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Physics Physics

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Wednesday 20 May

Instrumentation and Detectors

Development of a xenon triple point apparatus suitable for calibrating long-stem SPRTs and preliminary measurements of the temperature

Yikun Zhao, Jintao Zhang, Xiaojuan Feng et al. (+5 more)

Xenon is of high chemical-physical stability and health compatibility. The xenon triple point (Xe TP) is accounted for a promising candidate replacing the mercury triple point (Hg TP) from the set of the defining fixed points of the international temperature scale ITS-90. The success of the alternative highly depends on the level of the realization of the Xe TP using long-stem standard platinum resistance thermometers (LSPRTs). We report in this article our study on the development of an immersion-type Xe TP apparatus, which is suitable for calibration of both LSPRTs and capsule standard platinum resistance thermometers (CSPRT). We realize the melting plateaus of the Xe TP using the continuous heating method on the apparatus. The effective melting plateaus extend for 8-12 hours long with temperature flatness range of 0.37 mK-1.0 mK over the melted fractions from 0.2 to 0.75. We find the axial heat leak contributing a principal effect influencing measurements of the Xe TP. We investigate the effect by varying the offset temperatures on the outer wall of the Xe TP cell. We measure the Xe TP using two LSPRTs upon correction of the axial heat leak. The new measurement, giving the Xe TP of 161.405 71 (55) K (k=1) at the melted fraction F=1.0, agrees well with those previously obtained by the adiabatic apparatuses. Their differences fall within 0.11 mK to 0.42 mK. by. Those differences are well covered by the estimated measurement uncertainty.
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All authors Yikun Zhao, Jintao Zhang, Xiaojuan Feng, Yu Liang, Yongdong He, Hua Zhuo, Xiangrui Deng, Haibing Li

Optics

Scalable native signed optical computing enabled by dual-wavelength incoherent multiplexing

Yuan Ren, Yong Zheng, Ruixue Liu et al. (+4 more)

Incoherent photonic neural networks (PNNs) provide a robust platform for analog optical computing, yet efficient implementation of native signed operations remains challenging. Existing incoherent PNNs approaches often require additional spatial channels or temporal encoding steps to represent bipolar input signals, resulting in hardware overhead that scales with system size. Here, we demonstrate a dual-wavelength incoherent photonic architecture that natively supports both signed inputs and signed weights on a thin-film lithium niobate platform. By encoding complementary signal components onto two wavelength channels and performing computation within a shared physical path, the proposed scheme eliminates duplicated weighting units. As a result, the additional hardware overhead associated with signed computation remains constant per multiply accumulate operation, independent of matrix size. The fabricated device exhibits a modulation bandwidth exceeding 40 GHz and achieves four-quadrant optical multiplication with a standard deviation error of 1.27%. System-level functionality is validated through neural-network classification, achieving 95.1% accuracy on the Moons dataset and 91.63% on MNIST. These results establish a practical route toward scalable incoherent photonic computing systems with native bipolar processing capability.
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All authors Yuan Ren, Yong Zheng, Ruixue Liu, Yunpeng Song, Qinfen Huang, Min Wang, Ya Cheng

Optics

Local Chiral Optical Responses in Phthalocyanine Molecular Assemblies Revealed by Photoinduced Force Microscopy

Masayoshi Fujii, Mamoru Tamura, Hidemasa Yamane et al. (+1 more)

Photoinduced force microscopy (PiFM) provides a force-based probe of nanoscale polarization-dependent molecular excitations. Here, we theoretically investigate PiFM images of zinc phthalocyanine assemblies using the discrete dipole approximation with nonlocal molecular susceptibilities. Under linearly polarized illumination, intermolecular dipole coupling splits the molecular resonance into bonding and antibonding modes. These modes produce distinct force distributions: bonding modes enhance signals at molecular termini, whereas antibonding modes localize responses in intermolecular regions, reflecting collective intermolecular polarization modes. Under circularly polarized illumination, intermolecular coupling and anisotropic molecular packing generate spatially varying local circular dichroism signals with enhanced asymmetric force factors. These results establish PiFM as a real-space probe of collective polarization modes and coupling-induced local chiral optical responses.
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All authors Masayoshi Fujii, Mamoru Tamura, Hidemasa Yamane, Hajime Ishihara

Optics

Towards compact high-frequency nonreciprocal devices using nanoplasma-switched time-varying metasurfaces

Mikhail Sidorenko, Jin Zhang, Xuchen Wang et al. (+3 more)

Time-modulated systems have received growing interest in recent years. They allow us to tailor effects, such as frequency conversion, single-direction propagation, etc. For the microwave band, semiconductor elements, such as varactors, are usually used as time-modulated elements but their modulation frequency has been limited to the few-gigahertz range. Recent advances in nanoplasma switches, i.e., two-state electronic switches based on a gas discharge in a nanometer-scale gap, provide a new potential for developing time-modulated systems with high operating frequencies. Here, we develop an analytical framework based on the time-Floquet method for the design of nonreciprocal time-modulated devices based on two-state time-modulated elements, for instance, nanoplasma-based switches. A practical example of a microwave isolator operating at 100~GHz frequency is developed and studied both analytically and using full-wave simulations. A potential realization in a parallel-plate waveguide is also simulated numerically.
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All authors Mikhail Sidorenko, Jin Zhang, Xuchen Wang, Zhipei Sun, Sergei Tretyakov, Viktar Asadchy

