sun, Yang Li, Huatian Hu, Wen Chen, Hongxing Xu

Abstract: Remote excitation using guided optical modes -- such as waveguides, fibers, or surface waves -- offers a promising alternative to direct optical excitation for surface-enhanced Raman scattering (SERS), particularly in applications requiring reduced heating, minimal invasiveness, and on-chip integration. However, despite its widespread use, systematic comparisons between remote and direct excitatio… ▽ More Remote excitation using guided optical modes -- such as waveguides, fibers, or surface waves -- offers a promising alternative to direct optical excitation for surface-enhanced Raman scattering (SERS), particularly in applications requiring reduced heating, minimal invasiveness, and on-chip integration. However, despite its widespread use, systematic comparisons between remote and direct excitation remain limited. Here, we quantitatively benchmark both schemes by measuring power-dependent SERS responses from individual plasmonic nanogaps. We statistically analyze the maximum achievable SERS intensity before structural degradation, extract local temperatures, and evaluate signal-to-noise ratios (SNR). Our findings reveal that both remote and direct SERS share a common electric-field limit, despite exhibiting different levels of heating. This suggests that spectral evolution is primarily governed by the local electric field, which drives nanoscale atomic migration rather than excessive heating. Nonetheless, the lower heating associated with remote excitation enhances the Raman SNR by approximately 30%, improving measurement quality without compromising signal strength. This study establishes a quantitative framework for evaluating excitation strategies in plasmonic sensing, and challenges common assumptions about the role of heating in nanostructural stability under strong optical excitation. △ Less

Submitted 30 July, 2025; originally announced July 2025.

Comments: 5 figures

A Self-Evolving AI Agent System for Climate Science

Authors: Zijie Guo, Jiong Wang, Fenghua Ling, Wangxu Wei, Xiaoyu Yue, Zhe Jiang, Wanghan Xu, Jing-Jia Luo, Lijing Cheng, Yoo-Geun Ham, Fengfei Song, Pierre Gentine, Toshio Yamagata, Ben Fei, Wenlong Zhang, Xinyu Gu, Chao Li, Yaqiang Wang, Tao Chen, Wanli Ouyang, Bowen Zhou, Lei Bai

Abstract: Scientific progress in Earth science depends on integrating data across the planet's interconnected spheres. However, the accelerating volume and fragmentation of multi-sphere knowledge and data have surpassed human analytical capacity. This creates a major bottleneck for discovery, especially in climate science. To address this challenge, we introduce EarthLink, the first self-evolving AI agent s… ▽ More Scientific progress in Earth science depends on integrating data across the planet's interconnected spheres. However, the accelerating volume and fragmentation of multi-sphere knowledge and data have surpassed human analytical capacity. This creates a major bottleneck for discovery, especially in climate science. To address this challenge, we introduce EarthLink, the first self-evolving AI agent system designed as an interactive "copilot" for Earth scientists. Through natural language interaction, EarthLink automates the entire research workflow by integrating planning, code execution, data analysis, and physical reasoning into a unified process that directly addresses this limitation. Beyond efficiency, it exhibits human-like cross-disciplinary analytical ability and achieves proficiency comparable to a junior researcher in expert evaluations on core large-scale climate tasks, including model-observation comparison and climate change understanding. When tasked with an open scientific problem, specifically the discovery of precursors of the Atlantic Niño, EarthLink autonomously developed a research strategy, identified sources of predictability, verified its hypotheses with available data, and proposed a physically consistent mechanism. These emerging capabilities enable a new human-AI research paradigm. Scientists can focus on value and result judgments, while AI systems handle complex data analysis and knowledge integration. This accelerates the pace and breadth of discovery in Earth sciences. The system is accessible at our website https://earthlink.intern-ai.org.cn. △ Less

Submitted 3 November, 2025; v1 submitted 23 July, 2025; originally announced July 2025.