Applied Physics

Lasing from SOI-integrated GaAsSb nanowires via resonator-driven optical feedback

J. Zöllner, C. Doganlar, C. García Marcilla et al. (+3 more)

Silicon photonic integrated circuits critically depend on compact on-chip light sources, for which nanowire (NW) lasers are an attractive solution. However, their practical implementation is often limited by broad emission linewidths and poor frequency stability resulting from weak optical feedback. Here, we integrate individual GaAsSb NWs by transfer-printing onto silicon-on-insulator (SOI) racetrack resonators to realize optical feedback at silicon-transparent wavelengths. Finite-difference-time-domain simulations reveal efficient coupling between the hybrid NW-waveguide mode and the fundamental TE resonator mode, with calculated cavity Q-factors exceeding 10$^4$. Experimentally, we observe feedback-induced lasing emission at a low threshold (P$_{th}$) of 8.6 $\pm$ 1.8 $\mu$J/cm$^2$. Compared to identical NW lasers without SOI resonator, the linewidth is reduced by more than a factor of four at 3P$_{th}$ and remains stable below 1.8 meV up to 5P$_{th}$. Our results demonstrate NW-based light sources on SOI and show that tailored resonator designs enable improved linewidth control and frequency stabilization.
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All authors J. Zöllner, C. Doganlar, C. García Marcilla, S. Meder, G. Koblmüller, J. J. Finley

Chemical Physics

DynaMate2: runtime registration of expert-defined tools for agentic scientific workflow automation

Orlando A. Mendible-Barreto, Ajay Vallabh, Ubaldo M. Córdova-Figueroa et al. (+1 more)

Agentic large-language-model systems can coordinate scientific tools, but many implementations remain difficult for domain scientists to extend without modifying the source orchestration code or relying on unconstrained code generation. DynaMate2 is a LangGraph-based multi-agent framework for converting expert-defined Python functions into persistent AI-callable tools. The architecture separates domain execution from LLM supervision: registered tools perform scientific operations, while a supervisor LLM decomposes goals, selects specialist agents, routes inputs, and propagates outputs across steps. DynaMate2 supports: runtime tool registration from inline code, source files, and explicitly requested natural-language specifications; persistent storage of tools, agents, and conversation state; and a web interface for interactive workflow assembly. We demonstrate the framework on a molecular simulation workflow in which a single instruction retrieves a MACE foundation model, builds a NaCl-water configuration, runs an ASE molecular dynamics trajectory, and generates energy and temperature diagnostics. The demonstration illustrates how validated workflow components can be composed into a supervised agentic pipeline without rewriting the framework. DynaMate2 therefore provides a reusable template for extending LLM-based automation to research groups with existing Python workflows, while preserving the need for explicit tool validation, reproducibility logs, and deployment-specific safeguards.
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All authors Orlando A. Mendible-Barreto, Ajay Vallabh, Ubaldo M. Córdova-Figueroa, Yamil J. Colón

Instrumentation and Detectors

A 24-Channel Ultra-Low-Noise Preamplifier for dN/dx Measurements with Drift Tube Detectors

Jiajin Ge, Chihao Li, Can Suslu et al. (+6 more)

Cluster counting dN/dx is a promising method to enhance particle identification for gaseous detectors, especially in next-generation collider experiments like the FCC-ee, where good pion-kaon separation over a broad momentum range is essential. However, its implementation in large-scale systems has been limited by the challenging requirements for high-resolution signal amplification and readout. This paper presents a 24-channel ultra-low-noise preamplifier board designed for drift tube detectors to enable dN/dx measurements. The three-stage amplification topology employs SiGe transistors and integrates dedicated noise-minimization techniques, achieving a charge gain of 21.11 mV/fC from 0.3 fC to 50 fC, a bandwidth of 542 MHz, and a voltage gain of 47.8 dB. The measured voltage noise density is 0.35 nV/sqrt(Hz), surpassing most of the state-of-the-art preamplifiers for gaseous and silicon detectors. Validation tests conducted on the sMDT chambers at the CERN Proton Synchrotron test beam facility demonstrate that the proposed design meets the stringent preamplifier requirements for implementing the dN/dx method in drift-tube detector systems, achieving an equivalent noise charge of 0.14 fC and a signal-to-noise ratio of 73 when operated with a He:iC4H10 (90:10) gas mixture. The design also shows promise for broader application in other gaseous or semiconductor detectors.
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All authors Jiajin Ge, Chihao Li, Can Suslu, Yuxiang Guo, Emmett Salzer, Tiesheng Dai, Jianming Qian, Bing Zhou, Junjie Zhu

Fluid Dynamics

Deep Reinforcement Learning Discovers a Novel Control Algorithm for Mitigating Flow-Induced Vibrations in Underactuated Tandem Cylinders

Hussam Sababha and Mohammed Daqaq

This study presents the first experimental implementation of deep reinforcement learning (DRL) for the active real-time suppression of flow-induced vibrations in simultaneously vibrating tandem cylinders using rotary actuation, considering fully actuated and underactuated configurations. In the fully actuated case, where both cylinders are independently controlled, the DRL agent discovers a high-frequency, phase-locked bang-bang control strategy that suppresses the vibrations of both cylinders by more than 95%. Analysis of the training dynamics reveals a physically interpretable learning process in which the agent first identifies the optimal phase relationship between the actuators before refining the actuation frequency. In the underactuated configuration, where only the upstream cylinder is actuated, equally weighted rewards produce ineffective control, suppressing vibrations only in the actuated cylinder. Introducing asymmetric reward weighting enables the DRL agent to discover a low-frequency lock-on strategy that achieves 70% and 90% vibration suppression in the upstream and downstream cylinders, respectively. For staggered arrangements with lateral offset, conventional training fails to converge, requiring a curriculum learning approach. The resulting two-stage curriculum identifies a statically biased bi-harmonic rotational control signal capable of suppressing vibrations in both cylinders. The success of the underactuated control strategy highlights its potential to reduce energy consumption and hardware complexity in multi-body flow control systems.
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Optics

Mid-infrared single-photon sub-pixel temporal ghost imaging

Wen Zhang, Kun Huang, Zhibin Zhao et al. (+4 more)

Temporal ghost imaging (TGI) enables ultrafast temporal signal recovery using slow detectors, offering a promising route for high-speed mid-infrared (MIR) detection. However, conventional schemes remain limited in temporal resolution by the modulation bandwidth or pattern timescale, and are mostly confined to structured illumination. Here, we demonstrated a high-resolution MIR single-photon computational TGI system, which integrated nonlinear structured detection with sub-pixel temporal shifting. A pre-programmed near-infrared pump serves as a temporally optical gate to drive sum-frequency generation in a nonlinear crystal. Consequently, MIR waveforms at 3.4 $\mu$m were upconverted, and captured by a room-temperature silicon detector. We realized sub-pixel operation by fractional-bin temporal stepping of the gate and multi-shot fusion via pseudo-inverse reconstruction. The sub-pixel shifting strategy decouples the achievable resolution from modulation speed, enabling 40 ps temporal precision at a driving rate of only 3.125 Gbps. This performance surpasses both detector jitter and pattern-rate limits, while maintaining single-photon sensitivity. The presented paradigm establishes a versatile route for ultrafast MIR waveform reconstruction, opening new opportunities in high-resolution infrared sensing and quantum photonics.
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All authors Wen Zhang, Kun Huang, Zhibin Zhao, Huijie Ma, Ziyu He, Jianan Fang, Heping Zeng

Geophysics · Cross-listed from cs.CE

HyFrac.fun: A 3D Hydraulic Fracturing Simulator on Cloud

Jing Hu, Qian Liu and Jaroon Rungamornrat

When multiple hydraulic fractures propagate simultaneously from a horizontal wellbore, elastic stress-shadow interactions generate complex non-planar three-dimensional geometries whose effect on subsequent reservoir drainage has infrequently been quantified, because the propagation and production solvers have historically been incompatible stand-alone tools. This paper presents HyFrac.fun, a cloud-native platform that bridges this gap by exploiting a structural isomorphism between the two SGBEM–FEM governing operator systems. The platform enables automated zero-conversion handoff of the evolved 3D fracture mesh directly to the steady-state Darcy production solver for realizing a fully integrated lifecycle simulation of multi-stage non-planar hydraulic fractures. The lifecycle analysis reveals a double shadow phenomenon: the mechanical stress shadow that suppresses inner-fracture growth during stimulation mirrors a fluid pressure shadow that reduces the inner fracture's drawout rate at small cluster spacing. Critically, switching to a shear-thinning power-law fracturing fluid leaves the fracture trajectories and production rates almost unchanged, demonstrating that stress-shadow-controlled fracture geometry instead of fluid rheology is the primary determinant of long-term production efficiency at equal injection rates. These physics findings are accessible from integrated fracture propagation and production simulations.
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Optics

Coherent control of the Goos-Hänchen shift in Otto structure

Magdi Bajusair, Mohammad H. Alhakami and Saeed Asiri

We investigate controlling the lateral Goos-Hänchen (GH) shift for a TM-polarized field reflected from Otto structure containing four level N-type atomic medium. The N-type atomic configuration can be formed by coupling the standard three-level $\Lambda$ system to an additional upper energy level through a coherent driving field. The medium can then be switched from transparent to absorptive under the effect of the driving field. In the Otto structure, an air gap typically separates a dielectric prism from a metal film. We show that the sign and magnitude of the GH shift can be highly controlled when the air gap is replaced by the coherent atomic medium. This can be achieved by adjusting the strength of the applied fields to the atomic medium, while the geometrical characteristics of the proposed structure are unchanged.
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Optics

Wide-field mid-infrared edge-enhanced upconversion imaging

Mengyao Yu, Zhuohang Wei, Jianan Fang et al. (+5 more)

Edge-enhanced imaging is critical for visualizing weakly absorbing and transparent objects. Extending this functionality into the mid-infrared (MIR) region enables chemical sensitivity and improved imaging performance for biomedical, material, and remote-sensing applications. Here, we present a wide-field MIR edge-enhanced upconversion imaging system that integrates vortex-pump complex-amplitude engineering with aperiodic quasi-phase matching. In contrast to the bright-field modality, the wide-field edge-enhanced operation shows sensitive dependence on the crystal position relative to the Fourier plane. The system achieves single-shot operation with a 25-mm field of view and 79-$\mu$m spatial resolution, yielding a record-high space-bandwidth product of $7.9 \times 10^4$. We show that this capability enables direct visualization of phase gradients in transparent optical elements and enhances structural contrast in biological specimens. The demonstrated architecture combines high sensitivity, spectral specificity, and robust edge detection, offering a promising route toward advanced MIR imaging in industrial inspection and biomedical diagnostics.
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All authors Mengyao Yu, Zhuohang Wei, Jianan Fang, Jixi Zhang, Tingting Zheng, Shina Liao, Kun Huang, Heping Zeng

Optics

HotLoop Optimization of Petawatt Laser Focal Spot via a Twin-Focus Scheme

Qingfan Wu, Ying Gao, Minjian Wu et al. (+25 more)

Achieving diffraction-limited focusing of high-power laser pulses to generate ultra-high intensities is crucial for developing compact laser-driven particle accelerators and exploring strong-field quantum electrodynamics. However, accurately diagnosing and optimizing the focal spots of petawatt (PW) laser pulses remains a significant challenge. In this work, we present an experimental methodology utilizing a twin-focus scheme to precisely characterize the intensity distribution and wavefront of focused PW femtosecond laser pulses, and employ it to elucidate their power-dependent evolution. Furthermore, we optimized the focal spots at full power via our in-situ wavefront correction method termed “HotLoop', achieving a Strehl ratio of 0.80 for 1 PW laser pulses. Consequently, the cutoff proton energies in laser proton acceleration experiments were significantly enhanced. The success of this approach underscores the necessity of in-situ high-energy wavefront correction for ultra-high intensity laser-matter interactions.
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All authors Qingfan Wu, Ying Gao, Minjian Wu, Jiarui Zhao, Shiyou Chen, Tianhao Liang, Haoran Chen, Tan Song, Zhongshuai Zhang, Zhangyi Wu, Shirui Xu, Ziyang Peng, Tianqi Xu, Zhuo Pan, Yujia Zhang, Qihang Han, Ke Chen, Chenghao Hua, Pengcheng Fan, Yuntian Xie, Yifei Shen, Shengxuan Xu, Liyong Ma, Yixing Geng, Chen Lin, Yanying Zhao, Xueqing Yan, Wenjun Ma

Optics

Probing Lattice Dynamics in Real-Space and Real-Time

Navdeep Rana

The coherent lattice vibrations significantly impact physical and chemical processes in solids, such as heat transfer, displacive phase transitions, and thermal conductivity. Thus, probing lattice dynamics in real-space and real-time is essential for understanding ubiquitous phenomena in solids. High-harmonic spectroscopy (HHS) has emerged as a preferred technique for investigating static and dynamic properties of solids on ultrafast timescales. Yet, despite these accomplishments, the applicability of HHS to probe the influence of coherent lattice vibrations on electronic responses has remained unexplored. In this thesis, we explore the impact of coherent lattice dynamics on attosecond electronic responses in solids using HHS. We observe that coherent excitation of the in-plane phonon mode in graphene results in sidebands in the harmonic spectrum, separated by the frequency of the excited phonon mode. Additionally, we demonstrate the capability of HHS to characterize energy, polarization, phase difference, and the "chirality" of phonon modes. This thesis offers an avenue to probe phonon-driven processes in solids with sub-cycle temporal resolution. In the later segment, our focus shifts toward probing coherent lattice dynamics in real-space and real-time. We demonstrate that inelastic scattering techniques, combined with theoretical analysis, yield comparable results to those from time-resolved diffraction and imaging measurements within pump-probe configurations. Our findings exhibit excellent agreement with results from a time-resolved diffuse x-ray scattering experiment. Our proposed method serves as an alternative to time-resolved diffraction and imaging methods for probing lattice dynamics in real-space and real-time with atomic-scale spatiotemporal resolution.
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Optics

Engineering Hybrid Resonances in Nanophotonics

Shutao Zhang, Cheng-Feng Pan, Yandong Fan et al. (+9 more)

Hybridization of resonances is known to overcome inherent limitations of individual systems, enabling advanced functionalities and applications. Here we discuss hybrid plasmonic-Mie resonators that emerged recently as a promising direction in advancing nanophotonic structures by synergistically combining the strong near-field enhancement of plasmonic components with the low-loss, multipolar resonances of dielectric Mie elements. We review the recent progress in the field, encompassing the fundamental physical principles, structural design strategies, material platforms, computational optimization approaches, and representative device implementations. Our discussion starts by evaluating the complementary characteristics of plasmonic and Mie resonances followed by a description of the coupling between these resonances in order to boost light-matter interactions. Afterward, we explore the performance of efficient hybrid resonators for different application areas. Apart from the conventional metal-dielectric systems, we consider the recent class of epsilon-near-zero (ENZ) materials, which can provide unique advantages in terms of field localization, phase engineering, and energy flow management in the vicinity of zero-permittivity conditions, offering more flexibility in designing hybrid nano-optical devices. Lastly, we point out potential research avenues aiming to improve functional and efficient nanophotonic devices, especially those involving emerging topological material systems, such as Sb2Te3, Bi2Te3, Bi2Se3, combining plasmonic amplification, dielectric confinement, and spin-dependent optical behavior.
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All authors Shutao Zhang, Cheng-Feng Pan, Yandong Fan, Jehyeon Shin, Yuanda Liu, Yan Liu, Jun Ding, Jing Wu, Junsuk Rho, Yuri Kivshar, Joel K. W. Yang, Zhaogang Dong

Optics

Gold Bipyramids as a Promising Alternative to Gold Nanorods for Analytical and Biomedical Applications

Andrey M. Burov, Sergey V. Zarkov, Arina V. Drozd et al. (+3 more)

Pentagonal gold bipyramids with dimensions of 75x25 nm and a longitudinal plasmon resonance (PR) at 753 nm are synthesized. For comparison, gold nanorods with a diameter of 20 nm, lengths ranging from 95 to 50 nm, and longitudinal PR from 945 to 644 nm were synthesized by chemical etching. The samples were characterized by UV-vis spectroscopy and transmission electron microscopy (TEM). It is shown that the absorption spectral quality factor of the bipyramids is significantly higher than that of the nanorods. To compare the nanoparticles as platforms for surface-enhanced Raman scattering (SERS), their surface was functionalized with thiolated nitrobenzene molecules (NBT). It is demonstrated that the SERS enhancement factor for the bipyramids is approximately three times higher than that for the nanorods. The red shift of the bipyramids' PR after functionalization with NBT molecules is also about three times greater than for nanorods with the same PR. This agrees with the theoretical estimate of the bipyramids' PR shift being more sensitive to variations in the refractive index of the external medium or the dielectric shell thickness than that of gold nanospheres and nanorods. The high efficiency of the bipyramids as thermosensitizers for converting laser radiation into heat in photothermal therapy is experimentally and theoretically demonstrated. Effective photothermal killing of E. coli was shown upon irradiation with a laser at the plasmon resonance wavelength using nanobipyramids or nanorods.
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All authors Andrey M. Burov, Sergey V. Zarkov, Arina V. Drozd, Igor V. Borisov, Elena G. Zavyalova, Nikolai G. Khlebtsov

Fluid Dynamics

Multi-scale flow analysis for scale-aware urban-canopy models

Jingzi Huang and Maarten van Reeuwijk

As Numerical Weather Prediction (NWP) models approach hectometric resolution, they increasingly enter a regime where urban heterogeneity is only partially resolved and the assumptions underlying conventional urban canopy models (UCMs) become questionable. To address this scale gap, we apply a multi-scale coarse-graining framework (van Reeuwijk and Huang 2025, Boundary-Layer Meteorology) to building-resolving Large-Eddy Simulations (LES) of the University of Bristol campus. Two related morphologies are considered: an original layout with large open-space contrasts and a modified configuration with these regions infilled. By systematically filtering the LES fields, we quantify how flow heterogeneity evolves with resolution and identify a characteristic urban length scale at which resolved and unresolved variability are comparable. This scale is strongly morphology-dependent, with values of about 256 m for the original layout and 64 m for the modified case, showing that neighbourhood-scale organisation can remain important at resolutions relevant to next-generation NWP. We then perform an a priori assessment of distributed drag and turbulent-stress parameterisations. Parameterisations derived from idealised geometries perform reasonably well only at sufficiently coarse resolutions, where horizontal transport is negligible and the flow appears approximately homogeneous. At finer resolutions, their fidelity degrades rapidly because of increasing heterogeneity and filter-to-filter variability in morphology, with stronger limitations in realistic layouts than in idealised cuboid arrays. Overall, the results show that the applicability of urban parameterisations depends critically on the relationship between model resolution and a morphology-dependent heterogeneity scale, providing a systematic route for developing scale-aware UCMs for high-resolution NWP.
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Tuesday 19 May

Applied Physics

19 GHz Single-Ended-to-Balanced Modified Ladder-Lattice Filters Realized Using Periodically Polarized AlScN BAW Resonators

Merrilyn M. A. Fiagbenu, Shun Yao, Siddhant Sahoo et al. (+6 more)

We present a single-ended to balanced modified ladder-lattice filter topology, realized with periodically polarized piezoelectric (P3F) AlScN resonators, for single-ended to differential filtering applications. This filter topology eliminates the need for baluns or other passive components and can interface, for instance, directly between differential antennas and single-ended power and low noise amplifiers. Two filter designs operating at 19 GHz were implemented. The first design exhibited a minimum insertion loss of 1.3 dB, a 6.26% fractional 3-dB bandwidth, an average out-of-band rejection of 30 dB and occupied a 348 um x 476 um footprint, while the second higher-selectivity filter achieved 1.58 dB of minimum insertion loss, 5.11% fractional 3-dB bandwidth, 33 dB of average out-of-band rejection, and occupied a 392 um x 476 um footprint - Making them highly competitive for wireless communications filters. The working principle of the modified ladder-lattice topology is discussed, the design of the filters are presented, and the linearity of the filters is explored through intermodulation and power handling measurements.
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All authors Merrilyn M. A. Fiagbenu, Shun Yao, Siddhant Sahoo, Mojtaba Hodjat-Shamami, Daeho Kim, Craig Moe, Pinal Patel, Ramakrishna Vetury, Roy H. Olsson III

Fluid Dynamics · Cross-listed from cs.RO

Linear Motility Maps in Nonlinear Viscous Fluids

Yishun Zhou and Shai Revzen

Systems moving in low Reynolds number fluid regimes are known to be governed by a “motility map” which linearly relates their shape change rates to they body frame velocity moving through the fluid. A consequence of this is “Purcell's Scallop Theorem” – a locomotion system that undergoes shape changes that follow the same path forward and backward in time (reciprocal body deformations) cannot achieve net displacement, regardless of pacing of those changes.We show that linear-in-velocity motility maps extend to any power law viscosity (a.k.a. Ostwald–de Waele fluid), and therefore to many biological fluids in intermediate shear ranges. We also show that the linear-in-velocity property can be violated in Carreau-Yasuda fluids to produce net motion using an “inchworm” model consisting of two unequal masses with unequal drag coefficients performing reciprocal motions. Interestingly, the direction of motion can be switched by changing speeds. Our results show that the linear motility map of geometric mechaincs can be used to analyze and design locomotion in power-law fluids, and that some nonlinear drag relationships such as Carreau-Yasuda can be exploited to generate net locomotion in seeming violation of the “scallop theorem”.
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Applied Physics · Cross-listed from quant-ph

Hybrid Classical-Quantum Neural Networks for Multi-Characteristic Co-Optimization of Recessed-Gate AlGaN/GaN MIS-HEMTs

Rushat Rai, Pei-Jie Chang, Doan Viet Nguyen et al. (+8 more)

Optimizing recessed-gate AlGaN/GaN MIS-HEMTs requires accurate multi-characteristic models, but experimental semiconductor datasets remain costly and encode process-induced variability that simulations cannot faithfully reproduce. This work proposes a hybrid classical-quantum neural network (HQNN) for joint optimization of six electrical targets from a 24-dimensional fabrication/process vector. We systematically screen quantum-circuit templates to extract circuit-design guidance, then select a final HQNN and compare it directly with classical baselines. On 468 experimental fabricated devices spanning 17 process splits, the selected HQNN, Circuit (13, 5) at L = 2, reduces overall normalized root mean square error (nRMSE) by 24.4% relative to ANN. Target-wise, the HQNN lowers Vth,lin RMSE from 0.297 V to 0.270 V, Vth,rev RMSE from 0.278 V to 0.263 V, DeltaVth RMSE from 0.049 V to 0.045 V, SS RMSE from 22.22 mV/dec to 19.87 mV/dec, and Id RMSE from 5.75 x 10^-8 A to 4.35 x 10^-8 A, while Ion RMSE remains competitive (0.053 A vs. 0.056 A). Controlled ansatz ablations further show that performance depends strongly on architecture: parameter count, depth, and two-qubit gate count correlate positively with accuracy, expressibility (DKL) correlates negatively, and controlled-rotation entanglers outperform static controlled-NOT (CNOT)-based circuits in aggregate. A depolarizing-noise study on a representative 4-qubit circuit further suggests that comparable HQNNs may be trainable or deployable on near-term quantum hardware.
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All authors Rushat Rai, Pei-Jie Chang, Doan Viet Nguyen, Yuan-Chieh Chiu, Niall Tumilty, Yun-Yuan Wang, Simon See, Wen-Jay Lee, Tai-Yue Li, Nan-Yow Chen, Tian-Li Wu

Atmospheric and Oceanic Physics

Improving Ensemble CAPE Forecasts with a Diffusion Model Incorporating Aerosol Information

Zachary James, Joseph Guinness and Arthur DeGaetano

Convective available potential energy (CAPE) is an important variable for forecasting severe weather and understanding deep convection and precipitation. The latest versions of the Global Forecast System (GFS) and related Global Ensemble Forecast System (GEFS) have exhibited a bias towards underestimating CAPE values during the summertime. We train an artificial intelligence (AI) diffusion model to improve the skill and uncertainty quantification of afternoon 6-hour lead time ensemble forecasts over the United States. Our model takes a GFS CAPE forecast as input and outputs an ensemble that significantly outperforms both GFS and GEFS 6-hour forecasts on root mean square error, continuous ranked probability score, and Brier score. We propose a two-stage training pipeline to leverage both a larger historical GFS forecast dataset and a smaller historical GEFS dataset, despite the two using initialization and parameterization schemes that vary over time. We also show that classifier-free guidance can be used to control the skill and spread of the forecasts. We then demonstrate the versatility of our framework by adding aerosol optical depths (AODs) of black carbon, organic carbon, dust, sea salt, and sulfates as additional input features. Aerosols can invigorate or suppress convection depending on atmospheric conditions. Our AI models effectively incorporate aerosols to produce improved CAPE forecasts. We interpret the model components by using permutation feature importance to rank the influence of the different AODs and find that black carbon, organic carbon, and sulfate aerosols have a greater impact on the model's CAPE predictions than sea salt and dust aerosols.
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Optics · Cross-listed from eess.SP

Statistical Characterization of Wind-Induced Beam Refraction and UAV Instability in Water-to-Air Optical Channels

Mohamed Nennouche, Ikenna Chinazaekpere Ijeh and Mohammad-Ali Khalighi

Direct water-to-air (W2A) optical communications experience strong beam refraction at the dynamic sea surface and unmanned aerial vehicle (UAV) instability. This letter proposes a novel and tractable statistical channel model for a vertical W2A link between an underwater node and an UAV under varying wind speeds, modeling wind-induced pointing errors with a Beta mixture fitted via the Expectation-Maximization algorithm. By accounting for link interruptions due to total internal reflection (TIR) and effective receiver field-of-view limitations, we derive closed-form expressions for the channel distribution and link outage probability. Our analysis reveals a fundamental TIR-induced outage floor limiting link reliability and providing insight for robust W2A system design.
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Data Analysis and Statistics · Cross-listed from stat.ME

Pairwise Distance-Diffusion Analysis (PDDA): A Geometric Framework for Estimating Hurst Exponents in Multivariate Long-Memory Processes

Diogo C. Soriano, Frederique Vanheusden and Slawomir J. Nasuto

We introduce Pairwise Distance-Diffusion Analysis (PDDA), a geometric framework that connects the Hurst exponent to the scaling of pairwise distances in long-memory stochastic processes. From a single distance-plot representation, PDDA yields three complementary routes to persistence: R/S-PDDA, based on the growth of geometric extrema; MSD-PDDA, based on the scaling of the second moment of lagged distances; and recurrence-volume scaling, in which the decay of close returns with increasing temporal separation reflects the expansion of the lagged displacement cloud. The framework extends naturally to multivariate isotropic and anisotropic processes, where the local spatial dimension specifies the available degrees of freedom while the Hurst exponents govern their temporal expansion. These results establish the distance plot as a common geometric representation of persistence, providing a unified distance-based foundation for Hurst analysis.
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Fluid Dynamics

Simulations of Particle-Laden Flows with Large Dispersed-Phase Size Disparities Using Scalable Parallel Adaptive Methods

Linfeng Jiang, Enrico Calzavarini and Dominik Krug

The numerical simulation of multiphase flows involving dispersed components with large scale disparities, such as the collisions between millimeter-sized bubbles and micron-sized mineral particles in flotation, poses a significant computational challenge. Accurately resolving the thin boundary layers of finite-size objects while tracking massive numbers of small particles within a large turbulent domain is often prohibitively expensive on uniform grids. To address this, we present a parallel scalable computational framework that couples the lattice Boltzmann method with the immersed boundary method on a dynamically adaptive octree grid. A key algorithm is developed for the efficient parallel host-cell searching, which significantly accelerates the tracking of Lagrangian points on distributed unstructured grids. The accuracy and robustness of the code are rigorously validated against canonical benchmarks, including the flow induced by an oscillating cylinder and the sedimentation of a sphere. The framework is applied to the multiscale problem of bubble-particle collisions. In quiescent flow, the simulations accurately capture the hydrodynamic interception mechanism, reproducing the theoretical collision efficiency scaling law proportional to the square of the particle-to-bubble size ratio. Furthermore, the framework is applied to the simulation of fully resolved bubbles interacting with inertial point particles in homogeneous isotropic turbulence.
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Chemical Physics

Double Electron Attachment and Double Ionization Potential Equation-of-Motion Coupled-Cluster Approaches with Full and Active-Space Treatments of 4-Particle-2-Hole and 4-Hole-2-Particle Excitations and Three-Body Clusters

Jun Shen, Karthik Gururangan and Piotr Piecuch

The double electron attachment (DEA) and double ionization potential (DIP) equation-of-motion coupled-cluster (EOMCC) methods including up to 4-particle-2-hole (4$p$-2$h$) and 4-hole-2-particle (4$h$-2$p$) excitations on top of coupled-cluster singles, doubles, and triples (CCSDT), denoted DEA-EOMCCSDT(4$p$-2$h$) and DIP-EOMCCSDT(4$h$-2$p$), have been efficiently implemented in full and active-space forms. The resulting methods are applied to determine the ground and low-lying excited states of methylene, the singlet-triplet gap of trimethylenemethane, and the lowest singlet and triplet DIPs of 23 atoms and molecules. In all cases considered, the active-space DEA/DIP-EOMCC approaches recover the highly accurate parent DEA-EOMCCSDT(4$p$-2$h$)/DIP-EOMCCSDT(4$h$-2$p$) data at small fractions of the computational costs.
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Optics

Ultrafast excitation of Bloch plasmon polaritons in hyperbolic metamaterials with an extreme ultra-violet transient grating

Tlek Tapani, Hannes Kempf, Matteo Pancaldi et al. (+14 more)

Manipulating materials properties with light drives advances in materials science and photonics. Hyperbolic metamaterials are promising candidates as next-generation quantum optical media. They support Bloch plasmon polaritons, which are characterized by potentially infinite wave-vectors and long lifetimes, but cannot be excited through direct light illumination due to momentum mismatch. Here, we experimentally show that a transient grating, formed via interference of fully coherent seeded free-electron laser pulses in a thin insulator film, enables the excitation of Bloch plasmon polaritons in an underlying hyperbolic metamaterial. Finite element simulations confirm the role of the transient grating in facilitating phase-matching and mode excitation. Our findings demonstrate a route to spatiotemporally excite Bloch plasmon polaritons modes, offering an alternative to permanently nanostructured gratings and potentially enabling ultrafast control of optical modes excitation.
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All authors Tlek Tapani, Hannes Kempf, Matteo Pancaldi, Laura Foglia, Emanuele Pedersoli, Roberta Totani, Adriana Valerio, Riccardo Mincigrucci, Ivaylo Nikolov, Miltcho B. Danailov, Aitor De Andrés, Roman Krahne, Paolo Vavassori, Filippo Bencivenga, Flavio Capotondi, Denis Garoli, Nicolò Maccaferri

Data Analysis and Statistics · Cross-listed from stat.ME

Compensator-Based Inference for Signal Detection Under Unknown Background

Aritra Banerjee and Sara Algeri

The problem of detecting new signals in the presence of an unknown background is ubiquitous in scientific discoveries and is especially prominent in the physical sciences. Most solutions proposed thus far to address the problem focus on estimating the background distribution and using that estimate to infer the signal. By studying the geometry of the problem, this article demonstrates that estimating the background distribution is somewhat unnecessary for inferring the signal intensity. Instead, it suffices to estimate a single parameter, referred to as the compensator, to account for the incomplete knowledge on the background, substantially simplifying the problem's complexity and enabling proper uncertainty propagation. Such a compensator is shown to govern the conservativeness of the inference, both in the proposed setup and in likelihood-based approaches.
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Instrumentation and Detectors

Procurement and Purification of Liquid Argon for the LEGEND-200 Experiment

Malgorzata Harańczyk, Patrick Krause, Tomasz Mróz et al. (+8 more)

LEGEND-200 requires high-purity liquid argon for effective background discrimination. In this paper, we present the design, construction, and performance of a dedicated liquid argon purification system, along with the procurement and purification of liquid argon for filling the LEGEND-200 cryostat to its total capacity of 91 t. The purifier is based on copper catalyst and molecular sieve to remove oxygen and water. Starting with liquid argon of 5.5 quality, featuring an effective scintillation light triplet lifetime $\tau_t$ of about 0.9 $\mu$s, we achieved a final purity corresponding to $\tau_t$ = 1.3 $\mu$s. After complete filling of the LEGEND-200 cryostat, the measured effective triplet lifetime was 1.16 $\mu$s. The notable reduction is caused by a residual nitrogen impurity introduced by an accidentally spoiled liquid argon delivery. An excessive nitrogen influx was prevented by the LEGEND Liquid Argon Monitoring Apparatus (LLAMA), which served as one of the three independent purity monitors during the filling campaign.
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All authors Malgorzata Harańczyk, Patrick Krause, Tomasz Mróz, Laszlo Papp, Krzysztof Pelczar, Stefan Schönert, Mario Schwarz, Christoph Vogl, Grzegorz Zuzel, Marco Balata, Nina Burlac

Computational Physics

Adaptive Multi-Fidelity Structural Optimization under Fluid-Structure Interaction

Aditya Narkhede, Erick Rivas and Kevin Wang

The design of structures and vehicles subject to fluid-structure interaction (FSI) often requires high-fidelity coupled analysis. While the design variables pertain to the structure, the computational cost is dominated by the fluid solver, making iterative optimization prohibitively expensive. This paper presents an adaptive multi-fidelity optimization method combining high-fidelity FSI analysis with a lightweight surrogate for fluid-induced loads and a decision model that selects between surrogate and high-fidelity fluid evaluations. During optimization, completed FSI analyses incrementally update a non-intrusive surrogate model based on nearest-neighbor search and radial interpolation. A hybrid Lagrangian-Eulerian mapping function is developed to transfer fluid loads between structural designs. The evolution of surface orientation is handled by decomposing the traction vectors into local orthonormal bases. An adaptive Gaussian process regression model is employed to predict surrogate error and quantify uncertainty, allowing risk-aware selection of when coupled analysis is required. As design evaluations cluster near the optimum, the accuracy of the surrogate model naturally improves, thereby reducing the reliance on the fluid solver. It requires no offline training, preserves the high-fidelity structural model in all design evaluations, and ensures that the final design is evaluated by high-fidelity FSI analysis. The fundamental idea is justified theoretically using a simplified model problem, which shows that the leading-order error is a monotonically increasing, concave, and bounded function of the fluid added mass. The framework is demonstrated on two benchmark problems. For shape optimization of a flexible panel under shock loading, results show an $80\%$ reduction in computational cost while maintaining accuracy within $2.3\%$ of fully high-fidelity FSI optimization.
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General Physics

Optical and magnetic penetration depths under a modified electromagnetic coupling in charged bosonic condensates

F. Minotti and G. Modanese

We establish the relation between optical condensate spectral weight and static magnetic screening in a proposed effective theory of charged bosonic condensates with an additional diamagnetic coupling. Starting from an explicit Ginzburg–Landau functional, we derive both the London equation and the transverse low-frequency conductivity. At fixed condensate parameter $q^2n_s/m^\ast$, the modified coupling doubles the inverse-square magnetic screening length and the optical condensate weight, giving $\lambda_{\rm mag}=\lambda_{\rm stiff}=\lambda_L/\sqrt{2}$, where $\lambda_L^{-2}=\mu_0q^2n_s/m^\ast$. Their ratio is therefore unity in both the standard and modified local theories: it tests consistency between measurement methods but cannot distinguish the couplings. A structured comparison of published results for Nb, Pb, YBCO, MgB$_2$, and Ba(Fe,Co)$_2$As$_2$ identifies the roles of sample matching, absolute calibration, nonlocality, and spectral-weight extraction. We formulate the requirements for a discriminating absolute-response experiment and discuss a complementary single-particle spectral prediction. The analysis separates experimentally accessible consistency checks from tests requiring independent information about condensate parameters or a different observable.
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